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UTILIZATION OF PREFERENTIAL TARIFFS AND ITS IMPACT ON INTRA-REGIONAL TRADE: THE CASE OF
ASEAN FREE TRADE AREA (AFTA)
MOHAMMED FAIZ BIN SHAUL HAMID
ASIA-EUROPE INSTITUTE UNIVERSITY OF MALAYA
KUALA LUMPUR
2017
Univers
ity of
Mala
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UTILIZATION OF PREFERENTIAL TARIFFS AND ITS IMPACT ON INTRA-REGIONAL TRADE: THE
CASE OF ASEAN FREE TRADE AREA (AFTA)
MOHAMMED FAIZ BIN SHAUL HAMID
THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF
PHILOSOPHY
ASIA-EUROPE INSTITUTE UNIVERSITY OF MALAYA
KUALA LUMPUR
2017 Univers
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UNIVERSITY OF MALAYA
ORIGINAL LITERARY WORK DECLARATION
Name of Candidate: Mohammed Faiz Bin Shaul Hamid
Registration/Matric No: QHA120002
Name of Degree: Doctor of Philosophy
Title of Project Paper/Research Report/Dissertation/Thesis (“this Work”):
Utilization of Preferential Tariffs and Its Impact on Intra-Regional Trade: The Case
of ASEAN Free Trade Area (AFTA)
Field of Study: Economics
I do solemnly and sincerely declare that:
(1) I am the sole author/writer of this Work; (2) This Work is original; (3) Any use of any work in which copyright exists was done by way of fair
dealing and for permitted purposes and any excerpt or extract from, or reference to or reproduction of any copyright work has been disclosed expressly and sufficiently and the title of the Work and its authorship have been acknowledged in this Work;
(4) I do not have any actual knowledge nor do I ought reasonably to know that the making of this work constitutes an infringement of any copyright work;
(5) I hereby assign all and every rights in the copyright to this Work to the University of Malaya (“UM”), who henceforth shall be owner of the copyright in this Work and that any reproduction or use in any form or by any means whatsoever is prohibited without the written consent of UM having been first had and obtained;
(6) I am fully aware that if in the course of making this Work I have infringed any copyright whether intentionally or otherwise, I may be subject to legal action or any other action as may be determined by UM.
Candidate’s Signature Date:
Subscribed and solemnly declared before,
Witness’s Signature Date:
Name:
Designation:
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ABSTRACT
ASEAN Free Trade Area (AFTA) was established in 1992 with the main objective of
increasing intra-ASEAN trade. Under AFTA, tariff reduction and elimination were
introduced through the Common Effective Preferential Tariff (CEPT) and ASEAN
Trade in Goods Agreement (ATIGA). As a direct impact of AFTA, the study focuses on
the measurement of utilization of preferential tariffs under AFTA and the impact of
intra-regional trade from the angle of intra-industry trade and revealed comparative
advantage for the three most sensitive industries in ASEAN. A Panel Regression Model
is then developed to investigate the determinants of preferential tariff utilization, intra-
industry trade and revealed comparative advantage for the three industries.
The study reveals for the first time, the utilization rate (UR) of AFTA for Malaysia
using actual transaction level data at HS2 level for year 2007 to 2011. The UR showed
that in general, AFTA only benefitted Malaysia’s export to a very low degree and it also
implies that AFTA has not directly benefitted Malaysia’s export to ASEAN in total,
recording only an average UR of 13.7% that represents only 3.4% of Malaysia’s total
exports to the world. The concentration of products with high UR were mostly for lower
value products and high value products on the other hand mostly do not benefit from
AFTA due to competing Most Favoured Nation (MFN) tariffs.
The Intra Industry Trade (IIT) and Revealed Comparative Advantage (RCA) indexes
examined the bilateral trade pairs of ASEAN-5 countries with a total of 1680
observations for agriculture, automotive and textile industries. The agriculture industry
showed trade creation effect for products such as ground nuts, soy bean, oil seeds,
coffee and tea and trade diversion effect due to high degree of competition between
Thailand and Vietnam for rice. The automotive industry showed a country centric result
where trade creation effect was focused between Thailand, Indonesia and Philippines,
whereas Malaysia and Vietnam in most cases were isolated from the significant pairs of
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countries for RCA and IIT. The textile industry in general showed two types of results.
The first is on the competitiveness of ASEAN countries among each other for low
processed or raw products and secondly, no competition between ASEAN countries for
finished products such as clothing, apparel and others, which represent higher export
values.
Finally, by using the Hausman-Taylor (HT) estimation, determinants of preferential
tariff utilization (PTU), RCA and IIT for agriculture, automotive and textile industries
were investigated. The study found that the overall margin of preference and export
values did not significantly affect the utilization rate of AFTA for the three industries.
However, the impact of AFTA seems to be more positive in providing comparative
advantage to Malaysia in the three industries. Exports, particularly in the textile
industry, have a strong positive correlation with RCA and PTU. Also, the RCA showed
positive relationship with exports for the textile and agriculture industries. In respect to
IIT, this study showed that a strong relationship between the margin of preference and
IIT for the agriculture sector. The IIT also corresponded positively with the increase in
export and utilization rates in the textile industry.
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ABSTRAK
Kawasan Perdagangan Bebas ASEAN (AFTA) ditubuhkan pada tahun 1992 dengan
tujuan utama untuk meningkatkan perdagangan sesama negara ASEAN. Di bawah
AFTA, pengurangan dan penghapusan tarif diperkenalkan melalui “Common Effective
Preferential Tariff” (CEPT) dan “ASEAN Trade in Goods Agreement” (ATIGA).
Kajian ini ditumpukan pada penggunaan “preferential tariff” di bawah AFTA dan
impak perdagangan sesama negara ASEAN menerusi intra-industry trade dan revealed
comparative advantage untuk tiga industri yang paling sensitif di ASEAN. Kajian
dilanjutkan dengan “Panel Regression Model” untuk mengkaji penentu untuk
penggunaan tariff, intra-industry trade dan revealed comparative advantage untuk tiga
industri tersebut.
Kajian ini adalah yang pertama untuk menganalisa penggunaan tariff (UR) bagi
AFTA untuk Malaysia dengan data pada tahap transaksi HS2 untuk tahun 2007 hingga
2011. Analisa UR secara kasar menunjukkan bahawa UR hanya memberi manfaat
kepada eksport Malaysia ke ASEAN pada tahap yang amat rendah. Sebagai implikasi,
AFTA tidak memberi manfaat secara langsung kepada eksport Malaysia ke ASEAN
dengan penggunaan hanya pada 13.7% dan secara keseluruhannya hanya melibatkan
3.4% daripada hasil eksport Malaysia ke seluruh dunia. Hasil kajian juga menunjukkan
bahawa tumpuan produk-produk dengan UR yang tinggi adalah produk yang
mempunyai nilai yang lebih rendah dan pada masa yang sama produk-produk yang
bernilai lebih tinggi kebanyakkannya tidak mendapat manfaat daripada AFTA
disebabkan saingan dari tarif Most Favoured Nation (MFN).
Kajian seterusnya menyiasat Intra-Industry Trade (IIT) dan Revealed Comparative
Advantage (RCA) untuk perdagangan dua hala sesama negara ASEAN-5 dengan 1680
pemerhatian bagi industri pertanian, automotif dan tekstil. Industri pertanian
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menunjukkan kesan “trade creation” bagi produk-produk seperti ground nuts, soy bean,
oil seeds, coffee and tea dan kesan “trade diversion” berdasarkan kepada persaingan
yang tinggi antara Thailand dan Vietnam untuk produk “rice”.Industri automotif pula
menunjukkan keputusan yang tertumpu kepada negara dengan kesan “trade
creation” antara Thailand, Indonesia dan Filipina manakala Malaysia dan Vietnam
tidak mencatatkan indeks RCA dan IIT yang memberangsangkan. Industri tekstil secara
amnya boleh dibahagikan kepada dua kategori. Kategori pertama ialah bagi produk-
produk yang tidak diproses yang menunjukkan saingan yang amat tinggi sesama negara
ASEAN dan produk-produk yang diproses seperti pakaian dan sebagainya tidak
menunjukkan sebarang saingan yang signifikan.
Akhir sekali, anggaran Hausman-Taylor digunakan untuk mengkaji penentu
“preferential tariff utilization” (UR), RCA dan IIT bagi industri pertanian, automotif
dan tekstil. Hasil kajian menunjukkan bahawa “margin of preference” dan nilai eksport
tidak memberi kesan kepada UR di bawah AFTA untuk tiga industri tersebut. Walau
bagaimanapun, impak AFTA dilihat lebih positif dalam memberi kelebihan kepada
Malaysia melalui RCA. Eksport, terutamanya bagi industri tekstil mempunyai korelasi
positif dengan RCA dan UR. Bagi IIT pula, kajian menunjukkan hubungan
positif “margin of preference” dan IIT untuk industri pertanian dan IIT juga
menunjukkan hubungan positif untuk meningkatkan eksport dan UR bagi industri
tekstil.
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ACKNOWLEDGEMENTS
I would like to extend my greatest appreciation to everyone who directly and
indirectly contributed to the success of this thesis. In particular, I would like to first
thank my family, especially my wife and children for the support given to me
throughout the duration of completing this thesis. My pursuit of working on this thesis
to earn a Doctor of Philosophy degree came at a challenging time for me. Like many
people of my age, this is a transition period to a family life and without the support from
my wife, children and family; I would not have been able to complete this thesis.
Apart from my support mechanism, I would like to also thank my supervisor Dr.
Mohamed Aslam for guiding me throughout the process of completing this thesis. With
his invaluable experience and expertise in international trade and economics, he
provided guidance that were thought provoking and his familiarity and expertise in the
subject matter was vital in providing me with confidence in areas that I was unsure of.
I would also take this opportunity to thank the University in general for providing the
facilities and support for postgraduate students, in particular, the Asia-Europe Institute
(AEI). The seminars, conferences and talks that were convened by AEI was very useful
in providing international insights on some areas of my research. I vividly remember the
opportunity to meet, talk and listen to the lecture by the former Secretary General of
ASEAN, Dr. Surin Pitsuwan when AEI hosted his lecture. It did provide me insights on
intra-ASEAN trade and some dynamics that I would have missed out without such
interactions.
Throughout the period of working on this thesis, I have faced great challenges that
made me feel that there is no light at the end of the tunnel. However, the sparks of light
emerged with the support and contributions of all mentioned above.
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TABLE OF CONTENTS
Abstract ....................................................................................................................... iv
Abstrak ........................................................................................................................ vi
Acknowledgements ................................................................................................... viii
Table of Contents ........................................................................................................ ix
List of Figures………………………………………………………………………xiii
List of Tables .............................................................................................................. xv
List of Abbreviations ................................................................................................. xxi
CHAPTER 1: INTRODUCTION
1.1 The Foundation of ASEAN 1
1.2 The Evolution of ASEAN 4
1.3 Preferential Trade Agreement (PTA) - 1977 10
1.4 Asia-Pacific Economic Corporation (APEC) 11
1.5 ASEAN Free Trade Area (AFTA) 12
1.6 ASEAN Vision 2020 17
1.7 ASEAN Economic Community 18
1.8 ASEAN Trade in Goods Agreement (ATIGA) 19
1.9 ASEAN Economies 21
1.10 ASEAN Selected Industries 26
1.10.1 Agriculture Industry 26
1.10.2 Automotive Industry 30
1.10.3 Textile and Clothing Industry 34
1.11 Problem Statement 38
1.12 Organization of the Study 42
CHAPTER 2: LITERATURE REVIEW
2.1 Introduction 43
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2.2 Purpose of Trade Agreements 42
2.3 Trade Effects of AFTA 46
2.4 Preferential Tariff Utilization 54
2.5 Preferential Tariff Utilization in ASEAN 58
2.6 Trade Integration, Revealed Comparative Advantage (RCA) and
Intra-Industry Trade (IIT)
73
2.7 Summary 79
CHAPTER 3: THEORETICAL FRAMEWORK AND METHODOLOGY
3.1 Theory of Free Trade Area 80
3.2 Terms of Trade Effect of FTA 87
3.3 Theories on Product Fragmentation
3.3.1 International Product Fragmentation Theory 88
3.3.2 Product Specialization in Preferential Trade Agreement
91
3.3.3 Effects in the Partner Country 94
3.3.4 Rules of Origin 96
3.4 Economics of Rules of Origin 97
3.5 Relationship between ROO, Utilization Rate and Trade Performance
101
3.6 Conceptual Framework 102
3.7 Research Objectives 104
3.8 Methods and Data
3.8.1 Utilization of Preferential Tariff under AFTA 106
3.8.2 Intra Industry Trade (IIT) 109
3.8.3 Revealed Comparative Advantage (RCA) 112
3.8.4 Reclassification Method 115
3.8.5 Panel Regression Model 119
3.8.6 Estimation 123
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CHAPTER 4: RESULTS AND DISCUSSION
4.1 Introduction 125
4.2 Utilization of Preferential Tariff under AFTA: Case of Malaysia 125
4.3 Intra-Industry Trade (IIT) and Revealed Comparative Advantage (RCA) in Agriculture, Automotive and Textile & Clothing Industry
4.3.1 IIT for Agriculture Industry 133
4.3.2 RCA for Agriculture Industry 137
4.3.3 Summary of IIT and RCA in Agriculture Industry 147
4.3.4 IIT and RCA for ASEAN countries in Agriculture Industry
153
4.4 Automotive Industry
4.4.1 IIT for Automotive Industry 158
4.4.2 RCA for Automotive Industry 161
4.4.3 Summary of IIT and RCA in Automotive Industry 164
4.4.4 IIT and RCA for ASEAN countries in Automotive Industry
165
4.5 Textile and Clothing Industry
4.5.1 IIT for Textile and Clothing Industry 168
4.5.2 RCA for Textile and Clothing Industry 172
4.5.3 Summary of IIT and RCA in Textile and Clothing Industry
176
4.6 Panel Regression Model 185
4.6.1 Determinants of Utilization Rate 186
4.62 Determinants of Revealed Comparative Advantage 189
4.6.3 Determinants of Intra-Industry Trade 191
CHAPTER 5: SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Introduction 193
5.2 Utilization of Preferential Tariff under AFTA: Case of Malaysia
5.2.1 Summary and Conclusion 193
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5.2.2 Policy Implications 200
5.3 Agriculture Industry in ASEAN
5.3.1 Summary 201
5.3.2 Conclusion 204
5.3.3 Policy Recommendations 205
5.4 Automotive Industry in ASEAN
5.4.1 Summary 208
5.4.2 Conclusion 209
5.4.3 Policy Recommendations 210
5.5 Textile and Clothing Industry in ASEAN
5.5.1 Summary 213
5.5.2 Conclusion 214
5.5.3 Policy Recommendations 216
5.6 Summary and Conclusion of the Panel Regression Model 218
5.7 Limitations 220
5.8 Further Area of Research 221
Appendix………………………………………………………………….
223
Bibliography……………………………………………………………… 342
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LIST OF FIGURES
1.1 Trend of ASEAN Total Trade and Intra-ASEAN Trade, 1993-2013 25
1.2 Trend of the percentage of CEPT tariff lines with zero tariff rates,
2000-2013
26
1.3 Value of agriculture exports of individual ASEAN-5 countries against
years (2001-2014)
28
1.4 Exports of ASEAN-5 countries in automotive industry by country
(value in USD thousand)
32
1.5 Value of Exports in USD Billion for ASEAN-5 in textile and clothing
industry
36
3.1 Illustration of Viner’s Model 83
3.2 Effects of International Product Fragmentation 89
3.3 Trade in Preferential Trade Agreements 91
3.4 Trade in intermediary products and the partner country 94
3.5 ROO impact in Trade Agreements 98
3.6 Conceptual Framework 103
3.7 Reclassified HS4 Products to HS3 level for Agriculture Industry 117
3.8 Reclassified HS4 Products to HS3 level for Automotive Industry
117
3.9 Reclassified HS4 Products to HS3 level for Textile and Clothing
Industry
118
3.10 Number of product lines covered at HS3 for Agriculture, Automotive
and Textile and Clothing Industry
119
3.11 ROO relationship under CEPT/ATIGA and MFN Tariffs - Estimation 121
4.38 Scatter Diagram of UR and Exports/MOPR, Textiles Sector 185
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5.1 Exports of Malaysia to ASEAN (excluding Singapore) in Million USD
against Average AUR for Malaysia (2007-2011)
196
5.2 Recommended strategy for exports of Malaysia to ASEAN (excluding
Singapore) in Million USD against Average AUR for Malaysia (2007-
2011)
198
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LIST OF TABLES
1.1 Chronology of AFTA related developments in ASEAN, 1992-2015 151.2 Milestones from CEPT to ATIGA 221.3 ASEAN Basic Indicators 2015 241.4 ASEAN Exports and Imports by country in 2015 241.5 Intra-ASEAN and Extra-ASEAN exports by country year 2015 251.6 Intra-ASEAN and Extra-ASEAN imports by country year 2015 251.7 Intra-ASEAN and Extra-ASEAN trade by country year 2015 261.8 Share of agriculture sector to all products exports of ASEAN-5
countries (values in USD thousand) 29
1.9 Value of agriculture exports of individual ASEAN-5 countries (values in USD thousand)
29
1.10 Top 5 agriculture products (HS3 level) of ASEAN-5 countries (values in USD thousand)
30
1.11 Share of automotive industry to all products exports of ASEAN-5 countries (values in USD thousand)
32
1.12 Exports of ASEAN-5 countries in automotive industry (value in USD thousand)
33
1.13 Share of Textile and Clothings Industry to all products exports of ASEAN-5 countries (values in USD thousand)
36
1.14 Exports of ASEAN-5 countries in textile and clothings industry (value in USD thousand)
37
1.15 Top 5 product items in HS3 exported by ASEAN-5 in Textile and Clothing Industry (value in thousand USD)
38
4.1 Malaysia: GUR, AUR export to ASEAN, 2007-2011 1344.2 Top ten products at HS2 level for GUR 1394.3 Top ten products at HS2 level for AUR 1394.4 Top Ten HS2 Malaysia's Average Export Value to ASEAN and
Corresponding GUR and AUR Values (2007-2011) 141
4.5 Top Ten HS2 Malaysia's Export to ASEAN vs World (Concentration) and Corresponding GUR and AUR Values (2007-2011)
145
4.6A Malaysia-Thailand IIT index for Agriculture, 2001-2014 2234.6B Indonesia-Thailand IIT index for Agriculture, 2001-2014 2244.6C Philippines-Thailand IIT index for Agriculture, 2001-2014 2254.6D Vietnam-Thailand IIT index for Agriculture, 2001-2014 2264.7A Malaysia-Indonesia IIT index for Agriculture, 2001-2014 2274.7B Thailand-Indonesia IIT index for Agriculture, 2001-2014 2284.7C Philippines-Indonesia IIT index for Agriculture, 2001-2014 2294.7D Vietnam-Indonesia IIT index for Agriculture, 2001-2013 2304.8A Indonesia-Malaysia IIT index for Agriculture, 2001-2014 2314.8B Thailand-Malaysia IIT index for Agriculture, 2001-2014 2324.8C Philippines-Malaysia IIT index for Agriculture, 2001-2014 2334.8D Vietnam-Malaysia IIT index for Agriculture, 2001-2013 234
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4.9A Malaysia-Philippines IIT index for Agriculture, 2001-2014 2354.9B Thailand-Philippines IIT index for Agriculture, 2001-2014 2364.9C Indonesia-Philippines IIT index for Agriculture, 2001-2014 2374.9D Vietnam-Philippines IIT index for Agriculture, 2001-2013 2384.10A Malaysia-Vietnam IIT index for Agriculture, 2001-2013 2394.10B Thailand-Vietnam IIT index for Agriculture, 2001-2013 2404.10C Indonesia-Vietnam IIT index for Agriculture, 2001-2013 2414.10D Philippines-Vietnam IIT index for Agriculture, 2001-2013 2424.11A RCA Index for Thailand-Malaysia in Agriculture Industry 2434.11B RCA Index for Indonesia-Malaysia in Agriculture Industry 2444.11C RCA Index for Philippines-Malaysia in Agriculture Industry 2454.11D RCA Index for Vietnam-Malaysia in Agriculture Industry 2464.12A RCA Index for Thailand-Indonesia in Agriculture Industry 2474.12B RCA Index for Philippines-Indonesia in Agriculture Industry 2484.12C RCA Index for Malaysia-Indonesia in Agriculture Industry 2494.12D RCA Index for Vietnam-Indonesia in Agriculture Industry 2504.13A RCA Index for Thailand-Philippines in Agriculture Industry 2514.13B RCA Index for Malaysia-Philippines in Agriculture Industry 2524.13C RCA Index for Indonesia-Philippines in Agriculture Industry 2534.13D RCA Index for Vietnam-Philippines in Agriculture Industry. 2544.14A RCA Index for Malaysia-Thailand in Agriculture Industry 2554.14B RCA Index for Indonesia-Thailand in Agriculture Industry 2564.14C RCA Index for Philippines-Thailand in Agriculture Industry 2574.14D RCA Index for Vietnam-Thailand in Agriculture Industry 2584.15A RCA Index for Thailand-Vietnam in Agriculture Industry 2594.15B RCA Index for Malaysia-Vietnam in Agriculture Industry 2604.15C RCA Index for Philippines-Vietnam in Agriculture Industry 2614.15D RCA Index for Indonesia-Vietnam in Agriculture Industry 2624.16A Product Categories with significant IIT values in ASEAN Agriculture
Industry 263
4.16B Product Categories with significant RCA index for Malaysia-ASEAN countries in Agriculture Industry and number of competing countries
264
4.16C Product Categories with significant RCA index for Thailand-ASEAN countries in Agriculture Industry and number of competing countries
265
4.16D Product Categories with significant RCA index for Indonesia-ASEAN countries in Agriculture Industry and number of competing countries
266
4.16E Product Categories with significant RCA index for Philippines-ASEAN countries in Agriculture Industry and number of competing countries
266
4.16F Product Categories with significant RCA index for Vietnam-ASEAN countries in Agriculture Industry and number of competing countries
266
4.17A Thailand-Malaysia IIT Index for Automotive Industry, 2001-2014 2634.17B Indonesia-Malaysia IIT Index for Automotive Industry, 2001-2014 2634.17C Philippines-Malaysia IIT Index for Automotive Industry, 2001-2014 2644.17D Vietnam-Malaysia IIT Index for Automotive Industry, 2001-2014 264
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4.18A Malaysia-Thailand IIT Index for Automotive Industry, 2001-2014 2654.18B Indonesia-Thailand IIT Index for Automotive Industry, 2001-2014 2654.18C Philippines-Thailand IIT Index for Automotive Industry, 2001-2014 2664.18D Vietnam-Thailand IIT Index for Automotive Industry, 2001-2014 2664.19A Malaysia-Philippines IIT Index for Automotive Industry, 2001-2014 2674.19B Thailand-Philippines IIT Index for Automotive Industry, 2001-2014 2674.19C Indonesia-Philippines IIT Index for Automotive Industry, 2001-2014 2684.19D Vietnam-Philippines IIT Index for Automotive Industry, 2001-2014 2684.20A Malaysia-Vietnam IIT Index for Automotive Industry, 2001-2013 2694.20B Thailand-Vietnam IIT Index for Automotive Industry, 2001-2013 2694.20C Indonesia-Vietnam IIT Index for Automotive Industry, 2001-2013 2704.20D Philippines-Vietnam IIT Index for Automotive Industry, 2001-2014 2704.21A RCA Index of Thailand-Malaysia Automotive Industry (2001-2014) 2714.21B RCA Index of Indonesia-Malaysia Automotive Industry (2001-2014) 2714.21C RCA Index of Philippines-Malaysia Automotive Industry (2001-2014) 2724.21D RCA Index of Vietnam-Malaysia Automotive Industry (2001-2013) 2724.22A RCA Index of Malaysia-Thailand Automotive Industry (2001-2014) 2734.22B RCA Index of Indonesia-Thailand Automotive Industry (2001-2014) 2734.22C RCA Index of Philippines-Thailand Automotive Industry (2001-2014) 2744.22D RCA Index for Vietnam-Thailand Automotive Industry (2001-2013) 2744.23A RCA Index for Malaysia-Indonesia Automotive Industry (2001-2014) 2754.23B RCA Index for Thailand-Indonesia Automotive Industry (2001-2014) 2754.23C RCA index of Philippines-Indonesia Automotive Industry (2001-2014) 2764.23D RCA index of Vietnam-Indonesia Automotive Industry (2001-2013) 2764.24A RCA Index for Malaysia-Philippines Automotive Industry (2001-2014) 277
4.24B RCA Index for Thailand-Philippines Automotive Industry (2001-2014) 2774.24C RCA Index of Indonesia-Philippines Automotive Industry (2001-2014) 2784.24D RCA Index of Vietnam-Philippines Automotive Industry (2001-2014) 2784.25A RCA Index of Malaysia-Vietnam Automotive Industry (2001-2014) 2794.25B RCA Index of Thailand-Vietnam Automotive Industry (2001-2014) 2794.25C RCA Index of Indonesia-Vietnam Automotive Industry (2001-2014) 2804.25D RCA Index of Philippines-Vietnam Automotive Industry (2001-2013) 2804.26A Product Categories with significant IIT values in ASEAN Automotive
Industry 281
4.26B Product Categories with significant RCA index for Thailand-ASEAN countries in Automotive Industry and number of competing countries
281
4.26C Product Categories with significant RCA index for Indonesia-ASEAN countries in Automotive Industry and number of competing countries
282
4.26D Product Categories with significant RCA index for Philippines-ASEAN countries in Automotive Industry and number of competing countries
282
4.26E Product Categories with significant RCA index for Vietnam-ASEAN countries in Automotive Industry and number of competing countries
282
4.27A Thailand-Malaysia IIT Index for Textile and Clothing Industry, 2001-2014
283
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4.27B Indonesia-Malaysia IIT Index for Textile and Clothings Industry, 2001-2014
284
4.27C Philippines-Malaysia IIT Index for Textile and Clothings Industry, 2001-2014
285
4.27D Vietnam-Malaysia IIT Index for Textile and Clothings Industry, 2001-2013
286
4.28A Malaysia-Thailand IIT Index for Textile and Clothing Industry, 2001-2014
287
4.28B Indonesia-Thailand IIT Index for Textile and Clothing Industry, 2001-2014
288
4.28C Philippines-Thailand IIT Index for Textile and Clothing Industry, 2001-2014
289
4.28D Vietnam-Thailand IIT Index for Textile and Clothing Industry, 2001-2013
290
4.29A Malaysia-Indonesia IIT Index for Textile and Clothing Industry, 2001-2014
291
4.29B Thailand-Indonesia IIT Index for Textile and Clothing Industry, 2001-2014
292
4.29C Philippines-Indonesia IIT Index for Textile and Clothing Industry, 2001-2014
293
4.29D Vietnam-Indonesia IIT Index for Textile and Clothing Industry, 2001-2013
294
4.30A Malaysia-Philippines IIT Index for Textile and Clothing Industry, 2001-2014
295
4.30B Thailand-Philippines IIT Index for Textile and Clothing Industry, 2001-2014
296
4.30C Indonesia-Philippines IIT Index for Textile and Clothing Industry, 2001-2014
297
4.30D Vietnam-Philippines IIT Index for Textile and Clothing Industry, 2001-2013
298
4.31A Malaysia-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
299
4.31B Thailand-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
300
4.31C Indonesia-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
301
4.31D Philippines-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
302
4.32A RCA Index for Thailand-Malaysia Textile and Clothing Industry (2001-2014)
303
4.32B RCA Index for Indonesia-Malaysia Textile and Clothing Industry (2001-2014)
304
4.32C RCA Index for Philippines-Malaysia Textile and Clothing Industry (2001-2014)
316
4.32D RCA Index for Vietnam-Malaysia Textile and Clothing Industry 317
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(2001-2014) 4.33A RCA Index for Malaysia-Thailand Textile and Clothing Industry
(2001-2014) 319
4.33B RCA Index for Indonesia-Thailand Textile and Clothing Industry (2001-2014)
321
4.33C RCA Index for Philippines-Thailand Textile and Clothing Industry (2001-2014)
322
4.33D RCA Index for Vietnam-Thailand Textile and Clothing Industry (2001-2014)
323
4.34A RCA Index for Malaysia-Indonesia Textile and Clothing Industry (2001-2014)
324
4.34B RCA Index for Thailand-Indonesia Textile and Clothing Industry (2001-2014)
326
4.34C RCA Index for Philippines-Indonesia Textile and Clothing Industry (2001-2014)
327
4.34D RCA Index for Vietnam-Indonesia Textile and Clothing Industry (2001-2013)
328
4.35A RCA Index for Malaysia-Philippines Textile and Clothing Industry (2001-2014)
330
4.35B RCA Index for Thailand-Philippines Textile and Clothing Industry (2001-2014)
331
4.35C RCA Index for Indonesia-Philippines Textile and Clothing Industry (2001-2014)
332
4.35D RCA Index for Vietnam-Philippines Textile and Clothing Industry (2001-2013)
333
4.36A RCA Index for Malaysia-Vietnam Textile and Clothing Industry (2001-2014)
334
4.36B RCA Index for Thailand-Vietnam Textile and Clothing Industry (2001-2014)
335
4.36C RCA Index for Indonesia-Vietnam Textile and Clothing Industry (2001-2014)
336
4.36D RCA Index for Philippines-Vietnam Textile and Clothing Industry (2001-2014)
337
4.37A Product Categories with significant IIT values in ASEAN Textile and Clothing Industry
338
4.37B Product Categories with significant RCA index for Malaysia-ASEAN countries in Textile and Clothing Industry and number of competing countries
339
4.37C Product Categories with significant RCA index for Thailand-ASEAN countries in Textile and Clothing Industry and number of competing countries
340
4.37D Product Categories with significant RCA index for Indonesia-ASEAN countries in Textile and Clothing Industry and number of competing countries
341
4.37E Product Categories with significant RCA index for Philippines- 182
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ASEAN countries in Textile and Clothing Industry and number of competing countries
4.37F Product Categories with significant RCA index for Vietnam-ASEAN countries in Textile and Clothing Industry and number of competing countries
183
4.39 Determinants of Utilization Rate (UR), by Sector 1884.40 Determinants of Relative Comparative Advantage (RCA), by Sector 1904.41 Determinants of Intra-Industry Trade, by Sector 192
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LIST OF ABBREVIATIONS
AFTA : ASEAN Free Trade Area
APEC : Asia-Pacific Economic Cooperation
ASA : Association of Southeast Asia
ASEAN : Association of Southeast Asian Nations
ASEAN-PMC : ASEAN-Post-Ministerial Conferences
ATIGA : ASEAN Trade in Goods Agreement
AUR : Adjusted Utilization Rate
CEPT : Common Effective Preferential Tariff
COO : Certificate of Origin
GUR : Generalized Utilization Rate
GDP : Gross Domestic Product
HS : Harmonized System
IIT : Intra-industry trade
MFN : Most Favoured Nation
MOPR : Margin of Preference Rate
NIC : Newly Industrialized Country
NTB : Non-tariff barriers
PTA : Preferential Trade Agreement
RCA : Revealed Comparative Advantage
ROO : Rules of Origin
SOM : Senior Officials’ Meeting
SEOM : Senior Economic Officials’ Meeting
UN : United Nations
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UNCTAD : United Nations Conference on Trade and Development
UR : Utilization Rate
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CHAPTER 1: INTRODUCTION
1.1 The Foundation of ASEAN
On 8 August 1967 five Foreign Ministers from the countries of Malaysia, Indonesia,
Thailand, Singapore, and the Philippines completed negotiations on the 1967 ASEAN
Declaration1. This declaration, also known as The Bangkok Declaration, effectively
created the Association of Southeast Asian Nations (ASEAN). The creation of ASEAN
showcased the desire of the five nations to further regional cooperation and create an
overarching sense of community among the nations of Southeast Asia. In fact,
ASEAN’s expressed purpose was to “to accelerate the economic growth, social progress
and cultural development in the region through joint endeavors in the spirit of equality
and partnership in order to strengthen the foundation for a prosperous and peaceful
community of South-East Asian Nations”.
Initially, the success of ASEAN seemed unlikely given both the region’s deeply
rooted internal divisions and the common meddling of external powers in the area. Even
in the pre-colonial and ancient periods, geographic isolation made it difficult for the
kingdoms and cultures of Southeast Asia to share a strong common bond or link.
Though some historians will note that “there were interactions between the divergent
parts of the region and even, arguably, the beginnings of a weak sense of community;”
preexisting divides became solidified during European colonialism (Narine, 2002).
Throughout the 19th and 20th centuries the colonized states of Southeast Asia oriented
towards their various Western colonizers. Heavily influencing everything from political
ideology to philosophical thought to, in some cases, religion the Western world left
unique intangible marks on each Southeast Asian states. Subsequently, the main
1 The five Foreign Ministers who completed negations on and signed the 1967 ASEAN Declaration were Tun Abdul Razak of Malaysia, Adam Malik of Indonesia, Thanat Khoman of Thailand, Marciso Ramos of the Philippines and S. Rajaratnam of Singapore.
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economic activities of the countries colonized were structured in a way to cater for the
trade and benefit of the colonizers. As a result, following World War II and during the
nationalist movements in Southeast Asia, the people of Southeast Asia needed to
overcome considerable barriers to form a sense of regional identity. Their actions, in
fact, highlighted the extent of the region’s division.
Post World War II, the states of Southeast Asia believed in the imminence of their
independence. After all, “the Japanese occupation of most of the region had swept away
the apparatus of colonial rule, and rendered impossible its simple restoration when the
war was over” (Tarling, 1999:pg. 71). Yet when Indonesia declared independence on 17
August 1945 they found themselves fighting a bitter war against the Netherlands who
had not anticipated the state’s strong nationalist movement. Following Indonesia; the
Philippines gained independence in 1946, Burma or Myanmar in 1948, and the states of
Indochina in 1954. Additionally as the Cold War intensified Western nations began
countering the multiple threats of communism with the process of further
decolonization (Church, 2003). Great Britain granted independence to Malaya in 1957
and Singapore, Sarawak, and Sabah in 1963 after suppressing communist insurrections
in these states. Divisions between non-communist and communist nations in Southeast
Asia caused friction between the nations in the area and gave Western nations like the
United States reasons to meddle in regional affairs. Yet they also, however, prompted
the first movement of official regional cooperation within Southeast Asia.
In the late 1950s and early 1960s the countries that were at the forefront of Southeast
Asian regionalism were also the area’s most pro-Western and anti-communist nations.
Initiated by the efforts of Malaya’s then Prime Minister Tunku Abdul Rahman2, the
2 Prime Minister Tunku Abdul Rahman first publicly proposed the idea of “closer cooperation among countries of South-East Asia especially in the economic, social, cultural” fields in a meeting with
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nations of Malaya, Thailand and the Philippines united in Bangkok on 31 July 1961 to
form the Association of Southeast Asia (ASA) in Bangkok. ASA, though the area’s first
regional organization and attempt at regional unification, only further divided the
nations of Southeast Asia. The establishment of ASA effectively divided Southeast Asia
into two camps: those actively opposed to communism and the authority of China and
those with a pro-China disposition. Furthermore, tensions eventually arose between the
members of ASA itself. While Malaya and the Philippines “originally envisioned an
organization modeled on the European Economic Community [with] strong institutional
structures and obligations,” Thailand favored the creation of an “organization with a
much looser structure and without binding obligations upon its members” (Narine,
2002). The obstacle and divisions facing ASA piled up and eventually crippled the still
young organization. ASA’s most insurmountable challenge occurred on 16 September
1963 when Malaya, Singapore, Sarawak, and Sabah amalgamated into the nation of
Malaysia. British interference coupled with Philippines’ refusal to accept the
independence of Sabah caused both Indonesia and the Philippines to refuse to recognize
the state of Malaysia. Indonesia went so far as to adopt the policy of Konfrontasi in
regard to Malaysia and Singapore when it in turn became independent. Konfrontasi,
which refers to a policy of regional disruption, led to both guerilla movements and
economic sanctions within and between Indonesia and Malaysia. Ironically, however,
Indonesia’s attempts to significantly undermine Malaysia significantly hurt them
economically as well. In many issues, the policy of Konfrontasi revealed the full extent
of Southeast Asia’s mutual dependency and showcased the necessity of a regional
organization. In 1967 when General Suharto reversed Indonesia’s prior policies and
“went from being a state largely indifferent to efforts at regional organization to a major
President Garcia, the then President of the Philippines. Together the issued a joint statement, the Rahman/Garcia Communiqué, which announced their intentions to the rest of Southeast Asia.
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proponent of regionalism” (Tarling, 1999: pg. 35). Since outsiders like Indonesia
unfavorably saw the prior regional organization of ASA as being politically aligned
with the Western world, it was determined that a new regional organization should be
created. Thus, ASEAN emerged and eventually evolved with the changing periods.
1.2 The Evolution of ASEAN
Founded under a “spirit and sense of belonging,” ASEAN leaders subscribed to
the five C’s: consolidation, consultation, consensus, caring, and cornerstone (Keling,
Som, Saludin, Shuib and Ajis, 2011). Though it was founded by the five nations of
Malaysia, Singapore, Thailand, the Philippines, and Indonesia, its membership
eventually increased to include Brunei, Cambodia, Laos, Vietnam, and Myanmar in the
1980s and 1990s. ASEAN grew eventually in size, influence, and arguably
effectiveness; but it began as a fairly directionless and unorganized organization. When
ASEAN first originated it was designed with a fairly loose organizational structure. The
ASEAN committee was originally separated between four key components:
i. ASEAN Ministerial Meeting (AMM)
ii. ASEAN Standing Committee (ASC)
iii. Ad Hoc and Fixed Committee
iv. ASEAN Secretary Members
The AMM was the organization’s main decision-making body and the ASC existed
to support the AMM. Leadership of these committees rotated annually between member
countries and they were chaired by the foreign minister of the host nation. ASEAN’s
organizational structure and elected committees, as it was designed between 1967 and
1976, is said to be unclear and overlapping (Keling, Som, Saludin, Shuib and Ajis,
2011). The article The Development of ASEAN from Historical Approach notes, “even
the ambassadors and Foreign Ministers’ responsibility as ASEAN Standing Committee
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was burdening. This is because the issues and affairs relating to political economy,
social and cultural understandings were under their responsibility. This made them
unable to focus on the real objectives especially concerning economic development”
(Keling, Som, Saludin, Shuib, and Ajis, 2011). As a result, ASEAN found itself limited
in scope and effectiveness. Though ASEAN produced numerous recommendations
during this period, few took shape and were implemented. Yet, even though their
progress proved slow, ASEAN did make strides during its formative years especially in
the fields of political security and stability.
Alongside the ASEAN Treaty of Amity & Cooperation (TAC), which was enacted in
1967, many other legislative initiatives advocating mutual respect and intra-region
cooperation and peace would come into effect. During ASEAN’s second Summit in
Kuala Lumpur, in 1971, the Kuala Lumpur Declaration took form. This declaration
advocated the implementation of neutral policy in Southeast Asia and the establishment
of the Zone of Peace, Freedom, and Neutrality Declaration (ZOPFAN). Agreed upon by
all countries, the main objectives of ZOPFAN aimed to promote peace and stability in
Southeast Asia and to avoid political intervention from superpowers. Non-
interventionist or neutral policies, though initially agreed upon by all of the ASEAN
nations, had some critics. The effectiveness of these policies were often debated among
ASEAN members and “the interest to change this principle was voiced by Thailand and
the Philippines tried to suggest the flexible interaction approach or healthy intervention
enabling a small amount of intervention without jeopardizing the non-intervention
principle. In fact, between the 1970s and 1990s many signs existed suggesting that
ASEAN was moving towards ‘limited intervention’ policies.
One of these signs occurred during a coup d’état in Cambodia in 1970 when ASEAN
became the middleman in order to help resolve Cambodia’s internal problems. They
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successfully persuaded conflicting parties to negotiate and earned partial responsibility
in resolving this crisis (Keling, Som, Saludin, Shuib and Ajis, 2011). Within the next
decades ASEAN took many more steps in becoming more involved in Southeast Asia
affairs.
The Bali Summit between the 23rd and 25th of February in 1976 produced the
Declaration of ASEAN Concord. This declaration agreed to expand political
cooperation, to resolve issues through peace, and to take every action to collectively
stand for the ASEAN principle (Narine, 2002).3 From here, ASEAN went on to take a
vested interest in the affairs of Southeast Asia. After the ASEAN Regional Forum or
ARF was suggested by Australia during an ASEAN Ministerial Meeting in Jakarta in
July 1990, it came into existence for the first time on the 25th of July 1994 in Bangkok.
This forum aimed to be a key player in problem solving, disputes, and security threats
as well as nuclear threats among country members in a peaceful manner. It also hoped
to open dialogue with foreign countries especially in regard to security and policy in the
Asian Pacific4. Other ASEAN ‘limited interventionist’ policies include the ASEAN’s
ten Heads of States agreement that no member country would possess, place, own,
manufacture, transport, or utilize nuclear weapons when they instituted the Southeast
Asia Weapons-Free Zone (SEANWFZ) in 1995. Similarly, in 2004 when discussing
cooperation in the Strait of Malacca the Melaka Straits Singapore Coordinated Patrol
(MSSCP) originated between Malaysia, Singapore, and Thailand. Tasked with dealing
with pirates, border disputes, water security, illegal fishing, illegal immigrants, and
3 Also addressing the economic side of regional security. ASEAN nations agreed to cooperate on intraregional trade liberalization and the trade of basic commodities like food.
4 The ARF was made up of 23 members, including all 10 of the ASEAN nations. Members included Brunei, Singapore, Thailand, Burma, Myanmar, Cambodia, Malaysia, Indonesia, Laos, the Philippines, Vietnam, the European Union, Australia, Canada, China, India, Japan, South Korea, North Korea, New Zealand, Russia, the United States, Papua New Guinea, and Mongolia.
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border invasions; this patrol sought to act collectively and promote effective diplomatic
ties. These new and more firm tactics revealed ASEAN’s growing influence and their
steadfast determination to remain a safe and stable region.
ASEAN’s desire for the entire Southeast Asian region to continue developing and
remain safe and stable stemmed from the region’s growing reputation as an area for
investment and trade. The countries saw it as imperative that ASEAN become a
stronger and more effective apparatus to ensure ASEAN’s future successes. At that
time, ASEAN’s strongest successes and its most noteworthy prospects were centered on
economic development. By lowering trade barriers and lifting restrictions on foreign
investment within ASEAN, Southeast Asian countries successfully emerged as one of
the most attractive investment destinations in the developing world. Japan became one
of the first countries to invest in Southeast Asia, especially in Indonesia, because they
needed cheap labor and weaker environmental legal standards. Their investments helped
strengthen infrastructures of the Southeast Asian nations and provide them with relative
prosperity. The successes in economic development among individual ASEAN
countries like Thailand, Singapore, Indonesia, and Malaysia was in part the catalyst to
ASEAN’s effectiveness. The platform enabled the countries to take the advantage and
invest in the nearest neighboring countries, in terms of natural resource or labor force
from less developed countries in the region. Rapid development of the Southeast Asian
nations caused ASEAN to make structural changes to their administration and
organization and to begin undertaking more economic development initiatives.
Additionally at the 1976 Bali Conference also known as Bali Concord I, ASEAN
adopted a new and more efficient organizational structure. The new organizational
structure included five committees:
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i. ASEAN Heads of States Meetings, for cooperation programs
ii. ASEAN Foreign Ministers Meetings, held once a year
iii. ASEAN Economic Ministers Meeting, held twice a year
iv. Other Minister Meetings
v. ASEAN Secretariat
The restructuring process also included the establishment of the annual ASEAN-
Post-Ministerial Conferences (ASEAN – PMC), the Senior Officials Meeting (SOM),
and the Senior Economic Officials Meeting (SEOM). These conferences and meetings
sought to facilitate dialogue and cement formal advisory for ASEAN’s main
committees. Yet, even with these changes, the organization of ASEAN still remained
flawed. For instance, the ASEAN Secretariat remained underfunded and understaffed
throughout the 1970s and 1980s. Even when ASEAN was again restructured in 1992 the
ASEAN Secretariat failed to gain a significant role in policy making or any other
function that might push the organization toward greater integration. Regardless of
ASEAN’s internal shortcomings, however, they still began to take a more active role in
Southeast Asia’s economic landscape.
At the Bali Concord I, ASEAN member countries decided to develop some specific
industries through specialization by each country. Every ASEAN member country in
1970s received a different project allocation that involved investment ranging between
USD250 million and USD350 million. Each country held responsibility for 60% of the
total equity of these projects. Malaysia and Indonesia received hand-area fertilization
projects, the Philippines received a phosphate project, Thailand received a soda ash
project, and Singapore received a diesel engine project. Of these, both Thailand’s and
Singapore’s projects proved unprofitable and both these countries undertook new
projects. Singapore undertook a Vaccine for Hepatitis B project and Thailand developed
a stone salt ash soda project. Eventually, the Philippines also switched projects to a
fotosphatic fertilizer copper fabrication project. All of these projects indicated at
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Southeast Asia’s determination to develop an industrial economy and ASEAN’s
intention to make this goal a reality.
Responding to a 1969 UN Economic Commission for Asia & the Far East Report,
ASEAN also began to attempt to facilitate intra-regional trade between members. The
report, which concluded that the development potential of Southeast Asia remained
limited by small internal markets, advocated that ASEAN members implement more
import-substitution policies. Prior to the commissioning of the report, the Philippines,
Thailand, and Malaysia had followed Singapore’s lead by switching focus to export-
oriented products. These nations viewed import-substitution unfavorably as they did not
believe it generated industry or growth in employment. ASEAN believed they could
reverse this trend between members by creating eight committees to focus solely on
economic issues (Narine, 2002). 5 Through these committees ASEAN developed
affiliations with multiple non-governmental organizations with economic objectives and
allowed a number of profitable organizations and regional private businesses to use the
ASEAN logo.
Yet many of their efforts were stymied by competition amongst member countries.
All of the ASEAN states except Singapore produced natural resources for the first
world; with Japan, the United States, and the European Union being their primary
partners (Narine, 2002: p. 117)6. In the 1980s only about 15% of ASEAN exports and
14% of their imports consisted of intra-regional trade. Without Singapore, the ASEAN
intra-regional trade dropped much lower to about 5%. Noting these statistics, ASEAN
committee members decided to make efforts to introduce intra-ASEAN trade
5 Five of these committees reported to the ASEAN Economic Minister, while three fell under the responsibility of the Standing Committee.
6In 1985 the United States and Japan made up of 45% of ASEAN exports and 35% of their imports and the European Union made up for 11% of ASEAN exports and 14% of their imports.
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liberalization in the hopes that it would generate more intra-regional trade. ASEAN
members believed that unilateral liberalisation would favour the creation of more trade,
reveal the strong intent of transforming the region into an attractive production base,
and indeed, give substance to the rhetorics of regionalism. Its critics argued, on the
other hand, that the hurdles posed by NTMs (non-tariff measures) and “other high costs
implied by administrative and rules of origin compliance, are obviously more malign,
casting doubts on the sustainability of future regional efforts” (Pelkmans-Balaoing and
Manchin, 2007). These criticisms did not sway ASEAN members, however, and they
began to aggressively pursue trade liberalization policies.
1.3 Preferential Trade Agreement (PTA) - 1977
One of the first trade liberalization initiatives ASEAN undertook was the 1977
Preferential Trade Agreement (PTA). The ASEAN PTA had little immediate impact
and in 1987 “its members looked over their trade policy and attempted to make
significant changes to the agreement.” Changes to the ASEAN PTA included:
i. Exclusion lists be lowered to no more than 10% of the number of traded
items and/or 50% of the value of intra-ASEAN trade;
ii. Inclusion of excluded product list with a 25% minimum margin of
preference;
iii. Increasing tariff reductions of preexisting PTAs to 50%;
iv. Restraining non-tariff barriers (NTBs) and negotiating a curtailment of
such NTBs;
v. Reducing the ASEAN content level to 35% (Hakim, 2004).
Despite admirable efforts, the ASEAN PTA failed to enhance intra-ASEAN trade.
Competition between ASEAN members and lack of political will from ASEAN
governments prevented the ASEAN PTA from being effective. Though the ASEAN
PTA did not greatly impact Southeast Asian economies, ASEAN countries separately
recorded a significant rate of economic growth during the 1980s. Singapore especially
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developed swiftly by embarking on an independent program of unilateral trade
liberalization. Since they remained too small to indulge in the luxury of protectionism,
they instead chose to implement policies like reducing trade barriers and by increasing
the level of non-tariff barriers on goods like cereals. Their development occurred so
quickly that it helped inspire the term Newly Industrialized Country (NIC). Noting
Singapore’s progress many world leaders assumed that other ASEAN nations like
Malaysia, Thailand, and possibly Indonesia would also continue to develop on such a
large scale and in many ways they did. Yet even as ASEAN nations progressed a
noticeably different degree of industrialization among these nations still existed. In
many ways these nations proved limited by their protectionist and interventionist
policies. Lowering trade barriers through ASEAN PTA could only accomplish so much
when the individual ASEAN nations compensated by using other instruments of
protection. By protecting their economies using fiscal charges, restrictive licensing,
advance sales taxes, quotas, foreign-exchange restrictions, and state-trading monopolies
they sabotaged their ability to maximize the trade and exports. Changing circumstances,
however, prompted these ASEAN nations to rethink their strategies and policies.
1.4 Asia-Pacific Economic Corporation (APEC)
In the 1970s and 1980s ASEAN undertook a number of other free trade initiatives
like the ASEAN PTA, but none of them greatly affected Southeast Asia’s economic
landscape. In addition to “the commitment of the ASEAN member countries to reducing
trade barriers in order to enhance trade in the ASEAN region, the ASEAN member
countries were also actively involved in promoting open trade and practical economic
cooperation among Asia-Pacific economies (APEC)”. ASEAN viewed the
establishment of the cooperation of APEC as an opportunity to enhance trade in the
entire region. Founded in 1989; its members included the ASEAN nations and the
countries of Australia, Canada, Chile, Hong Kong, China, Japan, Korea, Mexico, New
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Zealand, Papua New Guinea, Peru, Russia, and Chinese Taipei. When united together,
APEC makes for a formidable economic force. Their members account for about 42%
of the world’s population, make up about 47% of the global trade, and total a combined
GDP of 17,921 USD billion. Strong internal relations resulted in a high level of intra-
regional trade, which, most likely, was not yet due to the existence of APEC. Of all of
their trade, 70% of APEC’s export destination and import sources are from intra-
regional trade7. Optimistic with this raw potential, APEC’s economies pursued a trade
openness known as “open regionalism.” This philosophy implied that any reductions of
trade barriers achieved for its members are extended to non-member countries.
Following this philosophy, APEC’s members reached a monumental agreement at a
meeting on Bogor in 1994, which established the long-term objectives of investment
and open trade. The agreement asserted that nations were required to lower trade
barriers. Yet this philosophy was easier agreed upon then implemented. Since 1994,
several attempts were made to implement the Bogor Agreement. A meeting in Manila
established clear steps by setting the Manila Action Plan for APEC (MAPA). The
MAPA contained the Individual Action Plans (IAPs) and the Collective Action Plans
(CAPs). It also included the elimination of non-tariff measures, standard harmonization,
deregulation, governmental procurement, trade liberalization measures, and the
intervention in situations of trade frictions (Soesastro, 1995). APEC’s process of trade
liberalization, however, remained completely voluntary and represented the concerted
unilateral actions undertaken by individual APEC members based on their own
priorities, plans, and level of development. Though the APEC agreement remained
nonbinding and the organization itself retained some flaws, the experience provided
ASEAN with an important stepping stone of its path to successful trade liberalization.
7These specific statistics date back to the year 2000.
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1.5 ASEAN Free Trade Area (AFTA)
ASEAN found some success with their free trade initiatives with the establishment of
the ASEAN Free Trade Area (AFTA). This occurred after “the ASEAN nations
reviewed their past and current trade agreements and agreed to move to a deeper
economic cooperation” (Soesastro, 1995). Initially, the main objectives of AFTA among
others included strengthening economic integration, creating a freer movement of goods
and increasing intra-ASEAN trade. ASEAN wanted AFTA to “provide and create an
integrated market of 330 million people, growing at 7% a year [in 1992]” and to
continue establishing an environment attractive to foreign investment. Learning from
the past mistakes and benefiting from the passage of time, ASEAN believed they finally
knew how to effectively generate intra-regional trade and liberalize the economy. Table
1.1 shows a short description on the key chronology of AFTA from 1992 to 2015.
AFTA asserted that all ASEAN goods could be traded to member states’ markets
with either minimum tariffs or without any tariffs. AFTA appeared more promising than
the ASEAN PTA. Additionally through AFTA the process of trade liberalization
seemed to be occurring much more fairly than under the ASEAN PTA. For instance,
unlike under the ASEAN PTA no reciprocal rule existed in AFTA stating that only the
nominating country could grant margin preferences. Instead, AFTA contained a tariff
reduction schedule under the Common Effective Preferential Scheme (CEPT) that
applied to all ASEAN members.
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Table 1.1: Chronology of AFTA-related developments in ASEAN, 1992-2015
Year Event/Target 1992 ASEAN Free Trade Agreement (AFTA) and a Common Effective
Preferential Tariff (CEPT) introduced and signed. 1995 ASEAN Framework Agreement on Services (AFAS) introduced and
signed 1997 Chiang Mai Initiative (CMI) was introduced while facing the Asian
Financial Crisis ASEAN Vision 2020 was adopted
2003 Bali Concord II: ASEAN Community is comprised of three pillars: i. ASEAN Political-Security Community,
ii. ASEAN Economic Community, and iii. ASEAN Socio-Cultural Community
2007 ASEAN Charter and ASEAN Economic Community (AEC) Blueprint signed
2010 Elimination of tariffs for products under CEPT Inclusion Lists of ASEAN-6 for intra-ASEAN trade ASEAN Trade In Goods Agreement (ATIGA) implemented and the cancelation of NTMs by Brunei Darussalam, Indonesia, Malaysia, Singapore, and Thailand Target of elimination of all barriers to trade and allow 70% ASEAN equity ownership in four priority service sectors (air travel, e-ASEAN, health care, tourism)
2013 Target of elimination of all barriers to trade and allow 70% ASEAN equity ownership in logistics services
2015 Target of ASEAN Economic Community Target of elimination of tariffs by Cambodia, the Lao People's Democratic Republic, Myanmar, and Viet Nam Target of elimination of all barriers to trade and allow 70% ASEAN equity ownership in all service sectors
Source: Author’s Illustration
In order to expedite the process of trade liberalization along the 25th ASEAN
Economic Minister Meeting (AEM) and the 4th AFTA Council, ASEAN members opted
to shorten the AFTA implementation schedule. They accomplished this by introducing
two programs of tariff reduction: the Fast Track Program and the Normal Track
Program. Under the Fast Track Program tariffs above 20% would be reduced to 0-5%
within ten years or by January 2003 and tariffs at 20% or below would be reduced to 0-
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5% within seven years8. Sectors in the Fast Track Program included fats & oils, mineral
products, chemicals, plastics, leather & hides, paper & pulp, apparel & textiles, gems,
cement, metal articles & base metals, electrical appliances & machinery, and
miscellaneous manufactured articles. Meanwhile products or goods in the Normal Track
Program with tariffs above 20% would be reduced to 20% within five to eight years and
then to 0-5% within seven years or by 2008. Tariffs of 20% or below in this program
would be reduced to 0-5% within ten years.
Yet the original CEPT Scheme did exclude some products and thus drew several
criticisms. As of the January 1992 ASEAN Summit, the CEPT Scheme included fifteen
product groups and 41,147 tariff lines. This accounted for about 88% of the tariff lines.
All unprocessed and processed agricultural products except vegetable oil, however,
were excluded from the original agreement9. By this time Southeast Asia experienced a
decline in agricultural shares, which indicated the degree of the area’s industrialization.
Even so strong objections were raised to this exclusion, because the agricultural
industry remained an important part of Southeast Asia’s economy. Most critics proved
unsatisfied by just AFTA’s acknowledgment of agriculture with just the creation of the
ASEAN Cooperation on Food, Agriculture, and Forestry (COFAF). Though this
committee aimed to strengthen food security in the region and to facilitate intra-ASEAN
and international trade in agricultural and forestry product, it did not seem ambitious
enough for proponents of ASEAN’s agricultural sector10.
8 Indonesia, Malaysia, the Philippines and Thailand all agreed to the first part of the Fast Track Program; while all of these countries except Thailand committed to the second part of the Fast Track Program.
9 The inclusion of vegetable oil or palm oil as the only agricultural product in the CEPT scheme made sense considering both Malaysia and Indonesia produced a large amount of palm oil annually.
10Other objectives of COFAF were to increase productivity using technology, build agricultural rural communities and human resources, develop private sector involvement and investment, manage and conserve natural resources, and strengthen ASEAN cooperation and joint approaches.
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In the 1990s, the agriculture sector still retained a not-irrelevant percentage of
foreign earnings for all of the ASEAN nations except Singapore. 13.5% of Indonesia’s
total export value, 10.5% of Malaysia’s, 9.9% of the Philippines’, and 22.7% of
Thailand’s stemmed from the agricultural sector. Furthermore, 5.8% of Thailand’s total
export value alone came from rice exports. The agricultural sector additionally
remained noteworthy for generating national income and providing jobs and
opportunities to those individuals in rural areas. Using statistics and information like the
value of agricultural products and the industry at large AFTA’s critics persuasively
argued that these products should be included on the CEPT Scheme.
In September 1994 revision of the CEPT Scheme included unprocessed agricultural
products. The new CEPT Scheme consisted of three lists for the different agricultural
products: the Immediate Inclusion List, the Temporary Exclusion List, and the
Sensitivity List. 87% or 1,760 of tariff lines fell under the Immediate Inclusion List or
the Temporary Exclusion List and by 2003 all of those of the products in the first two
lists merged into the CEPT Scheme. Similarly, products on the sensitive list all began
their transitioning their liberalization to the CEPT Scheme by 2010. Eventually, all the
products in these lists will have final import tariffs from 0-5%. These revisions
demonstrated ASEAN’s acknowledgement of the importance of the agricultural sector
on intra-regional and foreign trade and resulted in a growth in intra-ASEAN agricultural
trade.
In 2004, ASEAN also recognized the rapidly growing influence of other industries
on the Southeast Asian landscape. ASEAN leaders agreed to accelerate the reduction of
tariffs on eleven industries deemed a priority integration sector. All of the priority
integration sectors were selected on the basis of comparative advantage in natural
resource endowments, labour skills and cost competitiveness, and value-added
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contribution to ASEAN's economy. These sectors included the automotive industry, the
electronics industry, the wood-based industry, the airline industry, the tourism industry,
rubber products and textiles, and agro-based products, and fisheries. In 2003 the above
industries accounted for more than 50% of intra-ASEAN trade, 48.4 billion USD of
intra-ASEAN exports, and 43.4 billion USD of intra-ASEAN imports (ASEAN
Secretariat, 2015). As ASEAN leaders decided, completion of tariff reductions for these
sectors occurred in 2007 after being brought forward three years from 2010. Overall,
“gradually reduced trade barriers together with macroeconomic stabilization resulted in
an increase in export and trade” and brought notable success to AFTA (Shimizu, 2007).
ASEAN kept working diligently to make ASEAN nations attractive destinations for
external investment. The ASEAN Investment Area (AIA), founded in October 1998 and
signed by ASEAN Economic Ministers in Manila, aimed to encourage direct flow from
inside and outside ASEAN aiming to make a competitive, open and liberal investment
area. The ASEAN Economics Ministers aimed to build ASEAN as a competitive
investment area by the 1st of January 2010 and establish the area as a free investment
region by 2020. Furthermore, in the 2000s ASEAN began negotiating a series of free-
trade agreements (FTAs) with third parties. In 2012 ASEAN arranged both a FTA with
China and a Comprehensive Economic Partnership with Japan which had elements of
an FTA. They also worked to establish an FTA with India between 2011 and 2016.
Additionally bilateral FTAs between individual ASEAN members and non-ASEAN
parties were numerous: a total of 26 non-reported initiatives and 8 WTO-notified
agreements (Pelkmans-Balaoing, 2007). These agreements are both independent of
ASEAN and through ASEAN, helped further initiate trade and export in ASEAN.
1.6 ASEAN Vision 2020
In a December 1997 ASEAN summit, the Heads of Governments of ASEAN signed
the ASEAN Vision 2020. The ASEAN Vision 2020 did not propose any new
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institutions or measures, but it did envision the completion of a number of ASEAN’s
central goals. Goals in the ASEAN Vision 2020 included:
i. The ASEAN region be in full reality;
ii. The Zone of Peace, Freedom, and Neutrality be fully established;
iii. The Treaty of Amity and Cooperation in Southeast Asia be functioning fully;
iv. The ASEAN region be free from all weapons of mass destruction;
v. The gap in the level of development among members be significantly narrowed;
vi. The entire region of Southeast Asia be bound by a common regional identity;
vii. The emergence of ASEAN as a green organization and a leader in sustainable
development;
viii. The intensification of the relationship between an outward-looking ASEAN, its
Dialogue Partners, and other regional organizations.
These goals demonstrate the motivation behind ASEAN’s newest policies, their
visions for the future, and their complete faith in the enduring strength of their
organization.
1.7 ASEAN Economic Community
The 9th ASEAN Summit on October 2003 was the turning point in establishing the
ASEAN Economic Community. It was during this summit when ASEAN agreed to
adopt the “Declaration of ASEAN Concord II”. This declaration stated that the ASEAN
Economic Community, as envisioned by ASEAN, hopes to maintain the following
characteristics:
i. A production base and single market;
ii. A highly competitive economic region;
iii. A region of equitable economic development;
iv. A region that is completely integrated into the global economy.
In order to achieve these goals AEC will have areas of mutual cooperation that
include human resources development, more in-depth consultation on financial and
microeconomic policies, trade financing measures, improved communications
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connectivity and infrastructure, development of electronic transactions through e-
ASEAN, regional sourcing promoted through integrated industries, and enhanced
private sector involvement in ASEAN. All in all, the AEC hopes to “transform ASEAN
into a region with free movement of goods, services, investment, skilled labour, and
freer flow of capital” (ASEAN Economic Community). As adopted by the ASEAN
Leaders on the 20th of November 2007 in Singapore, the ASEAN Economic Blueprint
documents the master plan that guides the development of the AEC.
1.8 ASEAN Trade in Goods Agreement (ATIGA)
At the 21st ASEAN Free Trade Area (AFTA) Council Meeting held in the
Philippines in August 2007, there was consensus among ASEAN countries of adopting
a comprehensive trade in goods agreement in ASEAN. During the meeting, ASEAN
economic ministers expressed the need to further improve and expand the current CEPT
scheme and to transform it into a comprehensive trade in goods agreement.11 (Table 1.2
provides the milestones and key documents from the emergence of CEPT up to
ATIGA.)
The move to develop a comprehensive agreement governing most aspects of trade in
goods within the region occurred at a time when ASEAN is nearing the completion of
AFTA, and has begun forging free trade agreements with its major trade partners. In
2007, nearly 93.67 per cent of the total products in ASEAN have zero to 5 per cent
tariffs, in accordance with the implementation of the provisions of CEPT. During the
same year, 98.58 per cent of the total products in the region, including sensitive
commodities, have already been phased into the CEPT Inclusion list. The average tariffs
on intra-ASEAN trade among the ASEAN 6, reduced to 1.6 per cent in 2007, from
11 See the ASEAN Joint Media Statement on the 21st Meeting of the ASEAN Free Trade Area (AFTA) Council held in Makati City, Philippines in August 2007.
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12.76 per cent in 1993. The average import duty on intra-ASEAN trade for Cambodia,
Laos, Vietnam and Myanmar was at 4.4 per cent in 2007 (ASEAN Secretariat, 2007).
These indications were clear to propose that there was an increasing recognition that
tariff reduction alone was not sufficient to ensure the free flow of goods within the
region and with trade partners. In ASEAN itself, there was a growing awareness of the
need to address the issue of non-tariff measures to further facilitate trade in goods. In
2007, ASEAN was already in the process of promoting the consistency and
transparency of technical regulations on intra-ASEAN trade through the development of
the ASEAN Guideline on Good Regulatory Practice.
Another underlying reason for ASEAN to enhance the CEPT scheme was due to the
increasing number of free trade agreements and trade liberalization efforts with its
Dialogue Partners, which require better tariff and non-tariff measures. The AFTA
Council resolved to finalize and present the Trade in Goods Agreement in the 40th
ASEAN Economic Ministers Meeting, which was slated in August 2008 in Singapore.
The Philippines, along with other ASEAN members, formally signed ATIGA in
February 2009. The agreement was formally signed in 2009 and it was one of the many
agreements signed by ministers during the 14th ASEAN Summit. The signing of
ATIGA, among others was aimed to benefit the forecasted benefits from regional
integration, which includes increased trade and investment and bigger market with
greater opportunities and at the same time to increase intra-ASEAN trade.
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Table 1.2: Milestones from CEPT to ATIGA
1992 Agreement on the Common Effective Preferential Tariff Scheme for the
ASEAN Free Trade Area, Singapore, 28 January 1992
1995 Protocol to Amend the Agreement on ASEAN Preferential Trading
Arrangement, Bangkok, 15 December 1995
1995 Protocol for the Accession of the Socialist Republic of Vietnam to the
Framework Agreements on Enhancing ASEAN Economic Cooperation,
Bangkok, 15 December 1995
Protocol to Amend the Agreement on the Common Effective Preferential
Tariff Scheme for the ASEAN Free Trade Area, Bangkok, 15 December 1995.
Protocol for the Accession of Socialist Republic of Vietnam to the Agreement
on the Common Effective Preferential Tariff Scheme for the ASEAN Free
Trade Area, Bangkok, 15 December 1995
1998 ASEAN Framework Agreement on the Facilitation of Goods in Transit, Ha
Noi, 16 December 1998
Protocol on Notification Procedures, Makati, Philippines, 8 October 1998
1999 Protocol on the Special Arrangement for Sensitive and Highly Sensitive
Products, Singapore, 30 September 1999
2000 Protocol Regarding the Implementation of the CEPT Scheme Temporary
Exclusion List, Singapore, 22-25 November 2000
2003 Protocol to Amend the Agreement on the Common Effective Preferential
Tariff (CEPT) Scheme for the ASEAN Free Trade Area (AFTA) for the
Elimination of Import Duties, 31 January 2003
2004 First Protocol to Amend the Protocol on Special Arrangements on Sensitive
and Highly Sensitive Products, 3 September 2004
2007 Protocol to Provide Special Consideration for Rice and Sugar, 23 August 2007
2009 ASEAN Trade in Goods Agreement, Cha-am, Thailand, 26 February 2009
2010 Protocol to Amend the Protocol to Provide Special Consideration for Rice and
Sugar, Ha Noi, Viet Nam, 28 October 2010
Source: Author’s Illustration
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1.9 ASEAN Economies
Table 1.3 shows the basic indicators of all 10 ASEAN countries in 2015. It must be
noted that in terms of population and land area, ASEAN is already diverse. Indonesia
for instance with the largest population land area forms the majority of ASEAN’s land
and population. Diversity can also be seen in terms of population density. Singapore
with 7,540 persons per km is more than 50 times denser than average ASEAN
population density. This trend is also reflected in the GDP.
ASEAN’s trade in goods data according to countries is shown in Table 1.4. Major
exporters of ASEAN above the mark of 100 billion USD are Indonesia, Malaysia,
Thailand, Singapore and Vietnam and the major importers above the same value are the
same countries as well.
Table 1.3 : ASEAN Basic Indicators 2015
Country Total land area
Total population
Population density
Annual population
growth
Gross domestic product
at current prices
Gross domestic product
per capita at current prices
km2 thousand persons per km2
percent US$ million US$ US$ PPP
Brunei Darussalam
5,769 406 70 1.6 16,117 39,678 73,775
Cambodia 181,035 14,962 83 1.5 15,511 1,036 3,081
Indonesia 1,860,360 248,818 134 1.4 860,849 3,459 9,467
Lao PDR 236,800 6,644 28 2.0 10,283 1,547 4,531
Malaysia 330,290 29,948 91 1.5 312,071 10,420 23,089
Myanmar 676,577 61,568 91 1.0 54,661 887 3,464
Philippines 300,000 99,384 331 1.8 269,024 2,706 6,403
Singapore 716 5,399 7,540 1.6 297,941 55,182 78,761
Thailand 513,120 68,251 133 0.5 387,573 5,678 14,131
Viet Nam 330,951 89,708 271 1.1 171,219 1,908 5,314
ASEAN 4,435,618 625,090 141 1.3 2,395,252 3,831 9,389
Source: (ASEAN Secretariat, 2015)
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Table 1.4 : ASEAN Exports and Imports by country in 2015
Country International merchandise trade
Exports Imports Total trade
US$ million US$ million US$ million
Brunei Darussalam 11,445 3,611 15,057
Cambodia 9,148 9,176 18,324
Indonesia 182,551 186,628 369,180
Lao PDR 2,592 3,292 5,884
Malaysia 228,331 205,897 434,228
Myanmar 11,436 12,009 23,445
Philippines 53,978 65,130 119,108
Singapore 410,249 373,015 783,265
Thailand 228,730 249,517 478,247
Viet Nam 132,664 132,109 264,774
ASEAN 1,271,128 1,240,388 2,511,516
Source: (ASEAN Secretariat, 2015)
In terms of Intra-ASEAN exports as shown in Table 1.5, Singapore, Malaysia and
Thailand dominate in terms of value, however, in terms of share to total exports, Lao
PDR and Myanmar with 55% and 39.5% show that these two countries are very much
export dependent to ASEAN, despite their low value of exports.
Table 1.5: Intra-ASEAN and Extra-ASEAN exports by country year 2015, value in USD million, share in percent
Country Intra-ASEAN exports Extra-ASEAN exports Total exports
Value Share to total
exports
Value Share to total exports
Brunei Darussalam 2,093 19.8 8,491.1 80.2 10,584.1
Cambodia 2,037 19.1 8,643.5 80.9 10,681.4
Indonesia 39,822 22.6 136,470.5 77.4 176,292.7
Lao PDR 1,451 55.0 1,188.6 45.0 2,639.9
Malaysia 65,297 27.9 168,864.2 72.1 234,161.2
Myanmar 4,362 39.5 6,668.3 60.5 11,030.6
Philippines 9,211 14.9 52,598.7 85.1 61,809.9
Singapore 127,739 31.2 282,029.5 68.8 409,768.7
Thailand 59,425 26.1 168,147.8 73.9 227,573.6
Viet Nam 18,260 12.3 129,831.0 87.7 148,091.5
ASEAN 329,700.4 25.5 962,933.2 74.5 1,292,633.6
Source: (ASEAN Secretariat, 2015)
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Table 1.6: Intra-ASEAN and Extra-ASEAN imports by country year 2015, value in USD million, share in percent
Country Intra-ASEAN imports Extra-ASEAN imports Total imports
Value Share to total imports
Value Share to total imports
Brunei Darussalam 1,767.6 49.1 1,828.9 50.9 3,596.6
Cambodia 5,577.6 29.4 13,395.6 70.6 18,973.2
Indonesia 50,903.1 28.6 127,275.7 71.4 178,178.8
Lao PDR 2,045.0 74.4 703.9 25.6 2,748.9
Malaysia 53,779.1 25.7 155,139.1 74.3 208,918.2
Myanmar 7,092.6 43.7 9,133.4 56.3 16,226.1
Philippines 16,158.8 23.8 51,598.2 76.2 67,756.9
Singapore 75,457.2 20.6 290,790.1 79.4 366,247.3
Thailand 43,299.5 19.0 184,652.8 81.0 227,952.3
Viet Nam 22,537.1 15.5 123,148.4 84.5 145,685.6
ASEAN 278,617.6 22.5 957,666.2 77.5 1,236,283.8
Source: (ASEAN Secretariat, 2015)
Similar trend also can be seen in Intra-ASEAN imports where the share of Lao PDR
and Myanmar seems to be high, however, Brunei also has a high share of intra-ASEAN
imports. In terms of value, the same countries still dominate. As a summary, the total
intra-ASEAN trade and extra-ASEAN trade as shown in Table 1.7, Malaysia, Singapore
and Thailand has the highest values although in terms of share, their shares are very
much similar to the average ASEAN value. Lao PDR and Myanmar seems to have the
highest share of intra-ASEAN trade.
Intra-ASEAN trade increased at a faster rate than either overall ASEAN trade or
extra-ASEAN trade, with annual growth averaging at 10.5% as compared with 9.2%
and 8.9%, respectively (between 1993 and 2013) as discussed above.
Total trade posted a sixfold increase since the beginning of AFTA, from US$430
billion in 1993 to US$2.5 trillion in 2013. Intra-ASEAN trade has surged by more than
sevenfold in the same period from US$82 billion to US$609 billion, while extra-
ASEAN trade grew more than five times, from US$348 billion to US$1.9 trillion.
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Table 1.7: Intra-ASEAN and Extra-ASEAN trade by country year 2015 in USD million, share in percent
Country Intra-ASEAN trade Extra-ASEAN trade Total trade
Value Share to total trade
Value Share to total trade
Brunei Darussalam 3,860.6 27.2 10,320.1 72.8 14,180.7
Cambodia 7,615.5 25.7 22,039.1 74.3 29,654.6
Indonesia 90,725.3 25.6 263,746.2 74.4 354,471.5
Lao PDR 3,496.3 64.9 1,892.5 35.1 5,388.8
Malaysia 119,076.0 26.9 324,003.3 73.1 443,079.4
Myanmar 11,455.0 42.0 15,801.7 58.0 27,256.7
Philippines 25,370.0 19.6 104,196.9 80.4 129,566.9
Singapore 203,196.4 26.2 572,819.6 73.8 776,016.0
Thailand 102,725.3 22.6 352,800.6 77.4 455,525.9
Viet Nam 40,797.7 13.9 252,979.4 86.1 293,777.1
ASEAN 608,318.0 24.1 1,920,599.4 75.9 2,528,917.4
Source: (ASEAN Secretariat, 2015)
Figure 1.1 : Trend of ASEAN Total Trade and Intra-ASEAN Trade, 1993-2013
Source: (ASEAN Secretariat, 2015)
In terms of tariff lines reductions, ASEAN-6, namely Brunei Darussalam, Indonesia,
Malaysia, Philippines, Singapore and Thailand, has applied zero tariff rates for intra-
ASEAN trade in more than 99% of tariff lines since 2010. Progress has also been made
in the newer ASEAN Member States, i.e. Cambodia, Lao PDR, Myanmar, and Viet
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Nam (CLMV) where zero tariff rates have been applied to 72.6% of tariff lines in 2013,
a significant increase from only 45.9% in 2010. The trend is shown in Figure 1.2.
Figure 1.2 : Trend of the percentage of CEPT tariff lines with zero tariff rates, 2000-2013
Source: (ASEAN Secretariat, 2015)
1.10 ASEAN Selected Industries
1.10.1 Agriculture Sector
Agriculture has always been a very important sector to ASEAN. Even before
ASEAN existed, most of the ASEAN countries were predominantly dependent on
agriculture sector. Due to similar weather, land availability, demand for similar
agriculture produces, ASEAN countries typically produce similar products and the
surpluses from the local demand is then exported. That was initially the basic concept of
agriculture trade in ASEAN. With the advancement of technology and efforts to uplift
the agriculture sector by individual ASEAN countries, there are today several products
from some ASEAN countries around the world and some countries in ASEAN such as
Thailand and Vietnam also have emerged as the most important exporter of rice in the
world, which is an important staple food in many countries in Asia.
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As shown in Table 1.8, the exports of ASEAN-512 in the agriculture sector has
increased nearly 5 times from year 2001 to 2014. The total share of agriculture sector
however remained in the range of 3-4% only and this signals that despite the increase in
value of exports, the agriculture sector did not grow as rapidly as total ASEAN-5
exports to the world.
Similarly, as shown in Table 1.9, the values of export of ASEAN-5 countries
also increased from year 2001 to 2014. Thailand’s value increased from USD2.6 bilion
in 2001 to USD10.6 billion in 2014 and Vietnam made a bigger leap from USD1.7
billion to USD9.5billion for the same period of time. Figure 1.3 shows the intense
competition in exports between Thailand and Vietnam. Vietnam’s value of exports was
closely following the value of Thailand up to year 2010, when Vietnam overtook
Thailand’s value. The competition between both these countries still exists until today,
mostly due to the exports of rice.
Table 1.8: Share of agriculture sector to all products exports of ASEAN-5 countries (values in USD thousand)
2001 2005 2008 2011 2014
Exports of ASEAN-5 5,862,747 9,414,932 19,134,877 25,527,156 26,311,183 All Exports of ASEAN-5 to the World
191,881,734
328,867,192
492,805,612
611,760,305
691,135,682
Share of Exports (%) 3% 3% 4% 4% 4%Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Table 1.9: Value of agriculture exports of individual ASEAN-5 countries (values
in USD thousand) ASEAN-5 2001 2005 2008 2011 2014
Malaysia 309,343 365,224 526,995 767,455 877,112
Thailand 2,576,589 3,708,913 8,353,316 10,398,967 10,619,249
Indonesia 738,553 1,295,998 2,186,816 2,706,674 3,227,532
Philippines 544,429 690,044 904,803 1,204,917 2,051,762
Vietnam 1,693,833 3,354,753 7,162,947 10,449,143 9,535,528Source: Author’s Illustration and (ASEAN Secretariat, 2015)
12 ASEAN-5 for this study is limited to Malaysia, Thailand, Indonesia, Philippines and Vietnam
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Figure 1.3: Value of agriculture exports of individual ASEAN-5 countries in years (2001-2014)
In terms of product categories, HS100- Maize (corn), Rice, Buckwheat, millet
and canary seed, Oats, Barley, Wheat, and Rye recorded the highest value especially
due to the exports of rice. This was surprisingly followed by HS090- Coffee, Tea,
Pepper, Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla as
ASEAN countries were not top exporters of coffee and tea in the 1990s. The value for
this product category, particularly led by coffee and tea, climbed to USD6.3 billion in
2014, which shows rapid growth, and it also complements the concentration of rice
exports. Another product that also complements rice export is HS080- Nuts, Citrus
Fruits, Banana, Melons, Grapes, Apricots, and Apples. ASEAN’s export in this category
increased in this category mainly due to the exports of local fruits found in many
ASEAN countries, such as banana, pineapple and watermelon.
The integration of the agriculture sector under ASEAN is guided by the ASEAN
Roadmap for Integration of Agro-based Products. The product coverage in the roadmap
are both limited in number and value when it is compared to the range of agriculture
‐
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
14,000,000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Malaysia
Thailand
Indonesia
Philippines
Vietnam
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products traded within ASEAN and between ASEAN and its trading partners. The
roadmap only covers some agricultural products such as peas and beans, certain seeds,
tomatoes and related products, and vegetable oils. The measures identified in the
roadmap to increase intra-ASEAN trade and investment are tariff elimination, non-tariff
measures, customs cooperation, implementation of CEPT, rules of origin improvement,
standards and conformance and logistics.
Table 1.10: Top 5 agriculture products (HS3 level) of ASEAN-5 countries (values in USD thousand)
Products 2001 2005 2008 2011 2014 Maize (corn), Rice,
Buckwheat, millet and canary seed, Oats, Barley,
Wheat, Rye
2,284,596 3,792,265 9,299,798 10,368,126 7,612,219
Coffee, Tea, Pepper , Capsicum, Cinnamon
Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla
1,134,339 1,855,369 4,133,031 5,571,648 6,271,014
Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots,
Apples 769,709 1,433,095 2,118,409 3,182,877 4,421,034
Manioc, Frozen Vegetables, Dried Vegetables
418,882 551,644 875,153 1,740,488 2,296,891
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt,
Wheat Gluten
282,426 486,612 942,243 1,897,144 1,901,039
Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Intra-ASEAN trade in the agriculture sector has not increased in most ASEAN
countries. This is due to the fact that most ASEAN countries produce the same or
similar products. Most ASEAN countries also have the same export market and tend to
compete with each other.
ASEAN agriculture products are also predominantly produced to fulfill the domestic
needs. However, integration only exists when it is technology-driven by large
agriculture-based companies and trade investors in ASEAN countries. The emergence
of large ASEAN businesses such as Sime Darby and San Miguel Corporation offers
some form of integration as well. In a research undertaken by the Southeast Asia
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Council on Food Security and Fair Trade or SEACON, on the impact of AFTA on the
rice sector, the study concluded that in many parts of Southeast Asia, millions of small
farmers have not and will have a hard time taking advantage of the opportunities
brought about by an expanding ASEAN market. It appears that the benefits of expanded
trade have been captured by processors, exporters or importers, middlemen or traders
while the small producers have remained poor (Bernabe, 2009).
Another view on agriculture sector integration is that the biggest integration in
ASEAN is not taking place through tariff elimination or other formal arrangements but
through biotechnology. Companies such as Cargill, Monsanto and Dupont are
transforming ASEAN rural areas into a big biotechnology lake with some help from the
Asian Development Bank (ADB) and some initiatives under ASEAN. These types of
corporations work by mobilizing support of ASEAN’s leading creditor, engaging with
ASEAN leaders, assist in training, demonstration farms and technical assistance on
biotechnology. They have narrowed the definition of food security to merely access of
food (Ofreneo, 2004).
1.10.2 Automotive Industry
The automotive industry in ASEAN is concentrated in the ASEAN-5 countries. Most
of the automotive industry exist in these countries due to technological expertise,
manufacturing capacity, infrastructure and vehicle manufacturing base, some of which
were transferred to these countries from investors or the initiatives embarked by the
countries under its respective automotive or manufacturing policies.
As shown in Table 1.11, the exports of ASEAN-5 countries to the world in the
automotive industry increased from USD5.2 billion to around 8 times higher value in
2014 with USD42.7 billion. The export values generally increased rapidly and the share
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of the automotive industry to total exports of all products also rose from 3% in 2001
gradually to 6% in 2014.
Table 1.11: Share of automotive industry to all products exports of ASEAN-5 countries (values in USD thousand)
2001 2005 2008 2011 2014 Exports of ASEAN-5 5,208,469 14,060,261 27,329,703 32,824,223 42,672,043 All Exports of ASEAN-5 to the World 191,881,734 328,867,192 492,805,612 611,760,305 691,135,682
Share (%) 3% 4% 6% 5% 6%Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Among the ASEAN-5 countries, Thailand has the highest value of export in the
automotive industry. As shown in Table 1.12 and Figure 1.4, Thailand’s export value
grew from USD3.1 billion in 2001 to USD 29.7 billion in 2014. Malaysia and Indonesia
recorded an increasing value as well, although, the value is way lower than Thailand.
Philippines recorded a growing value until year 2011 and the value decreased
tremendously from USD2.5 billion in 2011 to USD1.7 billion in 2014. Vietnam also
recorded an increasing trend, and since 2011 onwards, the export value of Vietnam in
the automotive industry grew rapidly and overtook the value of Philippines.
Table 1.12: Exports of ASEAN-5 countries in automotive industry (value in USD
thousand)
Country 2001 2005 2008 2011 2014 Malaysia 411,977 958,276 1,582,240 1,823,017 2,284,841Thailand 3,147,154 9,051,622 18,567,069 21,953,975 29,720,566Indonesia 738,968 1,948,060 3,913,461 5,231,006 6,899,067Philippines 725,265 1,688,638 2,472,905 2,508,394 1,672,120Vietnam 185,105 413,665 794,028 1,307,831 2,095,449
Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Thailand is the largest exporter in the automotive industry among the ASEAN-5
countries due to several factors. One of the most important factor is Thailand’s
openness to investments and its large automotive production base that is able to bring
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in various global component and parts manufacturers. Since most of the investors are
from more developed countries, the production in Thailand required high standards and
this helped Thailand raise its overall performance of the local industry. Thailand is
also ASEAN’s largest automotive market and most procurement activities in the
automotive industry happen in Thailand. This has resulted in high number of
component manufacturers to be present in Thailand to be in direct contact with their
customers.
Figure 1.4: Exports of ASEAN-5 countries in automotive industry by country (value in USD thousand)
Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Thailand is the largest exporter in the automotive industry among the ASEAN-5
countries due to several factors. One of the most important factor is Thailand’s
openness to investments and its large automotive production base that is able to bring
in various global component and parts manufacturers. Since most of the investors are
from more developed countries, the production in Thailand required high standards and
this helped Thailand raise its overall performance of the local industry. Thailand is
also ASEAN’s largest automotive market and most procurement activities in the
automotive industry happen in Thailand. This has resulted in high number of
‐
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
2001 2005 2008 2011 2014
Malaysia
Thailand
Indonesia
Philippines
Vietnam
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component manufacturers to be present in Thailand to be in direct contact with their
customers.
In contrast, Malaysia is the only ASEAN country that established its own
automotive brand and product. Since the inception of Proton in 1984, the automotive
industry in Malaysia has grown in the same pace as Proton itself (Austria, 2004). It is
also argued that Malaysia’s industry manufactures components and parts for the
automotive sector that are with the quality specifications of Proton and fail to adhere to
the standards and quality of international and global carmakers. There are also reports
mentioning that Malaysian auto parts producers move to Thailand in order to compete in
the global market (Lau, 2006). Automotive part producers in other parts of ASEAN are
mostly smaller players that lack the capabilities to be globally competent.
The initial production integration in ASEAN was first driven by using the
ASEAN Industrial Cooperation Scheme (AICO) system, especially used by Japanese car
makers and part producers. AICO was launched in 1996 and can be regarded as one of
the most important element of the automotive roadmap to promote resource sharing
among ASEAN members in order to increase industrial growth and investment, improve
manufacturing scale economies, and widen the scope of ASEAN-based industries, and
thus achieve greater ASEAN integration (Lau, 2006). Japanese carmakers took this
opportunity to consolidate and rationalize production throughout ASEAN. One good
example was Toyota where it was able to establish a production system whereby
components from Thailand, Malaysia, and Indonesia were exported to the Philippines
for assembly of certain motor vehicles (e.g., the Toyota Camry and Corolla). In return,
Thailand, Malaysia, and Indonesia were obliged to import certain motor vehicle
components from the Philippines for the assembly of designated motor vehicles (e.g., the
Kijang and Soluna) in their respective countries (Lau, 2006). By using this method,
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Toyota was able to concentrate the production of components in individual countries and
achieve the economies of scale necessary to produce cost-effectively.
The biggest obstacles to greater intra-regional trade and production are non-
tariff barriers. While ASEAN have long acknowledged this as a problem, non-trade
barriers remain extremely hard to eliminate, not least because they vary greatly in
nature, from customs surcharges to technical product requirements. The incidence of
non-tariff barriers in the automotive sector is high in terms of additional taxes and
charges, as well as technical regulations (Singapore), automatic import licensing
(Brunei and Malaysia) and non-automatic import licensing (Indonesia and the
Philippines) (ASEAN Secretariat, 2015).
Although the ASEAN integration is creating conditions to facilitate greater
cooperation among countries, robust intra-regional competition continues. As a result,
the automotive industry is a particularly difficult sector in which to build consensus
because individual countries (e.g., Malaysia, Indonesia, and Thailand) want to be the
regional hub for the industry (Lau, 2006).
1.10.3 Textile and Clothing Industry
In general, ASEAN as a region and some ASEAN countries in particular are well-
known producers and exporters of textiles and clothing to the world. ASEAN has
clinched around 9.4% of the total world exports in this industry as of year 2015. For the
purpose of this research, the textile and clothing industry is investigated for the
ASEAN-513 countries. As shown in Table 1.13, the value of ASEAN-5’s exports of
textile and clothing products nearly tripled from USD24.4 billion in year 2001 to
13 For this thesis, ASEAN-5 is restricted to Malaysia, Thailand, Indonesia, Philippines and Vietnam
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USD71.8 billion in year 2014. Although the value increased dramatically, the share of
exports remain in the range of 9-10% from year 2005 onwards, mostly due to also the
rapid increase in value for all product exports of ASEAN-5.
Table 1.13: Share of Textile and Clothings Industry to all products exports of ASEAN-5 countries (values in USD thousand)
2001 2005 2008 2011 2014 Exports of ASEAN-5 24,385,026 31,793,894 37,690,297 55,177,235 71,759,100 All Products export for ASEAN-5 191,881,734 328,867,192 412,035,935 611,760,305 691,135,682
Share of Exports 13% 10% 9% 9% 10%Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Specifically based on country level value, the ASEAN-5’s exports in the textile and
clothing industry can be described in Table 1.14 and Figure 1.5 below. Although there
is a general trend of increase in value for the year 2001 to 2014 for all countries except
for Philippines, the value recorded by Vietnam is completely at its own category.
Vietnam’s export rose from USD3.8 billion in year 2001 to USD40.6 billion for the
same period. The increase in value is more than 10 times and this is precisely shown in
Figure 1.5. The surpassing of Vietnam against other ASEAN countries after year 2005
can be viewed also as a normalisation effect in values for other ASEAN countries.
Other ASEAN countries did not really grow in value after the emergence of Vietnam as
the top exporter of textile and clothing. This Vietnam’s effect is partly due to Vietnam’s
accession to World Trade Organization (WTO) in year 2007, allowing the exports to
larger markets at better tariffs.
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Table 1.14: Exports of ASEAN-5 countries in textile and clothings industry (value in USD thousand)
ASEAN-5 Countries 2001 2005 2008 2011 2014
Malaysia 2,387,187 2,799,730 3,223,696 3,738,460 3,555,134
Thailand 6,154,507 7,655,345 8,202,853 9,311,883 8,351,972
Indonesia 9,208,361 10,063,179 12,054,495 16,582,753 16,875,587
Philippines 2,694,461 2,589,197 2,237,298 1,624,200 2,174,932
Vietnam 3,839,886 8,485,017 15,115,220 23,630,922 40,587,015
Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Figure 1.5: Value of Exports in USD Billion for ASEAN-5 in textile and clothing industry
Source: Author’s Illustration and (ASEAN Secretariat, 2015)
Apart from the country level export values, the top five product categories with
the highest exports for ASEAN-5 countries are shown in Table 1.15. Besides product of
HS540- Man-made: filaments yarn and synthetic yarn, all other products in the top 5 are
finished products. This implies that collectively the values of products exported by
ASEAN-5 countries are dependent on the four finished product categories. Although the
man-made filaments yarn and synthetic yarn did not record as high value as the four
finished products, it has a broader importance to some of ASEAN countries.
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5
10
15
20
25
30
35
40
45
2001 2005 2008 2011 2014
Malaysia
Thailand
Indonesia
Philippines
Vietnam
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ASEAN textile and clothing industry consist of mainly production of man-made
filaments yarn and synthetic yarn and fabrics in one country in ASEAN and shipped to
another country in ASEAN, to be made a finished product. ASEAN’s integration in the
textile and clothing industry would mean a comprehensive integrated textiles and
clothing industry with all elements of the supply chain across several ASEAN members
(i.e., the production of fibers, spinning of yarns, knitting or weaving of fabrics, and
cutting and sewing of finished apparel), as well as at least some regional integration into
global supply chains (George Siy, 2007).
Table 1.15: Top 5 product items in HS3 exported by ASEAN-5 in Textile and Clothing Industry (value in thousand USD)
HS Code Product Category 2001 2005 2008 2011 2014
620
Women and man:overcoat, jacket, dresses, undergarments etc
6,652,898 8,046,358 9,403,845 11,401,799 14,105,468
640 Footwear 4,133,863 5,558,785 7,949,057 11,162,334 19,293,803
610
Women and man: coat, jacket, suits, undergarments, knitted/croch etc
2,836,068 4,689,279 6,770,458 8,251,607 10,150,769
611
Jerseys, babies garments, track suits, swimwear kintted/croch etc
2,199,143 2,370,714 3,570,276 4,808,750 6,599,582
540 Man-made: filaments yarn and synthetic yarn
2,078,362 2,539,096 2,746,910 3,881,364 3,490,775
Source: Author’s Illustration and (ASEAN Secretariat, 2015)
In envisioning such level of integration, ASEAN embarked on the ASEAN’s
Roadmap for Integration of Textiles and Apparel Products Sector (ARITAP). ARITAP
covered the full textile and clothing supply chain, including raw fibers (e.g., raw cotton,
wool, and polyester staple fibers), yarns, fabrics, and finished apparel or textile articles.
It also provided the elimination of tariffs on intra-ASEAN trade in all sector products,
as well as other measures to encourage integration. The removal of global quotas also
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had a larger influence on the degree of production integration among the ASEAN
countries than the tariff eliminations and reductions mandated in ARITAP. The lifting
of these quotas under the World Trade Organization (WTO) Agreement on Textiles and
Clothing (ATC) on January 1, 2005, enormously increased competition among global
suppliers to the U.S. and EU markets, including the ASEAN countries.
ASEAN’s level of integration due to supply chain is also contributed by the variation
or uniqueness across individual ASEAN countries’ economies. The availability and
relative cost of labour are two important determinants of success in the clothing
industry. It has been a precedence to locate the more labour intensive clothing factories
in the countries with relatively less developed economies, such as Vietnam, Cambodia,
and Laos, where labor costs are relatively low and there is a large pool of available
labor. Production of the more capital-intensive textiles (yarns and fabrics) and higher-
quality apparel is concentrated in the ASEAN countries with higher labor costs such as
Thailand, Malaysia, and to a lesser extent, Singapore. Cross-border integration is
nurtured by investment from the fabric-producing countries in ASEAN into the lower-
cost-apparel manufacturing countries of Vietnam and Cambodia.
1.11 Problem Statement
The ambition of any regional free trade agreement especially for goods is quite
straightforward. The aim is among others to integrate and increase trade within the
region by reduction of tariffs. Based on the historical evolution of trade integration in
ASEAN discussed in the earlier sections, many measures were taken by ASEAN since
its inception leaning towards this goal. The most common method in integrating
countries through trade is by tariff reductions which is more precisely called preferential
tariffs. Since the introduction of PTA 1977 and AFTA in 1993, the aims were mainly to
reduce tariffs, to allow increased trade among countries in ASEAN which is intra-
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regional in nature. Although different approaches were used under the PTA 1977 and
measures to determine preferential tariffs changed in the course of AFTA
implementation, the objective remained the same, which is to reduce the tariffs. AFTA’s
approach was based more on a scheduled and gradual method of tariff reduction, which
gives ASEAN countries several leeway and flexibility to avoid tariff reduction or
elimination, although some countries might have exercised such tariff reduction or
elimination.
Under such circumstance, ASEAN’s value in terms of intra and extra-regional trade
increased rapidly from the year 1993 onwards, which can be argued as a natural growth
of trade, given the developing economies and GDP growth rate of countries at that point
of time. This natural growth of trade volume within ASEAN is most of the time
confused with the impact of AFTA. Several researchers, Ministers and Leaders
continuosly praise AFTA to the rapid increase in trade value within ASEAN. However,
the question remains whether the value of the increase in trade is actually the impact of
AFTA. When analyzed at the recent stage, after around 20 years of AFTA
implementation, despite growth in value of trade, the share of intra-regional trade within
ASEAN is only at 24.1% in 2014. This value is way below other regional trade
agreements that account to 55-75% intra-regional trade for the same period of time. It
remains a puzzle that if AFTA’s success with its major reductions in tariff and
elimination of most tariffs is real, how this intra-regional trade share could remain low.
For this purpose, to ensure and investigate the actual use of AFTA, the tariffs under
AFTA that is actually used would give the actual indication of what essentially AFTA
had contributed to. This would then show the actual relationship between tariff
elimination/reduction under AFTA and its impact to volume of trade especially in
investigating intra ASEAN trade. Investigating the utilization of actual tariffs also
would decipher the common thinking AFTA’s success is based solely on the number of
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tariff lines covered or percentage of tariff elimination. The impact of AFTA cannot be
related directly to the trade volume or percentage of tariff elimination, which is
commonly practiced today.
Having AFTA in a set of developing countries like ASEAN also poses opportunities
to industries to specialize in certain products and diversify the products within the
region. A high level of integration within countries in ASEAN would allow countries to
complement each other and increase intra-regional trade. The concept of sourcing from
the own region, due to the tariff elimination would allow countries to reduce costs by
importing required resources within the region. This was also part of the ambition of
AFTA that laid the idea of creating regional hub for certain industries with different
ASEAN countries specializing in different resources and products. In the initial stage of
AFTA, such efforts were championed by foreign investors which sourced products from
different countries with the goal of reducing costs. Since investors are driven by
monetary benefits, most of the efforts were not sustained to show that AFTA actually
integrated businesses in ASEAN which then allowed the increased volume of trade.
ASEAN countries from the beginning based on the discussion of history and
evolution of ASEAN were mostly competitive with each other. They produced similar
products and had similar resources. With the advancement of technology, this trend
somehow changed although the nature of ASEAN countries still remain as competitive
to each other. This is significant by comparing the ASEAN countries attracting similar
foreign investors to their countries. However, with AFTA, the opportunity to integrate
the entire ASEAN market existed and in corresponding to the complementary and
specialization effect, AFTA provided the platform. Despite integration initiatives and
tariff reduction under AFTA, products diversification is not apparent, thus suggesting
countries continue competing for the same markets and produce similar products.
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As a conclusion the problem statements can be summarized as follows:
i. There exist a great amount of misunderstanding among several researchers
and public figures that AFTA has helped increase trade value within ASEAN.
When analyzed at the recent stage, after 20 years of AFTA implementation,
despite six fold growth in value of total trade, the share of intra-regional trade
within ASEAN is only at 24.1%, way below other regions with similar
arrangements.
ii. There are very few studies that use actual transaction level data to analyze the
actual relationship between tariff elimination/reduction under AFTA and its
impact to volume of trade. By not capturing this, many policies in tariff
reduction and coverage under AFTA do not bring any benefit to ASEAN
countries.
iii. Having AFTA in a set of developing countries like ASEAN also poses
opportunities for industries to specialize in certain products and diversify the
products within the region. A high level of integration within countries in
ASEAN would allow countries to complement each other and increase intra-
regional trade. However, this level of integration is not reflected in the
proportion of intra ASEAN trade.
iv. The concept of sourcing from the own region, due to the tariff elimination
would allow countries to reduce costs by importing required resources within
the region. This was also part of the ambition of AFTA that layed the idea of
creating regional hub for certain industries with different ASEAN countries
specializing in different resources and products. Despite integration
initiatives and tariff reduction under AFTA, products diversification is not
apparent, thus suggesting countries continue competing for the same markets
and produce similar products within ASEAN.
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1.12 Outline and Organization of the Study
The study is divided into five chapters. The first chapter is Introduction,
followed by Literature Review, Theoretical Framework and Methodology, Results and
Discussion and Conclusion and Recommendation. The following is the organization of
the chapters:
i. Chapter 1: Introduction ii. Chapter 2: Literature Review iii. Chapter 3: Theoretical Framework and Methodology iv. Chapter 4: Results and Discussion v. Chapter 5: Conclusion and Recommendations
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CHAPTER 2: LITERATURE REVIEW
2.1 Introduction
This chapter covers the literatures that are related to trade effects of AFTA and
the utilization of preferential tariff under AFTA. This chapter discusses the various
approaches that have been used in studies of AFTA including the trade effects as well as
study on utilization of preferential tariff under AFTA. For the purpose of the utilization
of preferential tariff, the chapter also explores studies of other regions that have
examined utilization of preferential tariff.
The purpose of reviewing the above studies is to compare and provide the gap in
the existing studies on trade effects as well as arguments for further examination of
utilization of preferential tariff under AFTA.
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2.2 Purpose of Trade Agreements
There are two kinds of problems that a trade agreement might solve. The first is that
the trade policy decisions of one government give rise to an externality that affects the
welfare of another government. This is the possibility that is stressed in the traditional
economic approach to trade agreements. This method is used by a government to set its
import tariff to maximize national welfare and recognize that some of the cost of the
tariff falls upon foreign exporters whose products sell at the lower world price. This
terms of externality as described by (Helpman, Elhanan, & Krugman, 1989) point out
that unilateral tariff choices can be inefficient in the presence of monopolistic
competition, even in the absence of terms of trade movements.
This would then naturally point out that governments would set unilateral tariffs that
are higher than what would be efficient. Ultimately, the purpose of a trade agreement is
then to eliminate the terms of trade driven restrictions in trade volume that arise when
policies are set unilaterally and thereby offer governments a means of escape from a
Prisoner’s Dilemma (Bagwell & Staiger, 2002). The impression that is given by
Bagwell and Staiger is focused on the elimination of tariffs that is related to the trade
volume and it would not necessarily mean the total elimination of tariffs or terms of
trade driven restrictions for the entire list of goods in an agreement. The purpose of
trade agreements is merely to escape from the restrictions or policies that are set
unilaterally by a government and it would only make sense if the volume of trade that is
related to the so-called escape is granted such escape route by an agreement.
This is sometimes not the case in many trade agreements whereby the governments
maximize national welfare by protecting certain industries and nevertheless the volume
of trade that actually matters is not given the so called escape route. It must be pointed
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out that this traditional approach seems unrealistic to substantiate the hypothesis that
governments maximize national welfare.
The second problem that a trade agreement would solve is when government is
unable to make credible commitments to its own private sector. As an example, a
government may commit that in future it will not protect certain industry or it will
undertake extensive regulatory reforms. Although such commitment is potentially
valuable to the government, as it would allow investment in cost reduction or increase
in exports, if the private sector does not respond to the government’s decision, then it
might not be credible for the government to follow through on its proposed plan. A
trade agreement can potentially help a government solve its time-consistency problem
(Bagwell & Staiger, 2002) if the agreement enhances the credibility of the government’s
plan.
Trade Agreements from the perspective of a government, moreover a developing
government would surely emphasize on the welfare benefits of the arrangement. This
theory by Jacob Viner (Viner, 1950) of Preferential Trade Agreements to which Meade
(1955) and Lipsey (1957) at that time came into attention after the steps taken to
establish the European Community by the Treaty of Rome 1957.
As specifically mentioned by Bhagwati and Panagariya (1996) , the theories at that
point of time was for the static effect of European Community, thus there are many
factors that must be considered in understanding the economics of preferential trade
agreements. Specific concern on both the purposes mentioned above is the trade effect
and in determining the actual effect of trade, it should address the underlying problems
in studies related to trade effects.
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2.3 Trade Effects of AFTA
The literature on trade effects of regional trade agreements (RTA) can be
divided into three most important aspects. The first aspect would be studies on intra-
regional trade that adopts the principle of economic theories that originate from Jacob
Viner (1950) and the expansion of the theories with various modified empirical models.
The second aspect is focused at the externality of the region’s trade, whereby other
factors such as foreign direct investment and the architecture of the region is concerned.
This aspect deals more towards the political-economy characteristic that a regional trade
bloc would be able to achieve. The third aspect deals with specific trade effects for a
particular trade agreement or trade area. The focus on particular area expands the
theories on issues basis and some of the literature are focused at specific industries. For
the purpose of this chapter, the literature that are selected are a combination of the first
and third aspect as the author views that the fundamental economic theories lay a
foundation and the subject of interest of this study is focused in ASEAN or more
specifically on AFTA.
Deriving from the first aspect mentioned above, one of the most commonly used
approaches in testing the trade effects of a trade agreement is the gravity model. This
method was employed by Frankel and Wei (1996) that discovered the intra-ASEAN
bias to be significant for every year for the period of 1970 to 1992. Despite the fact that
the study showed that although simple trade shares portrayed intra-regional trade to be
less significant relative to ASEAN’s external trade, two members traded 600% more
than two otherwise identical economies. Interestingly, although the entrepot role of
Singapore was addressed by an additional dummy for bilateral trade that involved
Singapore in the study, the bias persist.
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Furthermore, the intra-ASEAN orientation is slightly reduced when the openness of
ASEAN, which is significantly more than what is predicted by the model is taken into
account. However, when the East Asian bloc consisting of China, South Korea and
Japan is tested simultaneously, the ASEAN effect disappears. Therefore, the study
suggested that the observed bias may not be due to preferential tariffs within ASEAN
itself but it would partly be a more prevailing inclination to trade within the larger East
Asian bloc.
Lee and Park (2005) also found a similar result. They found ASEAN economic
integration to have a significant positive effect on intra and extra regional trade but the
statistical significance of the AFTA bloc faded out when the plus three countries were
introduced (China, South Korea and Japan). This study indicated specifically that intra-
regional trade in ASEAN has very little impact from AFTA. The question that arises in
this study is the importance of AFTA in motivating intra-regional trade. It was seen in
both studies that inclination towards the East Asian bloc reduced intra-regional trade
perhaps due to the dependence of some major trade partners in ASEAN with the East
Asian bloc or it could also be due to the ineffectiveness of preferential tariffs within
ASEAN. Another reason that could have contributed to these results is the impact of
AFTA was observed from an aggregate perspective and it was not examined according
to the milestones of AFTA to start with. This indication could bring two assumptions.
First, the inception of AFTA did not have natural effect of increasing intra-regional
trade ASEAN due to the dependence and growth of the region together with the East
Asian bloc. The second assumption that could be deduced is the studies did not examine
in the right industry or timeframe and the results were not aligned to the milestones of
AFTA.
The first assumption is further supported by the study conducted by Soloaga and
Winters (1999) through their gravity estimation. By examining nine major trade blocs
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from 1980 to 1996, they found a highly significant increase in extra-bloc coefficients,
together with a fall in intra-ASEAN trade. The suggestion that the pull factor of extra-
bloc coefficients with a fall in intra-ASEAN trade suggest that naturally ASEAN at that
point of time was a region that depends heavily on trade outside the region. There could
be several factors that cause this results which among others include the fact that some
ASEAN economies were similar in its level of development and GDP, ASEAN
countries were competing with each other in similar export industries and ASEAN
countries were heavily dependent on imports from East Asian bloc or other parts of the
world, in which for those exports, ASEAN has not fully developed its economy. This
brings to the question on whether AFTA was a mismatch of countries that could not
effectively complement each other’s economy to a positive level. However, it must be
stressed that both the assumptions above still remain unanswered as these studies used
aggregated data without regard to AFTA milestones.
Clarete, Edmonds and Wallack (2002) extended the study above similarly up to year
2000, which gave a better impression on post-AFTA effects. The study conversely
showed that AFTA might have reduced extra-ASEAN trade and found no evidence on
an effect on the pattern of intra-regional exports and imports. It further suggested that
the inclusion of the CLMV countries into ASEAN in the 1990s might have diluted the
positive impact of AFTA. This study however in contrast suggests that the inclusion of
newer members could have reduced extra regional trade although the pattern for intra-
regional trade was not conclusive. Once again, this study supports the assumption that
the countries that were part of AFTA from the beginning were countries with similar
economies and compete with each other, thus finding trade partners outside the region
to complement their economy’s needs. With the CLMV countries gradually joining
AFTA in phases, it could have perhaps created an opportunity between the economies
of existing AFTA members and the new members to trade under AFTA as there was
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wide disparity in economies of the existing members and the new members. This
deduction would only be valid if AFTA was actually fully implemented and used
intensively during this period of time.
On the other hand, the results could have also been a natural effect as those countries
that joined AFTA were naturally the trade partners of the existing AFTA members and
their joining into AFTA only further impacted the extra regional trade bias. This further
suggests that the role of AFTA was not conclusive unless there was evidence on full
implementation and utilization of AFTA.
Sen, Srivasta and Pacheco (2013) analysed the early effects of the expansion of
ASEAN into ASEAN+6 architecture which included Australia, New Zealand, China,
India, Japan and South Korea. By utilizing an augmented gravity model, the study
examined the impact of membership in a bilateral versus plurilateral PTA for the period
of 1994 to 2006. The method used was by augmenting the traditional gravity model and
separately estimating the effects of bilateral memberships against plurilateral PTA
memberships. The study resulted in a disaggregated country-by-country indication that
plurilateral PTAs have had a more significant impact relative to bilateral PTAs in
stimulating trade among the ASEAN+6 countries. This study which employed the
addition of six countries excluding the United States are all major trade partners of
ASEAN. The results of the study strengthens the argument that even though AFTA was
implemented with new members, the complementary role of external trade partners of
the plus six countries plays significant role to ASEAN’s trade. It can be further
suggested that the economic uniqueness of the 16 countries lays as a better foundation
than bilateral trade arrangements.
Another empirical study developed by Endoh (2000) also investigated trade effects of
AFTA. The research aimed to examine trade relationships of countries within the Asia-
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Pacific region during the post-World War II period. Under the cross-section setting, the
gravity model was estimated using 80 countries’ trade flows at intervals of 5 years from
1960 to 1995. In order to control for regional effects in each region, sets of regional
dummies: ASEAN, APEC (89), EAEC and APEC (95) were added accordingly in the
gravity specification. This enabled to resolve the issue of overlapping memberships in
these regional blocs as well as differences in the objectives of each regional formation.
Specific to ASEAN economies, the result suggested no significant ASEAN effect on the
members’ trade flows. This study provided a method to dissect ASEAN from other
RTAs that some members of ASEAN would be part of. Therefore, the overlapping
membership issue of RTA was addressed in this study and it further strengthens the
point that ASEAN economies did not feel the effect relative to the effects in other RTAs
and further brings to the question, the two assumptions put forth.
Sharma and Chua (2000) examined whether ASEAN would be impacted by other
regional economic cooperation, i.e. APEC for the period of 1980 to 1995. The trade
flows of 33 APEC countries were investigated with the aim to unfold trade effects. By
using the gravity model on time series data of ASEAN-5’s trade flows individually, it
resulted in significant trade effects on the membership’s trade flows. The paper further
concluded that ASEAN-PTA which was signed in 1977, failed to boost intra-ASEAN
trade flows. An increase in intra-ASEAN trade that had become visible was instead
perceived to be driven by the increase in size of the economies. It also suggested that
increase in intra-ASEAN trade was a result from the APEC membership countries
rather than ASEAN membership.
Elliott and Ikemoto (2004) applied the approach to investigate ASEAN’s trade
relationships pre and post AFTA and examine if AFTA’s objective of increasing intra-
regional trade was negatively affected by the 1997 Asian Financial Crisis. By using the
gravity model, the study estimated trade flows of 35 countries during the period
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between 1982 to 1999. The study also included regional dummies to control RTA
effects for APEC, ASEAN, EU and NAFTA respectively. The result pointed out that by
using Ordinary Least Squares (OLS) method on the time series, trade flows of ASEAN-
5 were not significantly influenced by AFTA especially in the years following its
formation. The most surprising result was the 1997 Asian Financial Crisis was not
found to obstruct AFTA’s goal as imports among ASEAN members were perceived to
have increased in comparison with imports from non-members. Even though with the
use of time series, the study still resulted with insignificant effect to intra-regional trade
within ASEAN, and more interestingly, the study observed the impact of the 1997
Asian Financial Crisis and it proved that it increased intra-regional imports compared to
non-members.
Kien and Hashimoto (2005) examined AFTA members’ trade flow using a panel data
framework for the period from 1988 to 2002. The paper then estimated the gravity
model using the Hausman-Taylor (HT) variable estimation method on 39 countries
panel trade data to measure trade effects. This paper was in contrast to other research,
applied regional dummies that were time variant. Other studies specified that regional
dummies would be time invariant. Therefore, the paper allowed changes through time in
the panel database. The paper implied that AFTA affected export flows of member
countries. It also suggested that AFTA members had increased trade between
themselves about 87% more than would have otherwise occurred without AFTA.
Okabe and Urata (2013) examined the impact under AFTA on intra-ASEAN trade by
applying a gravity model. The study concluded positive and significant trade creation
effects from the tariff elimination for a wide range of products. The study also found
that the elasticity of tariff reduction on imports tends to be much larger than that on
exports. Another interesting issue pointed out in the study was trade creation effects for
the new ASEAN members were relatively small to those of the old members. The study
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argued that that there is a need to expand the study further by looking at the use of
AFTA and by reducing or removing the non-tariff measures. The study also specifically
mentioned that the low utilization of AFTA could be a cause for the limited impact of
AFTA on intra-ASEAN trade.
Most common among these studies were the use of gravity model with dummy
variables to test trade effects in particular to AFTA, intra and extra-regional trade
effects and whether there is trade creation and diversion effect. The approach used by
the studies evolved from the very beginning up to date. The literature can be
summarized with the use of gravity model under four different angles to determine trade
effects of AFTA.
The first angle would be by applying some dummy variable such as bilateral trade
that was performed by Frankel and Wei (1996). Some other studies have also applied
dummy variables at different stages and most common is the inclusion of regional
dummies. The issue with regional dummies was the dummies were time invariant, thus
suggesting the lack of validness in the results of actual effects of AFTA. At the same
time, some literature such as the study by Kien & Hashimoto (2005) provided a solution
by applying a time series to the regional dummy. The main issue that is not addressed
by applying such dummies is the complexity of AFTA itself. There were several
milestones of AFTA from its formation in 1992 up to date. Given the milestones and
key events in the whole period of time, it is difficult to use dummy variables unless the
dummy variable is defined and linked to the use of AFTA.
The second angle of these literatures use a comparative effect approach by observing
bias to other regional blocs similar to the study conducted by Soloaga and Winters
(1999). By performing several observations of countries that are member of AFTA and
members to other regional trade agreements, this approach provided results on a
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comparative perspective. This approach was more of a guessing approach that lacked
credible evidence on the determinants of trade. Although some studies argued with the
determinants of trade, it could not be taken as an absolute evidence as it did not relate to
the use of AFTA.
The third angle of these works of literature uses panel data to investigate pre and
post-AFTA trade effects. Similar to the first angle explained above, the weakness of
these type of studies is its inability to take into account major milestones in AFTA. By
looking at data before and after AFTA, it would only to a certain extent capture the
trade effects of AFTA. Given different products with the various milestones in AFTA, a
pre and post-AFTA observation still do not answer the question of trade effect that was
caused by AFTA entirely.
The fourth angle of observation is focused on comparing the effects of trade on
newer members of AFTA and the older members of AFTA. Although the effects of
trade observed many patterns of trade, due to the lack of focus on the actual use of
AFTA, the results in these studies were more on examining the general effect of joining
AFTA rather than the actual effect of AFTA.
The four angles mentioned above did not entirely capture the actual effect which
is tariff elimination under AFTA into their investigations. This is due to the fact that
tariff elimination schedules are in phases and it varies according to country and tariff
elimination is not a guarantee for the tariff to be used under AFTA. The purpose of
trade agreements as explained by Bagwell and Staiger (2002), where a trade agreement
is aimed to eliminate the terms of trade driven restrictions in trade volume that arise
when policies are set unilaterally, is not entirely addressed in these studies. This, on the
other hand, opens up the opportunity to link trade effects and preferential tariff
utilization, which to the knowledge of the author does not exist for AFTA.
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Despite the various objectives of the studies explained above, it can also be
summarized that most studies did not particularly take into account of the development
of AFTA and the various stages of implementation. As AFTA was implemented in
stages since its inception, the actual measure of the effectiveness of AFTA should
derive from the availability of the preferential tariff and not a uniform approach that
looks at AFTA since its foundation and after that. It also should be emphasized that
tariff liberalization effort under AFTA took about 15 years and yet up to 2015, there are
remaining tariff lines that are not liberalized unilaterally by some countries. Without
any view of this implementation, the signals from AFTA in the studies above was not
entirely able to conclude in detail the characteristics of tariff liberalization and its
effects to trade flow.
Having a diverse level of economies in ASEAN, effects of AFTA for different
industries and sectors would also vary. To capture this difference, the studies above
could not indicate the purpose of tariff elimination bilaterally as each ASEAN member
decides on their external tariff under a schedule. The actual effect of trade, be it intra-
regional, extra-regional, trade creation or trade diversion would only work if the actual
implementation is taken into account. This is an area, which should be given emphasis
to be explored further.
2.4 Preferential Tariff Utilization
Preference utilization in any trade agreements refers to the use of preference in
the reduction of tariffs or duties either it is a reduction of tariff to certain lower level or
to zero in most cases. The literature on preference utilization can be divided into two
aspects. The first would be based on the probability of the preference being used which
draws back to the hypotheses that the higher the preferential margin between what
offered in a particular trade agreement with the usual tariff enjoyed for example under
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the Most Favoured Nation (MFN) term would reflect a high probability of usage of the
preference. The second set of literature investigating the preference utilization focus on
the actual use of preference by looking into the transaction level data with different
methodologies which include examining certificates produced by customs, non-tariff
barriers, and customs data.
There is, however, a vital link between both aspects. Most or nearly all
preference utilization does not come without a cost. The costs can be related to fulfilling
the rules of origin (ROO) requirements and other formalities that can be specific to each
trade transaction. Such formalities in many cases suggest that preference would only be
used when a substantial volume is involved, thus the savings enjoyed under such
transaction would be economical.
A number of studies on preference utilization can be seen in the European Union
(EU) or the US markets which data on preference utilization is available. Most literature
focused on the two aspects above by illustrating the different sectors using a number of
methodologies. Among the complete assessment on preference utilization for the EU
was conducted by Candau, Fontagne, & Jean (2004). The study was aimed to examine
the effectiveness of EU’s preferential agreements in granting their partners improved
market access. By looking at the level of utilization of exporters when entering the EU’s
market which includes several protection measures, the study suggested that
underutilization of preferences does not have a large average impact on the protection
faced by exporters when acceding the European market. It, however, suggested that
utilization of preferences is lower when the preferential margin is small suggesting that
compliance costs are not negligible. In general, the study came up with a result of 82%
on average for the utilization rate and for the higher preferential margin products.
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Bureau, Chakir, & Gallezot (2006) used a probit model and year 2002 data at
exporter product level for agriculture in the EU and US suggested a positive relationship
between the probability of using preferences and preferential margins as well as export
values with overall utilization rates above 80%. Interestingly, the study concluded that
only a very small proportion of the imports eligible to preferences is actually exported
outside a preferential regime. Besides that, the study showed that the flow of imports
from poorest countries remained very limited with even a generous tariff preferences
which led to question the overall impact of preferential agreements.
Another study by Hakobyan (2012) which used panel data to assess utilization
rates of the US GSP found a positive impact of the preference margin and export
volumes. The study noted that about 40% of imports qualifying for GSP enter the US
without using the available preferences. The study was undertaken by constructing a
panel dataset that combines a measure of GSP utilization at the country product level
and country industry level production data for 68 GSP eligible countries exporting
about 5000 products to the US from 1997 to 2008. The findings suggested that a higher
local content share and greater remoteness of beneficiary countries lead to higher
utilization rates. In addition the study found that utilization rate rises with the preference
margin, size of exports, regional cumulation and declines with degree of processing.
Brenton & Ikezuki (2004) focused on impact of exports under the African
Growth and Opportunity Act (AGOA) to the US. The study revealed that the utilization
rates were generally high overall but there were a range of countries that suffered low
utilization level which was characterized to be below 50% for the textile industry.
Noting this disparity the study suggested that studies related to determinants of
preference utilization should examine the cost involved in utilizing preferences.
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Cost impact was also the focus of study by Carrere & De Melo (2004) which
observed the preferential access for Mexican exports to the US under NAFTA. The
study explained that there exist variations in utilization rates for different categories of
goods with different cost impact that various types of ROO have on these goods.
Another interesting study on cost impact by Agostino, Demaria, & Trivieri
(2010) investigated specifically on whether costs of compliance may prevent exporters
from taking full advantage of potential benefits. Although the study was focused at non-
reciprocal preferential regimes granted by the EU on agricultural export flows, the study
was able to capture the view of exporter costs. By adopting gravity framework using
554 lines of agricultural products for 131 developing countries in 2002 found that the
costs of compliance play a role in making the schemes work. A lower cost would
suggest greater impact of preferential margins.
It can be summarized that these studies have concretely shown results in three
areas. First, the hypothesis that higher the margin is between the preferential tariff and
MFN rate, the higher the utilization rate would be. The above studies that used the
actual data at transaction level give a strong indication that the hypothesis is correct.
However, adopting such method for the purpose of AFTA would be difficult besides
availability of data itself. AFTA is a non-reciprocal preferential regime and there exist a
schedule that scrutinizes the plan to reduce the tariffs and often the plans are also
postponed. Unlike GSP for the EU which adopts a common external tariff as well, the
uniformity allows researchers to use methods that are straightforward.
Second, the studies provide the relationship between cost impact and utilization
of tariffs. A higher cost impact that is involved in using the preferential tariff coupled
with other non-tariff measures would reduce the utilization level of tariffs. This is quite
a universal issue that is faced by trade agreements. Nevertheless, it is also faced by
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AFTA, where there are strict Rules of Origin (ROO) and the processes involved in
obtaining the preferential tariff. These real issues have been identified by ASEAN and
most of the recommendations in the above studies have been implemented by ASEAN.
The third point that these studies make is that utilization of tariffs would provide
attractiveness to trade regionally rather than trading with other regions. This point is
however difficult to be realized in AFTA. The studies above were focused on large and
developed economies such as the US and the EU. With such economies, attractiveness
to regional trade is higher due to the availability of diverse products in multiple
industries. However, within AFTA, the attractiveness factor could possibly realized
only in industries which the members of AFTA are already globally known for. This
could also be an area that can be examined further.
2.5 Preferential Tariff Utilization in ASEAN
Studies on preferential tariff utilization in ASEAN are quite limited to the use of
probability and cost as a proxy of utilization. There are also very limited studies that use
actual transaction level data. Most studies have provided significant link between
preference utilization and intra-regional trade.
One of such study by Leelawath (2012) noted that “as a consequence of AFTA,
intra-trade between Thailand and other ASEAN countries has shifted between 13.8% in
1992 and 21.2% in 2009”. Yet, he added, not all Thailand exporters fully took
advantage of AFTA’s tariff preferences. Instead many are still subjected to MFN rates.
His study investigated Thailand’s utilization of preferential tariff under AFTA on its
exports to other ASEAN members as well as potential reasons exporters opt not to
utilize such benefits. Additionally, the study also came up with a number of policy
recommendations to overcome these problems, to promote the further utilization of
preferential tariffs, and boost the volume of trade between Thailand and ASEAN
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member countries. In making comparison of previous studies, the paper pointed out that
the majority of studies operated based on the assumption that tariff utilization was at
100% and they did not take into account the fact that not all exporters take advantage of
preferential tariffs under AFTA. Essentially, this means that every unit of eligible
exporting product is subject to the rates of preferential tariffs. Unfortunately, this is not
always the case. Unlike the available data on preference utilization under the GSP
scheme, these studies still do not answer the question on whether AFTA through its
preferential tariffs has actually increased intra ASEAN trade or not.
Nevertheless, regardless of AFTA’s utilization rate, intra-ASEAN trade has
increased. However, the question remains whether AFTA was behind the increase in
intra-ASEAN trade. Between the establishment of AFTA in 1992 and 2010, Thailand’s
volume of exports in the study increased by ten times and their volume of imports has
increased by six times. These figures grew simultaneously until the global financial
crises. Recent years, possibly because of the implementation of AFTA, transformed
Thailand to a net exporter in the ASEAN market. Prior to 1992, a trade deficit existed
between Thailand and other ASEAN member nations. Nonetheless, since then Thailand
has started to have a positive trade balance and experienced the continued increase in
the differences between their exports and imports until 1995. The study also pointed out
that in 1992, Thailand’s intra-ASEAN trade represented only 13.8% of its total trade. In
contrast, the majority of Thailand’s exports went to the United States, the European
Union, and Japan. About 22.4% of their total trade was with the United States, 20.5%
was with the European Union, and 17.5% was with Japan. Of all the ASEAN member
countries, Thailand’s trade with Singapore was the most significant. Trade between
Thailand and Singapore made up about 8.7% of the former’s total trade14. Between
14Meanwhile Thailand trade with the other ASEAN nations was incredibly low. Trade with Indonesia made up about .9% of their total exports, trade with the Philippines .5%, trade with Laos .4%, and trade with the other ASEAN nations made up between .01% and 2% of their total exports.
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1992 and 2003, after the implementation of AFTA, these numbers shifted. By 2003, a
total of 20.6% of Thai exports went to ASEAN nations15. Meanwhile a less significant
proportion of their exports went to the United States, the European Union, and Japan at
17%, 14.4%, and 14.2% respectively. Though by 2010 the increase of the rate of growth
of intra-ASEAN trade in Thailand had begun to slow, their overall trade continued to
diversify. Trade data in 2010 indicates that ASEAN now made up 22% of Thailand’s
total trade.16 Other notable trade beneficiaries of Thai exports include the European
Union, Japan, China, and the United States. As evidenced by all of this data, recent
decades benefitted Thailand economically. Leelawath, to at least a certain degree,
attributes these changes to AFTA. Thus, it makes sense that his first instinct would be to
promote trade liberalization by improving utilization rate.
Numerous factors contribute to the low utilization rates of the CEPT scheme.
Most notably, AFTA’s margins of preference on high trade volume goods probably
remain too small to compensate for the administrative costs of qualifying for the
preferences. In reality, though the MFN tariff rates and CEPT rates vary greatly among
countries, the differences between the two rates is relatively small within AFTA. In
their study, Manchin and Pelkmans-Balaoing (2007) noted that the “rates envisioned
here (in AFTA are) certainly low relative to the known record of other discriminatory
schemes”. In fact, average MFN rates for AFTA members tend to be less than 10%;
while there usually is only a difference of about 5% or less between MFN rates and
preferential rates. Though, newer ASEAN members such as Cambodia, Lao PDR,
15The breakdown of Thailand’s intra-ASEAN trade in 2003 looks like this: 7.3% of their exports went to Singapore, 4.8% went to Malaysia, 1.6% went to Vietnam, 2% went to the Philippines, .1% went to Brunei, 2.8% went to Indonesia, .9% went to Cambodia, .6% went to Laos, and .5% went to Myanmar.
16 Thailand’s intra-ASEAN trade in 2010 breaks down as such: 4.6% of the exports went to Singapore, 5.4% to Malaysia, 3.0% to Vietnam, 2.5% to the Philippines, .1% to Brunei, 3.8% to Indonesia, 1.2% to Cambodia, 1.1% to Laos, and 1.1% to Myanmar.
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Myanmar and Vietnam usually find themselves excluded from these calculations. Small
discrepancies between these two tariff rates can sometimes restrict the attractiveness of
using the CEPT scheme under AFTA, especially when it can be expensive for exporters
to request the preferential rates. One of the most expensive aspects of requesting
preferential rates can be the efforts taken to prevent the re-exporting of imported
products from non-member countries. These efforts attempt to prevent the “trade
deflection which refers to the phenomenon that occurs when a non-member country
exports a good to a member country and then re-exports to another member country so
as to take advantage of the tariff preferential given within the free trade area”. As such,
the rules of origin (ROO) became established. A ROO proves the origin of a product, in
order to prove that an export of one country to another ASEAN member country is
genuinely a product of that nation. Exporters must comply with ROOs so that their
products can qualify for AFTA preferential tariff rates.
This requires that exporters obtain certificates of origin (COO) before shipping
their products or, otherwise, only receiving the MFN tariff rates for their products. For a
product to receive a COO, over 40% of its content or materials must be from the
originating country. Other barriers to AFTA utilization may also include a lack of
private sector awareness, a lack of clarity in the application of the rules of origin,
problems with customs procedures, and the lack of dispute settlement mechanisms.
Despite these obstacles, there has been little progress on removing non-tariff barriers
because there has been no agreement on what that entails.
Based on the requirements of the ROOs, Leelawath (2012) “uses the ratio of
export volume certified by the COO to total export to measure the utilization rate of
tariff preferential for each particular product”. Using the analysis adopted from the
approach used in the by Kohpaiboon and Jongwanich (2006) and the study conducted
by Wignaraja et. al (2010), this study operated with the assumption that every unit of
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products certified by a COO is exported to an ASEAN member country. With complete
regard to the statistical data, this study uses the HS 4 digit-level exports from Thailand
to all of the other ASEAN nations in 2009. All of this data was obtained from several
sources; including the Department of Foreign Trade, Department of Trade Negotiations
and UNCTAD Handbook of Statistics Online. In order to complete these utilization
calculations, the study used the total number of exports of all products to each ASEAN
member country between 2000 and 2009.
The overall results of this data display positive trends of the utilization rates of
Thailand’s exports to all of the other ASEAN countries. Interestingly, the utilization
rates for Vietnam, Indonesia, and the Philippines increased significantly. Utilization
rates for Vietnamese exports increased from 6% in 2000 to 46% in 2008. Meanwhile the
rates for Indonesia increased between 20% and 60% in those same years and the rates
for the Philippines increased from 14% to 46%. In spite of this, however, the utilization
rates of Thai exports to Cambodia and Myanmar essentially remain stagnant. Though
these rates began at close to zero, they grew slightly between 2005 and 2008. By 2008,
Cambodia had a utilization rate of .49% and Myanmar had a utilization rate of 1.7%.
Varying utilization rates for each country can be attributed to the different products each
country heavily imports from Thailand
As such, the study also focuses on the groups of products that make substantial
contributions to the Thai economy. The study selected the top twenty of Thailand’s
exported products to compute the tariff preferential utilization rates for each ASEAN
member country. In total, the export volume of Thailand’s top twenty products makes
up about 70% of its total exports. Top exports products in Thailand can be grouped into
four categories: manufacturing products, agricultural products, agro-industry products,
and minerals and fuels. Using this information, the utilization rate for each product
category can be calculated with a share of each product’s export volume to the volume
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of the top twenty exported products as weights. This new information provides the
overall utilization rates of Thai exports to all ASEAN countries in 2009. The weighted
utilization rate of Thai exports to Brunei was 5.76%, Indonesia’s was 51.67%,
Malaysia’s was 20.79%, the Philippines’ was 58.57%, Singapore’s was 3.53%,
Cambodia’s was 2.82%, Laos’ was 2.99%, Myanmar’s was 1.68%, and Vietnam’s was
54.65%. Interestingly, the utilization rates for Thai exports are highest in countries with
a middle level of development: namely, Indonesia, the Philippines, and Vietnam. This
likely relates to other results that show that, for the most part, the utilization rate of
manufacturing exports were higher than the other exports sectors. For exports to the
Philippines, Vietnam, Myanmar, Indonesia, Cambodia, and Malaysia the products with
the highest utilization rate were from the manufacturing sector.17 Yet other smaller
nations like Brunei and Laos, the utilization rate of agro-industry products led other
sectors; while, in ASEAN’s most developed nation, Singapore, the utilization rate for
exports was highest for minerals and fuels18. However, even in many of the sectors with
the highest utilization rates, many of the rates remained shockingly low. These low
utilization rates indicate that many Thai exporters do not benefit from AFTA and that
the barriers facing trade liberalization through AFTA may be more significant than
previously though.
The study also was further extended to survey 250 Thai firms in sixteen
industries that attempted to identify the most substantial factors preventing firms from
utilizing AFTA’s preferential tariffs. Out of the 250 firms surveyed, only 151 had
obtained COOs and utilized AFTA preferential tariffs by 2009. Of these 151 firms,
17 Utilization rates for manufacturing products exported from Thailand to Vietnam and the Philippines were 61.66% and 61.96%, respectively.
18In Brunei the utilization rate for products in the agro-industry was 20.44%, it Laos the utilization rate for products in the agro-industry was 6.69%, and in Singapore the utilization rate for exports of minerals and fuels was 6.10%
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“73.5% claimed that AFTA could raise their export revenue; and 64.2% claimed that
they could gain market access to new export [destinations] because of AFTA”. The fact
most firms utilizing the preferential tariffs believe it improves their trade prospects
indicates that, as least the problem lays not the preferential rates themselves, but rather
with the constraints preventing exporters from utilizing the preferential rates. Survey
results indicate that the main restrictions blocking Thai exporters from receiving such
privileges include:
The exporters’ inability to access information related to AFTA. Many exporters
fail to be aware of the products eligible for preferential tariffs and have only a
limited knowledge of the COO application process. In fact of the 99 firms that
had never received a COO, 45.5 % of them stated that they did not know
whether their products could have duty-free access to other countries and 47.5%
of them did not know where or how to obtain a COO.
The complexity and cost of obtaining a COO. It requires both a significant
amount of time and money for an exporter to apply for a COO. For exports on a
smaller scale, “the benefits from tariff preferential would be offset by the cost of
obtaining the COO.” The results of the survey reveal that 54.5% of the 99 firms
believed that the process for receiving a COO was too difficult.
The relatively small differences between AFTA preferential tariffs rates and the
MFN rates. Many exporters choose not to take advantage of the preferential
tariff rates, because the difference between the AFTA preferential tariff rate and
the MFN rate can be minimal or even zero.
The exporters’ dependency on imported raw materials. Sometimes, “the
dependence on raw materials from overseas causes the inability for Thai
exporters to comply with the rules of origin under AFTA.” Due the cost
effectiveness and quality of these raw materials, exporters often opt not to
benefit from the preferential tariff rates. As indicated by the survey, “it was
reported that the production of air conditioners and parts; and plastic products
uses high-technological imported raw materials. So the exporters could not
comply with the rules of origin.”
The degree of competition in ASEAN markets. Business environments can be
one of the factors for Thai exports in making decisions on whether or not to
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utilize AFTA’s preferential tariffs. If the “degree of competition in an importing
ASEAN country is insignificant, [than] the consumers are insensitive to the
change in price. Then it is less likely for the exporters to go through the COO
application procedure because they know that their product can be sold in the
ASEAN member’s market anyway.” The survey suggests that 46.5% of the
firms choose not to apply for COO because of the small size and lack of
competition in their market.
Manchin and Pelkmans-Balaoing (2007) assert that “even if preferences would
have been fully utilized, no matter how marginal, the amount of trade affected would
only be in the region of 35% -37% of total intra-ASEAN imports”. After all, they also
note that the products where the difference between CEPT and MFN rates is non-
existent account for 62.78% and 65.34% of total value of intra-ASEAN imports in 2001
and 2003, respectively19. Ultimately, even if increased participation in AFTA would
benefit exporters in Thailand, it remains doubtful that the enhanced utilization of AFTA
preferences would significantly further increase regional trade.
Other studies at the industry and national levels, however, also suggest that
utilization rates of all FTA preferences in East Asian nations, and not just those under
AFTA, are low. Overall, FTAs throughout the region remain underutilized. Hayakama
et al. (2009) empirically examines the determinants on the utilization of the Korean-
ASEAN Free Trade Agreement (KAFTA). This study offers specific insight on the
values of FTAs on extra-ASEAN trade and the effect they have on further regional
economic integration. Using a specific database provided by the Korean Customs and
Trade Development Institute; the study analyzes the effects of tariff margins, ROOs,
19assuming that the costs of documentation and the administration of origin rules are comparable to the (EU-based) estimates of 3-4.5% of total value of goods imported and then the relevant shares fall to around 16% of the total value of regional trade for ASEAN.
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and average export volume on the utilization rates of KAFTA’s preferential tariffs
(2012)20.
The study agreed with Leelawath’s assertion that “the utilization of the FTA
requires firms to incur considerable amounts of additional cost and, due to such,
additional costs, not all exporters regularly utilize FTA procedures” (Hayakawa et al,
2012). This much holds true in FTAs relating to both intra-ASEAN trade and extra-
ASEAN trade. Additionally, they also firmly maintain that the use of FTAs can generate
benefits for firms in terms of saving on tariff payments as FTA preferential rates are
usually lower than standard tariff rates. The greater the tariff margin (the gap between
FTA rates and general rates), the more substantial the benefits for firms using utilizing
FTA rates will be. Thus, they assert that the greater the tariff margin and the less
restrictive the ROOS, the more likely a firm will be to use the FTA scheme. They also
maintain that “the amount of a specific export transaction per se is very important
because a larger export volume leads to a larger saving on tariff payments, even if the
tariff margin is insignificant” (Hayakawa et al., 2012). So, ultimately, the three factors
of tariff margin (margin effects), rules of origin restrictiveness (ROO effect), and
average export volume (scale effect) determine the utilization rate of all FTAs like
AFTA and KAFTA.
Hayakawa et. al (2012) focuses on the utilization range of a bilateral FTA,
instead of on its unilateral preferential rates. As of December 2011, South Korea had
seven effective FTAs. By the start of 2012, their share of trade with their FTA partners
20This study defines ‘utilization rate’ slightly differently than the previous study. It defines utilization rate as the share of imports that actually receive preferential treatment in total imports that are eligible to receive such preferential treatments. Unlike the study conducted by Leelawath, this study does not include products that do not meet the necessary ROOs.
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was estimated to equal about 35% of their total volume of trade)21. These FTAs play an
important part of trade policy in South Korea and are believed to have a significant
impact on bilateral trade, GDP, and FDI. Yet only a limited amount of research exists
regarding the relationship between ROOs and Korea’s FTAs, similarly to how few
academic papers regarding ASEAN and AFTA incorporate utilization rates into their
analyses. As such, this study maintains a unique perspective and sheds light on a less
explored area of FTAs in the East Asia region. The study employs a conceptual
framework on exporters’ choices on FTA use. Total profit of a firm can be expressed in
the given equation: Total Profit = Operating Profit – Fixed Costs. The operating costs in
this equation can also be given by: Operating Profit = (p‐c‐t)X (Hayakawa et al., 2012)22.
As mentioned above, firms will only use the FTA preferential tariff rates if the total
profits when using the FTA are greater than the total profits without it. Thus, utilization
rates are only effective if: . Or, in other words,
the larger the difference in operating profit, the better the chance that firms will choose
to implement FTA schemes in their exporting practices. Essentially, this means that:
. The
left-hand side or LHS of this equation can be effected by two the variables of tariff
margin and procurement adjustment costs. Complying with ROO requirements can
cause procurement adjustment costs to increase. Large tariff margins and low
procurement adjustment costs result in a large LHS. Meanwhile, the right-hand side of
the inequality can be equal to just such an administrative cost.
21Their FTAs included the Korea-Chile FTA, the Korea-Singapore FTA, the Korea-EFTA FTA, the Korea-ASEAN FTA, the Korea-India CEPA, the Korea-EU FTA, and the Korea-Peru FTA. Additionally, the Korea-US FTA was scheduled to be implemented at the start of 2012.
22 In the equation calculating operating profit p stand for the price of the product, c stands for the unit cost, and t stands for tariff. The X in the equation denotes volume of production for exporting.
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These variables reveal four key scenarios. Ultimately, these conditions note the
following:
i. The larger the tariff margin, the more likely the FTA rates will be
selected.
ii. A lower procurement adjustment cost raises the probability of a firm’s
FTA use.
iii. The larger the size of each transaction, the more likely firms are to
utilize FTAs.
iv. Firms in countries with lower administrative costs are more likely to
use available FTAs.
Noting the basic behavior of firms on tariff scheme choice, the study next
specifies its empirical equation for estimation. It, in particular, examines the question of
which variables have a comparatively large impact on product-level FTA utilization
rates. These variables include margin effect, scale effect, and ROO effect. As illustrated
in the above equations, margin effect and scale effect have positive impacts on FTA
utilization, while ROO effect has a negative associations with FTA utilization.
Hayakawa, Kim, and Lee (2012) develop a baseline equation to examine the
relationship of tariff saving and FTA utilization with ROO effect. The equations
accounts for numerous variables including the country being analyzed, the product at
hand, the year, the tariff margin, the restrictiveness of the ROOS, and the procurement
adjustment cost. Dummy variables were also introduced into the baseline scenario to
provide some fixed effects and make up for a relative unavailability of data related to
the FTAs.
Similar to AFTA, in the earliest years of KAFTA a shortage of data existed.
This study uses data on FTA utilization for South Korea’s imports from ASEAN from
June 2007 to May 2011. Data from this period is broken down into five time periods:
June 2007 to December 2007, 2008, 2009, 2010, and January 2011 to May 2011.
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During these years South Korea imported goods from the ASEAN member nations of
Indonesia, Malaysia, Brunei, the Philippines, Myanmar, Cambodia, Vietnam, and Laos.
Yet KAFTA’s tariff reduction schedule included all of the ASEAN nations. The
ASEAN nation of Singapore, however, was excluded from the study’s calculations
because of pre-existing Korea-Singapore FTA 23 . In the reduction schedule the
implementations first went into effect for Indonesia, Myanmar, Malaysia, and Vietnam
on June 1, 2007. This was followed by the January 1, 2008 implementation date for the
Philippines; the July 1, 2008 implementation date for Brunei; the October 1, 2008
implementation date for Laos; the November 1, 2008 implementation date for
Cambodia; and the January 1, 2010 implementation date for Thailand. KAFTA enforces
temporal tariff reduction commitments on each member country and places all products
into one of two tracks: the normal track or the sensitive track. The sensitive track is
further separated between sensitive products and highly sensitive products24. Products
under the normal track were scheduled to have their tariffs completely eliminated by
2008 for South Korea, January 2010 for the ASEAN 6, January 2013 for Vietnam, and
January 2015 for the countries of Laos, Cambodia, and Myanmar 25 . Since tariff
reduction for products classified under the sensitive track had not begun at the time of
this study, this study’s data regarding FTA utilization for Korea’s imports from ASEAN
deals with products in the normal track only.
The data used by Hayakawa et al. (2012) has cross-sectional components that
are organized at the 10-digit HS level. Correspondingly, “the tariff margin is also
23The study excluded calculations of Singapore’s utilization rates to avoid any potential bias within the study’s analysis.
24Highly sensitive products are divided into five groups, labeled A through E. The products classified in group E are subject to exemption from KAFTA tariff elimination and reduction.
25Different dates for compete elimination of tariff for the “normal track goods are based on the different levels of development among the participating countries, and some of the ASEAN 6 countries are allowed to have an additional two-year grace period [with] 5% of normal track products.”
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constructed at the 10-digit level by using MFN and preferential tariff rates from
KAFTA’s phase-out program for the same period”. For the ROO restrictiveness index,
however, construction was undertaken at the 6-digit level. While the ROO
restrictiveness index is listed in the HS 2002 version, the other variables can be found in
the HS 2007 version. This means that by using the standard conversion system the
restrictiveness index can be mapped into the 6-digit level of the HS 2007 version.
Therefore, for this reason, products classified in the HS 01-10 are not considered in the
study26.
The study also carefully selects which products are eligible to receive
preferential tariff treatment. In the calculation of the results of the study products with
zero MFN tariff rates, products whose gradual tariff reduction has not started yet, and
products that are subject to tariff rate quota are not used in the data set. Utilization rates
of KAFTA between South Korea and each ASEAN member country differ. Statistics
indicate that the utilization of South Korea’s imports from ASEAN countries rapidly
improved from the first to the third year, climbing from 38% to 65.3%. Though in the
fourth year, however, the overall utilization rates dropped to 52.4%. Of all of the
ASEAN countries, Myanmar averaged the highest utilization rates and Laos
consistently had the lowest utilization rates27. The rates, coupled with a quantitative
measure of the restrictiveness of ROOs, help yield the study’s empirical results.
In order to quantitatively measure the restrictiveness of ROOs, the study adopts
a method proposed by Estevadeordal (2000). He developed his restrictiveness index or
RI to perform quantitative analysis on ROOs for NAFTA, ranging in categories from
26The study also does not include observations with zero-valued Average Imports and, as an outlier, products with a tariff margin larger than 300% are also dropped. Though products with a tariff margin of greater than 300% only account for less than .1% of the total observations.
27Myanmar’s utilization rates of ASEAN exports to Korea totaled 88.5%, while Laos’ utilization rates totaled 14.9%.
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minimum 1 to minimum 7. His RI was based on changes in tariff classification rules
and centered on the idea that “the basic idea of an RI is that the higher the index, the
more restrictive are the ROOs”. Yet ROOs in the case of Korean FTAs can be
significantly more complicated that this straightforward explanation. It remains evident
that “given that many modified types of ROOs are adopted, the study needs a certain
degree of adjustment, for example on how to deal with combination and/or selective
ROOs or how to index rules that are based on a change in chapter with some
exceptions”. The indexing of the ROOs under KAFTA is based on the later 2004 work
of Estevadeordal and Suominen, though a few adjustments were made to account for
products subject to combination and selective ROOs. Overall, in KAFTA 26 types of
ROOs exist for 3,077 products in HS 6-digit levels.
Since a log of the FTA utilization measure ranges from infinity to zero, the Tobit
estimation technique is used by Hayakawa et. al (2012). Results from this estimation on
the baseline equation approximated that all the coefficients were significant with the
expected signs. This indicates that “the magnitude of tariff saving has significantly
positive effects on FTA utilization; namely, the larger the gain in operating profit from
the use of FTA schemes the higher is the FTA utilization rate”. The estimation results
for the second equation, on the other hand, estimate the coefficients for Tariff Margin
and Average Exports to be significantly positive. These positive coefficients indicate
that both the margin effect and scale effect to play a central role in FTA utilization. The
coefficients also show that “the marginal effect on the ‘latent’ dependent variable,
namely how a one unit change in an independent variable alters the latent dependent
variable”. In order to calculate the margin, scale, and ROO effects on the observed rates
of FTA utilization, the marginal effect on the expected value for a dependent value on
uncensored observations must be calculated. Ultimately, three noteworthy conclusions
can be made from the results of the calculation of the marginal effect:
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1. The scale effect is most important in FTA utilization.
2. While scale effect in Malaysia, Thailand, and Cambodia is relatively large;
in Brunei, Laos, and Myanmar the scale effect is small.
3. Cambodia has a comparatively large margin effect.
The importance of the scale effect in FTA utilization is obvious because, in all
of the ASEAN countries, the scale effect provides around a five times larger
contribution than the ROO effect and a ten times larger contribution than the margin
effect. Cambodia might show an especially large effect due to the fact that many
exporters from Cambodia to South Korea are mostly the affiliates of Korean firms. High
MFN rates might also cause Cambodia’s similarly large margin effect. Yet, on the other
hand, the relative small contribution of Laos and Myanmar might be caused by the
fairly small size of most firms in these countries. These results shed light on Leelawath
(2012) previous discussion of the obstacles preventing increased utilization of AFTA
tariff rates.
While the two studies compare two different FTAs, AFTA and KAFTA, they
both discuss some of the same issues. Margin effect, ROO effect, and scale effect also
impact the utilization of AFTA’s preferential tariff rates. It remains additionally
possible that, like in KAFTA, that in AFTA the scale effect plays much more of an
important role in tariff preference utilization than either margin or ROO effect. This
means that in both Korea and ASEAN that “utilization of FTAs could keep expanding
as the average volume of trade increases and there is still much scope for enhancement
of FTA utilization even after completing the determination of the tariff reduction
schedule and ROOs.” The study concluded that “not only ex-ante but also ex-post
policies are well able to contribute greatly to raising FTA utilization” (Hayakawa et al.,
2012). They believe that policies designed to assist an increase in the average volume of
trade could potentially aid firms in claiming preferential rates more often when they
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trade. Increased utilization of KAFTA rates, they maintain, would be beneficial to both
Korea and ASEAN member nations and would generate trade in the region. This
concept, though it stands in line with Leelawath’s opinions, directly contradicts other
firmly held beliefs regarding FTAs and extra-ASEAN trade.
2.6 Trade Integration, Revealed Comparative Advantage (RCA) and Intra-
Industry Trade (IIT)
Among the earliest use of wide comparative advantage was the work by Balassa
(1977). The study undertook an analysis of the pattern of comparative advantage of
industrial countries for the period of 1953 to 1971. The study observed an association
between size and diversification of export based on the standard deviation of the
Revealed Comparative Advantage (RCA) indices of different countries. The results
showed that while the extent of export diversification tends to increase with the degree
of technological development a reversal takes place at higher levels (Balassa, 1977).
Richardson and Zhang (1999) used the Balassa index of RCA and analyzed the
United States in terms of the patterns of variation across time, sectors and regions. They
found the patterns to differ across different parts of the world, over time as also for
different levels of aggregation of export data. The difference were mainly due to
geographical proximity of trading partners and per capita income with the extent of
influence of these factors varying over time and across different sectors. The research
also showed that the high overall variability across regions in RCA indexes seem
unrelated to obvious explanations such as proximity or lingual or historical ties to the
US. At the same time, for goods, RCA variability across regions correlates somewhat
better with accounts of trade diversion and of regional preferences for and
discrimination against US exports. The study also found only little evidence of high or
increasing variability across disaggregated commodity sub-groups in US RCA indices.
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One of the interesting studies that focused at industry level in terms of the
relationship of the competitive or complementary nature of ASEAN countries with
China was undertaken by Tan (2005). In his study, Tan (2005) explored the impact of
liberalization of trade in textile and clothing industry in China on ASEAN countries for
the period of 1991 to 2003. The study found that ASEAN countries were more
competitive than complementary in their relationship with China in this sector (Tan,
2005). With the use of a constant elasticity of substitution model, the study also found a
significant negative effect of tariff elimination on ASEAN countries.
John Whalley (2006) took a different approach by introducing the impact of
eliminating trade restrictions under the Multi Fibre Arrangement (MFA) up to the end
of 2004 for exports of clothing and textiles using data from US, EU, China and other
main exporters. The result was only small impact on aggregate US and EU imports
of clothing and textiles, and equally only small impact on aggregate Chinese
exports of clothing and textiles. However, it was observed that there was a lot of
changes in the countries pattern of trade, and also within more narrowly defined product
categories. There were large increases in shipments from China to both the US
and the EU and for the US proportionally more so in textiles than in clothing. But
the US accounted for only 20 per cent of China's exports of clothing and textiles, and
exports to Japan (comparable in size to the US) hardly changed, and exports to
Hong Kong fell sharply. There were also large price falls for shipments to the US
and to certain EU countries (Germany). The shares of other Asian suppliers in US
markets generally stood still, with the largest falls occurring in preferentially treated
non-Asian suppliers such as Mexico. In the EU markets, with the exception of India,
all non Chinese Asian suppliers experienced fall in their market share.
Pholphirul (2010) focused in examining whether AFTA creates trade for
Thailand or actually diverts it away from the country. By using the Export Similarity
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Index (ESI), Intra-Industry Trade (IIT) Index, and Revealed Comparative Advantage
(RCA) rank correlation, the study revealed a high degree of similarity regarding the
trade structure between Thailand and AFTA, which indicates that there will be fewer
trade-creation benefits from AFTA and a greater likelihood of trade diversion once the
AFTA scheme has been fully implemented. This similarity pattern explains the reasons
for future collaboration among member countries and supportive arguments for the
future extension of ASEAN (“ASEAN+”). The study also suggested that market-
penetration and development strategies should be employed by Thai exporters when
accessing the ASEAN market.
Another study that looked into the impact of a policy decision was Adhikari
(2008). His study found that the post-quota world has not brought about a dramatic
transformation in the textile and clothings market as well as in sourcing patterns.
Among the losers of the post quota era, not all are on the same footing. While some
have graduated into the production of higher value products, others have lost out
because of their lack of competitiveness and their inability to adapt. The current
status quo is the result of the re-imposition of quotas on China as a part of the
temporary safeguard measures agreed by the country at the time of its accession to
the WTO. Countries that did not manage to withstand competition in the first six
month period after the phasing out of quotas need to be extremely cautious and
make every possible effort to enhance their competitiveness before the expiry of this
temporary measure in 2008. Given the history of protection in the textile and clothings
industry and rather strong political economy factors, market access remains the
largest single problem for the developing countries. However, this can be
resolved mainly through The study also recommended that there are several supply
side issues which are impeding the growth prospects of several developing
countries. These problems need to be addressed first at the domestic level. Despite
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protectionist barriers, the textile and clothings industry has not remained static over the
past five decades or so. It keeps evolving due to changing demand of the buyers,
sourcing patterns, availability of and access to technology, shifting levels of economic
growth and increased consciousness as well as sensitivity towards corporate social
responsibility and ethical procurement.
Matt Berdine et al.(2008) examined how the US textile and apparel industry can
remain competitive in the face of global competition. The study specifically addressed
what are the current competitive advantages and how they can be leveraged to enhance
the performance of US textile and apparel companies. In addition, the research sought to
examine the key components that are driving the competitiveness of the top textile and
apparel exporting regions in order to provide insight into how the US textile and apparel
industry can adapt and compete. The research methodology used a concurrent
triangulation strategy, which involves collecting quantitative and qualitative data
simultaneously. Overall, field-based interviews were conducted with 20 executives from
13 companies. The interview questions were categorized based on competitive
advantage variables, specifically focusing on innovation, marketing, and sourcing
criteria variables. Key findings of this research include evidence that US textile
companies drive the majority of the innovation in the supply chain to both suppliers and
customers. Also, the three competitive strategies that differentiate the products of US
firms from other regions of the world were research and development, marketing, and
customer service.
Ilyas, Mukhtar and Javed (2009) used year 1985 to 2005 as a reference period to
analyze competitiveness among Asian rice exporters in the world rice market using the
Balassa Revealed Comparative Advantage (BRCA) and White’s Competitive
Advantage (WRCA) over China in rice exports. There were no significant differences of
revealed competitive advantage between Thailand and Vietnam or between India and
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Vietnam in agricultural product trade or Pakistan and Vietnam in total merchandise
trade. Pakistan has a revealed comparative and competitive advantage in agricultural
product trade (in rice) over all other countries and in total merchandise trade (in rice)
over China, India and Thailand. Although Thailand and India are the two largest Asian
exporters of rice with 47 per cent of the market share in 2005, on an average they did
not have the greatest comparative and competitive advantage in rice exports. Pakistan
has the greatest advantage in rice exports, Vietnam ranked second and Thailand ranked
third in five major Asian exporters. Thus, it was concluded that both Pakistan and
Vietnam could take the advantage of competitiveness and raise their share respectively
in world rice market as compared with other Asian competitions.
Au and Chan (2003) examined the extent and determinants of intra industry
textile and clothing trade for OECD countries. Trade overlap was used as the
measurement of Intra Industry Trade (IIT). The general trend of intra-OECD trade and
the extent of IIT for textile and clothing trade in year 2000 were examined. Multiple
regression analysis was employed to verify empirically the proposed country-specific
determinants of bilateral IIT using bilateral trade data of the OECD countries.
Hypotheses relating to 5 country-specific variables tested showed strong significance
reflecting the different roles of the factors in the determination of IIT. It was also
identified that bilateral IIT in textile and clothing between OECD countries were highly
correlated.
Chemsripong (2010) applied the Grubel Lloyd Indices for the period between
year 2000 and 2010 for intra ASEAN trade and observed that there was strong empirical
support for the hypothesis that countries that have common borders and have eliminated
or lowered barriers on trade with each other will have relatively high levels of intra-
industry trade. Moreover, the extent of intra-industry trade will be positively correlated
with trade intensity. The level of intra-industry trade is higher between Malaysia,
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Singapore and Indonesia compared to the rest of the world. Thailand’s IIT was
increasingly changing from low-technology product to high-technology industries.
Turkcan and Ates (2010) examined composition of trade patterns, and
development of Intra-Industry Trade (IIT) for 367 trading partners in automotive
industry from year 1989 to 2006. In this paper, trade patterns and the extent of IIT in the
US automotive industry was analyzed by decomposing the US auto-industry trade into
inter-industry trade, horizontal IIT, and vertical IIIT and tested empirically various
country-specific factors concerning the determinants of IIT and its components between
the US and its major trading partners using the gravity model. The results showed that a
substantial part of IIT in the US auto-industry was vertical IIT and vertical IIT increased
over the data period. Increase in vertical IIT in auto-industry indicated that the
international fragmentation of production process has become important in the US auto-
industry.The econometric results mainly confirmed the fact that determinants of
horizontal IIT and vertical IIT differ. In particular, the finding showed that the extent of
the US horizontal IIT in automotive industry was positively correlated with difference
in per capita GDP and outward FDI variable while it was negatively correlated with
distance and bilateral exchange rate. On the other hand, vertical IIT was positively
associated with the average market size, differences in market size, differences in per
capita GDP, and outward FDI, and distance while it was negatively correlated with the
bilateral exchange rate variable.
Crinis (2012) examined the garment industry in Malaysia from 1970 to 2011. It
looked at the strategies employed by manufacturers to cope with both the end of the
Multi-fibre Arrangement (MFA) and the effects of the global economic crisis on the
industry in Malaysia. The garment industry in Malaysia is situated on the edge and is
almost totally reliant on contracts from the United States (US) and Europe for its
survival. Since the global economic recession, contraction in the consumption of
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garments in these countries had translated into factory closures and lay-offs in Malaysia.
It was argued that a regional strategy is necessary to cope with increasing levels of
competition from China and other parts of the world.
2.7 Summary
The key question to the literatures above was to examine the link of AFTA and
its trade effects, be it intra or extra ASEAN trade, trade creation or trade diversion.
Literatures above managed to link AFTA to trade effects, however, there is a grey area
that is not answered by the studies examined. The grey area is whether or not AFTA
was the contributor to trade effects of ASEAN. The literatures offer various different
approach, time and methods but mostly assuming that trade agreement such as AFTA
was simply implemented in 1993 and did not take into account the complexity and
dynamics of ASEAN. Most of the theories were based on static effect similar to studies
conducted on the European Community. This is against the principle proposed by
Bhagwati & Panagariya (1996) that in determining the actual effect of trade, it should
address the underlying problems in studies related to trade effects.
Central to resolve the underlying problem is to examine this gap by looking at
whether or not the trade agreements were used. In doing so, the second part of the
literature offered past studies with available data in the EU and US as well as some
studies undertaken in ASEAN. There exist a wide area to explore further on the
utilization of tariffs as focus in ASEAN has been more towards the cost impact of
preference utilization rather than the efficient use of the tariffs. Perhaps, due to the
limited data available and lack of consistency in applying trade policies has resulted
many researchers to turn away from undertaking such studies. An exploration of a study
focused at the efficient use of tariffs by any methods as discussed in this chapter would
enable to investigate the actual effect of AFTA to intra-ASEAN trade.
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CHAPTER 3: THEORETICAL FRAMEWORK AND METHODOLOGY
3.1 Theory of Free Trade Area
Trade theory related to a Free Trade Agreement or tariff related can be traced
back to the early years of neoclassical economics. The theory was dominated by the
approach of Augustin Cournot. His approach to economic analysis shaped “the core
structure of the twentieth-century economics” (Gomes, 2003). Cournot’s analysis on
international trade was in the form of mathematical expressions demonstrating that the
removal of tariffs causes a country worse off than under tariff protection especially
when it was analyzed with gains from trade measured in terms of money. Further in the
analysis, Cournot was able to show that there would be a “nominal reduction” of real
income in the importing country after the removal of tariffs (Gomes, 2003). This was
due to to the fact that the loss of producers of import-competing products outweighs the
gain to consumers. It was then concluded that imports reduce real income in the
importing country. This result was contrary to those derived using comparative cost
analysis and was criticized by other economists including Edgeworth, Viner, and
Samuelson (Gomes, 2003).
Paramount to the criticism was Viner who criticized Cournot’s argument of the
benefit of import duties is so obscure and falls short of establishing a case and stressed
that “it scarcely deserves attention on its own account” (Gomes, 2003). In effect,
protectionists used his findings commonly as a proof, which disproves the doctrine of
comparative cost advantage. Viner’s argument towards that was there would be a
possible additional gain to consumers “because at its reduced price the additional
purchases thereof may yield more satisfaction than the commodities they replace”
(Gomes, 2003).
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Another interesting early argument focused on the preferential duties was by
Pigou (1906) who provided theoretical arguments on the impact of protective tariffs on
revenue and income distribution published in Protective and Preferential Import Duties.
The article argues that theoretically tariff protection can increase the real income of a
factor used intensively in a protected industry. A hypothesis was made that if a country
has only two industries A and B, tariff protection given to industry A will increase the
output of that industry and reduce the output of industry B. This will in effect increase
the output produced by industry A and reduce the output of industry B. In this
connection, the argument that was in question was it was possible even with the
introduction of a tariff it would reduce the real national income as a whole and the
absolute return to the favoured factor may be improved by it. He then further
emphasized that free trade will have implication on the international movement of
factors of production. Tariff only raises the share of once factor to the national real
income, creates incentives for the international movement of disadvantaged factors.
Therefore, even if the introduction of a tariff is disadvantageous in terms of the share of
national income compared to labor, immigration of labor might not occur. However, he
suggested a different implication on capital since it is much easier to move from one to
another country.
A significant contribution to the analysis of international trade also came from
an Italian economist, Vilfredo Pareto. Pareto introduced a system of mathematical
descriptions to analyze trade in equilibrium involving many different markets. This
system based on the prices of goods brought some modifications to the traditional trade
theory, which was traditionally based on the labor theory of value. In some ways,
Pareto’s analysis is an extension of the classical Ricardian theory of trade in which
other economists use in their analysis.
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Eli Hecksher and Bertil Ohlin, two Swedish economists developed a theory by
incorporating neoclassical pricing in Ricardo’s comparative advantage theory, better
known as Hecksher-Ohlin (HO) Theory. The theory focused on analysis of the
determinants of comparative advantage and the effects of international trade on the
distribution of income. HO criticized that comparative advantage is entirely dependent
on differences in relative country supply condition, which is called the factor
endowments. HO points out that countries should export goods that use the country's
abundant factor intensively and import the goods that use the country’s scarce factor
intensively.
Before Viner’s model was developed, most economists believed that regional
trade agreements would increase welfare as those agreements would allow some degree
of trade liberalization. In contrast to this belief, Viner’s model showed that there could
also be a negative impact on welfare in a regional trade agreement. This model is
important as a framework as it lays the conditions that set if a FTA has positive or
negative impacts.
The main concepts in his model are trade creation and trade diversion that have
been expanded through his initial model by many economists. Trade creation is the
replacement of less efficient national production to a more efficient partner country
production. On the other hand, trade diversion is the replacement of more efficient non-
partner (third country not in the FTA) imports to less efficient partner country sourced
imports.
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Figure 3.1: Illustration of Viner’s Model
Source: Author’s Illustration adopted from Viner’s Model
Figure 3.1 above shows an illustration of Viner’s model. The figure shows the
demand and supply of a particular good for a domestic market of a country that wants to
join an FTA. Three levels of different prices are illustrated in the y-axis; first, the non-
partners price with the tariff, the partner’s price, and non-partner’s price. Viner’s model
also makes some assumptions as follows:
i. It is assumed that the country is small in an economic sense which means
that it does not have the pulling or pushing factor in influencing
international prices.
ii. The home country (domestic market) imposes a tariff on all imports of the
goods across the board prior to the FTA. The tariff in this model is
illustrated as either specific tariff or ad valorem. Tariff revenue is the tariff
multiplied by the quantity of imports.
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iii. non-partner is more efficient at producing the good than either the
domestic market or partner country in the FTA thus its price would be the
lowest among the three sets of category mentioned above.
Imports before the FTA is shown in the areas marked in brown and red. The
domestic market would produce a quantity of goods and local consumers would
purchase that quantity plus the imported units from non-partner that is able to supply the
product at lower price than partner country. In contrast, after FTA, the removal of tariffs
on imports from FTA partner would make these imports cheaper than non-partner for
the domestic market. As a consequence, the emergence of the blue and green area in
Figure 3.1 shows that with the lower price, more quantity is consumed. The lower price
then causes local production to shrink and reduce the product from the domestic
production.
Viner defined that the trade creation effect is the reduction in domestic
production that is met by more efficient imports as shown in the horizontal shift marked
blue in Figure 3.1. On the other hand, the marked green area shows a horizontal shift
that represents a rise in consumption and increase in imports. Gross trade creation can,
therefore, be summarized as the change in imports due to the FTA as shown in Figure
3.1 as the horizontal increase in Import after FTA and Import before FTA. This would
actually represent the sum of production and consumption effects of the FTA.
In contrast, at the same time, the FTA also causes trade diversion from the
imports from non-partner as imports from partner displace it. The country loses tariff
revenue on this imports as the source of imports from non-partners is replaced with
partners without tariff.
In understanding the welfare effects of an FTA to the domestic market, one has
to look at three variables as follows:
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i. Changes in producer surplus
ii. Consumer surplus; and
iii. Tariff Revenue
Producer surplus is defined as the amount that is benefitted by domestic
producers by selling their output in the market and this is represented as the area above
the supply curve and below the market price. In Figure 3.1, the loss in producer surplus
is reflected in the area marked yellow.
Consumer surplus, on the other hand, is defined as the consumers’ net benefit
from the market and is represented as the area under the demand curve and above the
market price. In Figure 3.1, the gain in consumer surplus is the sum of the areas marked
yellow, blue, brown and green. The loss in tariff revenue is then represented by the two
rectangles marked in brown and red. The net welfare effects of the FTA in the domestic
market is the combined effect of the changes in all these three variables and therefore is
the sum of area blue and green minus area red. The area marked blue is the gain from
switching from higher-cost domestic output to lower cost imports and the area green
represents the gain from switching from higher cost domestic output to lower cost
imports. Combined, both areas blue and green show the net gains from trade creation.
The area marked red, a net loss from trade diversion, then represents trade
diversion. The size of trade diversion depends on the original quantity of imports and
the difference between the partner’s and non-partner’s prices exclusive of tariffs. This
loss can be said as an efficiency loss because the discriminatory tariff regime under
FTA causes the country to lose tariff revenue while giving up the lowest cost imports.
As a conclusion, if the sum of the efficiency gains represented by areas blue and green
is larger than the efficiency loss shown in the area red, then the FTA is beneficial to the
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domestic market or the home country. If it is the other way round, the net welfare effect
would be negative.
Using Viner’s Model as the foundation, Meade (1955) introduced concepts
within a model with infinite supply elasticities and zero demand elasticity. The concept
presented trade creation as welfare gains and trade diversion as welfare loss. The
magnitude of welfare change depends primarily on the magnitude of trade creation and
trade diversion. Then, it also depends on the cost reduction brought by the trade creation
and the increase in cost when trade is diverted (Meade, 1955). Subsequently, Lipsey
(1957) presented that with the condition of a realistic downward sloping demand curve,
trade diversion would increase in welfare. On the other hand, an upward sloping curve
would have non-zero elasticity. Adding to this theory, Bhagwati (1957) viewed that for
the purpose of eliminating the possibility of trade diversion that has welfare gains, two
assumptions need to be made. First, the demand elasticity should be zero, and the
supply elasticity should be infinite. Meade (1955), Lipsey (1970), and Bhagwati
&Pangariya (1996) explained that the change of tariffs also has secondary effects in the
context of general equilibrium. Making a comparison between three countries, country
A exports good 1 to B and C, while country B exports good 2 to countries A and C, and
large country C produces all three goods, the secondary effect is then analyzed by
imposing tariff structure. If country A imposes tariffs on good 1 (t1) and good 2 (t2) and
the reduction of t2, for example, would lead to trade creation and welfare gain. It would
therefore in terms of general equilibrium, pose that the discriminatory tariff reduction t2
affects demands for goods 1 and 3 too.
For the case when the goods are substitute, then the import of good 3 decreases
that means it is trade diversion and export of good 1 increases signaling trade creation.
A small change in t2 would result in trade creation leading to welfare gain but, if t2
approaches zero, the trade diversion might be larger than trade creation leading to
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welfare loss. It should be stressed that the Meade-Lipsey model strictly abides a small
preferential reduction of tariff increases welfare while full liberalization (zero tariff) has
ambiguous effect.
3.2 Terms of Trade Effect of FTA
A few other scholars namely, Kemp (1964), Mundell (1964), Vanek (1965) and
others studied the terms of trade effect of FTAs. Theoretically, when a country
unilaterally reduces tariff to its trading partner while keeping tariff with the rest of the
world unchanged, terms of trade for trading partner improves on tariff-reducing country
and on the rest of the world. Terms of trade effect on tariff-reducing country with the
rest of the world are ambiguous (Mundell, 1964). Due to the terms of trade, FTAs can
dominate unilateral trade policies, especially for smaller countries which cannot affect
their terms of trade in isolation but can do it when they join FTA.
From a welfare perspective, it is ideal for large customs union to capitalize on
welfare maximizing tariffs, which are similar to welfare maximizing tariffs in a large
country case. At the same time, the monopoly power of each country on certain
products that it produces has an optimal tariff rate.
Trade creation and diversion remains a strong concept after the introduction of
economy of scale. It, however, must be expanded by cost reduction and trade
suppression (Corden, 1974). In theory, the formation of FTA expands the market and
lowers costs. At the same time, it also suppresses imports from rest of the world
(ROW), even though there might be more efficient producers in ROW. From the
welfare perspective, when two countries form an FTA in the presence of economy of
scale, the effects are still ambiguous. It leads to benefit the firms from countries in the
FTA as economy of scale and, larger market would not exist and encourage lower
average costs of production. However, it would also at the same time have a negative
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effect on the trade would be diverted from ROW. Therefore, the ideal situation is when
there is economy of scale and no external trade; both countries in FTA would gain. In
this situation, markets would expand and, the average cost will decline to signal a
positive effect. Trade diversion is obviously not present as there was no external trade.
The above theories take external tariffs of FTAs as given and when intra-FTA tariffs are
reduced external trade would change.
Another theory presented showed that a subset of countries could always form a
customs union in such a way that improves the welfare of members while leaving the
welfare of non-members unchanged which would increase the world welfare (Kemp &
Wan, 1976). This theory by Kemp and Wan (1976) is applicable when external trade
with non-members are kept and subsequently their welfare unchanged and eliminating
internal barriers within the customs union. It also requires inter-country transfers of
income within the customs union to ensure that no member will be worst off due to the
formation of customs union. Kemp & Wan (1976) in fact showed that a customs union
can always be formed in a way that improves the overall welfare. They concluded that
we do not observe a process of continual enlargement of customs union because of
institutional constraints, imperfect information and by political economy reasons (non-
economic motives).
3.3 Theories on Product Fragmentation
3.3.1 International Product Fragmentation Theory
In producing an end product, the world has moved to the international
fragmentation in the production processes with the lower transportation costs across
borders, improved technologies and reductions in trade barriers (Arndt & Kierzkowski,
2001). According to factor proportion theory, a country has a propensity to specialize in
production of products containing factor inputs that lie close to the factor proportions of
the country, since this makes the production relatively cheap. Differences between
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countries in factor costs and different requirements of factor-intensities in each stage of
production means that international fragmentation gives all countries, including
developing countries, opportunities to produce according to their comparative
advantage (Petersson, 2004). Arndt (2001) illustrates the effects of international
production fragmentation in an extended version of the Heckscher-Ohlin model. The
model assumes two countries, Home and Partner. In the first stage only the final goods,
X and Y, are assumed to make a way into the world market. The model also assumes
two factors of production, capital (K) and labor (L), and that the production of X is
relatively more labor-intensive, and hence, the production of Y is relatively more capital
intensive.
As presented in Figure 3.2, the factor requirements in each sector are given by
unitvalue isoquants X0 and Y0 and the factor-price ratio is given by (w/r).
Figure 3.2: Effects of International Product Fragmentation
(Source: Arndt, 2007)
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Introducing fragmentation to the model means that the production process of the
labor-intensive good X is divided into two stages, where for example the first stage is a
service stage that includes design and marketing, and the second stage is the assembly
production of the final product. It is also assumed that the two different stages of
production can be described in terms of their respective factor-intensities, and moreover,
that the factor-intensities differs.
The first stage of production (x1) is more capital-intensive than the second stage
of production (x2). Hence, the weighted average of the different components’ factor-
intensities is the total factor intensity of the final product X. The model also proclaims
that the labor-intensive stage of production x2 can be imported from a trading partner at
substantial cost savings. Taking x2 into account, the imports of the production function
of the X-industry can be completely explained by the x1-isoquants. Assuming positive
import of x2, the model takes into account the cost of imports of x2 measured in terms of
exports of x1. Hence, the quantity of capital and labor used in activity x1, together with
the amounts of capital and labor needed for production of the quantity of x1 that will
pay for imports of x2, equals the factor content of X. The new unit-value isoquant X11
will be shifted inwards closer to the origin since the production of good X will be
cheaper both when including the amount of x1 needed to produce one unit of final X and
the amount required to import the necessary x2 units.
At the initial factor-price ratio (w/r) the production costs of X have fallen while
relative commodity prices remain the same. As a consequence producers will want to
increase the output of X. The reduction of unit costs in the production of X changes the
relative factor prices and therefore causes a shift to (w/r)’, which is tangent to the
original Y-isoquant and the new X isoquant X11 and hence, the capital-labor ratios
increase in both industries.
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3.3.2 Product Specialization in a Preferential Trade Arrangement
The introduction of a PTA into the model is illustrated in Figure 3.3. The PTA is
assumed to be open to free trade in both end products and components. Initially, the
production is at Q and the consumption at C. The establishment of a PTA is assumed to
lower the price of X from Pd to Ppta. This will shift Home’s domestic production from Q
to Q’ and shift import to the Partner country. Hence, Home will change towards
relatively more capital-intensive production of Y. The new consumption at C’ is now at
a lower indifference curve than before, and hence, represents a welfare reducing effect.
In another set, the effect can also be welfare improving.
Figure 3.3: Trade in Preferential Trade Agreements
(Source: Arndt, 2001, p.80)
After introducing trade in components in the production of X in the PTA, the
production possibility curve expands from T’ to T’’ along the X-axis. The new
intersection between Ppta and the new production possibility curve shifts to Q’’. As in
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the previous example, illustrated in Figure 3.2, the output of good X increases while the
output of good Y decreases. In this situation the consumption moves to a higher
indifference curve to C’’, which tones down the negative effect of the PTA. Hence, the
introduction of trade in components in a PTA is always represented by a welfare
increase. Improved terms-of-trade for country Home is possible if the country is a large
member of the PTA since the regional increase in output of X and the decrease of
output of Y will cause a reduction in the relative price of X. The PTA price ratio will
rotate counterclockwise and hence lead to an even greater increase in Home’s welfare.
According to the Stolper-Samuelsson theorem, a fall in the relative price of the
endproduct will also cause the relative price of the factor used intensively in production
to decrease. Negative effects from a PTA that lower the price of the import competing
end-product X can in turn lead to downward pressure on wages and employment and a
smaller output of X. However, as illustrated in Figure 3.1, it is also important to point
out that component specialization in the X-industry affects factor prices in the opposite
way even with a lower relative price of the end product.
Hence, the introduction of specialization of components in a PTA that initiates
greater price competition among end-products should be beneficial for workers. Thus,
to the extent that the PTA also encourages intra-product trade i.e. trade in components
in the X-industry wages, industry output and employment will fall less or even rise. If
this effect dominates the terms of trade effect, both wages and employment will be
higher in the import competing X-industry than before.
For some countries, the price of end-products is regulated by trade relations with
nonmember countries rather than by the associated PTA. In such a situation, the main
objective for the country establishing a PTA with a low-wage country can be to
introduce trade in components in the import competing industry. The arrangement will
be welfare enhancing and in this way the country can benefit from cost savings from
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component specialization in order to stay competitive in the market of end-products.
After introducing trade in components in the production of X in the PTA, the production
possibility curve expands from T’ to T’’ along the X-axis. The new intersection
between Ppta and the new production possibility curve shifts to Q’’. As in the previous
example, illustrated in Figure 3.3, the output of good X increases while the output of
good Y decreases. In this situation the consumption moves to a higher indifference
curve to C’’, which tones down the negative effect of the PTA.
Hence, the introduction of trade in components in a PTA is always represented
by a welfare increase. Improved terms-of-trade for country Home is possible if the
country is a large member of the PTA since the regional increase in output of X and the
decrease of output of Y will cause a reduction in the relative price of X. The PTA price
ratio will rotate counterclockwise and hence lead to an even greater increase in Home’s
welfare. According to the Stolper-Samuelsson theorem, a fall in the relative price of the
endproduct will also cause the relative price of the factor used intensively in production
to decrease. Negative effects from a PTA that lower the price of the import competing
end product X can in turn lead to downward pressure on wages and employment and a
smaller output of X.
However, as illustrated in Figure 3.2, it is also important to point out that
component specialization in the X-industry affects factor prices in the opposite way
even with a lower relative price of the endproduct. Hence, the introduction of
specialization of components in a PTA that initiates greater price competition among
end-products should be beneficial for workers. Thus, to the extent that the PTA also
encourages intra-product trade i.e. trade in components in the X-industry wages,
industry output and employment will fall less or even rise. If this effect dominates the
terms-oftrade effect, both wages and employment will be higher in the import
competing X-industry than before.
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For some countries, the price of end products is regulated by trade relations with
nonmember countries rather than by the associated PTA. In such a situation, the main
objective for the country establishing a PTA with a low-wage country can be to
introduce trade in components in the import competing industry. The arrangement will
be welfare enhancing and in this way the country can benefit from cost savings from
component specialization in order to stay competitive in the market of end products.
3.3.3 Effects in the Partner Country
The effects in the Partner country when implementing the PTA can be of trade
diverting as well as trade creating nature. The removal of tariffs on both end products
from Home causes the price of good Y to fall in Partner, and thereby the country’s
terms-of-trade changes. This is illustrated in Figure 3.4 by the shift of the unit-value
isoquant from Y0 to Y’0. In turn, the wage-rental ratio increases from (w/r) to (w/r)’,
tangent to the new Y-isoquant at point a and the initial X-isoquant at point b.
Figure 3.4: Trade in intermediary products and the partner country
(Source: Arndt, 2001, p.83)
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Moreover, the introduction of trade in components to the PTA causes Partner to
abandon the production of component x1, which will instead be imported from Home.
The new production function for the X-sector is instead the x2-isoquant, which includes
the assembly production. The new relevant isoquant is set at X21 where it is tangent to a
lower expansion path of the initial factor-price ratio (w/r). Hence, the new factor-price
ratio equilibrium illustrates the change in terms-of-trade as well as the gains from
component specialization, and thus (w/r)’’ is tangent to Y’0 and X21.
The new factor-price ratio causes the capital-labor ratio in production to increase
to Oy’ and Ox’2. The described scenario with the introduction of component
specialization in the country’s export industry clearly strengthens the terms-of-trade
effect on the factor-price ratio. However, a decreasing welfare effect is also possible. As
recalled, total output of good X rises in the PTA region when trade in components is
introduced since Home is specializing in component x1 and is importing component x2
from Partner. If the increase in the regional supply of end product X is large relative to
shifts in demand, the relative price of X in the region will depreciate. Although Home
would benefit from this outcome, it would worsen the terms-of-trade for Partner and
hence, deteriorate the improved wage-rental ratio. To conclude the national welfare may
either increase or decrease with trade in endproducts between members of a PTA.
However, the introduction of intra-product specialization is unmistakably
beneficial to national welfare. Trade in components that leads to intra-product
specialization can convert a welfare reducing PTA into a welfare creating one, and
hence a PTA that encourages intra-product specialization among members should be
beneficial.
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3.3.4 Rules of Origin
An FTA involves the application of ROO in one form or another, which may
affect the effect of international fragmentation. If ROOs are not implemented in an FTA,
the definite effect will be a reduction of the effective tariff rate in the country with a
higher tariff structure, and the FTA will become a customs union (Panagariya, 2000). In
a partial analysis between Home, the country that has a high tariff structure, and Partner,
the preference receiving country, the lack of ROOs means that imported products in
Partner can be re-exported to Home free from tariffs. Partner is then likely to be the sole
supplier of the product to Home and will either produce the entire amount to be
exported to Home, import the good from a third country, or a mix of the two. The use of
ROO implies product discrimination on the basis of their ‘country origin’. A ROO
implies that in order to enter free of import tariffs, the commodity has to be classified as
originating from a specified area or region, most often the territories of the partners in a
FTA. Typically, two main distinctions are made; between foreign and domestic
products and among foreign products where not all imports are to receive preferential
treatment.
Since ROOs determine the eligibility for preferential treatment, one expects that
they will influence resource allocation depending on the way they are defined. If ROOs
change the origin of a product so that it acquires favorable treatment and hence creates
benefits for the producer that is larger than the increase in costs, the producer will adjust
production processes and input choices away from suppliers that would otherwise have
the lowest cost. In this way, the effect of ROOs that imply a shift from low-cost
suppliers outside the arrangements to high-cost partners will be a decrease in the cost
savings that arise from component specialization.
The inefficiency caused by ROO eliminates the possibility for producers to fully
exploit the benefits of intra-product specialization, and stands for a reduction in welfare
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gains. In this sense the ROO should be set in order to attain the least costly way, where
costs include both the costs of the agreement and, most importantly, the cost of
distorting the allocation of resources (Favley & Reed 1997). Moreover, concerns have
been raised about whether domestic content requirements will lead to lower production
levels of both the production of the end-product and the component, rather than boost
production. The potential for integration as well as the trade enhancing effects of
preferential treatment may be hampered by the employment of ROOs (Grossman 1981).
Moreover, for a small country the supply of components imported from abroad
and the domestic supply of the same input are determined by the world market price.
ROOs that require a certain percentage of the final product to contain region-specific
content will lead to greater average costs of the end-product at higher output quantities
than if all inputs were imported from abroad. This is because of the higher domestic
demand of inputs, which will lead to increasing price levels of components.
Furthermore, if the cost effect of ROO is the same as or greater than the tariff, the trade
agreement is unnecessary. Hence, it is reasonable to believe that the increased cost of
production due to ROO will still not shift the supply curve as much to the left as a tariff
does.
3.4 Economics of Rules of Origin
Most previous studies on the utilization rate of FTAs based on administrative
records from customs were mainly concerned with the impact of the restrictiveness of
the ROO on the utilization rate. In order to understand the underlying concept behind
the preferential tariff, which is ROO, it is important to look at the theory related to ROO
as the significant difference in theory between the use of MFN tariff and preferential
tariff lies on ROO.
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The ROO establish for each product in the tariff nomenclature of an FTA a set
of criteria specifying the amount and/or type of third party materials that may be
incorporated into a product without the product being disqualified for the preferential
tariff treatment. These criteria can specify a share of value added that must be
originating, specific stages of physical processing that must be carried out in the
territory of a member country or specific inputs that may not be imported from a non-
member.
The primary purpose of ROO is to prevent goods from non-member countries
trans-shipping through the member with the lower tariff to be sold in the country with
the higher tariff, thus avoiding payment of the higher tariff. The binding rules of origin
in general would first raise the cost of production. Inputs sourced from a regional
producer of intermediates by a final good producer would actually increase costs. The
context of rule of origin specified in terms of physical content by Krishna and Krueger
(1995) gives a good explanation.
Figure 3.5: ROO impact in Trade Agreements
(Source: Krishna and Krueger, 1995)
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The example in Figure 3.5 above shows that when a country produces using
imported capital (K) from a non-member of a Trade Agreement and domestic labour
(L), with a unit isoquant depicted by the curve, would minimize the cost by using the
combination of inputs with Labor/Capital ratio α0 at point x. The unit cost of this
production is represented by the area under the line AB. However, when the rule of
origin requires a higher level of domestic inputs for example α > α0 , it would move the
cost minimizing production point to Z with unit cost represented by the area under line
CD which is obviously larger than the area under AB. This effect on production costs is
the fundamental justification that makes rules of origin useful to prevent trade
deflection and other potential misuse.
Among the earliest work related to effects of rules of origin was from Grossman
(1981) in the context of domestic content requirement by governments on their own
producers. This work was then expanded by Krueger (1993), Krishna & Krueger (1995)
and Krishna K. (2006), who worked out more fully on the economic effects of rules of
origin. According to Krishna K. (2006) there are four laws on the effects of rules of
origin as follows:
i. Rules of origin can shelter industries from the effects of FTA;
ii. Details in the rule specification can matter significantly
iii. Short term and long term effects differ substantially
iv. Effects of increasing rule restrictiveness can be non-monotic and be
more complex
The first law that is most discussed is the effects of rules of origin. Besides
preventing trade deflection, rules of origin can be used or abused to alter the liberalizing
nature of a FTA. Rules of origin that require a key input be originating in the member
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countries can undo all liberalization if that input is not produced in any of the member
countries. Krishna also stressed that when a case where producers of an intermediate
input in one country are protected from international competition by a tariff. When the
country enters into a FTA, producers of a final good in the partner country that use this
intermediate can be bound by the rule of origin to use these protected intermediates at
the protected price in order for their final goods would be able to enjoy the preferential
tariff treatment by the FTA. This is an example where even though the partner country
may a zero tariff on the intermediates, the final good producers are effectively paying
the tariff-ridden price in order for their product to qualify. This phenomenon was also
dubbed as “exporting protection” by Krueger (1993). The second law sets out on the
calculation of regional value content (RVC) requirements. RVC’s specify the fraction of
value added in a product that must be originating in an FTA member in order for the
good to qualify as originating. Origin RVC calculations are not required for any purpose
other than origin determination and thus it is an added administrative overhead cost for
any producer who wishes to export under ADTA with a rule of origin based on RVC.
The third law lays the fact that the time frame actually matters. Based on the
work done by Krishna K. (2006), the last of which is the first full treatment in the
literature of donciditional policies like rules of origin in a full general equilibrium
framework. It shows that a rule of origin that is just binding or minimally restrictive
based on the pre-FTA stucture of prices and costs becomes non-binding once these
prices and costs adjust in the FTA environment. This result comes from changes
brought by the conditional policy on the factor price frontier faced by producers.
Furthermore, the changes in factor price frontier can induce changes in the wage-rental
ratio, which can then induce capital infows. Preferential access to a protected market
under binding rules of origin will attract investment in the production capacity of that
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good. This long term effect is particularly in the interest of relatively capital scarce
countries.
The fourth law holds the arguments for the non-monotonicity, which are bases
on a setup with heterogeneous firms in which as restrictiveness of the ROO increases,
begin to opt out of the preferential regime and revert to the MFN regime. In this regard,
it is shown that the combined imports of the FTA members from the rest of the world of
the final food first increase and then decrease as the restrictiveness of the rule increases.
Similar situation also happens in reverse for imports of the final good. At low
levels of restrictiveness, final goods producers redirect their output from their domestic
market to the FTA partner to take advantage of the benefits of the agreement (the
revenue transfer effect). This redirection of production from the domestic to the FTA
partner market will require the domestic market to be supplied by imports from the rest
of the world. As the restrictiveness of the ROO is increased, the cost increase caused by
the rule erodes the befits of the FTA and firms would switch from the FTA regime back
to the MFN regime in other words switching back to supplying their domestic market,
reducing imports from the rest of the world. Similar non-monotonicities are observable
in the prices of intermediates and final goods.
3.5 Relationship between ROO, Utilization Rate and Trade Performance
In assessing the impact of ROO, a causal relationship between a measure of
ROO and a measure of trade performance is required. There have been a few work that
analysed ROOs such as Estevadeordal (2000) where NAFTA’s product specific rule
were aggregated into a restrictive index. Similar indices were also expanded by Anson,
et al. (2005).
These studies have used performance measure taken as relative trade flows and
trade flows in a pair of countries affected by the ROO against pairs that are not affected,
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under the assumption that stringent ROOs will not just make the utilization of
preferences redundant, but will also stifle trade itself, by denying preferences. That is,
ceteris paribus, a stringent ROO acts like a reduction in the tariff-preference margin and
thus reduces trade flows (Cadot and Ing, 2014).
With the utilization rate data available, a revealed preference argument can be
made. As an example, when firm’s compliance costs are distributed around some
central value corresponding to the average firm and tariff preference margin for ceratin
product is 5 percent, the utilization of 100 percent would indicate that all firms have
ROO compliance cost below 5 percent. Conversely, if the utilization rate is 0 percent,
all firms have more than 5% compliance cost, while the utilization between 0 to 100
percent would reflect that firms have variable compliance costs that could be in the
range of 0 to 5 percent.
Using this similar argument, Pelkmans-Balaoing (2007) noted that the AFTA
utilization rate was on average only 5 percent and attributed this low rate to ROO and
other documentation requirements. They also found threshold effects in tariff-
preference margins (only at high levels did they affect trade), suggesting that the
compliance costs would offset the benefit of tariff reductions.
3.6 Conceptual Framework
In order to correspond to the problem statement in Chapter 1, the research is
designed and divided into three main components. The first part is the preferential tariff
utilization under AFTA for Malaysia and the second part is the impact of AFTA on
intra-regional trade for the three most sensitive industries in ASEAN, the agriculture,
automotive and textile industries. The third part is more of a combination of the first
and second, where panel regression model is developed to investigate utilization rate,
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revealed comparative advantage and intra-industry trade in the case of Malaysia for the
three sensitive industries. Figure 3.6 is an illustration of the approaches.
In the first part, the study aims to discover the direct impact of tariff elimination
under AFTA by examining the level of preferential tariff utilization. The theories
discussed in the earlier section that correspond to this are the theory on rules of origin
and the impact of rules of origin to trade performance. Both these theories are taken into
consideration because within the tariff elimination framework, the main prequisite is
rules of origin and without adhering to the rules of origin, goods will not enjoy the
preferential tariffs.
Figure 3.6: Conceptual Framework
The method that is then used to investigate the level of preferential tariff
utilization is by calculating two types of utilization rate, namely, generalized utilization
rate and adjusted utilization rate. These indices are based on the actual utilization level
of the preferential tariff, based on the certificate of origin produced in relation to the
rules of origin criteria. Malaysia is chosen for this exercise due to the actual data
Methods
Utilization Rate
(Generalised)
Utilization Rate
(Adjusted)
Theories
Economics of Rules of Origin
Impact of ROO on Trade
Performance
Part 1: Utilization of Preferential Tariff under AFTA
for Malaysia
Methods
Intra-Industry Trade (IIT)
Revealed Comparative Advantage (RCA)
Theories
Customs Union
Comparative Advantage
Product Specialization
in PTA
Part 2: Impact of AFTA on Intra-Regional Trade in Agriculture, Automotive and Textile Industries
Methods
Panel Regression Models
Theories
Theory of FTA
ROO, UR and Exports
Part 3: Determinants of Utilization Rates, RCA and IIT
for three industries for Malaysia
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availability.
The second part of the study intends to investigate the impact of AFTA to intra
ASEAN trade in the three most sensitive industries. The success of a trade agreement to
a region like ASEAN would be reflected in the level of intra-regional trade and three
industries are selected to examine this hypothesis, by calculating two indices, intra-
industry trade and revealed comparative advantage. By using both these methods, the
study would be able to determine whether ASEAN countries were competing with each
other or complementing each other. It would also reflect the amount of product
diversification that is brought by AFTA.
The last part of the study is a combination of both the first part and the second
part. A panel regression model is developed to investigate the determinants of
preferential tariff utilization, revealed comparative advantage and intra industry trade
for the three selected industries. The panel regression models would test whether or not
the theories explained in the earlier sections do correspond similarly based on actual
tariff utilization data.
3.7 Research Objectives and Questions
This research in general aims to analyse the impact of ASEAN Free Trade
Agreement (AFTA) from three angles. The first, is from the actual utilization of
preferential tariff under AFTA with the following objectives:
i. To examine the actual level of preferential tariff utilization under AFTA
and its effect to intra-ASEAN trade;
ii. To investigate and compare the impact on intra-ASEAN trade based on
the utilization level of preferential tariff under AFTA and MFN Tariff; and
iii. To examine the level of AFTA utilization by product categories.
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The second angle is focused in investigating industry level impacts of AFTA
with the following objectives:
iv. To analyze by selected industries the level of intra-industry trade. This
would allow examining the level of product diversification that is present as an
impact of AFTA, where a higher diversification would describe higher degree of
integration; and
v. To investigate whether under AFTA countries compete or complement
each other in intra-ASEAN trade for selected industries.
Further to that, the research would have a combination of both angles on the
third part of the research, where determinants of utilization rate, revealed comparative
advantage and intra-industry trade is investigated to test based on actual data, to what
extent does intra-regional trade is influenced by AFTA.
The specific research questions are as follows:
1. What is the actual transaction level of AFTA utilization and how does this
correspond to intra-regional trade within ASEAN?
2. What are the products that benefit largely from AFTA for Malaysia?
3. How can policymakers strategize to increase intra-regional trade through
tariff utilization?
4. How is the trend between ASEAN countries for revealed comparative
advantage and intra industry trade in sensitive industries?
5. What are the trade effects of AFTA in the three most sensitive industries?
Does AFTA create or divert trade with complementary or competitive
forces between countries?
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6. What are the determinants of utilization rate, RCA and IIT and to what
extend does it correlate to margin of preference and exports?
3.8 Methods and Data
3.8.1 Utilization of Preferential Tariff under AFTA
a) Methods
This section of research uses a similar concept employed by Pomfret, Kaufmann
and Findlay (2010), where utilization rate is defined as ratio of value receiving
preferential treatment against total value of imports. However, since the difference
between this study and the study by Pomfret, Kaufmann and Findlay (2010) is the data,
in which the latter has used customs data from the import viewpoint. This study,
however, focuses on the preferential treatment of AFTA under CEPT/ATIGA through
the issuance of the Certificate of Origin (CO). For this purpose, the concept adopted by
Pomfret, Kaufmann and Findlay (2010) is adjusted as the ratio of value receiving
preferential treatment against the total value of exports. The concept is also guided by
the work of Hayakawa, Laksanapanyakul, & Shiino (2013) where both methods of
customs data from the importer’s end and CO data from the exporter’s end is taken into
consideration. The basic utilization concept is described as follows:
Utilization Rate (Expressed in %) =
Value received preferential treatment under CEPT/ATIGA
Value of Exports
The formulation above works for the aggregate and disaggregated value. For the
purpose of this study, the utilization rate concept above is divided into two parts. First
the Generalized Utilization Rate (GUR) and second the Adjusted Utilization Rate
(AUR). GUR is the ratio between the value of CO per tariff line for the corresponding
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year against the total exports to the countries available for export in AFTA. In this case,
the numerator is the value of COs per tariff line at HS2 level for the years 2007 to 2011.
The number of tariff lines involved are 99 tariff lines. The denominator is the value of
Malaysia’s export to all ASEAN countries. Both the values are in USD. The
mathematical illustration of GUR in percentage is as follows:
GUR (t)ij= (X Co(t)ij) / (X(t)ij)
Where:
GUR (t)ij = General Utilization Rate of CEPT/ATIGA based on CO for country i
exporting to ASEAN j for tariff line t;
X Co(t)ij= Value of export which acquires the CO, for country i to ASEAN j for
tariff line t; and
X(t)ij = Total value of export of country i to ASEAN j for tariff line t
AUR on the other hand is defined as the ratio between the values of CO per
tariff line for the corresponding year against against the total exports to the countries
available for export in AFTA excluding values of MFN Proxy (here defined as values of
Singapore). Singapore is chosen as a proxy to reflect the MFN tariff as all its tariff rates
are at 0%. In this case, the numerator is the value of COs per tariff line at HS2 level for
the years 2007 to 2011. The number of tariff lines involved are 99 tariff lines. The
denominator is the value of Malaysia’s export to ASEAN minus the export values to
Singapore. Both the values are in USD. The mathematical illustration of AUR is as
follows:
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AUR (t)ij= (X Co(t)ij) / (Xnet(t)ij)
Where:
AUR (t)ij = Adjusted Utilization Rate of CEPT/ATIGA based on CO for country
i exporting to ASEAN j for tariff line t;
X Co(t)ij = Value of export which acquires the CO, for country i to ASEAN j for
tariff line t; and
Xnet(t)ij = Total value of export to ASEAN country minus export value for MFN
Proxy for tariff line t
b) Data
The data on the utilization rate is gathered at transaction level (values declared
under Form D28) for Malaysia from year 2007 to 2011 at FOB rate. The data used is the
compilation from the Ministry of International Trade and Industry, Malaysia. The
available data also consist of HS2 level values for 99 tariff lines of goods. The data on
Malaysia’s export to ASEAN countries at HS2 level from 2007 to 2011 is obtained
from the ASEAN Secretariat Statistics Database (ASEAN Secretariat, 2015). For the
purpose of both calculations of GUR and AUR, the value certified with CO in the
obtained records is assumed as exported to ASEAN countries. Since the data provided
by the Ministry of International Trade and Industry, Malaysia is in RM, the effective
exchange rate for the corresponding years is calculated using the average rate based on
daily 12.00pm count data of Bank Negara Malaysia.
28 Form D or Certificate of Origin is a document that certifies a product with the requirements of Rules of Origin under AFTA. Only products with this Form D issued by the authority of the exporting country would be able to enjoy tariffs under AFTA when the product is imported by another country under AFTA.
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3.8.2 Intra-Industry Trade (IIT)
a) Methods
An approach to examine the effect of FTAs in terms of trade creation or
diversion is by using Intra Industry Trade (IIT). IIT would allow to investigate if
abolishment of tariff in an FTA would create trade in particular industries or not and IIT
rate for countries in the FTA region should grow faster than the IIT rate for the same
countries against the rest of the world.
In general, IIT arises if a country simultaneously imports and exports similar
types of goods or services. The classification of the goods or services in the same sector
reflects the similarity nature of the goods or services. The concept of IIT first received
attention in the 1960s in studies by Bela Balassa on the increased trade flows among
European countries.
Grubel and Lloyd (1975) then provided the definitive empirical study on the
importance of intra-industry trade and how to measure it. Comprehensive theoretical
foundations for explaining intra-industry trade came later in the 1980s and 1990s mostly
based on a monopolistic competition framework. Intra-Industry trade is usually divided
to two types; horizontal intra-industry trade and vertical intra-industry trade. Horizontal
intra-industry trade refers to the simultaneous exports and imports of goods classified in
the same sector and at the same stage of processing. Whereas vertical intra-industry
trade refers to simultaneous exports and imports of goods classified in the same sector
but different stages of processing.
Intra Industry trade plays a vital role in trade of manufactured goods in
particular as most countries have become increasingly similar in their levels of
technology and the availability of capital and skilled labour. Due to different
endowment and non-identical trade structure, there is no definite comparative advantage
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within an industry. In this regard, the form of two-way exchanges within industry driven
by economies of scale rather than inter-industry specialization is more widely accepted
(Krugman, 1995).
IIT thus would reflect growth in intra-regional trade blocs and generate benefits
from trade by increasing product variety. A country engaged in high levels of IIT for
instance can concurrently reduce the number of products it produces and increase the
variety of goods available to domestic consumers. In order to produce fewer varieties, a
country can produce each variety of goods on a large scale with higher productivity and
lower costs. Therefore, IIT tends to be apparent between countries that are similar in
their factor endowment. Gains from trade will be large when economies of scale are
strong and products are highly differentiated.
Both economies of scale and product differentiation are essential for the trade
pattern of IIT. On economies of scale, it is specifically increasing returns to scale which
often plays an important role for the appearance of IIT (Hansson, 1989). It is economies
of scale in production, which makes each firm to produce only a specific set of varieties
of the products within a product group. Economies of scale are the fundamental reason
for IIT (Krugman, 1995). By trading, the countries will gain from having a larger
market. In the case of constant returns to scale, the production is determined by
comparative advantages, i.e. Heckscher-Ohlin theory.
b) Measuring Intra-Industry Trade (IIT): The Grubel-Lloyd Index
This study uses the index introduced by Grubel and Lloyd (1975) that measures
the level of intra industry trade. This measure, known as the Grubel–Lloyd index (GL
Index), is simple to calculate and intuitively appealing. Once a country’s export and
import value for a particular sector and period are known, it is calculated as:
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| || |
Where;
Xij is the value of country i’s exports of product j to the market under
investigation
Mij is the value of the country’s imports of product j from the market being
examined
When there is no intra-trade within a given industry, it is expected that a country
either export or import it, not both, in which the IIT index would be equal to 0. On the
other hand, if a country’s exports and imports within an industry were equal, the IIT
index would be equal to 1. The IIT Index is calculated for the three separate industries
in HS3 level classification to ensure that data are more accurate in representing product
level items.
c) Data Collection
For the purpose of IIT indices, data is collected from published materials by
International Trade Centre based in Geneva, which collects data from UNCOMTRADE
(International Trade Centre, 2015). The data that is collected is for the ASEAN-5
countries for year 2001 to 2014. However, for Vietnam, data for the year 2014 were
mostly unavailable at product level, therefore, it was only collected up to year 2013 for
Vietnam.
The types of data include individual ASEAN-5 values for exports and imports to
and from individual ASEAN-5 countries. The data is collected at HS4 level and it is
then combined to form the HS3 level data as explained in the next section in detail.
Exports of each individual ASEAN-5 to the world is also collected using the similar
method.
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3.8.3 Revealed Comparative Advantage (RCA)
a) Methods
The potential gains from FTA depend on whether the trade pattern between one
country and another in the FTA is complementary of substitutable. The purpose of RCA
index is to measure the competitiveness of the countries’ industries in the global market.
RCA index is a standard approach or methodology to estimate a country’s comparative
advantage or comparative disadvantage in commodities, industries or sectors. Based on
Ricardian theory, comparative advantage occurs due to technological dissimilarities
across nations, while the Hecksher-Ohlin (H-O) theory considers cost dissimilarities
arising due to differences in factor prices across nations, assuming constant technology.
In this regard, it can be summarized that trade theories in classical context are based on
pre-trade relative price differences across countries.
According to Balassa (1965), it is not necessary to observe all elements effecting
comparative advantage of any country rather one should observe patterns of trade. Since
data on trade explains revealed comparative advantage, it is a commonly accepted
measure. Balassa Index focuses on estimating comparative advantage of any country
and not on determining its sources. The revealed comparative advantage (RCA) index,
introduced by Balassa (1965), is used to determine the products in which a country has
a comparative advantage. It is defined as the ratio of a country’s share of the commodity
in the country’s total exports to the share of world exports of the commodity in total
world exports. A country is said to have a revealed comparative advantage if the value
of the index exceeds 1 and a revealed comparative disadvantage if the index’s value is
below 1. The larger the difference between countries’ RCA indices, the more suitable
they are as FTA partners.
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There were many other concepts after Balassa (1965) to determine comparative
advantage where some of the studies revised the definition of RCA and some other
measures also exist in literature on RCA globally which expands RCA with different
methodologies. These varieties among others include RCA indices with Normalized
Revealed Comparative Advantage Index (NRCA) that provides comparison over time
and space and some measures that evaluate comparative advantage in bilateral trade.
The RCA Balassa (RCAB) index is expressed as follows:
RCAB (Balassa Index) = Xij / Xin ÷ Xwj / Xwn
Where;
Xij is the export of country i, for, j commodity;
n is a set of all exported commodities of country i;
Xwj represents the export of world for same commodity j;
Xwn is a world export of all n commodities
In general the results of this index would assume that if the index is above 1, the
country has comparative advantage and when the index is below 1, the country has no
comparative advantage.
b) Measuring Revealed Comparative Advantage (RCA)
This study uses the revealed comparative advantage (RCA) index, introduced by
Balassa (1965), which determines the comparative advantage of a product for a country.
It is defined as the ratio of a country’s share of the commodity in the country’s total
exports to the share of world exports of the commodity in total world exports. A country
is said to have a revealed comparative advantage if the value of the index exceeds 1 and
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a revealed comparative disadvantage if the index’s value is below 1. The larger the
difference between countries’ RCA indices, the more suitable they are as FTA partners.
In general the results of this index would assume that if the index is above 1, the
country has comparative advantage and when the index is below 1, the country has
comparative disadvantage. To ensure that this model fits for the purpose of intra-
ASEAN trade, this study employs a formula based on the basic RCA formula above.
This formula is to show to what extent members of ASEAN are competing in the
ASEAN market and it will also show the degree of competitiveness of each ASEAN
country in selected ASEAN markets for all three industries. The formula is as follows:
RCAij = (Xijm / Xitm) / (Xawj / Xawt)
Where;
Xijm is exports of product j by country i to market under investigation;
Xitm is total exports of country i to market under investigation;
Xawj represents ASEAN’s exports of product j to the world;
Xawt represents total ASEAN’s exports to the world
For the purpose of this study, ASEAN countries that are involved in this formula
is only limited to Indonesia, Malaysia, Thailand, Philippines and Vietnam. The market
under investigation is based on the pairs explained in the earlier section, which would
allow the study to investigate deeper from each country’s point of view. This is repeated
for all three industries.
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c) Data Collection
For the purpose of RCA indices, data is collected from published materials by
International Trade Centre based in Geneva, which collects data from UNCOMTRADE
(International Trade Centre, 2015). The data that is collected is for the ASEAN-5
countries for year 2001 to 2014. However, for Vietnam, data for the year 2014 were
mostly unavailable at product level, therefore, it was only collected up to year 2013 for
Vietnam.
The types of data include individual ASEAN-5 values for exports and imports to
and from individual ASEAN-5 countries. The data is collected at HS4 level and it is
then combined to form the HS3 level data as explained in the next section in detail.
Exports of each individual ASEAN-5 to the world is also collected using the similar
method.
3.8.4 Reclassification Method
As specified in the earlier sections, two methods are used to investigate the impact of
AFTA on intra ASEAN trade. The methods are Intra-Industry Trade (IIT) and Revealed
Comparative Advantage (RCA). This study plans to investigate industry level impact of
AFTA, rather than only looking into aggregate values that would not represent the level
of integration in reality. For this purpose, the study reorganized the three industries from
HS4 level data to HS3 level data which represents a more accurate division on similar
products and not as broad as the HS2 level data. Furthermore, data at HS4 level
sometimes have too many zero values that might not be suitable for the purpose of data
analysis.
The three chosen industries are Agriculture, Automotive and Textile & Clothing.
The reason choosing agriculture is because most of the products in the agriculture sector
are basic non-processed products that do not go through sophisticated production
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process. Automotive was chosen to represent a growing market in ASEAN that has
products that are highly processed and the textile industry on the other hand is a
combination of both.
Next, to investigate the relationship at intra-ASEAN level, both indices are
estimated for five ASEAN countries, namely, Indonesia, Malaysia, Thailand,
Philippines and Vietnam. These countries are chosen based on the involvement in
AFTA and unlike many other studies that include Brunei and Singapore, Vietnam is
chosen to replace these countries. Brunei is excluded as the trade value for all the
products under the three industries are very low and inclusion of Singapore as a free
trade port would distort the actual benefit of AFTA as it would not represent the benefit
of AFTA.
The indices to determine the extent of intra ASEAN trade is then examined by
calculating the following pairs:
i. Malaysia in Indonesia market; ii. Malaysia in Thailand market; iii. Malaysia in Philippines market; iv. Malaysia in Vietnam market; v. Indonesia in Malaysia market; vi. Indonesia in Thailand market; vii. Indonesia in Philippines market; viii. Indonesia in Vietnam market; ix. Thailand in Malaysia market; x. Thailand in Indonesia market; xi. Thailand in Philippines market; xii. Thailand in Vietnam market; xiii. Philippines in Malaysia market; xiv. Philippines in Thailand market; xv. Philippines in Indonesia market; xvi. Philippines in Vietnam market; xvii. Vietnam in Malaysia market; xviii. Vietnam in Thailand market; xix. Vietnam in Indonesia market; and xx. Vietnam in Philippines market
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Both IIT and RCA indices are then calculated for all the three industries based
on the 20 relationships mentioned above. The reclassification of HS4 level products to
HS3 is described as following:
a) Agriculture Industry
Figure 3.7 : Reclassified HS4 Products to HS3 level for Agriculture Industry
HS3 Level Products HS4 Combinations
060 Cut flowers, Branch, Plants etc. 0601, 0602, 0603, 0604
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips
0701, 0702, 0703, 0704,0705, 0706, 0707, 0708, 0709
071 Manioc, Frozen Vegetables, Dried Vegetables
0710, 0711, 0712, 0713, 0714
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples
0801, 0802, 0803, 0804, 0805, 0806, 0807, 0808, 0809
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel
0810, 0811, 0812, 0813, 0814
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla
0901, 0902, 0903, 0904, 0905, 0906, 0907, 0908, 0909
091 Ginger,saffron,turmeric, thyme, bay leaves & curry
0910
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye
1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten
1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc.
1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc.
1210, 1211, 1212, 1213, 1214
130 Vegetable saps & extracts, Lac; natural gums, resins, gum-resins & balsams
1301, 1302
140 Vegetable Products and Materials 1401, 1402, 1403, 1404
b) Automotive Industry
Figure 3.8: Reclassified HS4 Products to HS3 level for Automotive Industry
HS3 Level Products HS4 Combinations
870 Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
8701, 8702, 8703, 8704, 8705, 8706, 8707, 8708, 8709
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi-Trailers
8710, 8711, 8712, 8713, 8714, 8715, 8716
*401 Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
4011, 4012, 4013 (*only products relevant to Automotive industry)
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c) Textile and Clothing Industry
Figure 3.9: Reclassified HS4 Products to HS3 level for Textile and Clothing Industry
HS3 Level Products HS4 Combinations
430 Furskins raw, tanned or dressed and artificial apparel and furs
4301, 4302, 4303, 4304
500 Raw silk and silk yarn 5001, 5002, 5003, 5004, 5005, 5006, 5007
510 Raw wool, wool yarn and animal hairs 5101, 5102, 5103, 5104, 5105, 5106, 5107, 5108, 5109
511 Woven fabrics of wool or animal hair carded or combed
5110, 5111, 5112, 5113
520 Cotton, cotton yarn and woven cotton 5201, 5202, 5203, 5204, 5205, 5206, 5207, 5208, 5209
521 Woven fabrics of cotton 5210, 5211, 5212
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables
5301, 5302, 5303, 5304, 5305, 5306, 5307, 5308, 5309
531 Woven fabrics of jute, vegetable fibre 5310, 5311
540 Man-made:filaments yarn and synthetic yarn
5401, 5402, 5403, 5404, 5405, 5406, 5407, 5408
550 Synthetic and artificial: filament tow, staple fibres
5501, 5502, 5503, 5504, 5505, 5506, 5507, 5508, 5509
551 Staple fibre; man made yarn, woven fabrics
5510, 5511, 5512, 5513, 5514, 5515, 5516
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc
5601, 5602, 5603, 5604, 5605, 5606, 5607, 5608, 5609
570 Carpets and other textile floor covering 5701, 5702, 5703, 5704, 5705
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc
5801, 5802, 5803, 5804, 5805, 5806, 5807, 5808, 5809
581 Embroidery in the piece of strips or in motifs
5810, 5811
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc.
5901, 5902, 5903, 5903, 5904, 5905, 5906, 5907, 5908, 5909
591 Transmission or conveyor belts; text prod & articles for tech use
5910, 5911
600 Fabrics, knitted/crocheted 6001, 6002, 6003, 6004, 6005, 6006
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc
6101, 6102, 6103, 6104, 6105, 6106, 6107, 6108, 6109
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc
6110, 6111, 6112, 6113, 6114, 6115, 6116, 6117
620 Women and man:overcoat, jacket, dresses, undergarments etc
6201, 6202, 6203, 6204, 6205, 6206, 6207, 6208, 6209
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc
6210, 6211, 6212, 6213, 6214, 6215, 6216, 6217
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents
6301, 6302, 6303, 6304, 6305, 6306, 6307, 6308, 6309
631 Rags, scrap twine, cordage, rope 6310
640 Footwear 6401, 6402, 6403, 6405, 6406
650 Hat and Headgear etc 6501, 6502, 6503, 6504, 6505, 6506, 6507
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With the reclassification above, the number of tariff lines covered would be 13
for agriculture, 3 for automotive and 26 for textile and clothings. The total number of
tariff lines covered at HS3 level for all three industries would be 42, while it would
provide a combination of 258 tariff lines at HS4 level. Figure 3.10 illustrates the
summary of product lines covered.
Figure 3.10: Number of product lines covered at HS3 for Agriculture, Automotive and Textile and Clothings Industry
Industry Number of Product Lines Covered at HS3
Number of combined Product Lines Covered at HS4 level
Number of HS3 product lines for 20 pairs (IIT)
Number of HS3 product lines for 20 pairs (RCA)
Agriculture 13 71 260 260 Automotive 3 19 60 60 Textile and Clothing
26 138 520 520
Total 42 258 840 840
When the product line level investigation is matched with the pairs under
investigation, total to 20 pairs, IIT and RCA repectively would result in 840
observations each (this is without considering time series data). Combined both IIT and
RCA would result in 1680 observations. This would allow the research to obtain results
that actually represent the status of integration in the respective industries.
3.8.5 Panel Regression Model
In assessing the impact of ROO, a causal relationship between a measure of
ROO and a measure of trade performance is required. There have been a few work that
analysed ROOs such as Estevadeordal (2000) where NAFTA’s product specific rule
were aggregated into a restrictive index. Similar indices were also expanded by Anson,
et al. (2005).
These studies have used performance measure taken as relative trade flows and
trade flows in a pair of countries affected by the ROO against pairs that are not affected,
under the assumption that stringent ROOs will not just make the utilization of
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preferences redundant, but will also stifle trade itself, by denying preferences. That is,
ceteris paribus, a stringent ROO acts like a reduction in the tariff-preference margin and
thus reduces trade flows (Cadot and Ing, 2014).
With the utilization rate data available, a revealed preference argument can be
made. As an example, when firm’s compliance costs are distributed around some
central value corresponding to the average firm and tariff preference margin for ceratin
product is 5 percent, the utilization of 100 percent would indicate that all firms have
ROO compliance cost below 5 percent. Conversely, if the utilization rate is 0 percent,
all firms have more than 5% compliance cost, while the utilization between 0 to 100
percent would reflect that firms have variable compliance costs that could be in the
range of 0 to 5 percent.
Using this similar argument, Pelkmans-Balaoing (2007) noted that the AFTA
utilization rate was on average only 5 percent and attributed this low rate to ROO and
other documentation requirements. They also found threshold effects in tariff-
preference margins (only at high levels did they affect trade), suggesting that the
compliance costs would offset the benefit of tariff reductions.
To describe the relationship between RCA, IIT, UR and exports, a panel
regression model is formulated. With higher RCA, it represents lower cost of
production, thus meaning that the cost for ROO with regional value content will be
minimal. With higher RCA values, UR should also be higher given the low ROO,
unless its MFN margin is high or 0%. A simple illustration of the argument is shown in
Figure 3.11.
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Figure 3.11: ROO relationship under CEPT/ATIGA and MFN Tariffs - Estimation
Specifications MFN Tariff CEPT/ATIGA
Conditions Assumption: Tariff Rate for product x = 20% Cost for additional requirement = None
Assumption: Tariff Rate for product x =10% Cost additional requirement = ROO requirement to source from region = +5% Administrative requirements = + 2%
Tariff Rate 20% 10%ROO requirement none Only from region, regional
value content (RVC) of 40%Additional cost for ROO
None. Can source from anywhere with least cost
5% additional as limited source of production in region
Administrative cost for getting ROO (certification, lab tests etc)
None. 2% additional
Total Costs: 20% 17%
As shown in Figure 3.11 above, although if CEPT/ATIGA tariff rates are lower
or even 0%, the cost involved in exporting the product increases with the requirements
for ROO, where instead of sourcing the materials to produce from the cheapest
available supplier globally, it forces the exporter to use less efficient materials with
higher cost from the region. The cost is then further increased with administrative
requirements to fulfill the ROO such as certification or lab tests. In this situation, ROO
would have increased the cost of production. Therefore, the question of whether or not
the tariff reduction of AFTA is beneficial can be seen from the following angles:
i. The cost of production for AFTA including the lower tariff under CEPT
provides savings to the importer in comparison to the use of MFN tariff.
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ii. A revealed comparative advantage (RCA) would show that the additional
costs required to fulfill ROO is lesser or eliminated.
iii. A high volume of exports would show that importers would be able to save
in scale despite small difference in MFN and CEPT tariffs.
A simple panel regression model is developed based on the results from the
Utilization Rates, RCA and IIT. This is to investigate the determinants of Utilization
Rate, RCA and IIT for Malaysia. The data that is used for this panel regression model is
based on the results in the earlier sections for Malaysia. The data is aggregated at HS2
level to ensure consistency for UR data.
In total, the data are a panel of 17 subsectors in the agriculture and textile
sectors, each of which is observed in every year over the period of 2007 to 2011. In the
case of the automotive sector, 2 subsectors are examined over the same years. For each
sector, three panel data model specifications are employed to examine the determinants
of the Utilization Rate (UR), Relative Comparative Advantage (RCA) and Intra-
Industry Trade (IIT). The econometric models estimated are as follows:
(1) URxyit = α0 + β1MOPRxyit + β2EXxyit + i + Ԑit (I =1,…,N; t=1,…,T)
(2) RCAxyit = α0 + β1MOPRxyit + β2EXxyit + URxyit + i + Ԑit (I =1,…,N;
t=1,…,T)
(3) IITxyit = α0 + β1MOPRxyit + β2EXxyit + URxyit + i + Ԑit (I =1,…,N;
t=1,…,T)
Where:
URxyit denotes the utilization rate;
RCAxyit denotes the revealed comparative advantage;
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IITxyit denotes intra-industry trade;
MOPRxyit denotes the average MFN rate for product i at HS2 tariff line minus
CEPT rate for ASEAN countries in percentage for year t;
EXxyit denotes exports of products I from country x (Malaysia) to ASEAN y for
year t;
The term I is the stochastic term of the model (capturing other possible
influences on the respective dependent variables);
The term i recognises the heterogeneity among sectors; and
The terms and refer to the parameters of the model to be estimated.
The first model is based on the hypothesis that all other things being equal, the
higher the margin of preference rate between the CEPT and MFN, the higher the
utilization rate. It would also investigate the notion of the higher the value of exports
per tariff line, the higher utilization rate should be recorded. The second model intends
to investigate the relationship of RCA with MOPR, exports and UR. The idea behind
this model is countries with significant RCA would have benefitted from the intra-
regional trade. Similarly, the relationship of IIT with the same variables is investigated
for the same purpose.
3.8.6 Estimation
The econometric model is estimated using two techniques: the fixed effects or
FE estimator and the random effects or RE estimator. The former basically assumes
that the i are fixed, non-random terms while the latter assumes that the i are random
and distributed independently of the overall stochastic term of the model, it. The
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Hausman test is performed to select which of the FE and RE estimators is the more
appropriate estimator, before proceeding to interpreting the results.
In what follows, the model is estimated using all observations, the Hausman test
is performed to select between the FE and RE estimators and then the coefficients of the
model are interpreted. The null hypothesis is that the preferred model is random effects.
It tests whether the unique errors are correlated with the regressors. Using the preferred
model, how a given 10% increase impacts on the dependent variable is considered.
Coefficients and standard errors are presented for each industry. All variables
are transformed to natural logs to take into account of data collinearity. The Hausman
test is used to determine the selection of a Fixed Effects or Random Effects in model in
each case.
The potential impact of the global financial crisis in 2008 and its impact in 2009
is accounted for by including a year dummy in each year where 2007 is the base year.
For example, a negative result in 2008 indicates that the dependent variable is lower on
average compared to the year 2007. In the case of the automotive industry, the sample
size is considerably smaller so an alternative and simpler approach is used to account
for the economic recession as follows. A binary dummy variable is included for the
years 2008 and 2009. This does control for the recession but does not have the
advantage of showing the relative effect compared to other years.
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CHAPTER 4: RESULTS AND DISCUSSION
4.1 Introduction
This chapter presents the results of the entire study. The first part discusses the
results on the utilization of preferential tariff under AFTA. The second part is the results
from intra-industry trade, followed by revealed comparative advantage for the three
selected industries. The last part of this chapter discusses the results from the panel
regression model.
4.2 Utilization of Preferential Tariff under AFTA: Case of Malaysia
The results of both Generalised Utilization Rate (GUR) and Adjusted Utilization
Rate (AUR) rates at aggregate level for all products were considerably low for the
period of 2007 to 2011. GUR in 2007 recorded 8.7% and increased to 9.7% in 2008,
12.8% in 2009, 17.5% in 2010 and 20% in 2011. The average GUR was 13.7% for the
period of 2007 to 2011 and the rate was very low. This shows that not many exporters
in Malaysia take advantage of AFTA’s preferential trade treatment. It also suggests that
the preferential tariff offered under AFTA was unable to influence the exporters of
Malaysia to expand trading within ASEAN. The utilization tariff rate was small
fraction of Malaysia’s export to ASEAN. Therefore it can be safely argued that the
increase in exports for Malaysia to ASEAN was not attributed to AFTA preferential
tariff. On the other hand, from Malaysia, there was an increasing trend of GUR from
2007 to 2011. The highest increment of GUR was between year 2009 to 2010 with an
increase from 12.8% to 17.5%. However, the increasing trend of GUR was inconsistent
with the export trend of Malaysia to ASEAN. GUR increased during the same period of
time although the values of exports fluctuated. This trend suggests that utilization of
preferential tariff was increasing regardless of what the volume of export was. It also
means that in terms of trend, exporters in reality are increasing the use of preferential
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tariff and the use of the preferential tariff does not constitute the same exports. Although
this is a positive outlook, a further investigation at the product level would be able to
explain the trend and perhaps the opportunities ahead. Table 4.1 below shows the
recorded GUR, AUR and the percentage of difference between both GUR and AUR.
Table 4.1: Malaysia: GUR, AUR export to ASEAN, 2007-2011
Year Generalized Utilization Rate
(GUR)
Adjusted Utilization Rate
(AUR)
Difference
2007 8.7% 20.0% 11.3% 2008 9.7% 20.6% 10.9% 2009 12.8% 22.7% 9.9% 2010 17.5% 25.4% 7.9% 2011 20.0% 26.2% 6.2%
Average 13.7% 23.0% 9.3% (Source: Author’s calculation)
When the rates for GUR exclude the exports to Singapore29, the values of AUR
also showed an increasing trend from 2007 to 2011. However, AUR remained low for
the period of 2007 to 2011 and the average AUR recorded was only 23%. The inclusion
of the MFN proxy as explained in the previous chapter is to exclude the majority of
products that is subjected to the MFN tariff. Since the MFN tariff is 0% for Singapore,
exporters would definitely not use preferential tariff under AFTA. The rationale behind
this adoption was to eliminate the products that would automatically not benefit from
the preferential tariff. By doing this, it was expected that the utilization rate would
increase, as it would only focus on product lines that was significant to the preferential
tariffs. Despite eliminating the MFN proxy product lines of Singapore, the utilization
rate remained low with an average of 23% (AUR). Although the rate was around 10%
higher than the average of GUR, this suggests that the application of MFN tariffs does
not significantly increase the preferential tariff utilization. This statement is based on
29 Singapore is selected as a proxy for MFN rates due to its MFN rates that are at 0%, which also suggest that preferential tariff is not significant for Singapore.
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the difference between GUR and AUR as shown in Table 4.1, which shows a
decreasing trend. The gap between GUR and AUR decreased from 11.3% in 2007 to
6.2% in 2011. Since the calculations were made with the assumption that MFN tariffs
was already embedded in the system, the reduction in this gap could explain that there
was a significant increase of products that utilized the preferential tariff despite the
existing MFN tariffs. This trend however also reflects the value of both GUR and AUR
would be levelled under the current conditions as the MFN tariffs pose competition in
the system. Whatever it takes, this trend suggests that Malaysia’s export that utilizes
preferential tariff under AFTA would always remain at certain level and the potential
for full utilization or 100% utilization of the preferential tariff cannot be achieved given
the competition of MFN tariff and the low coverage of tariff lines by some ASEAN
countries under AFTA.
In order to have a more comprehensive understanding of issues discussed above,
GUR was calculated at HS2 product levels and the selected top ten GUR is shown in
Table 4.2. The highest rates of GUR for the period 2007-2011 are HS87 (Vehicles other
than Railway or Tramway Rolling-Stock and parts thereof), the rate at 83%; HS40
(Rubber and Articles) the rate at 70%; HS09 (Coffee, Tea and Spices) the rate at 63%;
HS57 (Carpets and Other Textile Floor Coverings) the rate at 63%; and HS62 (Articles
of Apparel and Clothing Accessories) the rate at 56%. The top ten products for GUR
show that preferential tariff was really useful in exports and show that AFTA had
brought benefits to producers and consumers of those products. On the other end, for
year 2007 to 2011, 29 same tariff lines recorded 0% GUR, which means that there were
no shift at all for exporters to use preferential tariff for the 29 product lines. It could also
mean that either the ROO for these tariff lines were relatively too costly or the MFN
rates for these products were liberalized for most ASEAN countries. This shows that
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despite having preferential tariffs for the 29 tariff lines, this did not benefit Malaysia at
all.
The result of AUR at HS2 product level was outstanding. As shown in Table 4.3
below, the top ten products recorded rates ranging from 79% to 100%. There were also
6 tariff lines that had above 90% rates. These were HS91 (Clock and Watches) at 100%,
HS87 (Vehicles other than Railway parts etc) at 99%, HS57 (Carpets and Other Textile
Floor Coverings) at 94%, HS09 (Coffee, Tea and Spices) at 94%, HS62 (Articles of
Apparel and Clothing) at 94%, and HS81 (Other Base Metals, Cermets etc) at 91%. It
was also observed that most tariff lines at 0% for AUR suggest that the export value of
Malaysia for that particular tariff line was concentrated to Singapore. This suggests that
these products are highly dependent on AFTA’s preferential tariff and some products
fully utilize the preferential tariffs. It can also be summarized that these products reaped
the most benefits of AFTA for Malaysia’s export.
Table 4.2: Top ten products at HS2 level for GUR
HS Code 2007 2008 2009 2010 2011 Average
87: Vehicles other than railway or tramway rolling-stock, and parts and accessories
65% 89% 83% 80% 100% 83%
40: Rubber and articles thereof 38% 61% 96% 58% 100% 70%
09: Coffee, Tea, Mat+ and Spices 61% 57% 35% 88% 76% 63%
57:Carpets and other textile floor coverings
32% 29% 83% 83% 89% 63%
62: Articles of apparel and clothing accessories, not knitted or crocheted
36% 33% 50% 62% 100% 56%
99: Other Products 0% 1% 100% 100% 64% 53%
81: Other base metals;cermets;articles thereof
49% 100% 20% 70% 18% 51%
92: Musical instruments; parts and accessories of such articles
41% 54% 33% 49% 60% 47%
18: Cocoa and cocoa preparations 28% 59% 47% 42% 58% 47%
55:Man-made staple fibres 52% 32% 38% 46% 38% 41%
(Source: Author’s calculation)
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Table 4.3: Top ten products at HS2 level for AUR
HS Code 2007 2008 2009 2010 2011 Average
91: Clocks and watches and parts thereof
100% 100% 100% 100% 100% 100%
87: Vehicles other than railway or tramway rolling-stock, and parts and accessories
97% 100% 100% 98% 100% 99%
57:Carpets and other textile floor coverings
90% 84% 98% 100% 100% 94%
09: Coffee, Tea, Mat+ and Spices 100% 100% 71% 100% 100% 94%
62: Articles of apparel and clothing accessories, not knitted or crocheted
91% 78% 100% 100% 100% 94%
81: Other base metals; cermets;articles thereof
100% 100% 78% 100% 78% 91%
92: Musical instruments; parts and accessories of such articles
85% 100% 60% 100% 100% 89%
40: Rubber and articles thereof 53% 87% 100% 76% 100% 83%
61: Articles of apparel and clothing accessories, knitted or crocheted
87% 61% 100% 100% 53% 80%
18: Cocoa and cocoa preparations 53% 100% 83% 67% 92% 79%
(Source: Author’s calculation)
It is interesting to note that despite the increase in value as expected for the top
ten products for GUR and AUR, the rank of the top ten products did not change
significantly. Eight out of ten HS tariff lines or 10 products remained in the top ten for
both GUR and AUR which signifies that the use of preferential tariff were only
concentrated in similar products. In addition, by excluding Singapore for AUR
calculation, the values increased compared to GUR. However, by taking into account
that 54% of Malaysia’s exports to ASEAN for the period was actually to Singapore,
therefore, the results was expected to have significant difference. This generally shows
that in terms of trend, MFN tariff that were liberalized do not have significant effect on
utilization of preference tariffs offered under AFTA. Even though by excluding
Singapore, the utilization rate only increased around 10%. This suggests that utilization
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of preferential tariff was only focused in certain sectors that were not competing with
the MFN tariffs.
AUR values at product level has increased significantly only for products that
have high export volume to Singapore thus suggesting that the products that were
concentrated to other export destinations such as ASEAN were not much affected by the
AUR values. Besides the aggregate value and product level of export by commodity
classification, another aspect of the utilization rates that should be taken into account is
the export volume. Of the top ten HS2 commodity export value from Malaysia to
ASEAN for 2007-2011, the GUR and AUR were recorded considerably low.
As shown in Table 4.4, Malaysia’s main export to ASEAN is HS85 (Electrical
Machinery and Equipment etc), GUR of the product is 23% while the AUR is 73%
which is the highest in this list. The AUR for HS85 can be related to the exports of
Malaysia to ASEAN countries besides Singapore that use the preferential tariff. This
tariff line, HS85, shows that exporters of these industries efficiently use the preferential
tariff for trading. Some other product lines as recorded in Table 4.4 showed a low level
of tariff utilization, which are ranging from 0% to 38%. Despite the fact that there were
many product lines above 90% for AUR as suggested above, none of those product lines
represented a high value of export. The values in Table 4.4 therefore would suggest that,
Malaysia should focus on increasing the utilization rate for the products of higher export
value.
Although some of the products in the top ten list in Table 4.4 such as HS85,
HS84, HS73 and HS90 might be part of an assembly line of products belonging to some
multinationals, which would not enable the products to receive the ROO, there is a need
to explore ways to increase the utilization of preferential tariff in those product lines. At
the same time, other product lines such as HS39, HS29, HS15 and HS72 seem to have
potential to increase utilization of preferential tariff. In order for Malaysia to increase its
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export to ASEAN, the efficient utilization of preferential tariff for these high value
exports would enable Malaysia to increase its export to ASEAN as well as to compete
with other countries in the region.
In terms of Malaysia’s export concentration to ASEAN, the top ten product lines
showed a very surprisingly low level of utilization of preferential tariff. Table 4.5 shows
the top ten product lines with highest concentration to ASEAN and its corresponding
GUR and AUR values. Five product lines recorded 0% for both GUR and AUR and
others recorded mostly under 10% utilization. Taking into consideration that Malaysia
is focused to export to the ASEAN markets for these products, a higher utilization rate
was expected. Nevertheless, it suggests that these could be the potential product lines
that Malaysia could focus on increasing its tariff utilization to remain competitive in
ASEAN market.
Table 4.4: Top Ten HS2 Malaysia's Average Export Value to ASEAN and Corresponding GUR and AUR Values (2007-2011)
HS Code
Export Value to ASEAN
(Average 2007-2011) in USD
Billions
GUR AUR
85: Electrical machinery and equipment and parts thereof;etc 12.36 23% 73%
27: Mineral fuels, mineral oils and products of their distillation; bituminous substances;mineral waxes
9.32 0% 1%
84: Nuclear reactors, boliers, machinery and mechanical appliances, parts thereof
7.15 10% 21%
39: Plastics and articles thereof 2.05 16% 24%
15: Animal or vegetable fats and oils and their cleavage products;prepared edible fats’animal or vegetable waxes
1.41 24% 38%
29:Organic chemicals 1.13 23% 31%
73:Articles of Iron and Steel 1.09 4% 11%
72:Iron and Steel 1.07 7% 9%
90: Optical, photographic, cinematographic, measuring, checking, precision, medical or surgical instruments and appratus, parts and accessories thereof
1.00 8% 16%
(Source: Author’s calculation)
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Table 4.5: Top Ten HS2 Malaysia's Export to ASEAN vs World (Concentration) and Corresponding GUR and AUR Values (2007-2011)
HS Code Average Export % to ASEAN vs
World
GUR AUR
01:Live animals 99% 0% 0%
07:Edible vegetables and certain roots and tubers 85% 1% 4%
22:Beverages, spirits and vinegar 85% 8% 13%
47:Pulp of wood or of other fiborous cellulosic material, recovered (waste and scrap) paper or paperboard
84% 5% 5%
12:Oil seeds and oleaginous fruits; miscellaneous grains, seeds and fruit; industrial or medicinal plants;straw and fodder
82% 0% 0%
60:Knitted or crocheted fabrics 82% 2% 3%
10:Cereals 80% 0% 0%
66:Umbrellas, sun umbrellas, walking-sticks, seat-sticks, whips, riding-crops and parts thereof
75% 0% 0%
36:Explosives, pyrotechnic products;matches; pyrophoric alloys;certain combustible preparations
74% 0% 0%
91:Clocks and watches and parts thereof 73% 33% 100%
(Source: Author’s calculation)
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4.3 Intra-Industry Trade (IIT) and Revealed Comparative Advantage (RCA) in Agriculture, Automotive and Textile & Clothing Industries
4.3.1 IIT for Agriculture Industry
a) Intra-Industry Trade in Agriculture Industry: ASEAN-Thailand
From year 2001 to 2014, IIT value for ASEAN countries against Thailand on
average was below unity for the agriculture industry. Malaysia-Thailand IIT value
recorded an average value of 0.392 while Vietnam-Thailand value at 0.349, Philippines-
Thailand about 0.261 and Indonesia-Thailand about 0.233. The structure of IIT value by
13 product categories of agriculture i.e HS3 level, there were significant IIT value in
certain product categories while some other categories do not show any sign of IIT.
As shown in Table 4.6A, IIT index for Malaysia-Thailand is quite high in
HS070 with an average of 0.768. The trend from year 2001 to 2014 also shows a
fluctuating trend although for some years it recorded values close to unity. There were
also few other products that randomly had values close to unity in some years although
no definitive pattern was observed.
Table 4.6B shows IIT for Indonesia-Thailand. From the table, IIT values were
quite low for all categories of product. The highest value was recorded for product
HS120 with 0.446 on average. Product of HS120 also shows an increasing trend from
year 2001 to 2014 and in year 2014 the value was close to unity. For Philippines-
Thailand, as shown in Table 4.6C, product of HS120 recorded an average value of
0.772 with some years the values approaching to unity. Product of HS130 and HS080
both show a decreasing trend and the IIT value for Philippines-Thailand for those
products declined until 2014.
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Table 4.6D is the IIT values for Vietnam-Thailand which also did not show an
outstanding picture. Although there were some trends increasing or decreasing for
certain product categories, the trend was inconsistent.
b) Intra-Industry Trade in Agriculture Industry: ASEAN-Indonesia
From year 2001 to 2014, ASEAN-Indonesia IIT values were far from unity for
year 2001-2014. IIT for Malaysia-Indonesia was the highest with a value of 0.442 while
Vietnam-Indonesia about 0.205, Philippines-Indonesia about 0.132 and Thailand-
Indonesia about 0.233. For agriculture products by HS3 level, i.e. 13 products
categories, there were IIT in certain product categories while some categories do not
show any sign of IIT.
Malaysia-Indonesia IIT is shown in Table 4.7A. The IIT value for Malaysia-
Indonesia recorded a high value for HS071 with an average of 0.829. Although there is
no obvious trend of the IIT from year 2001 to 2014, some of the years recorded value
close to unity. Malaysia-Indonesia IIT recorded high value for product HS070 with
0.717. This product category also indicated values close to unity, however the values
were not maintained throughout the period. Product of HS080 on the other hand
recorded a decreasing trend from 2001 to 2014. IIT value for Indonesia-Thailand as
shown in Table 4.7B, did not record significant IIT although some years showed an
increasing and decreasing trend. Product of HS071 and HS120 showed an increasing
trend while product of HS070 and HS121 recorded a decreasing trend.
IIT for Philippines-Indonesia showed a very weak trend for all product
categories as shown in Table 4.7C. Product of HS081 for example did not even record a
single intra industry trade between Philippines and Indonesia. Similarly, as shown in
Table 4.7D, Vietnam-Indonesia aslo recorded a low value. The only quite significant
intra-industry trade was for product HS090 that recorded an average 0.538. This product
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approached unity value in year 2009, which was 0.987, but the value dropped in years
after 2009.
c) Intra-Industry Trade in Agriculture Industry: ASEAN-Malaysia
For the case of Malaysia’s agriculture Industry, the average IIT with ASEAN
countries recorded was quite low. Malaysia-Indonesia recorded the highest IIT of about
0.442 while the IIT value for Malaysia-Vietnam about 0.143, Malaysia-Philippines
about 0.183 and Malaysia-Thailand about 0.392. The agricultural products by HS3 level
showed some product categories with IIT and some categories there were no sign of IIT.
IIT for Malaysia-Indonesia recorded high value for product HS071 with 0.829.
IIT for some years recoded value close to unity as shown in Table 4.8A. Product HS070
also recorded a high average value of 0.717 and two years recording close to unity
value.
IIT for Malaysia-Thailand recorded high value of IIT for product HS070 with
0.768, which fluctuated during the whole period of investigation. As shown in Table
4.8B, product of HS080, HS121, and HS140 all recorded a decline from year 2001 to
2014.
As for the Malaysia-Philippines and Malaysia-Vietnam IIT as shown in Table
4.8C and Table 4.8D, there were no significant value of IIT as the values remained low
in almost all categories.
d) Intra-Industry Trade in Agriculture Industry: ASEAN-Philippines
From year 2001 to 2014, the IIT value of ASEAN-Philippines was very low.
The IIT of Thailand-Philippines recorded an average value of about 0.261, while the IIT
value for Malaysia-Philippines was about 0.183 and Vietnam-Philippines was about
0.110.
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IIT value between these four countries and Philippines did not record any
significant value. As shown in the following tables, Table 4.9A, Table 4.9B, Table 4.9C
and Table 4.9D, only IIT for Thailand-Philippines for products of HS080 and HS120
recorded significant value with some years recording values close to unity.
e) Intra-Industry Trade in Agriculture Industry: ASEAN-Vietnam
IIT of ASEAN-Vietnam for the agriculture industry recorded a low average
value. The IIT for Vietnam-Thailand recorded an average value of 0.349, while the IIT
value for Vietnam-Malaysia recorded an average of 0.143. IIT for Vietnam-Indonesia
recorded 0.205 and IIT value of Vietnam-Philippines recorded 0.110.
As shown in tables 4.10A, 4.10B, 4.10C, 4.10D, it can be observed that only
very few product categories recorded IIT value close to unity. This values were
however very random and did not show any significant trend.
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4.3.2 RCA for Agriculture Sector
a) RCA Index of ASEAN countries-Malaysia
For all HS3 products of agriculture for 2001-2014, RCA index for Vietnam-
Malaysia showed an average of about 2.211, which is the highest, compared to other
countries. Then, it is followed by Indonesia-Malaysia, with an average index of about
1.167. The other two countries, Thailand and Philippines showed an average value of
RCA below 1, which were 0.790 and 0.304 respectively. However, this aggregate value
does not represent each product under the HS3 that actually gives clearer picture of
competiveness of each product in the agriculture industry in the case of Malaysia.
Table 4.11A shows Thailand-Malaysia RCA index. From the table, Thailand is
most competitive with highest RCA in product of HS110 - Starches; inulin,Flour and
meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten where the value
was 3.729 followed by product of HS120 - Ground Nuts, Seeds, Oil Seeds, Soya Beans
etc. with a value of 2.051. The other two products that recorded significant RCA were
HS100 - Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat,
Rye with RCA value of 1.803 and product of HS070 - Cabbages, Cauliflowers,
Vegetables, Potatoes. Lettuce, Carrots, Turnips with RCA value of 1.494. The RCA
index for these four product categories remained consistent throughout the observation
periods although the RCA values fluctuated in certain years. However, product of
HS110 and HS100 both show a declining trend.
Next, Table 4.11B presents Indonesia-Malaysia RCA index. The table shows
that Indonesia has significant competitive advantage in 5 product classification. The
highest RCA index for Indonesia-Malaysia was recorded for product of HS120 -
Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. with an average of 4.702, followed by
product of HS091 - Ginger, saffron, turmeric, thyme, bay leaves & curry with RCA
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value of 2.706, product of HS070 - Cabbages, Cauliflowers, Vegetables, Potatoes.
Lettuce, Carrots, Turnips with RCA value of 2.456, product of HS140 - Vegetable
Products and Materials with RCA value of 1.269 and product of HS090 - Coffee, Tea,
Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla with
RCA value of 1.053. RCA index for product of HS120 and HS070 both recorded
significantly high average values, but both products showed a declining trend. RCA
index for product of HS120 fell from 6.051 in year 2001 to 1.089 in 2014 whereas RCA
index for product of HS 070 loss its competitiveness in 2010 and in 2014 the value
recorded a low level of competitiveness with the RCA index recording 0.500. The other
3 product sectors remain indifferent although with some minimal fluctuations during the
investigated periods.
The RCA index for Philippines-Malaysia is shown in Table 4.11C. Based on the
table, only one product, HS130- Vegetable saps & extracts, Lac; natural gums, resins,
gum-resins & balsams has a competitive advantage in Malaysian agriculture industry,
where the RCA index was 1.237. However, the product has shown rapid increase in
competitiveness in Malaysia’s agriculture market from year 2011 onwards. Other
products as shown in the table recorded a less significant competitiveness in the
Malaysian agriculture industry.
RCA index for Vietnam-Malaysia is shown in Table 4.11D. On average,
Vietnam had a significant advantage in product of HS120 - Ground Nuts, Seeds, Oil
Seeds, Soya Beans etc. where the value recorded was 10.691, followed by HS100 -
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye with
RCA index of 9.248. Other products that recorded positive RCA index were HS090 at
2.295, HS 070 at 1.962, HS110 at 1.414 and HS121 at 1.108. Of these competitive RCA
index, HS120 and HS100 showed ecreasing trend of RCA from year 2001 to 2013. In
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the case of product HS121, the product recorded a decreasing trend and eventually after
2008, Vietnam, has lost its competitiveness in this category of product. RCA index for
product of HS090 has been rather stable from 2001 to 2014 although there were slight
fluctuations recorded. RCA index for product of HS070 has showed remarkable
increase in trend from the product being incompetitive in Malaysia agriculture industry
in 2008, which was then turned in an upward trend recording a competitive RCA index
with 6.304 in 2013.
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b) RCA Index of ASEAN countries-Indonesia
For all the HS3 products of agriculture industry for year 2001-2014, all four
ASEAN countries recorded significant comparative advantage in the Indonesian market.
The RCA index of Vietnam-Indonesia recorded the highest value with an average of
4.202, and then followed by Philippines-Indonesia with RCA index of 1.490 while
Thailand-Indonesia recorded RCA index of 1.431 and Indonesia-Malaysia with RCA
index of 1.054.
The RCA index for Thailand-Indonesia as shown in Table 4.12A is concentrated
in 5 product categories for the period of 2001-2014. The average RCA index for
product of HS110 -Starches; inulin, Flour and meal of vegetables, Wheat, Cereal grain,
Flour, Malt, Wheat Gluten recorded significant RCA index with 6.530 followed by
RCA index for product of HS081-Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus
Fruits and Melon Peel with 5.577, HS100-Maize (corn), Rice, Buckwheat, millet and
canary seed, Oats, Barley, Wheat, Rye with 2.554, HS120 -Ground Nuts, Seeds, Oil
Seeds, Soya Beans etc with 1.727 and HS070-Cabbages, Cauliflowers, Vegetables,
Potatoes. Lettuce, Carrots, Turnips with 1.583.
The recorded RCA index values above did not show a consistent trend and the
values fluctuated during the period of investigation. Product of HS081 showed an
unrecovered declining trend from year 2009 onwards when the RCA index dropped
from 5.828 in 2009 and reduced to 2.899 in 2014. Similar trend was also shown for
product of HS100 when the RCA index dropped in 2004, from 5.882 in year 2003 to
1.828 in year 2004. It even touched onto losing its competitiveness in year 2005
recording only 0.712 and years after that, it remained in the range of 0.460 to 2.700.
Product of HS120 also recorded a declining trend and since year 2010, Thailand loss its
comparative advantage in the Indonesian market for this product category. The only
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category that shows an increasing trend is product of HS070, which gained its
competiveness in year 2005 and thereafter showed a stable value until year 2014.
The RCA index of Philippines-Indonesia in the agriculture industry is shown in
Table 4.12B. The average RCA index for the period 2001-2014 of 9.879 was recorded
for product of HS070-Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots,
Turnips. The values faced some rise and fall throughout the period, however, it showed
a declining trend since year 2011 where the RCA index fell from 13.543 to 2.397 in
2014. This is then followed by product of HS130-Vegetable saps & extracts, Lac;
natural gums, resins, gum-resins & balsams which recorded RCA index of 4.624.
Product of HS121-Locust Beans, Medicinal Plants, Swede, Mangolde etc. recorded an
average RCA index of 3.783 which did not show significant RCA index throughout the
period of 2001-2014.
As shown in table 4.12C, Malaysia-Indonesia RCA index on average was
significant for product of HS120-Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. with
6.188, followed by product of HS070-Cabbages, Cauliflowers, Vegetables, Potatoes.
Lettuce, Carrots, Turnips with 3.886 and product of HS140-Vegetable Products and
Materials with 1.090. HS070 and HS120 both showed values that were consistent for
the whole period of investigation. Product of HS140 only remained competitive for a
short period of time, which is from 2009 to 2011.
The RCA index of Vietnam-Indonesia in the agriculture industry is shown in
Table 4.12D. Product of HS120-Ground Nuts, Seeds, Oil Seeds, Soya Beans etc.
recorded highly significant RCA index of 23.929. The competitiveness recorded was
only attributed for the period from 2001 to 2010. From year 2011 onwards, the RCA
index of Vietnam-Indonesia plunged downwards and loss its competitiveness for this
product category. Product of HS100- Maize (corn), Rice, Buckwheat, millet and canary
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seed, Oats, Barley, Wheat, Rye recorded an average RCA index of 15.574 with huge
fluctuations during the period of investigation. It was however observed that despite the
fluctuations, Vietnam was still competitive in the Indonesia agriculture industry for the
whole period of investigation except for year 2009, when the RCA index recorded
showed a loss in competitiveness. Similar trend was also revealed for product of
HS070- Cabbages, Cauliflowers, Vegetables, Potatoes, Lettuce, Carrots, Turnips which
recorded an average RCA index of 8.408. The exception however was in year 2007,
when Vietnam loss its competitiveness for this product category. Product of HS090-
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise,
Vanilla recorded an average RCA index of 2.668 with values that remained stable
throughout the period of investigation. Product of HS081-Coffee, Tea, Pepper ,
Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla recorded RCA
index of 1.111 on average and showed an increasing trend especially from year 2007
onwards when the values turned from uncompetitive to competitive in 2007 and
remained stable up to year 2013.
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c) RCA Index of ASEAN countries-Philippines
The RCA index was on average significant for Vietnam-Philippines with 3.799
followed by Vietnam-Indonesia with 1.652 for the period 2001-2014. The RCA index
for Thailand-Philippines and Malaysia-Philippines recorded an average of 0.589 and
0.088 respectively.
This average RCA index, however, was quite different at each product category.
The RCA index for Thailand-Philippines on average recorded significant values for
product of HS100 – Maize (corn), Rice, Buckwheat, millet and canary seed, Oats,
Barley, Wheat, Rye with 2.500 and HS110- Starches; inulin,Flour and meal of
vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten with 2.757. Although both
product categories showed rise and fall in value, the values remained stable throughout
the period investigated. The RCA index for Malaysia-Philippines on the other hand, as
described in Table 4.13B, did not show any significant RCA value for all product
categories.
The RCA index for Indonesia-Philippines is shown in Table 4.13C. The RCA
index was significant for products of HS121- Locust Beans, Medicinal Plants, Swede,
Mangolde etc.where the index recorded was10.812, followed by HS120- Ground Nuts,
Seeds, Oil Seeds, Soya Beans etc. with 6.780 and HS071- Manioc, Frozen Vegetables,
Dried Vegetables with 1.239. The RCA index of HS121 and HS120 remained strong
and stable for the whole period of investigation while HS071 loss its competitiveness in
2010 and regaining competitiveness only in 2014.
The RCA index for Vietnam-Philippines was significant for product of HS100-
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye with
an average of 29.886 as shown in Table 4.13D. Although the values fluctuated for the
period under investigation, the value remained double digits. Product of HS120- Ground
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Nuts, Seeds, Oil Seeds, Soya Beans etc. recorded an average of 8.021 although the
value showed a sharp downfall from having a significant double digit RCA value to
insignificant value since 2006 onwards. The RCA values did not regain significance up
to 2014. Product of HS110 and HS090 both with an average RCA index of 4.849 and
4.370 recorded a stable and strong value throughout the period of investigation.
d) RCA Index of ASEAN countries-Thailand
On average, for all product categories under the agriculture industry for the
period of 2001 to 2014, the RCA value was recorded significant only for Vietnam-
Thailand where the value was 3.058. Other RCA values that recorded insignificant
average values were Philippines-Thailand where the value was 0.872, Indonesia-
Thailand that recorded 0.715 and Malaysia-Thailand with a value of 0.431.
Despite an overall average insignificant value, the RCA-Index of Malaysia-
Thailand recorded an average significant value for 2 product categories as shown in
Table 4.14A. Product of HS140- Vegetable Products and Materials recorded an average
RCA index of 2.059 with a substantial shift from insignificant RCA value up to year
2007 to a stable significant value from year 2008 onwards. The RCA index for
Malaysia-Thailand was also significant for product of HS070-Cabbages, Cauliflowers,
Vegetables, Potatoes. Lettuce, Carrots, Turnips with an average value of 1.632.
Indonesia exhibited 3 product categories with significant RCA index as shown
in Table 4.14B. The RCA index for product of HS140-Vegetable Products and showed
an increasing trend from year 2006 to 2014 with an average of 3.948. This is followed
by the RCA index for product of HS091- Ginger,saffron,turmeric, thyme, bay leaves &
curry which recorded an average of 2.085. However, the RCA index for this product
category has shown a decreasing trend. From year 2001 to 2005, the RCA index for
product of HS091 was significant and from year 2006 to 2014, the RCA index fell to
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become insignificant and the values decreased rapidly. As for product of HS120-
Ground Nuts, Seeds, Oil Seeds, Soya Beans etc, the RCA index for Indonesia–Thailand
recorded an average of 1.097.
As shown in Table 4.14C, the RCA index for Philippines-Thailand recorded an
average of 4.459 for HS121-Locust Beans, Medicinal Plants, Swede, Mangolde etc..
Although it was a significant value, the trend shows rise and fall in the value throughout
the period of investigation. Since year 2013, the RCA index of Philippines-Thailand for
product of HS121 became insignificant. Prodcut of HS130-Vegetable saps & extracts,
Lac; natural gums, resins, gum-resins & balsams recorded an average of 4.053 with
stable and significant values throughout the whole period while showing an increasing
trend for the period 2012 to 2014. Product of HS110 and HS120 recorded RCA index of
1.068 and 1.311 respectively, however the trend shown by both product category were
inconsistent for some of the years.
The RCA index of Vietnam-Thailand for the agriculture industry is shown in
Table 4.14D. It points out the high RCA index for HS120-Ground Nuts, Seeds, Oil
Seeds, Soya Beans etc. with an average of 29.649. The trend however is showing a
decline, which started off with RCA index with double-digit values in year 2001 to
2010 and declined to single digit for year 2011 onwards. Product of HS081-Dried Fruits,
Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel recorded RCA index with
an average of 2.784, product of HS110- Starches; inulin,Flour and meal of vegetables,
Wheat, Cereal grain, Flour, Malt, Wheat Gluten with an average of 1.840, product of
HS080-Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples with 1.738,
product of HS140 with an average of 1.180 and product of HS090 with 1.027.
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e) RCA Index of ASEAN countries-Vietnam
The RCA index for the ASEAN countries-Vietnam in the agriculture industry in
2001-2013 showed that on average, only the RCA index of Indonesia-Vietnam recorded
a significant value of 1.763. The RCA index of Thailand-Vietnam recorded 0.902, while
the RCA index for Philippines-Vietnam recorded 0.510 and Malaysia-Vietnam recorded
0.235.
As shown in Table 4.15A, the RCA index of Thailand-Vietnam showed a
significant value for product of HS120- Dried Fruits, Frozen Fruits, Preserved Fruits,
Citrus Fruits and Melon Peel with an average of 5.279 and product of HS081-Dried
Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel recorded an
average value of 2.938. The RCA index for product of HS120 remained consistent
during the whole period of investigation and product of HS081 has shown an increasing
trend in year 2009 onwards with significant RCA index values.
The only significant RCA index recorded for Malaysia-Vietnam was for product
of HS120-Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. which recorded 1.436 on
average and showed an increasing trend from year 2006 onwards as shown in Table
4.15B. The RCA index of Philippines-Vietnam in the agriculture industry is shown in
Table 4.15C. The RCA index for Philippines-Vietnam recorded significant RCA value
for product of HS130-Vegetable saps & extracts, Lac; natural gums, resins, gum-resins
& balsams with 3.283. Since year 2005, the RCA index for Philippines-Vietnam gained
significant values for this product category and the trend recorded was increasing and in
2014, the value recorded was 16.404. The RCA index for Philippines-Vietnam also
recorded significant value for product of HS121 with an average of 1.719.
Table 4.15D shows the RCA index of Indonesia-Vietnam in the agriculture
industry. There were 7 product categories that recorded significant RCA values. Product
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of HS121 recorded RCA index of 5.726, followed by product of HS091 with RCA
index of 4.923, product of HS080 with RCA index of 4.290, product of HS090 with
RCA index of 3.232, product of HS130 with RCA index of 1.279, product of HS121
with RCA index of 1.105 and product of HS140 with RCA index of 1.045. The RCA
Index of Indonesia-Vietnam in the agriculture industry recorded significant values for
most product categories and only six product categories did not record significant
values.
4.3.3 Summary of IIT and RCA in Agriculture Industry
a) Summary of IIT for Agriculture Industry
The IIT values by country show that the level of IIT between countries in
ASEAN for the agriculture sector is very low and limited. As shown in Table 4.16A,
only Malaysia, Thailand and Indonesia recorded significant IIT values. This shows that
intra industry trade between ASEAN countries was very low and limited. It also
suggests that ASEAN countries were more focused on inter industry trade instead.
Table 4.16A: Product Categories with significant IIT values in ASEAN Agriculture Industry
Country HS Code Pair Country
Malaysia 070 Indonesia
071 Indonesia
070 Thailand
Thailand 120 Indonesia
070 Malaysia
120 Philippines
Indonesia 090 Vietnam
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This is understandable as most of the agriculture products do not go through
advanced processing. The nature of the production for agriculture products consist of
relatively simple transformation of raw materials with which the ASEAN countries are
endowed. This transformation usually are not suited to division across the economies in
ASEAN.
b) Summary of RCA Index for Agriculture Industry
Although Malaysia has shown significant RCA values for four product
categories as shown in Table 4.16B below, for all the product categories, Malaysia faces
steep competition with ASEAN countries. The manner of such competition does not
suggest that Malaysia has total competitive advantage although they recorded
significant RCA values.
Table 4.16B: Product Categories with significant RCA index for Malaysia-ASEAN countries in Agriculture Industry and number of competing countries
Country HS Code Pair Country Competing countries
Malaysia 140 Thailand 1
070 Indonesia 3
120 Indonesia 3
120 Vietnam 2
Thailand, despite recording significant RCA values for many product categories,
most products showed that it was competing with other ASEAN countries (Table
4.16B). Thailand’s RCA index without such competition is only for HS110 and HS081.
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Table 4.16C: Product Categories with significant RCA index for Thailand-ASEAN countries in Agriculture Industry and number of competing countries
Country HS Code Pair Country Competing countries
Thailand 070 Malaysia 2
100 Malaysia 1
110 Malaysia 1
120 Malaysia 2
070 Indonesia 2
081 Indonesia 1
100 Indonesia 1
110 Indonesia 0
120 Indonesia 3
100 Philippines 1
110 Philippines 1
081 Vietnam 0
120 Vietnam 1
Indonesia also recorded many product categories with significant RCA values,
some of which were competing with other ASEAN countries. However, Indonesia
recorded the highest number of product categories with sole significant RCA within
ASEAN. The product categories were mostly apparent for the pairs between Indonesia
and Vietnam.
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Table 4.16D: Product Categories with significant RCA index for Indonesia-ASEAN countries in Agriculture Industry and number of competing countries
Country HS Code Pair Country Competing countries
Indonesia 070 Malaysia 2
090 Malaysia 1
091 Malaysia 0
120 Malaysia 2
140 Malaysia 0
091 Thailand 0
120 Thailand 2
140 Thailand 1
071 Philippines 0
120 Philippines 1
121 Philippines 0
080 Vietnam 0
090 Vietnam 0
091 Vietnam 0
120 Vietnam 2
121 Vietnam 1
130 Vietnam 1
Philippines, similar to Malaysia recorded significant RCA values only for a few
items, all of which were in competition with other ASEAN countries. It also must be
noted that Philippines and Malaysia do not have any significant RCA values for each
other, suggesting that both countries do not have any advantage in terms of AFTA for
the agriculture sector. Vietnam recorded many product categories with significant RCA
values. Most of them were in competition with Thailand and Indonesia. Vietnam’s sole
competitive RCA value was recorded for HS090 and HS121.
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Table 4.16E: Product Categories with significant RCA index for Philippines-ASEAN countries in Agriculture Industry and number of competing countries
Country HS Code Pair Country Competing countries
Philippines 120 Thailand 2
070 Indonesia 3
120 Indonesia 3
121 Vietnam 1
130 Vietnam 1
Table 4.16F: Product Categories with significant RCA index for Vietnam-ASEAN countries in Agriculture Industry and number of competing countries
Country HS Code Pair Country Competing countries
Vietnam 070 Malaysia 2
090 Malaysia 1
100 Malaysia 1
110 Malaysia 1
120 Malaysia 2
121 Malaysia 0
070 Indonesia 3
081 Indonesia 1
090 Indonesia 0
100 Indonesia 1
120 Indonesia 3
120 Thailand 2
090 Philippines 0
100 Philippines 1
110 Philippines 1
120 Philippines 1
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In conclusion, it can be summarized that for the agriculture sector in ASEAN,
the intra industry trade is quite limited due to most of the products are upstream
products and the economies do not offer product differentiation. The RCA value on the
other hand was quite forthcoming. Thailand, Indonesia and Vietnam in general have
shown intense competition with each other in the agriculture sector. The trend recorded
also proved that Vietnam has in certain products competed with other ASEAN countries
and caused other countries to lose their competitiveness. Thailand despite being one of
the largest agriculture exporter in the world might have concentrated its market outside
ASEAN, causing Vietnam to take advantage in terms of competitiveness in ASEAN.
The level of RCA among these countries actually suggest that AFTA might have
only assisted some countries to integrate within ASEAN. The competition among
Thailand, Indonesia and Vietnam coupled with the limited level of IIT values further
suggests that integration efforts under AFTA for the agriculture sector has created
competition but it has not helped countries to specialize in particular products.
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4.3.4 IIT and RCA for ASEAN countries in Agriculture Industry
a) Malaysia
The IIT values for ASEAN countries in the Malaysian agriculture sector was
recorded high only for product of HS070, HS071 with Indonesia and product of HS070
with Thailand. Similarly, product of HS070 also recorded significant RCA values for
both Indonesia and Thailand. This however was not the case for product of HS071
where Indonesia did not record significant RCA value in Malaysia’s market suggesting
a one-way trade. The RCA values of Thailand and Indonesia dominated Malaysia’s
agriculture industry with Thailand recording high RCA values for product of HS100,
HS110 and HS120. Indonesia’s position in product of HS090, HS091, HS120 and
HS140 was considerably competitive. Except for product of HS070 and HS120,
Thailand and Indonesia were not competing with each other for the same product
categories. This however changed when Vietnam is included in the comparison.
Vietnam recorded high RCA values for the entire product categories mentioned above,
which suggests that Vietnam is competing with both Thailand and Indonesia in all the
products that they have significant RCA values. Vietnam’s RCA values are also not
matched with the IIT values that suggest that most products were one-way trade.
Product of HS100 and HS120 recorded considerably high RCA values for Vietnam that
showed a declining trend similar to the decline by Thailand. This might be due to the
change in export concentration during this period of time.
In general, the trend and values of IIT and RCA in the Malaysian agriculture
market shows some degree of competition between Indonesia, Vietnam and Thailand
particularly in HS070 and HS120. The results also suggest that most products were one-
way trade as IIT values were only significant for very few products.
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b) Thailand
The IIT values for ASEAN countries in Thailand’s agriculture industry only
recorded significant values for product of HS070 with Malaysia and product of HS120
with Indonesia. The RCA values for ASEAN countries in Thailand’s agriculture
industry recorded a steep competition between Indonesia, Philippines and Vietnam for
product of HS120. Vietnam’s RCA values for product of HS120 severely dropped,
while Indonesia recorded an increasing trend for its RCA values for product of HS120.
Philippines on the other hand recorded fluctuating values for product of HS120 due to
the intense competition among ASEAN countries.
Other product categories recorded significant RCA values as well for ASEAN
countries although there was no intense competition between ASEAN countries.
Product of HS140 recorded an increasing RCA trend for both Indonesia and Malaysia.
Indonesia recorded a significant decrease in RCA value for product of HS091 although
other ASEAN countries did not show any significant trend for product of HS091.
ASEAN countries’ IIT and RCA values did not show any close links in
Thailand’s agriculture market. However, it was observed that there was intense
competition between ASEAN countries for HS120.
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c) Indonesia
The IIT values of ASEAN countries in Indonesian agriculture industry was only
prevalent for product of HS071, HS070 and HS120 with Malaysia. Other countries did
not show significant levels of IIT values, suggesting one-way trade between most the
pairs investigated. Being the largest consumer market for agriculture industry in
ASEAN, the RCA values present interesting values. All four ASEAN countries
investigated showed a positive RCA value for product of HS070. Thailand in general
has shown a slowly increasing trend, while Vietnam has shown extreme increase in
RCA values especially since year 2009. Malaysia and Philippines both recorded
fluctuating values. The trend shows that all four ASEAN countries are competing
against each other for their market share in Indonesia. It also shows that Vietnam
possesses higher RCA values after 2009 that might have affected Malaysia and
Philippines position for product of HS070.
Vietnam also showed very high value for product of HS100, although the trend
seemed to fluctuate. This is more evident as Thailand’s position for product of HS100
depleted badly since 2004 which suggest that the intense competition between Vietnam
and Thailand for product of HS100 somehow shows that Vietnam has gained better
position in Indonesia.
Similar trend was also observed in product of HS081. Thailand’s RCA value
declined badly since 2004 and Vietnam gained competitive values since 2002 and the
trend increased rapidly. Vietnam’s competitiveness in product of HS081 resulted in
Thailand losing its competitiveness.
The level of competition among ASEAN countries for the similar products in
Indonesia has shown that Vietnam has mostly competed against other countries within
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ASEAN and managed to position itself in a more competitive level in the Indonesia
agriculture market.
d) Philippines
The IIT values for ASEAN countries in the Philippines market did not show any
significant value except for product of HS120 with Thailand which recorded a
fluctuating trend for the years under investigation. This shows that most of ASEAN’s
trade with Philippines were focused in one way trade.
An interesting trend was observed for RCA values of product HS120. Indonesia
recorded rapid increase in competitiveness for product of HS120, while Vietnam loss its
competitive value since year 2007. The trend shows that both country competed in the
same product category and Indonesia has emerged more competitive than Vietnam in
product of HS120.
Besides product of HS120, product of HS100 recorded significant RCA values for
Thailand and Vietnam. Indonesia recorded a high product of HS121 RCA value, while
Vietnam managed to remain competitive in product of HS090 and HS110 throughout
the period of investigation.
Malaysia did not show any significant RCA and IIT values in the Philippines
agriculture market. The other three ASEAN countries all showed some levels of
competitiveness in different products although competition was apparent between
Indonesia and Vietnam for some of the products.
e) Vietnam
The IIT value that was significant in Vietnam’s agriculture market was for product of
HS090 with Indonesia. Product of HS090 also recorded an increasing RCA value,
which shows that intra industry trade is observed for this product category. Malaysia,
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Thailand and Indonesia recorded significant RCA values for product of HS120. In terms
of trend, the three countries compete with each other causing Indonesia’s RCA value to
decrease and Malaysia’s RCA value rose steadily throughout the period of investigation.
Thailand’s RCA value remained significant although it fluctuated during the whole
period. Thailand however showed an increasing trend for its RCA value for product of
HS081. Both Philippines and Indonesia also recorded an increasing trend for product of
HS130 and HS121. Indonesia recorded the highest number of products with significant
RCA values, recording significant values also in product of HS080 and HS091.
The number of products with significant RCA values covered by Indonesia is quite
interesting, as similarly, many Vietnamese products also gained significant RCA values
in the Indonesian agriculture market.
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4.4.1 IIT for Automotive Industry
a) Intra-industry Trade in Automotive Industry: ASEAN-Malaysia
The IIT values for ASEAN countries and Malaysia in the Automotive Industry was
recorded the highest for the Indonesia-Malaysia IIT in product of HS871 and HS870
with 0.652 and 0.643. Both these product categories have shown some inconsistent
trend from year 2001 to 2014. Product of HS870 for Indonesia-Malaysia IIT calculated
close to unity values from year 2009 to 2013, however the value dropped to 0.601 in
2014.
Other countries in ASEAN did not record high IIT values for product HS870 and
HS871. For product HS401, Philippines-Malaysia recorded a considerably high IIT
value with an average of 0.618. Although the trend shows inconsistency in the values of
IIT from 2001 to 2014, some years for example, 2002, 2010 and 2012 calculated values
close to unity. The detailed values are shown in the tables below.
b) Intra-industry Trade in Automotive Industry: ASEAN-Thailand
The IIT index values for ASEAN countries in Thailand automotive industry was
generally low for most countries. In particular, significant values were only recorded for
product of HS870 and HS401.
Product of HS870 recorded the highest IIT value for Philippines-Thailand with
0.670. The trend from 2001 to 2014 shows that the value increased from 2002 and
peaked in 2006 having a close to unity value. However, since then, the IIT value has
decreased and only recorded 0.400 for year 2014.
Product of HS401 recorded the highest for the IIT value of Indonesia-Thailand with
an average of 0.664. The values did not show any consistent trend although it amounted
to close to unity values for some years.
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c) Intra-industry Trade in Automotive Industry: ASEAN-Philippines
The IIT index values of ASEAN countries-Philippines were only significant for product
of HS870. On average, product of HS870 recorded 0.675 for Vietnam, 0.670 for
Thailand and 0.561 for Malaysia. The trend for Malaysia showed that the values were
increasing and from year 2013 onwards, where it amounted to close to unity values.
Malaysia also recorded a high value of IIT with Philippines for product of HS401 with
0.618. Although there was no apparent trend in the values, values for some years were
recorded close to unity.
d) Intra-industry Trade in Automotive Industry: ASEAN-Indonesia
The IIT values for ASEAN countries Indonesia’s automotive industry generally
recorded some high values with some countries. The highest value recorded was for
product of HS870 with Philippines at 0.675. This is followed by product of HS871 for
IIT Malaysia-Indonesia with 0.652. The trend however shows that it is in a decreasing
trend from year 2001 to 2014.
The IIT value for Thailand-Indonesia for product of HS401 was also significant
with 0.664. Other values besides those mentioned were insignificant and do not reflect
intra-industry trade.
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e) Intra Industry Trade in Automotive Industry: ASEAN-Vietnam
The IIT index recorded for ASEAN countries in Vietnam was very low for all
product categories. The only significant IIT index was for Indonesia-Vietnam for
product HS 401. It recorded a tremendous increase in IIT value from year 2010 onwards
for product of HS401 with Indonesia.
Similarly, for product of HS870, the IIT index for Indonesia-Vietnam recorded
significant values from year 2009 onwards. Product of HS870 calculated values close to
unity in the period of 2009 to 2013.
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4.4.2 RCA for Automotive Industry
a) RCA Index of ASEAN countries-Malaysia
On average terms for all automotive industry products, Thailand strikingly had
revealed comparative advantage in all three-product classification and recorded RCA
value of 1.682. This is followed by the RCA values of Indonesia-Malaysia with an
average value of 0.889, Vietnam-Malaysia with 0.570 and Philippines-Malaysia with
0.413. Taking into consideration of these values, Thailand obviously is the most
competitive country in Malaysia’s automotive industry. The tables (4.21A-4.21D) show
each country’s RCA index.
The RCA index for Thailand-Malaysia was significant for all three product
categories. Product of HS870, HS871 and HS401 recorded stable values. Product of
HS871 remained borderline competitive level since 2003 although the RCA index
remained consistent after 2003.
Indonesia-Malaysia RCA index for product of HS870 and HS401 both show a
trend that changed from being competitive to not competitive. The RCA index for
product of HS870 became insignificant in 2009 and never recovered it, while product of
HS401’s RCA index also became insignificant in 2006 and never recovered it. The
trend of such decline is reflected in Indonesia-Malaysia overall average value, which
shows insignificant RCA value.
The rest of Philippines-Malaysia and Vietnam-Malaysia both do not have
revealed comparative advantage in Malaysia’s automotive industry except for Vietnam
recording an increasing value for product of HS871. Since year 2009, Vietnam gained
competitiveness in this product category and has shown an upward
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b) RCA Index of ASEAN countries-Thailand
The RCA Index for ASEAN countries in Thailand’s automotive Industry
showed very interesting values. On average, for automotive industry from 2001 to 2014,
the RCA index for Philippines-Thailand was the highest value with 3.367. This was
followed by Indonesia-Thailand with 1.658 and Vietnam-Thailand with 1.464. Malaysia
was the only country without significant RCA index in Thailand’s automotive industry.
The individual RCA index for each pair is shown in Tables 4.22A-4.22D. The
RCA index for Indonesia-Thailand recorded significant value for product of HS870
with 2.170 and between years 2001 to 2014, the RCA values remained competitive but
the value fluctuated during some periods. For product of HS871, it also recorded
significant RCA values although for some years, the RCA index became insignificant.
Product of HS401 initially was competitive for Indonesia in the Thailand market,
however, it declined to uncompetitive level since year 2008 and never bounced back.
The RCA index of Philippines-Thailand showed significant values for product
of HS870 with an average of 7.567. This high RCA value trend is in a declining trend
since year 2009 despite still having significant value. The RCA index for Philippines-
Thailand also showed some years with significant value for product of HS871 although
for most of the years under investigation, Philippines remained uncompetitive in
Thailand’s automotive market. The RCA index for Vietnam-Thailand on the other hand
recorded competitive RCA value for product of HS871 with an average value of 3.775.
c) RCA Index of ASEAN countries-Indonesia
In the Indonesia automotive industry, the RCA index for Thailand-Indonesia and
Philippines-Indonesia showed a considerably high value of average RCA index. The
RCA index for Thailand-Indonesia recorded 3.813 and Philippines-Indonesia recorded
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2.357. The RCA index for Malaysia-Indonesia and Vietnam-Indonesia did not record
significant values.
The high RCA value recorded for Thailand-Indonesia was due to product of
HS871 which recorded 6.162 and product of HS870 which recorded 4.851.Both these
product categories remained competitive throughout the period of investigation.
The RCA value for Philippines-Indonesia was significant due to product of
HS870 recording average of 5.386. Philippines also recorded a competitive value for
product of HS871 with an average of 1.517.
d) RCA Index of ASEAN countries-Vietnam
The RCA index for Thailand-Vietnam and Indonesia-Vietnam recorded
competitive and significant average RCA value for the automotive industry. The RCA
index for Thailand-Vietnam recorded a value of 3.373, while Indonesia-Vietnam
recorded RCA index of 1.947. The RCA index for Philippines-Vietnam and Malaysia-
Vietnam both did not have a significant value recording only 0.750 and 0.389
respectively.
The significant RCA index recorded for Thailand-Vietnam was mainly due to
product of HS871which recorded an average of 7.667. However, it must be noted that
this value decreased rapidly from year 2001 with 22.155 to year 2014 with only 1.815.
Thailand-Philippines also recorded competitive value for product of HS401, however,
this value showed an inconsistent trend with an average of 1.738.
Indonesia-Vietnam also showed a strong RCA value for product HS871
recording an average of 4.241. This RCA value throughout the period was inconsistent
in some years, causing Indonesia to lose its competitiveness.
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4.4.3 Summary of IIT and RCA in Automotive Industry
The automotive sector presented a higher degree of intra-industry trade with
connected markets between Malaysia, Thailand, Indonesia and Philippines. Vietnam did
not show any significant IIT value and this shows that in comparison to the four more
developed market, products from Vietnam in the automotive industry might not be as
diversified as the other four. The level of integration between the four countries in
general shows high level of integration within ASEAN.
The RCA value of ASEAN by country shows that there is still competition
between ASEAN countries for the similar product. It however shows that despite some
competition, each ASEAN country was able to be competitive in some product category
except for Malaysia. Malaysia did not record any competitive value for any of its
market destination in general. The RCA values also suggest that Indonesia and Thailand
mainly compete with each other in most ASEAN markets in the automotive industry.
Philippines on the other hand bring in a unique position to compete with Indonesia and
Thailand in most markets. The degree of RCA suggests that some ASEAN countries are
competing in the similar product, although the IIT values suggest otherwise. It can be
summarized that the automotive industry is quite integrated between Indonesia,
Thailand and Philippines although to certain extent, Vietnam has progressed well to
gain competitiveness in some ASEAN markets.
4.4.4 Summary of IIT for Automotive Industry
The IIT values showed that except for Vietnam, all other ASEAN countries
recorded significant IIT values especially for product of HS870. The high level of IIT
was most prevalent between Indonesia and other ASEAN countries. Philippines,
Malaysia and Thailand also recorded significant IIT values. Interestingly, Vietnam did
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not have any significant IIT values with any ASEAN countries, suggesting lower level
of integration. Indonesia’s strength in the IIT shows that there is strong product
diversification and this is supported by its IIT values with all ASEAN countries except
for Vietnam.
Table 4.26A: Product Categories with significant IIT values in ASEAN Automotive Industry
Country HS Code Pair Country
Indonesia 870 Malaysia
871 Malaysia
401 Thailand
870 Philippines
Philippines 401 Malaysia
870 Thailand
Malaysia 870 Philippines
401 Philippines
Thailand 870 Philippines
The pairs of country recording significant IIT values are also unique. As shown
in Table 4.26A, Malaysia, Thailand and Indonesia respectively recorded significant IIT
values with Philippines. This suggest that the trade between Philippines and the three
countries are two ways, and Philippines may have diversified its products allowing the
intense two way trade that is shown in the respective IIT values.
4.4.5 Summary of RCA in Automotive Industry
Thailand emerged as the country with most number of pairs with competitive
values for its trade with individual ASEAN country in the automotive industry. From
the 8 pairs shown in Table 4.26B, Thailand has RCA without any competition in the
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Malaysian market for product of HS870 and HS401. While Thailand also recorded quite
significant competitiveness in the Indonesia and Philippines automotive markets, there
remains some competition for Thailand with other ASEAN countries.
Table 4.26B: Product Categories with significant RCA index for Thailand-ASEAN countries in Automotive Industry and number of competing
countries
Country HS Code Pair Country Competing countries
Thailand 870 Malaysia 0
871 Malaysia 1
401 Malaysia 0
870 Indonesia 1
871 Indonesia 1
870 Philippines 1
871 Philippines 2
401 Philippines 1
Indonesia also recorded RCA values that were not competing with other
ASEAN countries in some markets. Indonesia’s competitiveness for product of HS870
in the Thailand market and product of HS871 in Vietnam market showed that Indonesia
enjoys high competitive levels for both these markets and no other ASEAN country is
competing for the same product category in those markets. Indonesia also recorded
significant RCA values for product of HS870 with Philippines and product of HS871
for Thailand and Philippines market and product of HS401 for Philippines market.
Indonesia was at least competing with another ASEAN country in these markets.
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Table 4.26C: Product Categories with significant RCA index for Indonesia-ASEAN countries in Automotive Industry and number of competing countries
Country HS Code Pair Country Competing countries
Indonesia 870 Thailand 0
871 Thailand 1
870 Philippines 1
871 Philippines 2
401 Philippines 1
871 Vietnam 0
The level of competitiveness of Philippines was in product of HS870 with
Thailand and Indonesia and product of HS871 with Indonesia. Philippines brings an
unique position into the automotive industry within ASEAN, as most RCA levels
recorded were between Thailand and Indonesia and Philippines gradually was able to
compete in both markets although there was competition from either Thailand or
Indonesia.
Table 4.26D: Product Categories with significant RCA index for Philippines-ASEAN countries in Automotive Industry and number of competing countries
Country HS Code Pair Country Competing countries
Philippines 870 Thailand 1
870 Indonesia 1
871 Indonesia 1
Vietnam on the other hand recorded significant RCA level for product of HS871
with Thailand and Philippines. However, Vietnam faces steep competition with ASEAN
countries in penetrating those markets.
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Table 4.26E: Product Categories with significant RCA index for Vietnam-ASEAN countries in Automotive Industry and number of competing countries
Country HS Code Pair Country Competing countries
Vietnam 871 Thailand 2
871 Philippines 2
4.5.1 IIT for Textile and Clothing Industry
a) Intra-industry Trade in Textile and Clothing Industry: ASEAN countries-Malaysia
Among the ASEAN countries under investigation, Thailand-Malaysia recorded
the most number of product items with high IIT values. The IIT values of Thailand-
Malaysia were significant for product of HS521, HS540, HS551, HS 560, HS591 and
HS630. Of these six product items, three showed an increasing trend, namely, product
of HS560, HS591 and HS630. Other product items showed a fluctuating trend.
The IIT values of Indonesia-Malaysia were recorded significant for product of
HS521, HS560 and HS630. HS560 and HS630 showed a decreasing trend while product
of HS521 did not show any obvious trend. The IIT values of Philippines-Malaysia was
significant for product of HS550 and HS610, both with a decreasing trend from 2001 to
2014. The IIT value for Vietnam-Malaysia for product of HS550 recorded a significant
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b) Intra-industry Trade in Textile and Clothing Industry: ASEAN countries-Thailand
The IIT value of ASEAN countries with Thailand recorded the highest for
Indonesia. The IIT values for Indonesia-Thailand recorded 7 product categories with
significant values. Product of HS520 was the highest IIT recorded with most of the
years, the values were close to unity. Product of HS521, HS570, HS580, HS610 and
HS611 all recorded a fluctuating trend throughout the years under investigation while
product of HS590 showed a steep decrease for the IIT value after year 2012.
The IIT of Malaysia-Thailand recorded 6 product categories with significant value,
most of which showed an increasing trend. The product categories were HS521, HS540,
HS551, HS560, HS591 and HS630. For the IIT value of Philippines-Thailand, only one
product category recorded significant value and it was for product of HS630.
The IIT values for Vietnam-Thailand showed an interesting trend. With
significant IIT values for product of HS540, HS600, HS610 and HS611, all of which
only recorded an increasing trend after the year 2005. Vietnam-Thailand IIT values
prior to 2005 for these product items were negligible but the steep increase after 2005
shows that the increased integration of ASEAN has contributed towards the significant
IIT values for Vietnam-Thailand for the mentioned product categories.
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c) Intra-industry Trade in Textile and Clothing Industry: ASEAN countries-Indonesia
The IIT value of Thailand-Indonesia recorded the highest number of product
categories with significant values. There were seven product categories that recorded
IIT values that were considerably high and product of HS520 recorded close to unity
values for many years. Other product items with significant IIT values were product of
HS521, HS570, HS580, HS590, HS610 and HS611.
The IIT value of Malaysia-Indonesia was recorded significant for product of
HS521, HS560 and HS630, all of which showed a decreasing trend. For Vietnam-
Indonesia the IIT values was significant for product of HS590 and HS610. However,
Vietnam-Indonesia values were close to unity only after year 2005 and 2006.
Philippines-Indonesia IIT on the other hand did not record any significant value at all
with throughout the period of investigation.
d) Intra-industry Trade in Textile and Clothing Industry: ASEAN countries-Philippines
The IIT values for ASEAN countries with Philippines only recorded significant
values for the IIT of Malaysia-Philippines and Thailand-Philippines. The IIT values for
Malaysia-Philippines in the textile and clothing industry were significant for product for
HS550 and HS610. Both these product categories however showed a decreasing trend.
The IIT value for Thailand-Philippines was significant only for product of HS630
and other product categories did not really show any significant value. For Indonesia-
Philippines and Vietnam-Philippines, there were no significant IIT values for the period
of investigation.
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e) Intra-industry Trade in Textile and Clothing Industry: ASEAN countries-Vietnam
Among the ASEAN countries, the IIT of Thailand-Vietnam was the most
significant covering the most amounts of product categories with significant IIT values.
The product of HS540, HS600, HS610 and HS611 recorded significant IIT values for
Thailand-Vietnam.
Indonesia-Vietnam IIT value was significant for product of HS580 and HS610.
Other product categories for Indonesia-Vietnam showed some significant value for
certain years but it did not result in consistent significant values. For Malaysia-Vietnam,
the IIT values were significant for product of HS550.
Most of the significant IIT values recorded between ASEAN countries and
Vietnam was for the years after 2005 or 2006 and prior to those years, the values
recorded were way below unity and for some years were negligible.
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4.5.2 RCA for Textile and Clothing Industry
a) RCA Index of ASEAN countries-Malaysia in the Textile and Clothings Industry
The RCA Index for ASEAN countries-Malaysia only showed some level of
competitiveness for a few textile and clothing products. The RCA index for product of
HS560 remained stable from year 2001 to 2014 with an average of 1.305 for Thailand-
Malaysia. Other RCA index for Thailand-Malaysia generally has shown a decreasing
trend especially for the product of HS510, HS590 and HS600. Product of HS570 on the
other hand showed a fluctuating trend.
The RCA index for Indonesia-Malaysia showed significant values for product of
HS521 and HS540. The values remained competitive for the period of investigation and
other product categories also recorded highly competitive values randomly for some
years only.
For Philippines-Malaysia RCA index, a significant value was recorded for product of
HS631. Other product categories did not record significant values. The RCA index for
Vietnam-Malaysia recorded significant values for product of HS520 and HS590, both
with an increasing trend.
b) RCA Index of ASEAN countries-Thailand in the Textile and Clothing Industry
In Thailand’s textile and clothing industry, the RCA index of Indonesia-Thailand and
Vietnam-Thailand both showed competitive RCA values for several product lines. For
Indonesia-Thailand, it recorded significant RCA values for product of HS540, HS580
and HS600. There were also other product categories that recorded competitive values
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for Indonesia-Thailand, however, the values were only significant for some selected
years.
The RCA index of Vietnam-Thailand recorded significant values for product of
HS430, HS500, HS540, HS 550, HS590 and HS630. In terms of trend, some of the
product categories such as product of HS500, HS550 and HS630 showed a fluctuating
trend while some product categories such as HS540 and HS590 showed an increasing
trend.
For Philippines-Thailand, the only product category that recorded significant value
for the textile and clothing industry is HS 631. However, despite recording high RCA
values for some years, since year 2010, the RCA index for product of HS631 became
insignificant.
The RCA index for Malaysia-Thailand did not show any significant value except for
product of HS430. Since year 2008, the RCA value of Malaysia-Thailand for product of
HS430 became significant and remained significant until 2014.
c) RCA Index of ASEAN countries-Indonesia in the Textile and Clothing Industry
All ASEAN countries recorded significant RCA values for some product categories
in the Indonesia Textile and Clothing Industry. The RCA index of Malaysia-Indonesia
was significant for product of HS510, HS521, HS560, HS580, HS591, HS600 and
HS630. Product of HS521 interestingly showed a gradual increase in RCA value from
year 2001 to 2014.
The RCA index for Thailand-Indonesia recorded competitive values for product of
HS550, HS560, HS580, HS590 and HS600. There was however no apparent trend for
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these product categories. For Philippines-Indonesia, the RCA index was recorded
significant for product of HS530 and HS560 for some years.
The RCA index of Vietnam-Indonesia recorded significant values mostly after year
2005. The product of HS511, HS540, HS560, HS580, HS590 and HS600 recorded
significant values from year 2005 to 2013, mostly with an increasing trend.
d) RCA Index of ASEAN countries-Philippines in the Textile and Clothing Industry
The RCA Index of ASEAN countries in the Philippines market showed different
level of competitiveness for each ASEAN country. For Malaysia-Philippines, the RCA
index was insignificant except for product of HS560 and HS630 that showed some
significant values.
Both these product categories also showed an increasing trend from year 2001 to 2014.
For the same period, the RCA index of Thailand-Philippines was significant for
product of HS550, HS560 and HS581. Although recording significant values, the RCA
index for Thailand-Philippines did not show any trend. The values fluctuated during the
period of investigation.
The RCA index for Indonesia-Philippines showed significant values for product
of HS520, HS521, HS540, HS550, HS590 and HS600. The significant numbers were
however only for certain years only. For all these product categories, there was no clear
trend recorded as for some years, the values dropped significantly.
The RCA index for Vietnam-Philippines recorded significant values for product
of HS550 and HS590. Both these product categories recorded high values for some
years and the values declined in some years. There was no clear trend of the values
recorded although mostly it showed significant RCA values.
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e) RCA Index ASEAN countries-Vietnam in the Textile and Clothing Industry
ASEAN countries recorded significant RCA values for some product categories
in Vietnam’s Textile and Clothing industry. For Malaysia-Vietnam RCA Index, product
of HS 521 showed an interesting trend, increasing from year 2001 to 2014. The RCA
Index for Malaysia-Vietnam in general has shown significant value for this product
category and the values increased significantly after year 2008 with double digit values.
Product of HS540 also recorded a significant RCA value, although the trend was
declining. The RCA Index of Malaysia-Vietnam was considerably high in year 2001
and it begun to decrease gradually until year 2014. Besides the two product categories,
the RCA index for Malaysia-Vietnam also showed significant values for product of
HS551, HS560 and HS600.
The RCA index of Thailand-Vietnam recorded the most number of product
categories with significant values. Thailand-Vietnam is considered competitive for
product of HS520, HS521, HS540, HS550, HS551, HS560 ,HS570, HS580,
HS581,HS590 and HS600. All these product categories, although did show an obvious
trend, the values remained stable throughout the period of investigation and fluctuated
at certain point of time. Only product of HS430 showed a deep decline in RCA value
and in year 2009, Thailand-Vietnam RCA value became insignificant.
For Indonesia-Vietnam, the significant RCA index values covered a wide range
of product categories. Product of HS520, HS521, HS540, HS550, HS551, HS560,
HS570, HS590, HS600 and HS631, all recorded significant RCA values. While the
entire product categories with competitive values remained stable throughout the period
of investigation, product of HS520 showed a decreasing trend and product of HS631
showed a sharp increase from year 2005 onwards.
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The RCA index of Philippines-Vietnam was the least competitive among
ASEAN countries in the textile and clothing market, only recording random significant
RCA values for some years. The RCA index of Philippines-Vietnam was significant for
product of HS580 from year 2001 to year 2008, however, became insignificant after
2008.
4.5.3 Summary of IIT and RCA in the Textile and Clothing Industry
a) Summary of IIT for Textile and Clothing Industry
The overall IIT values by country for the textile and clothing industry showed
very few significant values. The majority of product categories did not record
significant IIT values which suggest that countries in ASEAN were still focused in inter
industry trade for textile and clothing industry. This situation may happen when the
market is less diversified, thus suggesting lower integration between the economies in
AFTA.
As shown in Table 4.37A, some of the significant IIT values varied across
product categories and country. Malaysia’s IIT values that were significant was
recorded with Thailand and Indonesia only. However, product of HS560 recorded
significant values for both Thailand and Indonesia. This indicates that there is high two-
way trade between Malaysia-Thailand and Malaysia-Indonesia for product of HS560.
Indonesia-Thailand and Thailand-Indonesia also both showed significant IIT
values for several product categories. Both these pairs recorded significant values for
HS520 and HS521. This also suggests that Indonesia and Thailand have the most
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number of product categories with significant IIT values. Nevertheless, when all the IIT
values for textile and clothing industry is observed, it is clear that intra industry only
exist dominantly for Malaysia, Thailand and Indonesia. The product categories covered
shows that there exists high level of two-way trade between these countries as shown in
Table 4.37A.
Table 4.37A: Product Categories with significant IIT values in ASEAN Textile and Clothing Industry
Country HS Code Pair Country
Malaysia 540 Thailand
560 Thailand
591 Thailand
560 Indonesia
630 Indonesia
Indonesia 520 Thailand
521 Thailand
580 Thailand
610 Thailand
Thailand 520 Indonesia
521 Indonesia
580 Indonesia
610 Indonesia
Vietnam 620 Thailand
b) Summary of RCA Index for Textile and Clothing Industry
As shown in Table 4.37B, Malaysia has shown competitiveness in all four
ASEAN countries for the textile and clothing industry. The number of product
categories with significant RCA index value was recorded highest in the Indonesian
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market. Seven product categories showed significant RCA index and three of the
product categories did not have any competing country. The three product categories are
for product of HS521, HS591 and HS630. This shows that Malaysia has gained revealed
comparative advantage in this product category for the Indonesian market.
This is then followed by product of HS430 that recorded one competing country
and HS600 with two competing countries. Product of HS560 and HS580 both face
intense competition with other ASEAN countries with three competing countries in the
Indonesian market.
Malaysia also recorded revealed comparative advantage without any competing
countries for product of HS630 in the Philippines market and product of HS600 in the
Vietnamese market. It was also observed that for the Vietnamese market, Malaysia
faced steep competition from other ASEAN countries. This steep competitiveness to
gain comparative advantage in a growing market like Vietnam requires Malaysia to
compete with other countries and the trend shows that Malaysia has shown increasing
RCA value for product of HS521 and decreasing trend for product of HS540 in the
Vietnam market.
Thailand as shown in Table 4.37C recorded RCA values without any competing
countries for 7 different categories. Product of HS560 recorded significant RCA values
with all pair countries however, in the Malaysian market, Thailand emerged as the only
country with significant RCA value for product of HS560. Thailand also recorded
significant value without competition for two product categories in Philippines. For the
Indonesia and Vietnam market, Thailand faced competition from other ASEAN
countries in some of the product categories.
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Table 4.37B: Product Categories with significant RCA index for Malaysia-ASEAN countries in Textile and Clothing Industry and number of competing countries
Country HS Code Pair Country Competing countries
Malaysia 430 Thailand 1
510 Indonesia 0
521 Indonesia 0
560 Indonesia 3
580 Indonesia 3
591 Indonesia 0
600 Indonesia 2
630 Indonesia 0
631 Indonesia 1
560 Philippines 1
630 Philippines 0
521 Vietnam 2
540 Vietnam 2
551 Vietnam 2
560 Vietnam 2
600 Vietnam 0
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Table 4.37C: Product Categories with significant RCA index for Thailand-ASEAN countries in Textile and Clothing Industry and number of competing countries
Country HS Code Pair Country Competing countries
Thailand 560 Malaysia 0
570 Malaysia 1
590 Malaysia 2
600 Malaysia 0
550 Indonesia 0
560 Indonesia 3
580 Indonesia 3
590 Indonesia 1
600 Indonesia 2
540 Philippines 1
550 Philippines 2
560 Philippines 1
570 Philippines 0
581 Philippines 0
430 Vietnam 0
520 Vietnam 1
521 Vietnam 1
540 Vietnam 2
550 Vietnam 1
551 Vietnam 2
560 Vietnam 2
580 Vietnam 1
581 Vietnam 0
Indonesia also recorded many product categories with significant RCA values,
most of which were competing with other ASEAN countries. However, Indonesia
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recorded the highest number of product categories with sole significant RCA with
ASEAN countries. The product categories were mostly apparent for the pairs between
Indonesia and Vietnam. Indonesia also recorded 9 product categories without any
competing countries. For product of HS590, Indonesia recorded significant RCA index
with all ASEAN countries. As shown in Table 4.37D, Indonesia’s product categories
with ASEAN countries is the highest, recording 24 product categories.
Philippines recorded significant RCA values only for a few items and most
significantly has revealed comparative advantage for product of HS631 that was
recorded with Malaysia, Thailand and Indonesia. Philippines’ RCA Index for this
product category showed no competing countries for the Thailand market. Philippines’
RCA index in Indonesia’s market was the most competitive as there product categories
with significant RCA Index were competing with other ASEAN countries.
Vietnam recorded many product categories with significant RCA values with all
four other ASEAN countries. As shown in Table 5.37F, most of the significant RCA
Index was recorded in the Indonesian market and Vietnam seemed to compete with
other ASEAN countries. However, Vietnam managed to show revealed comparative
advantage without any competing country for product of HS511 and HS540 in the
Indonesian market. Vietnam also posed competition in the Malaysian and Thailand
markets.
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Table 4.37D: Product Categories with significant RCA index for Indonesia-ASEAN countries in Textile and Clothing Industry and number of competing countries
Country HS Code Pair Country Competing countries
Indonesia 520 Malaysia 1
521 Malaysia 0
540 Malaysia 0
551 Malaysia 0
570 Malaysia 1
590 Malaysia 2
631 Malaysia 1
540 Thailand 1
551 Thailand 0
580 Thailand 1
590 Thailand 1
600 Thailand 0
520 Philippines 1
521 Philippines 0
540 Philippines 1
550 Philippines 2
590 Philippines 1
520 Vietnam 1
521 Vietnam 2
540 Vietnam 2
550 Vietnam 1
551 Vietnam 2
560 Vietnam 2
570 Vietnam 0
590 Vietnam 0
600 Vietnam 1
631 Vietnam 0
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Table 4.37E: Product Categories with significant RCA index for Philippines-ASEAN countries in Textile and Clothing Industry and number of competing countries
Country HS Code Pair Country Competing countries
Philippines 631 Malaysia 1
580 Thailand 1
631 Thailand 0
530 Indonesia 1
560 Indonesia 3
580 Indonesia 3
631 Indonesia 1
580 Vietnam 1
Table 4.37F: Product Categories with significant RCA index for Vietnam-ASEAN countries in Textile and Clothing Industry and number of competing countries
Country HS Code Pair Country Competing countries
Vietnam 520 Malaysia 1
550 Malaysia 0
590 Malaysia 2
430 Thailand 1
500 Thailand 0
540 Thailand 1
590 Thailand 1
630 Thailand 0
511 Indonesia 0
530 Indonesia 1
540 Indonesia 0
560 Indonesia 3
580 Indonesia 3
590 Indonesia 1
600 Indonesia 2
520 Philippines 1
550 Philippines 2
590 Philippines 1
600 Philippines 0
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As a summary, for the textile and clothing industry in ASEAN countries, there
are significant number of product categories with high RCA index values which shows
that ASEAN countries have been able to capture certain markets within ASEAN and
recorded significant RCA values.
There were also many product categories, despite showing significant RCA
values, were competing with another or more ASEAN countries. This shows that
ASEAN countries to some extent are competing in the same product category in the
same market. This is more evident when these competing countries show an increasing
trend and the other pair country show a decreasing trend.
In terms of the countries, Indonesia recorded the most product categories with
significant RCA values while Philippines recorded the least. It can be observed that
Indonesia and Vietnam offer the largest range of product categories with significant
RCA values.
The levels of RCA among these countries actually suggest that AFTA might
have wide implication of integrating the countries under investigation. Besides
Philippines, all other ASEAN countries managed to at least have one product category
with RCA value that were not competing with any other ASEAN country. However,
there still exist deep competition between ASEAN countries in certain product
categories but the similarities of the product categories were not very apparent.
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4.6 Panel Regression Model
This section presents the results from the panel regression model. Coefficients
and standard errors (in parenthesis) are presented for each industry. All variables are
transformed to natural logs. While some observations are lost due to the use of natural
logs, this is significantly outweighed by the benefit of controlling for potential
nonlinearity in the data. The Hausman test is used to determine the selection of a Fixed
Effects or Random Effects in model in each case.
Before investigating the data econometrically, Figure 4.38 presents scatter
diagrams of the relationships between UR and exports and then UR and MOPR in the
textiles sector (note that one large MOPR outlier is removed here). The findings show a
strong negative relationship between UR and exports and no significant relationship
between UR and MOPR. In the sections that follow, these relationships are investigated
more rigorously in a multivariate setting.
Figure 4.38: Scatter Diagram of UR and Exports/MOPR, Textiles Sector
A. UR and Exports B. UR and MOPR
-4-3
-2-1
0ln
ur
14 15 16 17 18lnex
-20
24
lnm
opr
-4 -3 -2 -1lnur
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4.6.1 Determinants of Utilization Rate
Table 4.39 presents the estimated determinants of the utilisation rate for the
three industries. In the case of the textile industry, an additional model which interacts
MOPR with exports is also considered. An interaction is used in modelling by
multiplying two variables together to get a combined effect. Interactions are important
given that a variable has different effect for higher levels of the other variable. In this
case, the examination considers whether sectors with higher levels of MOPR also have
higher levels of exports.
The model appears to be a relatively good fit for the data. For textile industry the
multiple restrictions of the model returns an F-score of 123.28 resulting in a probability
of 0% (prob>F=0.00) that the chosen model is misspecified. The model also reports an
R2 value of 44% overall and 47% for between groups. According to the results, in the
textiles industry, the modelling indicates that a 10% increase in MOPR leads to an
associated increase in utilisation rate of 38% when the interaction affect is included.
However, the result is not statistically significant, and is negative when no interaction is
undertaken. A 10% increase in exports is associated with a larger and statistically
significant 69% decline. When MOPR and exports are interacted, as described above,
the result is a 68% decline, which is not a significant change. This indicates that the
interaction may not be that important in this case.
Overall, the results are consistent indicating that exports generally appear to
negatively and substantially impact the utilisation rate. The impact of MOPR is less
negative for textiles but we find no evidence that it has a significant impact on the two
other sectors. In the agricultural and automotive sectors, MOPR appears to have a very
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small positive impact on utilization rate but there is no evidence of a statistically
significant relationship.
On the basis of the evidence, the margin of preference has little impact on
utilization rate. This is quite astounding as the three industries are the most protected
industries in ASEAN and tariff reduction for these product categories do not benefit
Malaysia despite a higher margin of preference. This indicates that, even though the
margin of preference is high, exporters in Malaysia most likely do not use AFTA to
export their products to ASEAN countries. The reasons could due to other non-tariff
barrier costs that outweighs the benefit or savings from the margin of preference.
The interaction between utilization rate and exports on the other hand showed
that higher exports lead to lower utilization rate. This shows that Malaysian exporters in
these three industries do not utilize AFTA for large exports, but rather smaller value
exports lead to larger utilization of AFTA. It also suggests that Malaysian exporters
might already have a better deal in place bilaterally for products with higher value.
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Table 4.39: Determinants of Utilization Rate (UR), by Sector
Textiles Textiles II Automotive Agriculture
Log MOPR -0.12** 0.38 0.01 0.02 (0.04) (0.37) (0.08) (0.04) Log Exports -0.69*** -0.68*** 0.46 -0.45 (0.18) (0.17) (0.37) (0.34) Exports & -0.03 (0.02) 2008 -0.14 -0.14 -0.78 (0.08) (0.08) (0.79) 2009 -0.16 -0.14 -0.7 (0.16) (0.16) (0.56) 2010 0 0.03 -0.41 (0.09) (0.09) (0.52) 2011 -0.09 -0.06 -0.46 (0.15) (0.16) Recession 0.21 (0.26) (0.65) Observations 59 59 10 23Groups 12 12 2 6 R-squared 0.44 0.47 0.36 0.004 Panel Model RE RE RE RE Robust SE Yes Yes Yes Yes Standard errors are in parentheses; Significance levels are: *10%, **5%, ***1% levels; Recession dummy used for automotive due
to small sample size. Agricultural smaller observations due to large number of utilisation rates of zero.
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4.6.2 Determinants of Revealed Comparative Advantage
According to theory, it is expected that higher utilisation rates, margin of
preferences rates and exports in specific sectors should lead to higher revealed
comparative advantages. For instance, if a sector has a higher relative level of exports
compared to other sectors, it may allow that sector to secure a higher comparative
advantage over the longer-term. Table 4.40 presents the estimated determinants of the
sectors Relative Comparative Advantage (RCA). The models are a somewhat good fit
for the data. The overall R2 values range from 14% to 30%.
In the textiles and agricultural sectors, an increase of 10% in exports is
associated with increases of 8% and 23% respectively. In automotive sector, a 10%
increase in MOPR decreases relative comparative advantage by a very large 37%. On
the basis of the evidence, there is some evidence to show that margin of preference has
impact on RCA and strong evidence to suggest exports boost comparative advantage.
With the exception of the automotive industry, both textile and agriculture industry
showed that higher utilization rate would lead to higher RCA.
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Table 4.40: Determinants of Relative Comparative Advantage (RCA), by Sector
Textiles Automotive Agriculture
Log MOPR 0.01 -0.37*** 0.01 (0.03) (0.03) (0.05)Log Exports 0.80*** 0.22 2.27* (0.17) (0.26) (0.64)Log UR 0.02 -1.25*** 0.12 (0.17) (0.25) (0.09)2008 0.01 0.12 (0.14) (0.17)2009 0.01 0.13 (0.07) (0.23)2010 -0.22* -0.4 (0.09) (0.19)2011 -0.39*** -1.05* (0.09) (0.29)Recession 0.22* 0.07Observations 59 23 23 Groups 12 6 6R-squared 0.30 0.14 0.14Panel Model RE FE RERobust SE Yes Yes Yes
Notes: Standard errors are in parentheses; significance: *10%, **5%, ***1% levels; Recession dummy used for automotive due to
small sample size. Agricultural smaller observations due to large number of utilisation rates of zero. Models determined by
Hausman Test. Automotive model selected using test of over-identifying restrictions.
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4.6.3 Determinants of Intra-Industry Trade
According to theory, it is expected that higher utilisation rates, margin of
preferences rates and exports should lead to higher intra-industry rate. For instance, if a
sector has higher FTA utilisation rates, it may provide that sector with more trading
opportunities and boost intra-industry trade.
Table 4.41 presents the estimated determinants of Intra-Industry Trade (IIT).
The models fit the data very well, particularly for agriculture where the overall R2 value
is 91%. In textiles, a 10% increase in exports is associated with a 26% increase in IIT.
The UR rate is also found to increase IIT. In agriculture, a 10% increase in MOPR is
associated with an increase intra-industry trade. An increase in exports also appears to
positively impact trade but the result is not statistically significant. A 10% increase in
the utilisation rate is associated with a highly elastic 13% reduction in trade. In the
automotive sector, the main result is that a 10% increase in the utilisation rate appears to
lead to a decline in IIT of 46%, making it a factor of three times as responsive to UR as
the agricultural sector. The results also show that the year 2008 is associated with a
substantial and statistically significant fall in trade with a sharp reversal in 2009. This is
somewhat in keeping with expected trade developments during the global financial
crisis.
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Table 4.41: Determinants of Intra-Industry Trade, by Sector
Textiles Automotive Agriculture Log MOPR 0 -0.02 0.08*** (0.01) (0.02) (0.02)Log Exports 0.26*** 0.17 0.04 (0.06) (0.12) (0.05)Log UR 0.14* -0.46*** -0.13*** (0.06) (0.13) (0.01)2008 0.11 -0.28*** (0.08) (0.06)2009 0.05 0.24** (0.14) (0.08)2010 0.11 0 (0.09) (0.09)2011 0.09 0.05 (0.08) (0.1)Recession -0.01 (0.11)Observations 59 10 23Groups 12 2 6R-squared 0.37 0.52 0.91Panel Model RE RE RERobust SE Yes Yes Yes
Notes: Standard errors are in parentheses; significance: *10%, **5%, ***1% levels; Recession dummy used for automotive due to small sample size. Agricultural smaller
observations due to large number of utilization rates of zero.
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CHAPTER 5: SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Introduction
This chapter summarizes the results of the research and the recommendations
that can be taken into consideration for policy decisions. The chapter is organized by
presenting the summary of utilization of preferential tariff under AFTA and its policy
recommendations, followed by a summary for each industry. The chapter also draws
limitations of this research and areas for further research.
5.2.1 Summary of Utilization of Preferential Tariff under AFTA: Case of Malaysia
On the utilization of preferential tariff under AFTA for Malaysia, the study
concluded that by employing both GUR and AUR, the overall utilization remained low
although both categories showed an increasing trend. However, in some product
categories, both GUR and AUR recorded a high value.
The question of whether preferential tariffs under AFTA benefitted Malaysia as
an exporter can be answered in two angles. Firstly, preferential tariffs under AFTA, in
general, benefitted Malaysia’s export only to a very low degree, although the trend of
the utilization seems to be increasing. Therefore it is quite difficult to imply that AFTA
has directly benefitted Malaysia’s export taking into account that of the 25% of
Malaysia’s total export to the world is to ASEAN and from this 25%, only 13.7% (on
average) utilized the preferential tariff under AFTA. This percentage, when compared to
the total exports of Malaysia to the world, only represent 3.4% of Malaysia’s exports.
However, it can be noted that there were some product categories, which
recorded a high utilization rate. Although these product categories were mostly not the
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main exports or represent a high value, these product categories effectively used the
preferential tariffs. At the same time, it also suggests that perhaps small and medium-
sized enterprises could have reaped the benefits of AFTA and these products perhaps
were competitive enough to be exported to ASEAN markets. These areas could be
regarded as Malaysia’s niche exports that benefitted from AFTA.
Secondly, when the study analyzed both GUR and AUR, it was observed that
despite bringing in an “MFN Proxy,” the utilization level represented the same product
categories. This further suggests that the tariff rates under MFN and CEPT did not alter
the variability of the product categories. Only certain products used the preferential
tariffs, and the MFN proxy did not alter much of the aggregate level data, but at the
product level, certain products recorded full utilization and suggested that there was no
variation in terms of products that used preferential tariffs. It is, therefore, safe to say
that wide-ranging tariff liberalization plan is less significant to Malaysia’s export as the
impact on utilization is only for some products.
Making a comparison with the MFN tariffs further shows that the preferential
tariff would only be significant for products with certain criteria and is concentrated
only in certain specific product and market. This implies that although significant
reforms are made to the restrictive rules of origin, it is expected that the degree of
utilization will not move to a higher level. Since the preferential tariff under AFTA is
complex with different levels of tariff reductions, focus on increasing the level of
utilization should be on existing products that actually use the preferential tariff. Unless
there are new industries or an elevated demand for new products, the trend of preference
utilization would remain in the similar products. Focus also should be given to product
lines with high value and considerably low level of utilization. Besides the
commendable efforts to reduce trade barriers, Malaysia could actually focus on
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increasing the utilization of AFTA for its high-value exports to ASEAN by reassessing
the applicability of the preferential tariff to its export destinations, which include the
assessment of MFN tariffs and rules of origin.
Despite the huge momentum of tariff reduction or elimination undertaken by
ASEAN countries under the CEPT/ATIGA Scheme, it has not led to the sudden
increase of exports of Malaysia to other ASEAN countries. This is partly also because
preferential tariffs were not eliminated immediately but through gradual elimination
over the period of more than 20 years. As such, Malaysian exporters have ample of time
to undertake strategic measures and appropriate business strategies to accommodate the
changes in tariff structure, to better utilize the tariff.
Some countries also still use import control mechanisms such as Approved
Permit (AP) system to safeguard strategic industries such as automotive, iron and steel.
The main contributory factor for the low level of utilization rates under AFTA for
Malaysia is due to the following:
a. Around 32% of products (25,349 tariff lines) of ASEAN countries do not
require products to be exported using the CEPT Scheme (issuance of COO
is not required), as MFN tariffs are already at zero per cent.
b. The majority of products of member countries with MFN zero tariff are
products of main export interest to Malaysia, representing approximately
71.6% of Malaysia’s total exports to ASEAN.
c. This is also coupled with the fact that Malaysia’s exports to Singapore,
which constitute on average of 65.6% of Malaysia’s total exports to
ASEAN, do not require the utilization of CEPT as tariffs for all products
have been eliminated.
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Given these factors, the useful information for the utilization of preferential
tariff under AFTA for Malaysia would be the AUR, where it excludes the export values
to Singapore. When these values are excluded, it showed a more accurate level of
preferential tariff utilization. Given these results, the AUR is mapped out against the
export values of Malaysia, excluding Singapore for the period of 2007-2011 as shown
in Figure 5.1 below.
Figure 5.1: Exports of Malaysia to ASEAN (excluding Singapore) in Million USD
against Average AUR for Malaysia (2007-2011)
Figure 5.1 shows that the concentration of products at HS2 level were mostly in
the low export values. Most of these product categories lie at exports value of USD 500
Million and lower and most products are also at utilization rate of 30% or below. Given
these results, it is important to note that there are also product categories that recorded
very high utilization rate together with export value. This disparity in the level of
ExportsofM
alaysiatoASEAN(ExcludngSingapore)
2007‐2011inMillionUSD
AverageAdjustedUtilizationRate(AUR)forMalaysia2007‐2011
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utilization can be used as a strategy for Malaysia in moving forward its trade agenda in
ASEAN. In order to effectively increase Malaysia’s export to foster intra-ASEAN trade,
the results in the chart above can be used as guidance to strategize the areas in which
Malaysia might have potential to further increase its exports or utilization of preferential
tariff.
Figure 5.2 shows the the chart with the recommended strategy for Malaysia by
zoning the chart into four different colour coded areas. The arrow shows the direction
for Malaysia to make full use of AFTA and foster intra ASEAN trade. When more
product categories move in this direction, it would represent higher export value and
higher utilization rate. The area with the most number of products is represented in red.
This area consist of products with low utilization rate and low export value. Given this
circumstance, product categories in this area should be regarded as a low priority group
of products for Malaysia.
The area in yellow represents the medium priority group of products for
Malaysia. Product categories that fall under this area have a reasonable level of
utilization spanning from 30% to 70%. However, the export value for these products are
low, recording a value of lesser than USD500 million. There is potential for Malaysia to
increase intra ASEAN trade for these products by increasing the exports and the level of
AFTA utilization for these product categories. The products such as HS74 (Copper and
Articles thereof), HS95(Toys, games, and sports requisites;oarts and accessories thereof
), HS55 (Man-made staple fibres), HS48 (Paper and paperboard), HS48 (articles of
paper pulp, of paper or a paperboard), HS03 (Fish and crustaceans, molluscs and other
aquatic invertebrates), HS83 (Misc articles of base metal), HS64 (Footwear, gaiters and
the like, parts of such articles), HS59 (Impregnated, coated, covered or laminated textile
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fabrics;textile articles of a kind suitable for industrial use) and HS30 (Pharmaceutical
products) lie in this medium priority group.
Figure 5.2: Recommended strategy for exports of Malaysia to ASEAN (excluding Singapore) in Million USD against Average AUR for Malaysia (2007-2011)
Next, the area in green and blue represents high priority group of products. The
area in green are products with high export values whereas the area in blue are products
with high utilization rates. The products in the green area already have a high export
value and Malaysia should continue to export these products to ASEAN. The
improvement that can be made for Malaysia is to increase the utilization rate of the
ExportsofM
alaysiatoASEAN(ExcludngSingapore)2007‐2011inMillion
USD
AverageAdjustedUtilizationRate(AUR)forMalaysia2007‐2011
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products in this green area. Only product of HS85 recorded considerably high utilization
rate with high export value. Other products only recorded utilization rate below 50%.
For these products, an increase in utilization would also allow more products to be
exported as well as foster intra-ASEAN trade. Products that fall under this green area
include HS27, which recorded highest export value with USD 3.78 Billion. However,
the utilization rate for this product category is only 1%. Other products that fall under
this category are HS85 (Electrical machinery and equipment and parts thereof), HS84
(Nuclear reactors, boilers, machinery and mechanical appliances; parts thereof), HS39
(Plastics and articles thereof), HS15 (Animal or vegetable fats and oils and their
cleavage products; prepared edible fats; animal or vegetable waxes), HS29 (Organic
chemicals), HS72 (Iron and steel) and HS90 (Optical, photographic, cinematographic,
measuring, checking, precision, medical or surgical instruments and apparatus; parts
and accessories thereof).
Moving to the area in blue, it represents the group of products with high
utilization rate and lower export values. There are two products that recorded 100%
AUR which shows that all the products exported under product of HS91 and HS75 used
preferential tariff under AFTA to export to ASEAN markets. This remarkable
utilization value can be improved further by expanding the export value to have a more
meaningful impact on AFTA’s impact to intra-ASEAN trade. It was also interesting to
note that product of HS87 which is mostly protected in many ASEAN markets recorded
AUR of 99%. The level of utilization in this product category shows that AFTA has
benefitted Malaysia’s automotive industry as the product of HS87 is mainly automotive
vehicles. Other products that fall under this category are HS91 (Clocks and watches and
parts thereof), HS75 (Nickel and articles thereof), HS57 (Carpets and other textile floor
coverings), HS09 (Coffee, tea, materials and spices), HS62 (Articles of apparel and
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clothing accessories, not knitted or crocheted), HS81(Other base metals; cermets;
articles thereof), HS92(Musical instruments; parts and accessories of such articles),
HS40(Rubber and articles thereof), HS61(Articles of apparel and clothing accessories,
knitted or crocheted), HS18(Cocoa and cocoa preparations) and HS80 (Tin and articles
thereof).
5.2.2 Policy Implications
Being the earliest regional trade agreement that Malaysia was involved in and
the 20 years of AFTA’s implementation, among the key policy implication of the results
in the above tables is the need for Malaysia to prioritize and focus in product categories
that can potentially foster and increase Malaysia’s exports to ASEAN through AFTA.
Given the development of AFTA with gradual tariff reduction over the years and even
today, after establishing the ASEAN Economic Community in 2015, intra ASEAN trade
is still low although with almost all zero tariff values.
From this study, policymakers can at least clearly see the areas in which
Malaysia should have high priority, medium priority and low priority based on the level
of AFTA utilization. This serves as an important guidance as trade negotiations for
tariff elimination and rules of origin could be strategized further according to areas
where Malaysia could have higher priority, in getting a better future deal with
Malaysia’s export destination. The areas identified as high priority also should be given
more attention to reduce trade barriers and focusing on these products would allow
Malaysia to increase its exports in the high priority products.
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5.3 Agriculture Industry in ASEAN
5.3.1 Summary
The results of both IIT and RCA shows differing trends across different product
categories. By identifying the most significant product categories for the agriculture
industry that is represented by some important trends, it gives a better understanding on
how ASEAN countries have integrated in the agriculture industry. The following
product categories with most significant RCA and IIT values are product of HS070,
HS090, HS100, HS110 and HS120.
a) Product of HS070 - Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips
All ASEAN-5 countries recorded significant RCA values for the product of
HS070. The main export destination is Indonesia and Malaysia. Indonesia sources
product of HS070 from all ASEAN countries, thus creating a high degree of
competition between the ASEAN countries. For the export destination of Indonesia,
there is a steep competition between Vietnam and Philippines, while Malaysia also
recorded trend showing that the RCA values were increasing. There was also
competition between Thailand, Indonesia and Vietnam when exporting to Malaysia
These pairs also showed a significant value of IIT for product of HS070 except for the
pairs of Philippines-Indonesia and Vietnam-Indonesia.
It can be summarized that for product of HS070, there exist a positive level of
integration between ASEAN-5 countries given both high RCA and IIT values. This is
with the exception of the steep competition between Philippines and Vietnam in the
Indonesian market. In the earlier years, 2001-2007, Vietnam recorded very high RCA
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values with Indonesia, however, the value dropped from 2008 onwards given the
competition from Philippines.
b) Product of HS090 - Coffee, Tea, Pepper, Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla
All the ASEAN-5 countries are importer of product of HS090, which mainly
consist of coffee and tea products. Indonesia and Vietnam are both competitive in their
export destinations which is not concentrated in certain markets only. Indonesia and
Vietnam also recorded significant IIT values showing that there exist two way trade
between both these countries. The product of HS090 shows that significant RCA
recorded between pair countries complement each other rather than compete with each
other.
c) Product of HS100 - Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye
Product of HS100 which consist mainly of Rice, the main export of ASEAN in
agriculture, showed that there has been steep competition between Thailand and
Vietnam for the same markets. From the trend, it can be observed that Thailand’s RCA
value was reducing, while Vietnam’s RCA value showed an increasing trend. This
suggest that Vietnam has started to take over Thailand’s export market in the same
countries. This also means that the high degree of competition between Thailand and
Vietnam has resulted in Thailand losing its competitiveness in some ASEAN countries.
f) Product of HS110 - Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten
Similar to the exports of rice or Product of HS100, Thailand and Vietnam
compete with each other for product of HS110 in the Malaysia and Philippines markets.
Thailand however is the only country with significant RCA value in Indonesia. The
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trend for product of HS110 shows that, despite some competition from Vietnam for
product of HS110 especially in the Philippines, where Vietnam’s RCA value surpassed
Thailand’s value, Thailand still remains competitive in larger markets when the market
value is combined for Malaysia, Indonesia and Philippines. Although there is some
degree of competition between Vietnam and Thailand for this product category,
Thailand remains more competitive.
g) Product of HS120 - Ground Nuts, Seeds, Oil Seeds, Soya Beans etc.
The RCA values for the product of HS120 were significant for all ASEAN-5
countries. The destination of export is also represented by all countries and this largest
pair of countries with significant RCA values shows that product of HS120 is most
integrated in ASEAN for the agriculture industry. Malaysia for example recorded
significant RCA value for the markets of Indonesia and Vietnam, while Thailand
recorded significant RCA for Indonesia, Malaysia and Vietnam markets. Indonesia and
Vietnam on the other hand recorded highly significant values with nearly all other
countries.
In terms of trend, there were significant movement of RCA value in each
market. For Malaysia as the export destination, the RCA values were reducing in trend
from both Vietnam and Indonesia. The reduction in RCA values for Malaysia also
suggest that Malaysia is less dependent on the imports from Vietnam and Indonesia as
the imports from Thailand and local supply might have taken over the need for
importing. Similar trend was also shown for the Indonesian market. After year 2011, the
highest RCA value which was from Vietnam loss its significance and Vietnam was not
penetrating the Indonesia market anymore after 2011.
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In terms of the Thailand market, although initially Vietnam recorded very high
RCA values, the values started to drop dramatically after year 2008. This was also
similarly relevant for the Philippines market. The issue of Vietnam losing its
competitiveness in all of its market although still recording significant value only in
Thailand, coupled with the fact that other countries also recording significant RCA
values shows that the competition between countries in this product category is positive
and has resulted in deeper integration.
This product category, in comparison to other categories offers a wider range of
products with different level of processing. Therefore, it allows countries to diversify
their products and the degree of integration for this product category is considered the
highest in the agriculture industry given the pairs of countries with significant RCA
values.
5.3.2 Conclusion
For the three product categories above which mainly recorded the pairs with
significant RCA values, a few different patterns can be observed as follows:
a) High level of integration – Trade creating
i. Product of HS120 - Ground Nuts, Seeds, Oil Seeds, Soya Beans etc.
showed the highest level of integration, recording the most pairs of
countries with significant RCA values that did not negatively impact the
competition within ASEAN and this was also supported with higher IIT
values.
ii. Product of HS070 - Cabbages, Cauliflowers, Vegetables, Potatoes.
Lettuce, Carrots, Turnips also showed a high level of integration,
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recording both significant RCA and IIT values. This is with the
exception of the steep competition between Philippines and Vietnam in
the Indonesian market.
b) Complementary – Trade creating
i. Product of HS090 which mainly involves the coffee and tea products
showed that although Vietnam and Indonesia as main exporters for these
products compete with each other in the ASEAN market, both countries
did not show any pattern of causing the other country to lose its
competitiveness.
c) High degree of competition – Trade diverting
i. Product of HS100 which mainly consist of rice, the main export in
agriculture, showed a high degree of competition between Vietnam and
Thailand. The trend of significant RCA values showed that Thailand in
most cases was losing its competitiveness to Vietnam.
ii. Product of HS110, similarly also showed a high degree of competition
between Vietnam and Thailand, however, Thailand is still able to be
competitive in large market such as Indonesia.
5.3.3 Policy Recommendations
During the period of investigation, ASEAN-5 countries have shown different
trends of competitiveness for each product categories in the agriculture industry. This
competitiveness and some of the product categories which did not even show any level
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of significant competitiveness reflects that there are policy mismatch that curbs further
integration in the agriculture industry.
One of the remaining issues that are faced by the agriculture industry in ASEAN
is the expectation of individual countries to adhere to different trade liberalisation
schedules. The agriculture products in ASEAN, unlike other industries, are mostly not
included in the CEPT scheme or if included, the tariffs are absolutely high. This needs
structural reforms in policies for individual ASEAN countries to allow national policies
that foster and capitalises ASEAN as a competitive exporter of agriculture products
especially in fostering food security in the region. Cooperation at ASEAN alone without
change in national policies would not create the opportunity for ASEAN to position as a
competitive agriculture exporter to the rest of the world.
Countries would also need to consider more flexible and accommodating
regulatory policies to handle cross border issues for the agriculture industry. Most
agriculture produces are cheaper direct consumer products that travel from one country
to another more informally. These cross border trade activities can be improved by
integrative policies that can legitimise such activities.
Public-private partnership that involve cross border investments between
ASEAN countries would also be necessary to enhance productivity and research.
ASEAN countries need to create specialisation by focusing on products that they are
competitive in and this focus can be strengthened when investment policies between
countries in ASEAN is more relaxed and flexible. One country that lets go of their
predominantly large export, for example black tea, to produce green tea should enable
the producer of black tea in that particular country to invest in another country within
ASEAN that specializes in black tea. However, the problem in the agriculture industry
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in most ASEAN countries is investments in agriculture industry is highly protected by
government and cross border investments rarely take place.
The benefits of a more integrated agriculture industry in ASEAN can have
spillover effects if ASEAN is well integrated. One most important aspect to be more
integrated will be to adopt standardisations. Exports out of ASEAN should be able to
meet the international standards and as proven today, countries like Thailand
particularly is able to adhere to several international standards that has elevated the
industry in Thailand from 1990s to today. Learning from this experience, with the
capacity of an integrated ASEAN countries, it would be able for ASEAN to compete
with countries like China or Brazil. One good example is the Australia-New Zealand
Closer Economic Relations Trade Agreement (ANZCERTA), which was able to
increase agriculture trade between Australia and New Zealand although both countries
have similar products.
In making ASEAN a single market and production base of the world market
with free flow of goods, services, investment and freer flow of capital, the agriculture
industry in ASEAN needs to face the challenge of streamlining member countries based
on their competitiveness and how to address issues arising from loss of production in
certain products to domestic market and the period of adjusting to it. Furthermore, a
more integrated ASEAN agriculture industry would enable ASEAN to collectively
expand an integrated market and complement with other larger economies in East Asia
such China, Republic of Korea and Japan that will make a stronger force in international
trade.
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5.4 Automotive Industry in ASEAN
5.4.1 Summary
The results of both IIT and RCA shows that for all the three product categories
under the automotive industry showed a high degree of integration between Thailand,
Indonesia and Philippines. The summary of competitiveness for the three product
categories are as follows:
a) Product of HS401- Conveyor or Transmission Belts, New Pneumatic Rubber tyres, Retreaded/Used Tyres, Inner tubes of Rubber
The product of HS401 mainly represents products such as rubber tyres,
conveyor belts and parts used in automotive industry recorded significant RCA value
for Thailand and Indonesia. Thailand is competitive in exporting to Malaysia and
Philippines while Indonesia is competitive for its exports to Philippines. Interestingly,
all the trends for the three pairs showed a consistent value for year 2001 to 2014. The
significant RCA value is further supported by significant values of IIT, suggesting two-
way trade between several pairs of ASEAN countries. Eventhough both Thailand and
Indonesia are main exporters to ASEAN countries, both countries recorded high IIT
values between each other suggesting two way trade and product diversification that
reflects high degree of integration. It must, however, be cautioned that Vietnam did not
show significant level of integration from both RCA and IIT indices for this product
category.
b) Product of HS870 - Tractors, Public Transports Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
The main product of automotive industry, which is cars, transport vehicles,
chassis and body for motor vehicles, is represented under product of HS870. Countries
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recording significant RCA value for these products are Thailand, Indonesia and
Philippines. Thailand’s RCA was most encouraging with constant RCA values from
2001 to 2014 and showed an increasing value for the Philippines market. This is
followed by Indonesia that recorded significant RCA value with Thailand and
Philippines. The values recorded by Indonesia was stable from year 2001 to 2014.
Indonesia and Thailand also showed high IIT value suggesting two-way trade.
Philippines also recorded high two way trade with Indonesia and Thailand and recorded
the highest RCA values for Thailand and Indonesia markets. Although Philippines
marked the highest RCA value for both these markets, the trend shows that Philippines
lost its competitiveness since the beginning of 2008.
c) Product of HS871- Motorcycles, Bicylces, Motorcycles Accessories, Trailers, Semi-Trailers
Thailand, Indonesia and Philippines also recorded significant RCA values for
product of HS871, which mainly consist of motorcycles and bicycles. Thailand’s
highest RCA value was recorded for the Philippines market and significant values were
also recorded for Malaysia and Indonesia. Indonesia recorded significant values for
Thailand, Philippines and Vietnam. For this product category also, there was high IIT
values recorded for the trade between Thailand, Indonesia and Philippines reflecting the
high degree of integration between these countries.
5.4.2 Conclusion
For the three product categories above which mainly recorded the pairs with
significant RCA values, the automotive industry in ASEAN countries were focused
between Thailand, Indonesia and Philippines, whereas Malaysia and Vietnam in most
cases were isolated from the significant pairs of countries.
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a) High level of integration – Trade creating
For both the product of HS870 and HS871, Thailand, Indonesia and Philippines
recorded significant RCA values. Although competing in the same markets, the IIT
values between these countries were also high, suggesting that there were product
diversification in these countries. When put together the results from RCA and IIT for
these three countries, it can be concluded that there was a high degree of trade creation
effect.
b) Low level of integration or isolation
The RCA values for countries like Malaysia and Vietnam were not significant
for all products in the automotive industry. This also shows that these two countries
were not able to integrate into the ASEAN market cohesively like the other three
countries.
5.4.3 Policy Recommendations
As shown in the results, the level of integration for some ASEAN countries in
the automotive industry is already remarkable. The level of competitiveness between
these ASEAN countries has not been detrimental to one another, which shows that
countries are already diversified and increased the economies of scale as reflected in the
increase of ASEAN’s export value in the automotive industry from year 2001 to 2014.
The challenge however is for ASEAN to be a global hub for automotive production,
which requires greater collaboration between ASEAN countries to serve the global
market. AFTA in this case has provided ASEAN’s automotive industry the integration it
needed, where countries have specialized in certain products and increased the
economies of scale. At the same time, the reduction of tariffs under AFTA, allowed
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ASEAN countries to find its niche of competitive advantage. However, this is not
sufficient, if ASEAN intends to postion itself as a global production hub for the
automotive industry.
Besides the tariff elimination under AFTA, there are national policies that can
improve ASEAN countries to the next level. Most of ASEAN’s export market since
1990s has always been the Asian region, in particular where Japanese auto makers
marked their footprints in several ASEAN countries by investing in production plants.
Thailand and Indonesia have remarkably benefitted from such exercise. This is evident
taking into account that low cost labour and lower end productions of car makers from
Japan seem to crowd the ASEAN countries. Countries that already benefit from this
experience especially Thailand would need a boost to further advance their exports.
ASEAN automotive industry also need to consider in future to also tap into the
European market and adhere to Europe’s higher standards. This would require policies
that focus on innovations and higher standards.
The national policies of ASEAN countries in general are actively engaged in
increasing local production for small and low cost car segments. This is partly to meet
the local demand and this made policies of ASEAN countries not focusing in
international broader demand particularly from North America and Europe. ASEAN
countries also need to collaborate to integrate other countries like Vietnam and
Malaysia to certain extent into the value chain of the automotive industry by creating
competitive advantages and not initiating competing nationalistic incentives schemes
that inhibit regional integration. Among the initiatives that can be undertaken by
governments is to support the development of a local supplier base which would in turn
encourage international players to both establish local plants and to source more readily
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from ASEAN for their operations compared elsewhere in the world. There also should
be improvements in quality and ensuring compliance with international standards,
which will raise ASEAN’s profile and competitiveness.
For automotive products that involve rubber, ASEAN is the main producer of
rubber in the world, capturing a total of 75% of the world market share. Thailand leads
ASEAN with a market share of 35%, followed by Indonesia, 30%, Malaysia and
Vietnam about 10% each. The top export destination for rubber is China and in the
automotive industry, products that use rubber is topped by China and not any ASEAN
country. When broken down to rubber tyre products which is an industry worth
USD83.6 billion, the export market share is represented by China with 19%, Japan with
8.6%, Korea with 5%. ASEAN countries that are part of the major rubber tyre producers
are Thailand with 4.6% and Indonesia 2.1%. Given the loss of competitiveness of
ASEAN from exports of rubber to finished products such as rubber tyre products, there
is huge potential for ASEAN countries to succeed in rubber products that involve
automotive industry. ASEAN would need a more comprehensive policy to foster cross
border trade and create diversified products. Facilitation of cross border regional value
chains would encourage a broader spread of economic wealth, and allow for economies
of scale by automotive suppliers. This will then allow the establishment of areas of
excellence that can supply multiple OEMs.
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5.5 Textile and Clothings Industry in ASEAN
5.5.1 Summary
The results of both RCA and IIT for the textile and clothing industry shows that
most ASEAN countries compete and trade with each other mostly only in unprocessed
products or raw materials as the RCA values recorded for these product categories were
significant. Product categories with finished or consumer goods for the clothings
industy does not show high degree of competition between ASEAN countries although
the value of trade for these products were high. ASEAN countries trade less with each
other as most of these products produced in ASEAN countries are exported for the
global market. There still exist two way trade between ASEAN countries for those
product categories, reflected by significant IIT values. The significant RCA values that
were recorded for unprocessed products are as follows:
a) Product of HS520- Cotton, cotton yarn and woven cotton
For the product of HS520, which mostly involve cotton, cotton yarn and woven
cotton, three countries in ASEAN show significant RCA values. The main importers of
this product category are Vietnam, Malaysia and Phillippines. There exist some high
degree of competition between Indonesia and Thailand for the Vietnam market. The
trend shows that Thailand is losing its competitiveness to Indonesia after year 2005.
Indonesia has also shown an increasing trend for RCA values for the markets of
Malaysia and Philippines.
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b) Product of HS540- Man-made: filaments yarn and synthetic yarn
Similar to the product of HS520, the product of HS540 which mainly involves
man made filaments yarn and synthetic yarn, observed high degree of competition
between Indonesia, Vietnam and Thailand. In the period of 2001 to 2005, Thailand
recorded significant RCA values for Vietnam and Philippines markets but started to lose
its competitiveness especially to Indonesia that gained competitiveness in the same
markets after 2005.
c) Product of HS550 - Synthetic and artificial: filament tow, staple fibres
Thailand, Indonesia and Vietnam showed high degree of competition between
each other for product of HS550 which involves synthetic and artificial filament tow
and staple fibers. The trend shown by these three countries seem to fluctuate and only
Thailand’s RCA value remained significant for the whole period.
5.5.2 Conclusion
The textile and clothings industry in general showed two types of results. The
first is on the competitiveness of ASEAN countries among each others for low
processed or raw products that are mainly represented by product of HS520, HS540 and
HS550. In contrast, other product categories, mainly clothings, apparel and finished
products that are represented by product of HS610, HS611, HS620, HS621 and HS640
with high export values, did not show any level of competitiveness between ASEAN
countries. While there were some existing intra-industry trade between Thailand and
Indonesia, other pair of countries did not show significant RCA or IIT values. The
results for the textile and clothings industry by product category can be summarized as
follows:
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a) High level of integration – Trade creating
Product of HS520,521,560,580- The product categories although recording
lower value of exports between ASEAN countries, showed trade creating effect, with
significant RCA values and high IIT values between countries. Malaysia, Thailand,
Indonesia and Vietnam showed this trade creating effect
b) High degree of competition – Trade diverting
The product of HS520, HS540 and HS550 are the higher valued exports for low
processed or raw products for the textile industry. The results show that there exist high
degree of competition between ASEAN countries, particularly between Thailand and
Indonesia, where Thailand loss some of its competitiveness to Indonesia.
c) Low level of integration or isolation
The products with high export values that are processed, mainly apparel and
clothings such as product of HS610, HS611, HS620, HS621 and HS640 did not show
any signs of competitiveness for any ASEAN country in the ASEAN markets. The IIT
values for these product categories were also low, suggesting that integration between
ASEAN countries for these products were very low. This is due to mainly the fact that
ASEAN countries continue to export their finished products in the textile and clothing
industry to markets outside ASEAN.
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5.5.3 Policy Recommendations
ASEAN countries today are already seen as a formidable force in the textile and
clothing industry. However, the growing industry in ASEAN faces steep competition
with China and most competition is prevalent for low cost production, which comes
with low labour cost. These factors of competitiveness in ASEAN will not be
sustainable without sound policy judgments by ASEAN countries to compete and gain
comparative advantage against external main competitor, China. At the same time,
ASEAN countries would also need to build their capacity to face the technical change
of the industry.
Many of the textile industries is ASEAN compete with each other in upstream
products and this competition gets steeper when China is included in the picture.
ASEAN countries need to move away from their dependence to foreign owned firms
that mostly take advantage of the low labour cost to enter into the cheaper labour
ASEAN market. Although these investments spurred the growth of these countries for a
while, industries driven by foreign companies only will not be sustainable. This has
been the case for Vietnam and Cambodia, where thousands of foreign owned companies
are set up to produce in the textile and clothing industry. Investments like this will not
last long, as competition may arise especially with China and the risk of technology
change which could cause the whole industry in ASEAN countries to collapse. To
mitigate these risks, governments in ASEAN countries should develop their own
industry players by providing incentives or loans that would allow them to produce and
compete with the foreign companies. Skills and end user fashion and design also must
also be developed locally to enhance the local quality and design of the products. With
more local participation in the industry, especially SMEs, it would enable these ASEAN
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countries to have the local champions and avoid the over dependence on foreign owned
firms.
As shown in the results of this study, ASEAN countries have different strengths
and weaknesses for each product category. The strengths and weaknesses of these
ASEAN countries must be taken into consideration to ensure that ASEAN is fully
integrated in this industry by having an integrated supply chain. At the current situation,
the low intra-industry trade for finished products and in general intra-ASEAN trade for
the textile industry requires a boost from individual policymakers to move away from
the sentiment of protecting the industry and competing with neighbors and industry
players must be discouraged from the mentality of completing the whole production
only in one country. The risk of these sentiments and mentality is ASEAN countries
may lose what it is already their competitive advantage at the moment. Industry players
that think regionally are set to be in a better position by pulling the strengths from
different ASEAN countries. These efforts would be achievable only with improved
tariff elimination and trade facilitation, which is coupled with trade promotion,
increased investments in productivity and improved skills.
Moving away from the national protectionist agenda for this industry, countries
need to eliminate tariffs more rapidly and remove items that are still in the exclusion
list. Besides tariff elimination or reduction, the industry also depends on the Rules of
Origin (ROO). A full review of textile and clothing ROO and regional accumulation
rules need to be addressed and coordinated before entering into regional trade
agreements with other parties. The move by ASEAN to sign several FTAs with its
dialogue partners and the ambition of completing the Regional Comprehensive
Economic Partnership (RCEP) should be based on ROO that is standardized and
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facilitate intra ASEAN trade. Failure to achieve this would negatively impact ASEAN’s
strength as one trading bloc given the lower intra ASEAN trade value recorded in this
industry.
5.6 Summaries and Conclusion of the Panel Regression Model
For the investigated models, the margin of preference rate (MOPR) has little
impact, with the notable exception of trade in the agriculture sector. Exports appear to
have negative impacts on utilization rates, holding other factors constant. By contrast,
exports have strong positive overall impacts on comparative advantage and trade,
particularly in the textiles sectors.
The utilization rate plays a proportionately smaller role in impacting RCA. The
data indicate that RCA declined in the textiles and agricultural sectors in 2011.Overall,
the trade findings show significant variation in results across sectors. For example, the
MOPR has a significant positive impact on Intra-Industry Trade (IIT) but only in the
agricultural sector. Exports are also shown to have a positive impact on IIT, but the
result is only statistically significant for textile industry. The UR has a negative impact
on trade in the agriculture and automotive sectors but a positive impact in textiles.
The research has shed new light on the utilization of preference under AFTA for
Malaysia, looking at a set of products from three most restricted industries in ASEAN.
The models found that the overall margin of preference rate and export values do not
significantly affect the utilization rate of AFTA in the three industries.
The impact of AFTA, however, seemed more positive in providing revealed
comparative advantage to Malaysia in the three industries. Exports, particularly in the
textile industry, have a strong positive overall impact on revealed comparative
advantage. The preference utilization to a certain extent also corresponds positively for
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the textile and agriculture industry contributing to increase in revealed comparative
advantage. In terms of intra-industry trade, the study showed a strong relationship
between the margin of preference and intra-industry trade for the agriculture sector. The
intra-industry trade also corresponded positively with the increase in export and
utilization rates in the textile industry.
The effect of AFTA to Malaysia investigated in three different aspects by
investigating determinants for preferential tariff utilization revealed comparative
advantage and intra-industry trade showed varying results for the three industries that
were investigated. The agriculture sector showed that Malaysia strongly benefits from
intra-industry trade as the study found a significant positive relationship between the
increase of intra-industry trade and exports. A diversification of Malaysia’s agriculture
exports to ASEAN would increase exports and encourage two-way trade. The
agriculture sector also showed that intra-industry trade positively correlates with margin
of preference rate. The intra-industry trade also increases with the increase in
preferential tariff utilization under AFTA.
The positive effect of AFTA for the textile industry was recorded through
preferential tariff utilization rate and revealed comparative advantage determinants. The
increase in preferential tariff utilization for Malaysia in the textile industry increases
with the margin of preference rate which reflects that the reduction in preferential tariff
under AFTA helps to increase preferential tariff utilization. However, the increase in
preferential tariff utilization shows negative correlation with exports, in other words,
exports of Malaysia in the textile industry to ASEAN do not benefit from the utilization
of preferential tariff. This may be the case as preferential tariff utilization was only
useful for low-value exports in the textile industry. Malaysia’s revealed comparative
advantage in the textile industry is highly dependent on the exports value. The margin
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of preference only plays a minimal role in increasing Malaysia’s revealed comparative
advantage under AFTA for the textile industry.
The automotive industry of Malaysia did not gain from revealed comparative
advantage and intra-industry trade. However, there was some evidence to show that
increase in preference tariff utilization could increase exports and tariff reduction by
ASEAN countries could also play a vital role to increase preferential tariff utilization.
As a conclusion, the sectoral determinants of AFTA as discussed in the three
industries have shown different results for each industry. This suggests that there is no
“one size fits all” policy that can be effective in increasing Malaysia’s exports to
ASEAN. This result has successfully revealed that AFTA could have different impact
on each industry. The impact of AFTA given the multiple different results by industry
in this study suggest that the value or increase in intra-ASEAN trade is not the only or
ultimate measure of AFTA’s effect.
5.7 Limitations
The limitation of this research is mainly in accessing actual transaction level
data for the preferential tariff utilization. With the limited available data on preferential
tariff utilization and unwillingness of authorities to share the data due to either
confidentiality or lack of transaction level data keeping, this study only used data from
Malaysia. Although Malaysia represents a sample of country with one of the highest
value of intra-regional trade in ASEAN, there were no available data for other countries
or for a longer period of time that could resolve in a more comprehensive analysis. Data
availability is also quite limited at a more disaggregated level.
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The second part of the research is limited to ASEAN-5 countries. The lack of
consistent data from Cambodia, Laos and Myanmar and the possibility of higher AFTA
utilization by ASEAN-5 countries might not have given a full picture of the exact
transitions of these three countries into ASEAN Free Trade Area.
Another area of limitation for the overall research is cross border trade that is
not captured in official data. Most of these ASEAN countries are neighbors and trade
crossing land borders are usually in smaller scale but high in volume. Although there
exist greater intra-regional trade, these numbers that are reported officially might not be
represented by smaller scale trade. This is apparent in the borders of Cambodia, Laos,
Vietnam and Thailand especially in the agriculture sector.
Overall, the research was a policy driven analysis rather than a business driven
analysis. The research does not include and discuss business drivers or determinants
under AFTA but focuses on trade policy under AFTA that will be more useful for
policymakers rather than businesses.
5.8 Further Area of Research
The research can be expanded on the preferential tariff utilization front. There
have been very limited studies that analyze preferential tariff utilization under AFTA.
With a more robust data collection and assistance of ministries and agencies of ASEAN,
the expansion of data would enable a more comprehensive outcome and compare the
level of ASEAN countries’ dependence on AFTA and this would enable countries and
businesses to focus their efforts in areas that would have reasonable benefits.
The analysis on RCA and IIT can also be expanded to include Cambodia
particularly in the textile and clothing industry. Cambodia has increased its market share
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as one of the largest textile and clothing producer in the world. This inclusion would to
certain extent allow a more robust analysis on the textile and clothing industry.
There are also opportunities to further discuss the value chain accumulation
rules strategies in ASEAN by focusing on certain industries and linking the supply
chain of products that are truly produced and completed in ASEAN. With more
available data at disaggregated level, it would enable ASEAN countries to evaluate the
supply chain within ASEAN.
The research also can be further expanded by including China to evaluate the
competitiveness between ASEAN countries and China and how China would have an
impact towards intra ASEAN trade given that ASEAN is also engaged with China in
ASEAN-China Free Trade Area.
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APPENDIX
Table 4.6A: Malaysia-Thailand IIT index for Agriculture, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.613 0.302 0.459 0.490 0.492 0.363 0.381 0.386 0.355 0.386 0.200 0.201 0.274 0.224 0.366
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.811 0.844 0.653 0.934 0.688 0.473 0.798 0.631 0.989 0.621 0.537 0.991 0.848 0.927 0.768
071 Manioc, Frozen Vegetables, Dried Vegetables 0.583 0.329 0.500 0.065 0.301 0.059 0.029 0.079 0.946 0.388 0.352 0.749 0.818 0.710 0.422
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.806 0.342 0.836 0.646 0.968 0.711 0.327 0.585 0.951 0.898 0.444 0.846 0.431 0.371 0.654
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.392 0.960 0.250 0.063 0.281 0.417 0.095 0.292 0.531 0.629 0.382 0.120 0.168 0.242 0.345
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.742 0.759 0.070 0.043 0.079 0.056 0.057 0.136 0.068 0.065 0.091 0.153 0.087 0.097 0.179
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.514 0.343 0.492 0.215 0.274 0.391 0.811 0.400 0.915 0.563 0.784 0.347 0.513 0.296 0.490
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.001 0.001 0.000 0.001 0.004 0.000 0.000 0.001 0.005 0.001 0.001 0.000 0.000 0.001
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.714 0.590 0.443 0.388 0.271 0.172 0.181 0.191 0.153 0.093 0.092 0.076 0.097 0.081 0.253
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.206 0.079 0.386 0.024 0.097 0.100 0.229 0.886 0.372 0.304 0.186 0.094 0.032 0.034 0.216
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.480 0.795 0.719 0.826 0.983 0.898 0.695 0.223 0.939 0.198 0.064 0.137 0.091 0.111 0.511
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.115 0.816 0.800 0.204 0.177 0.813 0.081 0.235 0.311 0.900 0.805 0.791 0.866 0.599 0.537
140 Vegetable Products and Materials 0.621 0.650 0.931 0.789 0.693 0.851 0.305 0.023 0.005 0.004 0.016 0.013 0.023 0.018 0.353
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Table 4.6B: Indonesia-Thailand IIT index for Agriculture, 2001-2014
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.045 0.054 0.125 0.086 0.340 0.240 0.122 0.097 0.461 0.856 0.859 0.448 0.282 0.327 0.310
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.781 0.918 0.545 0.133 0.122 0.566 0.079 0.263 0.567 0.351 0.490 0.641 0.379 0.345 0.441
071 Manioc, Frozen Vegetables, Dried Vegetables 0.017 0.261 0.106 0.322 0.456 0.184 0.378 0.384 0.680 0.985 0.275 0.354 0.752 0.738 0.421
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.458 0.275 0.517 0.269 0.185 0.206 0.000 0.459 0.007 0.322 0.079 0.361 0.168 0.052 0.240
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.000 0.004 0.011 0.016 0.006 0.004 0.008 0.007 0.015 0.010 0.014 0.019 0.008
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.055 0.018 0.022 0.130 0.083 0.080 0.075 0.177 0.025 0.052 0.214 0.196 0.035 0.067 0.088
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.028 0.029 0.071 0.009 0.066 0.216 0.588 0.000 0.338 0.162 0.702 0.099 0.364 0.033 0.193
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.010 0.000 0.000 0.032 0.000 0.000 0.000 0.019 0.027 0.019 0.008 0.014 0.012 0.000 0.010
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.094 0.056 0.010 0.057 0.032 0.045 0.004 0.001 0.004 0.005 0.004 0.009 0.101 0.059 0.034
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.037 0.119 0.253 0.137 0.449 0.170 0.438 0.673 0.634 0.817 0.568 0.353 0.696 0.904 0.446
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.414 0.291 0.523 0.568 0.191 0.537 0.994 0.555 0.258 0.081 0.206 0.896 0.182 0.107 0.415
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.379 0.513 0.507 0.592 0.731 0.407 0.240 0.537 0.565 0.470 0.371 0.139 0.282 0.160 0.421
140 Vegetable Products and Materials 0.000 0.000 0.030 0.000 0.000 0.000 0.002 0.011 0.000 0.000 0.001 0.000 0.000 0.034 0.006
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Table 4.6C: Philippines-Thailand IIT index for Agriculture, 2001-2014
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.020 0.005 0.000 0.006 0.006 0.021 0.063 0.098 0.158 0.206 0.040 0.026 0.046
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.667 0.667 0.000 0.000 0.000 0.000 0.000 0.122 0.000 0.104
071 Manioc, Frozen Vegetables, Dried Vegetables 0.005 0.000 0.000 0.000 0.040 0.015 0.239 0.177 0.071 0.135 0.710 0.836 0.281 0.468 0.213
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.615 0.617 0.667 0.132 0.603 0.942 0.932 0.901 0.354 0.677 0.580 0.612 0.007 0.000 0.546
081 Dried Fruits, Frozen Fruits, Preserved Fruits,Citrus Fruits and Melon Peel 0.349 0.098 0.156 0.201 0.067 0.342 0.044 0.004 0.006 0.000 0.000 0.000 0.006 0.000 0.091
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.174 0.000 0.731 0.000 0.976 0.909 0.671 0.292 0.889 0.211 0.256 0.122 0.094 0.024 0.382
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.753 0.884 0.000 0.000 0.880 0.333 0.776 0.333 0.667 0.158 0.000 0.342
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.005 0.000 0.000 0.003 0.000 0.025 0.003 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.003
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.003 0.032 0.117 0.411 0.612 0.516 0.723 0.329 0.324 0.372 0.244 0.237 0.471 0.314
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.211 0.785 0.873 0.822 0.813 0.742 0.976 0.782 0.808 0.946 0.845 0.890 0.353 0.968 0.772
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.018 0.032 0.000 0.029 0.079 0.022 0.026 0.022 0.636 0.000 0.000 0.000 0.000 0.224 0.078
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.357 0.518 0.354 0.646 0.969 0.925 0.646 0.519 0.845 0.441 0.121 0.198 0.130 0.071 0.481
140 Vegetable Products and Materials 0.000 0.000 0.133 0.000 0.050 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.042 0.169 0.028
Univers
ity of
Mala
ya
226
Table 4.6D: Vietnam-Thailand IIT index for Agriculture, 2001-2014
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.007 0.011 0.000 0.028 0.001 0.007 0.012 0.019 0.057 0.111 0.019
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.717 0.375 0.667 0.375 0.965 0.667 0.909 0.974 0.236 0.789 0.730 0.148 0.052 0.585
071 Manioc, Frozen Vegetables, Dried Vegetables 0.046 0.201 0.132 0.319 0.319 0.482 0.244 0.978 0.699 0.398 0.692 0.991 0.877 0.491
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.000 0.000 0.000 0.130 0.625 0.147 0.214 0.331 0.888 0.591 0.740 0.917 0.768 0.412
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.131 0.101 0.132 0.371 0.430 0.278 0.586 0.426 0.775 0.862 0.434 0.078 0.253 0.374
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.732 0.571 0.219 0.084 0.106 0.102 0.007 0.002 0.070 0.009 0.012 0.116 0.062 0.161
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 0.083 0.412 0.321 0.150 0.207 0.828 0.000 0.952 0.574 0.271
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.912 0.077 0.063 0.093 0.098 0.018 0.008 0.056 0.005 0.006 0.040 0.273 0.178 0.140
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.041 0.657 0.341 0.710 0.262 0.615 0.591 0.997 0.983 0.719 0.289 0.100 0.402 0.516
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.386 0.492 0.515 0.671 0.411 0.543 0.853 0.721 0.992 0.789 0.623 0.466 0.592 0.619
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.364 0.017 0.279 0.169 0.059 0.157 0.279 0.070 0.130 0.214 0.000 0.298 0.337 0.183
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.834 0.950 0.815 0.180 0.429 0.437 0.481 0.942 0.930 0.044 0.275 0.119 0.646 0.545
140 Vegetable Products and Materials 0.764 0.939 0.140 0.730 0.013 0.007 0.064 0.014 0.081 0.160 0.008 0.020 0.012 0.227
Univers
ity of
Mala
ya
227
Table 4.7A: Malaysia-Indonesia IIT index for Agriculture, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.148 0.072 0.315 0.256 0.126 0.405 0.462 0.616 0.977 0.233 0.072 0.488 0.715 0.942 0.416
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.882 0.791 0.973 0.632 0.620 0.885 0.947 0.886 0.852 0.469 0.528 0.828 0.267 0.473 0.717
071 Manioc, Frozen Vegetables, Dried Vegetables 0.827 0.573 0.998 0.858 0.865 0.805 0.386 0.864 0.969 0.982 0.965 0.835 0.830 0.844 0.829
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.676 0.734 0.876 0.752 0.867 0.569 0.615 0.672 0.548 0.667 0.468 0.385 0.230 0.170 0.588
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.173 0.539 0.265 0.691 0.978 0.572 0.722 0.539 0.722 0.594 0.545 0.560 0.450 0.746 0.578
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.109 0.157 0.174 0.232 0.179 0.111 0.126 0.181 0.161 0.133 0.182 0.117 0.143 0.087 0.149
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.219 0.064 0.210 0.049 0.303 0.445 0.149 0.335 0.653 0.390 0.537 0.440 0.357 0.382 0.324
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.167 0.424 0.613 0.510 0.295 0.562 0.028 0.004 0.032 0.039 0.187 0.560 0.033 0.013 0.248
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.148 0.470 0.258 0.345 0.472 0.684 0.918 0.442 0.698 0.258 0.342 0.928 0.446 0.679 0.506
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.655 0.964 0.774 0.856 0.730 0.592 0.956 0.459 0.441 0.424 0.373 0.390 0.503 0.429 0.610
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.156 0.090 0.114 0.019 0.258 0.210 0.033 0.120 0.102 0.432 0.845 0.641 0.339 0.134 0.250
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.212 0.249 0.035 0.091 0.113 0.089 0.307 0.149 0.822 0.438 0.324 0.932 0.965 0.520 0.375
140 Vegetable Products and Materials 0.000 0.000 0.063 0.109 0.111 0.060 0.235 0.026 0.242 0.374 0.888 0.122 0.009 0.004 0.160
Univers
ity of
Mala
ya
228
Table 4.7B: Thailand-Indonesia IIT index for Agriculture, 2001-2014
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.045 0.054 0.125 0.086 0.340 0.240 0.122 0.097 0.461 0.856 0.859 0.448 0.282 0.327 0.310
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.781 0.918 0.545 0.133 0.122 0.566 0.079 0.263 0.567 0.351 0.490 0.641 0.379 0.345 0.441
071 Manioc, Frozen Vegetables, Dried Vegetables 0.017 0.261 0.106 0.322 0.456 0.184 0.378 0.384 0.680 0.985 0.275 0.354 0.752 0.738 0.421
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.458 0.275 0.517 0.269 0.185 0.206 0.000 0.459 0.007 0.322 0.079 0.361 0.168 0.052 0.240
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.000 0.004 0.011 0.016 0.006 0.004 0.008 0.007 0.015 0.010 0.014 0.019 0.008
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.055 0.018 0.022 0.130 0.083 0.080 0.075 0.177 0.025 0.052 0.214 0.196 0.035 0.067 0.088
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.028 0.029 0.071 0.009 0.066 0.216 0.588 0.000 0.338 0.162 0.702 0.099 0.364 0.033 0.193
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.010 0.000 0.000 0.032 0.000 0.000 0.000 0.019 0.027 0.019 0.008 0.014 0.012 0.000 0.010
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.094 0.056 0.010 0.057 0.032 0.045 0.004 0.001 0.004 0.005 0.004 0.009 0.101 0.059 0.034
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.037 0.119 0.253 0.137 0.449 0.170 0.438 0.673 0.634 0.817 0.568 0.353 0.696 0.904 0.446
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.414 0.291 0.523 0.568 0.191 0.537 0.994 0.555 0.258 0.081 0.206 0.896 0.182 0.107 0.415
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.379 0.513 0.507 0.592 0.731 0.407 0.240 0.537 0.565 0.470 0.371 0.139 0.282 0.160 0.421
140 Vegetable Products and Materials 0.000 0.000 0.030 0.000 0.000 0.000 0.002 0.011 0.000 0.000 0.001 0.000 0.000 0.034 0.006
Univers
ity of
Mala
ya
229
Table 4.7C: Philippines-Indonesia IIT index for Agriculture, 2001-2014
HS Product 2001 2002 2003 2004 2005 06 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.200 0.000 0.054 0.133 0.000 0.667 0.000 0.000 0.000 0.000 0.000 0.800 0.000 0.132
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.152 0.009 0.035 0.001 0.030 0.030 0.014 0.086 0.024 0.008 0.066 0.007 0.068 0.093 0.045
071 Manioc, Frozen Vegetables, Dried Vegetables 0.002 0.002 0.000 0.000 0.000 0.008 0.008 0.000 0.000 0.101 0.000 0.010 0.000 0.000 0.009
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.227 0.419 0.129 0.263 0.000 0.111 0.379 0.078 0.514 0.064 0.679 0.688 0.876 0.005 0.317
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.011 0.000 0.000 0.001 0.000 0.001
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 0.033 0.000 0.667 0.000 0.000 0.000 0.600 0.000 0.000 0.000 0.093
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.187 0.163 0.044 0.001 0.012 0.003 0.000 0.351 0.162 0.161 0.321 0.131 0.097 0.067 0.122
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.033 0.000 0.001 0.029 0.235 0.000 0.000 0.000 0.692 0.013 0.000 0.000 0.022 0.073
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.881 0.021 0.034 0.008 0.026 0.034 0.220 0.249 0.071 0.134 0.013 0.014 0.056 0.022 0.127
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.005 0.063 0.216 0.098 0.085 0.144 0.107 0.060 0.001 0.236 0.601 0.200 0.003 0.002 0.130
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.681 0.941 0.755 0.745 0.837 0.853 0.369 0.919 0.260 0.757 0.678 0.161 0.345 0.227 0.609
140 Vegetable Products and Materials 0.000 0.000 0.152 0.000 0.000 0.000 0.000 0.000 0.353 0.235 0.000 0.000 0.000 0.000 0.053
Univers
ity of
Mala
ya
230
Table 4.7D: Vietnam-Indonesia IIT index for Agriculture, 2001-2013
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.737 0.000 0.737 0.245 0.212 0.392 0.064 0.068 0.000 0.056 0.249 0.098 0.527 0.260
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.031 0.008 0.000 0.002 0.000 0.289 0.425 0.048 0.175 0.011 0.023 0.225 0.089 0.102
071 Manioc, Frozen Vegetables, Dried Vegetables 0.002 0.000 0.000 0.829 0.703 0.000 0.272 0.161 0.129 0.024 0.892 0.933 0.172 0.317
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.000 0.013 0.000 0.000 0.000 0.001 0.000 0.096 0.163 0.109 0.660 0.317 0.359 0.132
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.025 0.000 0.821 0.000 0.000 0.338 0.063 0.168 0.341 0.021 0.026 0.114 0.039 0.150
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.049 0.663 0.238 0.489 0.308 0.700 0.490 0.445 0.987 0.559 0.801 0.811 0.455 0.538
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.112 0.179 0.173 0.451 0.000 0.321 0.320 0.000 0.709 0.747 0.001 0.232
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.000 0.009 0.097 0.000 0.002 0.002 0.294 0.485 0.004 0.006 0.038 0.136 0.083
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.000 0.000 0.000 0.794 0.073 0.050 0.034 0.003 0.000 0.937 0.035 0.734 0.205
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.076 0.004 0.003 0.085 0.100 0.264 0.357 0.234 0.198 0.971 0.225 0.000 0.743 0.251
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.000 0.000 0.146 0.000 0.000 0.018 0.000 0.022 0.002 0.003 0.004 0.002 0.099 0.023
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.958 0.945 0.903 0.000 0.000 0.196 0.000 0.027 0.000 0.000 0.000 0.000 0.233
140 Vegetable Products and Materials 0.000 0.000 0.000 0.325 0.000 0.633 0.000 0.229 0.012 0.559 0.000 0.040 0.084 0.145
Univers
ity of
Mala
ya
231
Table 4.8A: Indonesia-Malaysia IIT index for Agriculture, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.148 0.072 0.315 0.256 0.126 0.405 0.462 0.616 0.977 0.233 0.072 0.488 0.715 0.942 0.416
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.882 0.791 0.973 0.632 0.620 0.885 0.947 0.886 0.852 0.469 0.528 0.828 0.267 0.473 0.717
071 Manioc, Frozen Vegetables, Dried Vegetables 0.827 0.573 0.998 0.858 0.865 0.805 0.386 0.864 0.969 0.982 0.965 0.835 0.830 0.844 0.829
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.676 0.734 0.876 0.752 0.867 0.569 0.615 0.672 0.548 0.667 0.468 0.385 0.230 0.170 0.588
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.173 0.539 0.265 0.691 0.978 0.572 0.722 0.539 0.722 0.594 0.545 0.560 0.450 0.746 0.578
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.109 0.157 0.174 0.232 0.179 0.111 0.126 0.181 0.161 0.133 0.182 0.117 0.143 0.087 0.149
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.219 0.064 0.210 0.049 0.303 0.445 0.149 0.335 0.653 0.390 0.537 0.440 0.357 0.382 0.324
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.167 0.424 0.613 0.510 0.295 0.562 0.028 0.004 0.032 0.039 0.187 0.560 0.033 0.013 0.248
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.148 0.470 0.258 0.345 0.472 0.684 0.918 0.442 0.698 0.258 0.342 0.928 0.446 0.679 0.506
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.655 0.964 0.774 0.856 0.730 0.592 0.956 0.459 0.441 0.424 0.373 0.390 0.503 0.429 0.610
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.156 0.090 0.114 0.019 0.258 0.210 0.033 0.120 0.102 0.432 0.845 0.641 0.339 0.134 0.250
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.212 0.249 0.035 0.091 0.113 0.089 0.307 0.149 0.822 0.438 0.324 0.932 0.965 0.520 0.375
140 Vegetable Products and Materials 0.000 0.000 0.063 0.109 0.111 0.060 0.235 0.026 0.242 0.374 0.888 0.122 0.009 0.004 0.160
Univers
ity of
Mala
ya
232
Table 4.8B: Thailand-Malaysia IIT index for Agriculture, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.613 0.302 0.459 0.490 0.492 0.363 0.381 0.386 0.355 0.386 0.200 0.201 0.274 0.224 0.366
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.811 0.844 0.653 0.934 0.688 0.473 0.798 0.631 0.989 0.621 0.537 0.991 0.848 0.927 0.768
071 Manioc, Frozen Vegetables, Dried Vegetables 0.583 0.329 0.500 0.065 0.301 0.059 0.029 0.079 0.946 0.388 0.352 0.749 0.818 0.710 0.422
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.806 0.342 0.836 0.646 0.968 0.711 0.327 0.585 0.951 0.898 0.444 0.846 0.431 0.371 0.654
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.392 0.960 0.250 0.063 0.281 0.417 0.095 0.292 0.531 0.629 0.382 0.120 0.168 0.242 0.345
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.742 0.759 0.070 0.043 0.079 0.056 0.057 0.136 0.068 0.065 0.091 0.153 0.087 0.097 0.179
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.514 0.343 0.492 0.215 0.274 0.391 0.811 0.400 0.915 0.563 0.784 0.347 0.513 0.296 0.490
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.001 0.001 0.000 0.001 0.004 0.000 0.000 0.001 0.005 0.001 0.001 0.000 0.000 0.001
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.714 0.590 0.443 0.388 0.271 0.172 0.181 0.191 0.153 0.093 0.092 0.076 0.097 0.081 0.253
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.206 0.079 0.386 0.024 0.097 0.100 0.229 0.886 0.372 0.304 0.186 0.094 0.032 0.034 0.216
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.480 0.795 0.719 0.826 0.983 0.898 0.695 0.223 0.939 0.198 0.064 0.137 0.091 0.111 0.511
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.115 0.816 0.800 0.204 0.177 0.813 0.081 0.235 0.311 0.900 0.805 0.791 0.866 0.599 0.537
140 Vegetable Products and Materials 0.621 0.650 0.931 0.789 0.693 0.851 0.305 0.023 0.005 0.004 0.016 0.013 0.023 0.018 0.353
Univers
ity of
Mala
ya
233
Table 4.8C: Philippines-Malaysia IIT index for Agriculture, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.593 0.067 0.044 0.000 0.000 0.000 0.000 0.200 1.000 0.000 0.667 0.462 0.148 0.000 0.227
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.313 0.865 0.567 0.075 0.129 0.000 0.000 0.107 0.178 0.912 0.115 0.841 0.158 0.304
071 Manioc, Frozen Vegetables, Dried Vegetables 0.900 0.000 0.000 0.000 0.000 0.391 0.000 0.000 0.333 0.000 0.000 0.000 0.000 0.653 0.163
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.163 0.596 0.143 0.169 0.016 0.563 0.373 0.368 0.436 0.162 0.034 0.014 0.005 0.009 0.218
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 1.000 0.000 0.167 0.029 0.000 0.000 1.000 0.000 0.762 0.000 0.000 0.024 0.286 0.000 0.233
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.148 0.000 0.052 0.015 0.030 0.026 0.005 0.011 0.025 0.189 0.069 0.018 0.095 0.008 0.049
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.271 0.085 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.054 0.000 0.029
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.000 0.000 0.000 0.000 0.800 0.000 0.000 0.000 0.000 0.000 0.000 0.022 0.047 0.062
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.027 0.003 0.007 0.006 0.042 0.005 0.048 0.116 0.260 0.134 0.019 0.103 0.085 0.061
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.033 0.025 0.007 0.005 0.003 0.039 0.297 0.682 0.646 0.319 0.439 0.550 0.990 0.640 0.334
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.035 0.057 0.000 0.232 0.674 0.695 0.005 0.827 0.389 0.495 0.000 0.285 0.950 0.034 0.334
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.988 0.116 0.132 0.228 0.000 0.071 0.085 0.779 0.387 0.325 0.232 0.608 0.321 0.101 0.312
140 Vegetable Products and Materials 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.632 0.076 0.000 0.051
Univers
ity of
Mala
ya
234
Table 4.8D: Vietnam-Malaysia IIT index for Agriculture, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.152 0.000 0.000 0.000 0.000 0.000 0.012
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.073 0.062 0.036 0.025 0.008 0.018 0.017
071 Manioc, Frozen Vegetables, Dried Vegetables 0.007 0.156 0.000 0.108 0.000 0.095 0.021 0.011 0.009 0.476 0.435 0.275 0.199 0.138
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.090 0.014 0.054 0.020 0.021 0.074 0.060 0.281 0.118 0.139 0.208 0.474 0.689 0.172
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.207 0.024 0.000 0.000 0.000 0.000 0.007 0.059 0.020 0.000 0.005 0.044 0.074 0.034
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.004 0.011 0.018 0.087 0.161 0.102 0.109 0.180 0.182 0.137 0.156 0.088
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.133 0.000 0.000 0.194 0.082 0.203 0.140 0.000 0.174 0.437 0.105
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.008 0.000 0.021 0.002 0.001 0.000 0.000 0.000 0.015 0.008 0.006 0.000 0.005
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.343 0.063 0.033 0.391 0.291 0.243 0.088 0.148 0.328 0.175 0.174 0.113 0.099 0.191
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.000 0.018 0.000 0.016 0.006 0.736 0.582 0.910 0.868 0.938 0.679 0.620 0.910 0.483
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.057 0.131 0.122 0.396 0.186 0.119 0.093 0.087 0.228 0.627 0.393 0.985 0.911 0.333
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.000 0.000 0.025 0.438 0.522 0.739 0.571 0.607 0.084 0.034 0.061 0.000 0.237
140 Vegetable Products and Materials 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.012 0.024 0.069 0.000 0.500 0.047
Univers
ity of
Mala
ya
235
Table 4.9A: Malaysia-Philippines IIT index for Agriculture, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.593 0.067 0.044 0.000 0.000 0.000 0.000 0.200 1.000 0.000 0.667 0.462 0.148 0.000 0.227
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.313 0.865 0.567 0.075 0.129 0.000 0.000 0.107 0.178 0.912 0.115 0.841 0.158 0.304
071 Manioc, Frozen Vegetables, Dried Vegetables 0.900 0.000 0.000 0.000 0.000 0.391 0.000 0.000 0.333 0.000 0.000 0.000 0.000 0.653 0.163
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.163 0.596 0.143 0.169 0.016 0.563 0.373 0.368 0.436 0.162 0.034 0.014 0.005 0.009 0.218
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 1.000 0.000 0.167 0.029 0.000 0.000 1.000 0.000 0.762 0.000 0.000 0.024 0.286 0.000 0.233
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.148 0.000 0.052 0.015 0.030 0.026 0.005 0.011 0.025 0.189 0.069 0.018 0.095 0.008 0.049
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.271 0.085 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.054 0.000 0.029
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.000 0.000 0.000 0.000 0.800 0.000 0.000 0.000 0.000 0.000 0.000 0.022 0.047 0.062
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.027 0.003 0.007 0.006 0.042 0.005 0.048 0.116 0.260 0.134 0.019 0.103 0.085 0.061
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.033 0.025 0.007 0.005 0.003 0.039 0.297 0.682 0.646 0.319 0.439 0.550 0.990 0.640 0.334
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.035 0.057 0.000 0.232 0.674 0.695 0.005 0.827 0.389 0.495 0.000 0.285 0.950 0.034 0.334
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.988 0.116 0.132 0.228 0.000 0.071 0.085 0.779 0.387 0.325 0.232 0.608 0.321 0.101 0.312
140 Vegetable Products and Materials 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.632 0.076 0.000 0.051
Univers
ity of
Mala
ya
236
Table 4.9B: Thailand-Philippines IIT index for Agriculture, 2001-2014
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.020 0.005 0.000 0.006 0.006 0.021 0.063 0.098 0.158 0.206 0.040 0.026 0.046
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.667 0.667 0.000 0.000 0.000 0.000 0.000 0.122 0.000 0.104
071 Manioc, Frozen Vegetables, Dried Vegetables 0.005 0.000 0.000 0.000 0.040 0.015 0.239 0.177 0.071 0.135 0.710 0.836 0.281 0.468 0.213
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.615 0.617 0.667 0.132 0.603 0.942 0.932 0.901 0.354 0.677 0.580 0.612 0.007 0.000 0.546
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.349 0.098 0.156 0.201 0.067 0.342 0.044 0.004 0.006 0.000 0.000 0.000 0.006 0.000 0.091
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.174 0.000 0.731 0.000 0.976 0.909 0.671 0.292 0.889 0.211 0.256 0.122 0.094 0.024 0.382
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.753 0.884 0.000 0.000 0.880 0.333 0.776 0.333 0.667 0.158 0.000 0.342
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.005 0.000 0.000 0.003 0.000 0.025 0.003 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.003
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.003 0.032 0.117 0.411 0.612 0.516 0.723 0.329 0.324 0.372 0.244 0.237 0.471 0.314
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.211 0.785 0.873 0.822 0.813 0.742 0.976 0.782 0.808 0.946 0.845 0.890 0.353 0.968 0.772
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.018 0.032 0.000 0.029 0.079 0.022 0.026 0.022 0.636 0.000 0.000 0.000 0.000 0.224 0.078
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.357 0.518 0.354 0.646 0.969 0.925 0.646 0.519 0.845 0.441 0.121 0.198 0.130 0.071 0.481
140 Vegetable Products and Materials 0.000 0.000 0.133 0.000 0.050 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.042 0.169 0.028
Univers
ity of
Mala
ya
237
Table 4.9C: Indonesia-Philippines IIT index for Agriculture, 2001-2014
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.200 0.000 0.054 0.133 0.000 0.667 0.000 0.000 0.000 0.000 0.000 0.800 0.000 0.132
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.152 0.009 0.035 0.001 0.030 0.030 0.014 0.086 0.024 0.008 0.066 0.007 0.068 0.093 0.045
071 Manioc, Frozen Vegetables, Dried Vegetables 0.002 0.002 0.000 0.000 0.000 0.008 0.008 0.000 0.000 0.101 0.000 0.010 0.000 0.000 0.009
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.227 0.419 0.129 0.263 0.000 0.111 0.379 0.078 0.514 0.064 0.679 0.688 0.876 0.005 0.317
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.011 0.000 0.000 0.001 0.000 0.001
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 0.033 0.000 0.667 0.000 0.000 0.000 0.600 0.000 0.000 0.000 0.093
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.187 0.163 0.044 0.001 0.012 0.003 0.000 0.351 0.162 0.161 0.321 0.131 0.097 0.067 0.122
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.033 0.000 0.001 0.029 0.235 0.000 0.000 0.000 0.692 0.013 0.000 0.000 0.022 0.073
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.881 0.021 0.034 0.008 0.026 0.034 0.220 0.249 0.071 0.134 0.013 0.014 0.056 0.022 0.127
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.005 0.063 0.216 0.098 0.085 0.144 0.107 0.060 0.001 0.236 0.601 0.200 0.003 0.002 0.130
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.681 0.941 0.755 0.745 0.837 0.853 0.369 0.919 0.260 0.757 0.678 0.161 0.345 0.227 0.609
140 Vegetable Products and Materials 0.000 0.000 0.152 0.000 0.000 0.000 0.000 0.000 0.353 0.235 0.000 0.000 0.000 0.000 0.053
Univers
ity of
Mala
ya
238
Table 4.9D: Vietnam-Philippines IIT index for Agriculture, 2001-2013
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.000 0.435 0.000 0.000 0.000 0.091 0.032 0.526 0.000 0.000 0.083
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
071 Manioc, Frozen Vegetables, Dried Vegetables 0.462 0.124 0.000 0.000 0.000 0.000 0.000 0.000 0.015 0.024 0.002 0.007 0.000 0.049
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.435 0.531 0.719 0.802 0.823 0.871 0.331 0.009 0.020 0.286 0.189 0.639 0.875 0.502
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.609 0.032 0.000 0.000 0.000 0.000 0.000 0.000 0.726 0.000 0.000 0.105
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 0.732 0.000 0.000 0.000 0.000 0.000 0.508 0.000 0.000 0.095
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.000 0.003 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.001 0.032 0.003
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.004 0.012 0.002 0.000 0.000 0.006 0.000 0.000 0.068 0.239 0.123 0.012 0.017 0.037
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.002 0.000 0.045 0.011 0.008 0.500 0.026 0.000 0.000 0.259 0.270 0.000 0.786 0.147
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.769 0.000 0.000 0.216 0.406 0.075 0.136 0.695 0.636 0.333 0.310 0.341 0.000 0.301
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.000 0.000 0.000 0.033 0.716 0.253 0.152 0.160 0.000 0.000 0.017 0.000 0.102
140 Vegetable Products and Materials 0.000 0.000 0.014 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002
Univers
ity of
Mala
ya
239
Table 4.10A: Malaysia-Vietnam IIT index for Agriculture, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.152 0.000 0.000 0.000 0.000 0.000 0.012
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.073 0.062 0.036 0.025 0.008 0.018 0.017
071 Manioc, Frozen Vegetables, Dried Vegetables 0.007 0.156 0.000 0.108 0.000 0.095 0.021 0.011 0.009 0.476 0.435 0.275 0.199 0.138
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.090 0.014 0.054 0.020 0.021 0.074 0.060 0.281 0.118 0.139 0.208 0.474 0.689 0.172
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.207 0.024 0.000 0.000 0.000 0.000 0.007 0.059 0.020 0.000 0.005 0.044 0.074 0.034
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.004 0.011 0.018 0.087 0.161 0.102 0.109 0.180 0.182 0.137 0.156 0.088
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.133 0.000 0.000 0.194 0.082 0.203 0.140 0.000 0.174 0.437 0.105
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.008 0.000 0.021 0.002 0.001 0.000 0.000 0.000 0.015 0.008 0.006 0.000 0.005
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.343 0.063 0.033 0.391 0.291 0.243 0.088 0.148 0.328 0.175 0.174 0.113 0.099 0.191
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.000 0.018 0.000 0.016 0.006 0.736 0.582 0.910 0.868 0.938 0.679 0.620 0.910 0.483
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.057 0.131 0.122 0.396 0.186 0.119 0.093 0.087 0.228 0.627 0.393 0.985 0.911 0.333
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.000 0.000 0.025 0.438 0.522 0.739 0.571 0.607 0.084 0.034 0.061 0.000 0.237
140 Vegetable Products and Materials 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.012 0.024 0.069 0.000 0.500 0.047
Univers
ity of
Mala
ya
240
Table 4.10B: Thailand-Vietnam IIT index for Agriculture, 2001-2013
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.007 0.011 0.000 0.028 0.001 0.007 0.012 0.019 0.057 0.111 0.019
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.717 0.375 0.667 0.375 0.965 0.667 0.909 0.974 0.236 0.789 0.730 0.148 0.052 0.585
071 Manioc, Frozen Vegetables, Dried Vegetables 0.046 0.201 0.132 0.319 0.319 0.482 0.244 0.978 0.699 0.398 0.692 0.991 0.877 0.491
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.000 0.000 0.000 0.130 0.625 0.147 0.214 0.331 0.888 0.591 0.740 0.917 0.768 0.412
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.131 0.101 0.132 0.371 0.430 0.278 0.586 0.426 0.775 0.862 0.434 0.078 0.253 0.374
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.732 0.571 0.219 0.084 0.106 0.102 0.007 0.002 0.070 0.009 0.012 0.116 0.062 0.161
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 0.083 0.412 0.321 0.150 0.207 0.828 0.000 0.952 0.574 0.271
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.912 0.077 0.063 0.093 0.098 0.018 0.008 0.056 0.005 0.006 0.040 0.273 0.178 0.140
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.041 0.657 0.341 0.710 0.262 0.615 0.591 0.997 0.983 0.719 0.289 0.100 0.402 0.516
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.386 0.492 0.515 0.671 0.411 0.543 0.853 0.721 0.992 0.789 0.623 0.466 0.592 0.619
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.364 0.017 0.279 0.169 0.059 0.157 0.279 0.070 0.130 0.214 0.000 0.298 0.337 0.183
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.834 0.950 0.815 0.180 0.429 0.437 0.481 0.942 0.930 0.044 0.275 0.119 0.646 0.545
140 Vegetable Products and Materials 0.764 0.939 0.140 0.730 0.013 0.007 0.064 0.014 0.081 0.160 0.008 0.020 0.012 0.227
Univers
ity of
Mala
ya
241
Table 4.10C: Indonesia-Vietnam IIT index for Agriculture, 2001-2013
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.737 0.000 0.737 0.245 0.212 0.392 0.064 0.068 0.000 0.056 0.249 0.098 0.527 0.260
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.031 0.008 0.000 0.002 0.000 0.289 0.425 0.048 0.175 0.011 0.023 0.225 0.089 0.102
071 Manioc, Frozen Vegetables, Dried Vegetables 0.002 0.000 0.000 0.829 0.703 0.000 0.272 0.161 0.129 0.024 0.892 0.933 0.172 0.317
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.000 0.013 0.000 0.000 0.000 0.001 0.000 0.096 0.163 0.109 0.660 0.317 0.359 0.132
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.025 0.000 0.821 0.000 0.000 0.338 0.063 0.168 0.341 0.021 0.026 0.114 0.039 0.150
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.049 0.663 0.238 0.489 0.308 0.700 0.490 0.445 0.987 0.559 0.801 0.811 0.455 0.538
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.112 0.179 0.173 0.451 0.000 0.321 0.320 0.000 0.709 0.747 0.001 0.232
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.000 0.009 0.097 0.000 0.002 0.002 0.294 0.485 0.004 0.006 0.038 0.136 0.083
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.000 0.000 0.000 0.794 0.073 0.050 0.034 0.003 0.000 0.937 0.035 0.734 0.205
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.076 0.004 0.003 0.085 0.100 0.264 0.357 0.234 0.198 0.971 0.225 0.000 0.743 0.251
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.000 0.000 0.146 0.000 0.000 0.018 0.000 0.022 0.002 0.003 0.004 0.002 0.099 0.023
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.958 0.945 0.903 0.000 0.000 0.196 0.000 0.027 0.000 0.000 0.000 0.000 0.233
140 Vegetable Products and Materials 0.000 0.000 0.000 0.325 0.000 0.633 0.000 0.229 0.012 0.559 0.000 0.040 0.084 0.145
Univers
ity of
Mala
ya
242
Table 4.10D: Philippines-Vietnam IIT index for Agriculture, 2001-2013
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.000 0.435 0.000 0.000 0.000 0.091 0.032 0.526 0.000 0.000 0.083
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
071 Manioc, Frozen Vegetables, Dried Vegetables 0.462 0.124 0.000 0.000 0.000 0.000 0.000 0.000 0.015 0.024 0.002 0.007 0.000 0.049
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.435 0.531 0.719 0.802 0.823 0.871 0.331 0.009 0.020 0.286 0.189 0.639 0.875 0.502
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.609 0.032 0.000 0.000 0.000 0.000 0.000 0.000 0.726 0.000 0.000 0.105
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 0.732 0.000 0.000 0.000 0.000 0.000 0.508 0.000 0.000 0.095
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.000 0.003 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.001 0.032 0.003
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.004 0.012 0.002 0.000 0.000 0.006 0.000 0.000 0.068 0.239 0.123 0.012 0.017 0.037
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.002 0.000 0.045 0.011 0.008 0.500 0.026 0.000 0.000 0.259 0.270 0.000 0.786 0.147
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.769 0.000 0.000 0.216 0.406 0.075 0.136 0.695 0.636 0.333 0.310 0.341 0.000 0.301
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.000 0.000 0.000 0.033 0.716 0.253 0.152 0.160 0.000 0.000 0.017 0.000 0.102
140 Vegetable Products and Materials 0.000 0.000 0.014 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002
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Table 4.11A : RCA Index for Thailand-Malaysia in Agriculture Industry.
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
060 Cut flowers, Branch, Plants etc. 0.091 0.055 0.058 0.045 0.049 0.046 0.055 0.056 0.062 0.073 0.051 0.054 0.092 0.078 0.062
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips
1.499 1.661 1.861 2.779 1.635 0.861 1.125 1.029 1.403 1.717 1.525 1.127 1.274 1.427 1.494
071 Manioc, Frozen Vegetables, Dried Vegetables 0.083 0.124 0.219 0.263 0.069 0.401 0.470 0.509 0.098 0.125 0.072 0.072 0.047 0.057 0.186
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples
0.350 0.120 0.128 0.062 0.038 0.115 0.099 0.077 0.102 0.081 0.056 0.077 0.053 0.045 0.100
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel
1.046 0.579 0.685 0.347 0.290 0.253 0.206 0.164 0.272 0.240 0.168 0.211 0.226 0.150 0.346
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, V ill
0.301 0.294 0.005 0.004 0.006 0.004 0.003 0.004 0.005 0.004 0.003 0.005 0.003 0.002 0.046
091 Ginger,saffron,turmeric, thyme, bay leaves & curry
0.173 0.322 0.572 0.086 0.094 0.094 0.120 0.075 0.234 0.265 0.254 0.087 0.088 0.113 0.184
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye
3.166 2.268 2.580 2.527 2.156 2.123 2.067 2.600 1.238 0.844 1.171 0.432 0.722 1.341 1.803
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gl t
5.689 5.883 4.233 3.177 4.315 3.617 3.185 3.129 3.484 3.425 3.222 3.075 2.431 3.335 3.729
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 1.266 1.057 0.772 11.815 0.722 2.403 0.865 0.891 0.644 1.125 1.051 2.023 2.380 1.706 2.051
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc.
0.020 0.038 0.087 0.023 0.073 0.265 0.521 0.325 0.055 0.131 0.121 0.231 0.175 0.091 0.154
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams
0.065 0.055 0.042 0.042 0.126 0.031 0.005 0.029 0.034 0.044 0.080 0.070 0.054 0.042 0.051
140 Vegetable Products and Materials 0.107 0.148 0.085 0.107 0.099 0.081 0.101 0.037 0.010 0.009 0.032 0.045 0.030 0.022 0.065
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Table 4.11B: RCA Index for Indonesia-Malaysia in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
060 Cut flowers, Branch, Plants etc. 0.094 0.237 0.125 0.103 0.095 0.120 0.138 0.110 0.085 0.034 0.040 0.250 0.476 0.700 0.186
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips
3.726 6.036 5.755 3.469 2.510 3.169 2.396 2.381 1.469 0.761 0.624 0.869 0.714 0.500 2.456
071 Manioc, Frozen Vegetables, Dried Vegetables 0.176 0.789 0.534 0.462 0.386 0.220 0.251 0.188 0.100 0.089 0.065 0.071 0.070 0.071 0.248
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples
0.167 0.424 0.306 0.489 0.345 0.635 0.439 0.321 0.337 0.318 0.432 0.321 0.438 0.457 0.388
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel
0.239 0.359 0.695 0.488 0.341 0.367 0.296 0.358 0.214 0.216 0.227 0.121 0.192 0.110 0.302
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla
1.396 1.498 1.132 1.275 1.075 1.012 0.952 0.993 0.719 0.858 0.841 0.816 1.144 1.037 1.053
091 Ginger,saffron,turmeric, thyme, bay leaves & curry
2.192 5.948 2.642 6.070 2.611 2.423 1.796 1.259 0.871 1.485 1.831 2.475 2.556 3.723 2.706
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye
0.062 0.134 0.147 0.084 0.151 0.089 0.345 0.200 0.060 0.067 0.001 0.001 0.001 0.001 0.096
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten
0.191 0.907 0.214 2.027 1.277 0.287 0.516 0.663 0.165 0.594 0.436 0.070 0.474 0.411 0.588
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 6.051 5.702 4.934 6.010 11.838 13.875 7.678 2.383 1.756 1.177 0.870 1.125 1.346 1.089 4.702
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc.
0.506 0.595 0.660 0.559 0.441 1.061 1.326 0.952 0.754 0.233 0.243 0.252 0.233 0.437 0.589
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams
0.531 0.445 0.581 0.629 0.800 0.863 0.734 0.895 0.442 0.515 0.477 0.491 0.350 0.478 0.588
140 Vegetable Products and Materials 0.935 1.390 1.776 1.584 1.554 1.483 1.596 1.512 0.698 0.804 0.867 1.536 1.140 0.886 1.269
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Table 4.11C: RCA Index for Philippines-Malaysia in Agriculture Industry.
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
060 Cut flowers, Branch, Plants etc. 0.038 0.127 0.035 0.004 0.000 0.006 0.000 0.001 0.004 0.000 0.014 0.018 0.006 0.000 0.018
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips
0.000 0.035 0.089 0.055 0.011 0.011 0.000 0.000 0.018 0.029 0.376 0.033 0.700 0.445 0.129
071 Manioc, Frozen Vegetables, Dried Vegetables
0.004 0.000 0.001 0.000 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.009 0.001
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples
0.030 0.012 0.013 0.006 0.011 0.039 0.024 0.045 0.141 0.346 0.735 0.594 2.404 2.286 0.478
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel
0.002 0.000 0.004 0.033 0.010 0.001 0.000 0.000 0.012 0.000 0.007 0.035 0.060 0.015 0.013
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg,
0.004 0.000 0.001 0.000 0.001 0.000 0.000 0.000 0.001 0.007 0.005 0.002 0.005 0.001 0.002
091 Ginger,saffron,turmeric, thyme, bay leaves & curry
0.000 0.000 0.000 0.439 0.831 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.005 0.000 0.091
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat,
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.024 0.001 0.002
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour,
0.000 0.007 0.001 0.002 0.001 0.005 0.000 0.006 0.024 0.022 0.045 0.005 0.035 0.024 0.013
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc.
0.513 0.738 0.217 0.321 0.564 0.446 0.988 0.633 0.166 1.979 1.710 2.663 0.515 0.864 0.880
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc.
3.441 1.668 0.040 0.096 0.176 0.610 1.102 0.390 0.015 0.530 1.791 1.099 0.752 0.889 0.900
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams
0.242 0.227 0.086 0.180 0.187 0.145 0.442 0.625 0.499 0.999 1.656 2.721 2.402 6.902 1.237
140 Vegetable Products and Materials 0.000 0.000 0.000 0.000 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.081 2.483 0.000 0.183
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Table 4.11D: RCA Index for Vietnam-Malaysia in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
060 Cut flowers, Branch, Plants etc. 0.092 0.000 0.000 0.000 0.010 0.000 0.000 0.091 0.087 0.000 0.003 0.002 0.026 N/A 0.024
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips
0.666 1.176 1.823 0.573 0.756 0.803 0.860 0.710 1.021 2.725 4.342 3.753 6.304 N/A 1.962
071 Manioc, Frozen Vegetables, Dried Vegetables 0.815 0.323 0.172 0.859 0.885 0.330 0.325 0.441 0.210 0.329 0.189 0.115 0.178 N/A 0.398
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples
0.078 0.391 0.681 0.796 0.407 0.210 0.217 0.223 0.335 0.436 0.406 0.106 0.068 N/A 0.335
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel
0.398 1.005 2.543 1.988 0.937 0.526 0.353 0.194 0.254 0.467 0.270 0.136 0.172 N/A 0.711
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise,
2.060 2.122 2.827 2.406 1.689 3.272 3.171 2.601 2.491 2.799 2.290 1.103 1.007 N/A 2.295
091 Ginger,saffron,turmeric, thyme, bay leaves & curry
0.000 0.000 0.388 0.013 0.177 0.000 0.041 0.008 0.030 0.025 0.000 0.035 0.078 N/A 0.061
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye
10.120 9.474 23.513 12.775 9.816 11.114 6.354 7.101 7.901 5.101 6.220 6.735 3.993 N/A 9.248
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat
0.062 2.262 4.949 1.143 0.866 0.694 2.348 1.406 0.686 1.128 1.040 0.882 0.912 N/A 1.414
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc.
23.369 34.814 36.730 13.235 8.172 2.537 5.018 3.808 2.570 3.515 2.434 0.876 1.902 N/A 10.691
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc.
0.907 2.019 3.410 1.334 1.654 1.451 1.339 0.722 0.436 0.630 0.350 0.079 0.069 N/A 1.108
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams
0.000 0.000 0.000 4.124 0.019 0.055 0.073 0.057 0.099 0.016 0.003 0.000 0.000 N/A 0.342
140 Vegetable Products and Materials 0.075 0.262 0.259 0.741 0.099 0.105 0.107 0.104 0.035 0.145 0.087 0.036 0.013 N/A 0.159
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Table 4.12A: RCA Index for Thailand-Indonesia in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.140 0.193 0.169 0.086 0.078 0.275 0.171 0.109 0.081 0.050 0.056 0.048 0.048 0.066 0.112
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.020 0.029 0.020 0.484 0.288 2.793 4.564 3.145 1.960 1.178 2.713 1.801 1.468 1.692 1.583
071 Manioc, Frozen Vegetables, Dried Vegetables 0.158 0.279 0.197 0.123 0.115 0.234 0.118 0.324 0.175 0.141 0.232 0.158 0.104 0.144 0.179
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.039 0.048 0.046 0.123 0.143 0.212 0.098 0.050 0.062 0.040 0.020 0.016 0.010 0.010 0.066
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 4.137 6.299 6.180 8.422 5.134 8.527 6.778 5.063 6.768 5.828 5.523 3.992 2.520 2.899 5.577
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.006 0.002 0.001 0.007 0.003 0.003 0.002 0.006 0.002 0.003 0.016 0.006 0.010 0.010 0.006
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.109 0.092 0.120 0.010 0.025 0.113 0.026 0.000 0.091 0.005 0.049 0.161 0.006 0.005 0.058
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 5.603 7.475 5.882 1.828 0.712 1.967 2.750 0.755 1.290 1.228 2.955 1.305 0.461 1.551 2.554
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 4.137 3.365 11.182 3.288 6.055 16.452 7.926 4.616 6.192 5.621 6.726 7.303 2.835 5.726 6.530
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 2.644 2.294 2.286 1.980 0.835 6.507 1.791 1.241 1.802 0.834 0.710 0.314 0.513 0.429 1.727
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.032 0.285 0.389 0.049 0.031 0.180 0.344 0.079 0.043 0.008 0.011 0.066 0.011 0.011 0.110
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.190 0.167 0.148 0.099 0.119 0.087 0.053 0.052 0.110 0.067 0.037 0.021 0.033 0.027 0.087
140 Vegetable Products and Materials 0.000 0.000 0.011 0.000 0.000 0.000 0.001 0.010 0.000 0.000 0.002 0.001 0.000 0.106 0.009
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Table 4.12B : RCA Index for Philippines-Indonesia in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.009 0.000 0.006 0.004 0.000 0.008 0.004 0.000 0.000 0.000 0.013 0.010 0.000 0.004
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 7.627 15.849 22.517 17.946 10.050 10.835 6.934 4.213 8.162 9.050 13.453 4.508 3.503 2.397 9.789
071 Manioc, Frozen Vegetables, Dried Vegetables 0.003 0.003 0.000 0.000 0.000 0.035 0.022 0.000 0.000 0.273 0.000 0.017 0.000 0.000 0.025
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.068 0.116 0.159 0.112 0.109 0.145 0.247 0.236 0.306 0.242 0.088 0.104 0.197 0.317 0.175
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.011 0.711 0.014 0.000 0.000 0.053
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.015 0.000 0.000 0.002 0.000 0.001
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 1.144 0.000 0.020 0.000 0.000 0.000 0.041 0.000 0.000 0.000 0.086
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.094 0.065 0.007 0.001 0.004 0.001 0.000 0.130 0.078 0.060 0.042 0.040 0.014 0.037 0.041
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.017 0.000 0.005 0.017 0.006 0.000 0.000 0.000 0.193 0.056 0.000 0.000 0.116 0.029
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.843 0.201 0.105 0.116 0.630 0.413 1.773 0.701 0.720 2.189 0.303 0.376 1.075 0.928 0.741
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.041 0.301 3.014 1.513 1.419 4.772 2.906 3.994 0.031 11.663 18.886 4.336 0.042 0.038 3.783
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 5.406 5.937 3.842 1.747 1.139 2.164 1.111 1.387 0.633 2.932 5.657 9.085 7.981 15.720 4.624
140 Vegetable Products and Materials 0.000 0.000 0.166 0.000 0.000 0.000 0.000 0.000 0.029 0.135 0.000 0.000 0.000 0.000 0.024
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Table 4.12C : RCA Index for Malaysia-Indonesia in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.009 0.010 0.026 0.015 0.007 0.031 0.455 0.256 0.112 0.423 1.705 0.975 0.269 0.789 0.363
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 3.342 4.477 6.058 7.390 5.788 4.034 2.634 3.106 2.745 4.137 2.813 1.552 4.710 1.615 3.886
071 Manioc, Frozen Vegetables, Dried Vegetables 0.141 0.359 0.591 0.341 0.305 0.150 0.060 0.149 0.130 0.143 0.113 0.064 0.051 0.052 0.189
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.097 0.279 0.265 0.290 0.274 0.255 0.193 0.168 0.176 0.264 0.213 0.097 0.058 0.042 0.191
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.026 0.150 0.118 0.254 0.338 0.148 0.166 0.137 0.167 0.152 0.138 0.060 0.057 0.066 0.141
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.092 0.145 0.120 0.165 0.110 0.060 0.063 0.102 0.087 0.101 0.136 0.064 0.089 0.047 0.099
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.307 0.223 0.344 0.150 0.483 0.701 0.143 0.263 0.585 0.598 1.085 0.880 0.565 0.880 0.515
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.006 0.041 0.072 0.028 0.027 0.035 0.005 0.000 0.001 0.002 0.009 0.004 0.050 0.165 0.032
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 2.722 3.350 1.601 0.416 0.409 0.558 0.433 0.195 0.123 0.147 0.146 0.102 0.138 0.212 0.754
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 3.352 6.020 8.685 4.430 7.049 5.897 6.956 8.298 8.616 7.281 6.131 5.853 4.071 3.998 6.188
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.049 0.032 0.044 0.005 0.068 0.125 0.022 0.063 0.056 0.107 0.288 0.150 0.048 0.032 0.078
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.072 0.072 0.012 0.030 0.050 0.041 0.132 0.075 0.428 0.240 0.149 0.541 0.381 0.168 0.171
140 Vegetable Products and Materials 0.000 0.000 0.064 0.090 0.094 0.046 0.210 0.021 7.042 5.810 1.754 0.126 0.005 0.002 1.090
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Table 4.12D: RCA Index for Vietnam-Indonesia in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.059 0.098 0.101 0.426 0.395 0.141 0.023 0.029 0.000 0.057 0.081 0.111 0.142 0.128
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 3.580 4.273 6.265 6.620 10.423 5.101 0.761 20.552 9.894 9.213 15.650 11.255 5.713 8.408
071 Manioc, Frozen Vegetables, Dried Vegetables 2.109 0.046 0.566 0.237 0.081 0.105 0.042 0.118 0.175 0.004 0.040 0.079 0.008 0.278
080
Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.000 0.047 0.000 0.000 0.000 0.002 0.000 0.213 0.610 0.361 0.791 0.389 0.520 0.226
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.002 0.048 0.029 0.055 0.009 0.065 1.029 2.199 1.917 3.296 2.140 1.593 2.054 1.111
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 3.989 2.330 0.576 0.907 0.764 1.313 7.085 1.390 5.242 2.978 2.294 4.088 1.725 2.668
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.627 0.680 1.570 3.763 0.000 0.817 0.998 0.000 0.493 1.205 0.003 0.781
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 22.492 40.949 31.404 3.315 5.051 10.582 27.828 2.594 0.493 14.506 25.498 14.612 3.139 15.574
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.093 0.000 1.303 0.000 0.173 0.432 1.575 0.927 0.810 0.431 0.835 4.366 0.652 0.892
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 52.276 94.828 74.316 17.965 33.240 0.297 10.016 0.409 23.082 3.680 0.122 0.000 0.843 23.929
121
Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.021 0.453 0.241 0.000 0.000 0.049 0.000 0.148 0.036 0.023 0.025 0.008 0.142 0.088
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.263 0.255 0.155 0.000 0.000 0.065 0.000 0.048 0.000 0.000 0.000 0.000 0.060
140 Vegetable Products and Materials 0.000 0.000 0.000 0.280 2.865 2.464 0.000 0.039 0.010 0.450 0.000 0.005 0.159 0.482
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Table 4.13A: RCA Index for Thailand-Philippines in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.444 0.425 0.480 0.446 0.363 0.258 0.257 0.180 0.143 0.125 0.158 0.143 0.239 0.222 0.277
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.035 0.026 0.002 0.001 0.059 0.002 0.044 0.001 0.000 0.001 0.001 0.012
071 Manioc, Frozen Vegetables, Dried Vegetables 0.340 0.677 0.589 0.257 0.129 0.453 0.183 0.242 0.118 0.450 0.099 0.057 0.579 0.027 0.300
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.006 0.006 0.020 0.003 0.087 0.027 0.051 0.041 0.007 0.015 0.024 0.018 0.001 0.000 0.022
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.106 0.273 0.263 0.554 0.362 0.478 0.477 0.593 0.541 0.298 0.370 0.516 0.529 0.099 0.390
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.003 0.001 0.002 0.004 0.002 0.000 0.005 0.003 0.017 0.003 0.008 0.001 0.002 0.000 0.004
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.008 0.008 0.006 0.151 0.106 0.013 0.029 0.033 0.015 0.041 0.027 0.046 0.012 0.019 0.037
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 2.120 2.283 4.075 2.007 1.049 1.340 3.765 5.750 1.473 3.347 1.381 0.500 1.864 4.052 2.500
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 4.874 5.130 2.345 2.850 3.097 2.060 2.220 2.295 3.243 2.429 2.243 1.976 1.849 1.988 2.757
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.568 0.282 0.783 0.307 0.248 0.569 0.803 0.955 0.747 0.835 0.691 0.797 1.217 0.650 0.675
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.017 0.035 0.000 0.046 0.179 0.054 0.056 0.031 0.007 0.000 0.000 0.000 0.000 0.005 0.031
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 1.628 0.663 0.587 0.879 0.928 0.801 0.624 0.672 0.790 0.360 0.181 0.327 0.216 0.154 0.629
140 Vegetable Products and Materials 0.000 0.000 0.042 0.036 0.129 0.000 0.045 0.042 0.009 0.003 0.027 0.053 0.008 0.008 0.029
Univers
ity of
Mala
ya
252
Table 4.13B: RCA Index for Malaysia-Philippines in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.014 0.005 0.001 0.000 0.000 0.000 0.001 0.007 0.003 0.006 0.002 0.002 0.034 0.008 0.006
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.408 0.230 0.116 0.023 0.345 0.196 0.021 0.268 0.214 0.132 0.138 0.161 0.222 1.634 0.293
071 Manioc, Frozen Vegetables, Dried Vegetables 0.004 0.001 0.000 0.002 0.001 0.016 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.001 0.002
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.002 0.036 0.002 0.001 0.000 0.019 0.005 0.007 0.027 0.014 0.004 0.001 0.003 0.003 0.009
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.002 0.003 0.001 0.001 0.000 0.000 0.000 0.001 0.013 0.001 0.000 0.000 0.004 0.000 0.002
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.041 0.039 0.045 0.026 0.041 0.041 0.064 0.043 0.036 0.031 0.042 0.076 0.048 0.063 0.045
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.007 0.023 0.109 0.073 0.046 0.021 0.029 0.341 0.340 0.036 0.067 0.011 0.080 0.081 0.090
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.000 0.001 0.000 0.001 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.007 0.001
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.339 0.600 0.670 0.564 0.338 0.298 0.160 0.155 0.269 0.067 0.195 0.162 0.279 0.175 0.305
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.007 0.011 0.001 0.001 0.001 0.011 0.170 0.822 0.239 0.169 0.148 0.303 0.230 0.128 0.160
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.053 0.060 0.000 0.013 0.111 0.392 0.003 0.185 0.044 0.078 0.000 0.055 0.298 0.005 0.093
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.204 0.017 0.010 0.025 0.000 0.006 0.019 0.268 0.082 0.087 0.067 0.357 0.201 0.116 0.104
140 Vegetable Products and Materials 0.172 0.175 0.034 0.010 0.007 0.000 0.035 0.015 0.041 0.004 0.000 0.011 0.043 0.009 0.040
Univers
ity of
Mala
ya
253
Table 4.13C: RCA Index for Indonesia-Philippines in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.008 0.021 0.254 0.060 0.020 0.000 0.005 0.000 0.000 0.000 0.000 0.000 0.003 0.001 0.027
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.102 0.020 0.126 0.004 0.051 0.043 0.014 0.056 0.016 0.005 0.075 0.004 0.026 0.023 0.040
071 Manioc, Frozen Vegetables, Dried Vegetables 0.659 0.722 0.850 1.361 2.804 2.186 1.473 1.649 1.188 0.722 0.695 0.732 0.788 1.519 1.239
080
Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.086 0.008 0.003 0.005 0.000 0.002 0.016 0.003 0.017 0.001 0.007 0.012 0.053 0.000 0.015
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.100 0.038 0.011 0.004 0.024 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.005 0.023 0.015
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.115 0.334 0.321 0.074 0.473 0.795 1.018 1.119 1.209 0.404 0.153 0.664 0.644 0.248 0.541
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.145 0.610 0.000 0.006 0.016 0.011 0.200 0.050 0.040 0.016 0.066 0.046 0.030 0.088
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.148 0.192 0.101 0.264 0.226 0.149 0.258 0.180 0.141 0.097 0.036 0.131 0.056 0.205 0.156
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.036 0.271 0.048 2.126 0.389 0.012 0.149 0.357 0.044 0.051 1.425 1.877 1.378 1.985 0.725
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.174 5.041 1.876 9.107 15.873 6.243 4.060 1.443 3.124 4.293 7.619 11.98 7.898 16.18 6.780
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 2.700 2.451 7.790 8.932 10.759 15.905 14.482 37.922 9.689 12.29 7.206 8.821 6.340 6.069 10.81
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 1.704 1.386 1.984 0.894 0.531 0.754 1.391 0.479 0.673 0.679 0.476 0.181 0.350 0.392 0.848
140 Vegetable Products and Materials 0.232 0.780 0.633 0.456 0.296 0.086 0.000 0.049 0.022 0.003 0.002 0.027 0.000 0.000 0.185
Univers
ity of
Mala
ya
254
Table 4.13D: RCA Index for Vietnam-Philippines in Agriculture Industry
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.000 0.043 0.045 0.371 0.058 0.249 0.133 0.052 0.011 0.039 0.077
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.007 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001
071 Manioc, Frozen Vegetables, Dried Vegetables 0.012 0.213 0.003 0.000 0.000 0.000 0.000 0.000 0.031 0.371 0.424 0.282 1.212 0.196
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.024 0.119 0.222 0.249 0.133 0.163 0.261 0.281 0.570 0.357 0.357 0.667 0.523 0.302
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.027 0.053 0.002 0.000 0.000 0.001 0.000 0.000 0.030 0.032 0.011 0.048 0.016
090 Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 2.546 6.160 9.180 4.482 4.463 3.277 4.647 2.170 2.791 3.945 4.164 4.262 4.721 4.370
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.143 1.480 1.162 1.501 0.310 0.925 0.417 0.173 0.095 0.080 0.483
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 21.675 24.299 24.815 26.356 48.384 53.190 41.099 34.212 32.332 33.362 18.381 19.086 11.323 29.886
110 Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 3.788 5.210 8.604 3.276 5.045 6.157 6.280 6.596 3.859 1.906 2.932 4.419 4.967 4.849
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 16.602 25.793 19.111 17.994 15.579 0.115 8.241 0.225 0.107 0.396 0.049 0.009 0.054 8.021
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.236 0.297 0.052 0.596 0.639 0.074 0.121 0.203 0.352 0.264 0.209 0.084 0.000 0.241
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.140 0.000 0.000 0.000 0.010 0.559 0.099 0.043 0.060 0.000 0.000 0.008 0.000 0.071
140 Vegetable Products and Materials 0.177 4.075 4.150 2.405 0.327 0.171 0.000 0.000 0.000 0.000 0.000 0.024 0.000 0.872
Univers
ity of
Mala
ya
255
Table 4.14A: RCA Index for Malaysia-Thailand in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.032 0.220 0.164 0.121 0.112 0.163 0.211 0.241 0.260 0.303 0.484 0.489 0.598 0.638 0.288
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.829 1.622 3.232 2.786 2.333 2.176 1.542 2.303 1.296 0.768 0.594 1.130 0.964 1.278 1.632
071 Manioc, Frozen Vegetables, Dried Vegetables 0.163 0.451 0.061 0.008 0.009 0.010 0.006 0.022 0.079 0.030 0.016 0.044 0.070 0.032 0.072
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.421 0.414 0.077 0.026 0.031 0.050 0.018 0.033 0.084 0.099 0.208 0.107 0.197 0.204 0.141
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.207 0.382 0.082 0.010 0.036 0.052 0.009 0.029 0.089 0.110 0.042 0.014 0.021 0.021 0.079
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.144 0.343 0.121 0.175 0.112 0.100 0.093 0.051 0.137 0.126 0.075 0.061 0.059 0.039 0.117
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.405 1.109 0.157 0.009 0.445 0.302 0.160 0.310 0.178 0.103 0.174 0.425 0.263 0.673 0.337
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.001 0.001 0.000 0.001 0.003 0.000 0.000 0.000 0.002 0.001 0.000 0.000 0.000 0.001
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 2.557 1.755 1.013 0.671 0.505 0.267 0.288 0.341 0.261 0.165 0.165 0.124 0.127 0.146 0.599
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.118 0.031 0.155 0.126 0.028 0.099 0.102 0.732 0.133 0.200 0.115 0.102 0.040 0.030 0.144
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.051 0.018 0.041 0.029 0.056 0.255 0.252 0.042 0.056 0.014 0.004 0.017 0.009 0.006 0.061
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.003 0.027 0.024 0.004 0.009 0.016 0.107 0.226 0.165 0.036 0.057 0.108 0.073 0.102 0.069
140 Vegetable Products and Materials 0.039 0.051 0.082 0.062 0.039 0.047 0.509 3.314 3.449 4.828 4.358 6.859 2.628 2.564 2.059
Univers
ity of
Mala
ya
256
Table 4.14B: RCA Index for Indonesia-Thailand in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.004 0.007 0.018 0.006 0.028 0.046 0.018 0.009 0.035 0.060 0.072 0.283 0.524 0.558 0.119
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.039 0.047 0.012 0.056 0.033 1.360 0.300 0.812 1.120 0.404 1.503 1.436 0.615 0.580 0.594
071 Manioc, Frozen Vegetables, Dried Vegetables 0.002 0.057 0.018 0.038 0.060 0.029 0.044 0.132 0.130 0.220 0.063 0.057 0.113 0.139 0.079
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.015 0.010 0.026 0.031 0.026 0.030 0.000 0.025 0.000 0.012 0.846 0.121 0.205 0.635 0.142
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.002 0.026 0.050 0.085 0.032 0.019 0.041 0.032 0.072 0.032 0.033 0.046 0.034
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.276 0.293 0.197 0.163 0.123 0.098 0.101 0.110 0.181 0.170 0.234 0.094 1.005 0.470 0.251
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 9.791 8.477 5.361 3.361 1.302 0.017 0.017 0.073 0.027 0.099 0.153 0.014 0.049 0.444 2.085
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.038 0.001 0.001 0.049 0.000 0.000 0.000 0.013 0.025 0.019 0.021 0.015 0.005 0.000 0.013
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.262 0.134 0.095 0.158 0.171 0.467 0.023 0.005 0.019 0.021 0.022 0.054 0.271 0.286 0.142
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.064 0.198 0.540 0.237 0.426 0.746 0.799 1.074 1.208 1.943 3.060 2.479 1.724 0.856 1.097
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.157 0.066 0.225 0.200 0.526 0.606 0.553 0.353 0.414 0.315 0.157 0.137 0.194 0.306 0.301
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 1.040 0.661 0.712 0.382 0.365 0.422 0.621 0.241 0.403 0.351 0.276 0.484 0.366 0.514 0.488
140 Vegetable Products and Materials 1.106 0.663 1.154 0.771 0.565 1.954 2.624 3.094 3.662 5.634 9.016 8.565 6.478 9.988 3.948
Univers
ity of
Mala
ya
257
Table 4.14C: RCA Index for Philippines-Thailand in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.006 0.002 0.000 0.002 0.002 0.004 0.011 0.018 0.033 0.033 0.013 0.007 0.009
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.006 0.001 0.000 0.000 0.000 0.000 0.000 0.039 0.000 0.003
071 Manioc, Frozen Vegetables, Dried Vegetables 0.001 0.000 0.000 0.000 0.005 0.007 0.052 0.054 0.011 0.089 0.133 0.158 0.247 0.221 0.070
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.012 0.016 0.052 0.072 0.066 0.047 0.122 0.115 0.085 0.083 0.142 0.079 0.380 0.157 0.102
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.019 0.016 0.029 0.107 0.022 0.193 0.022 0.002 0.004 0.000 0.000 0.000 0.004 0.000 0.030
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.005 0.000 0.003 0.001 0.005 0.040 0.051 0.077 0.128 0.043 0.093 0.096 0.039
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.431 0.148 0.000 0.000 0.059 0.189 0.071 0.013 0.184 0.356 0.000 0.104
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.004 0.000 0.000 0.006 0.000 0.034 0.011 0.000 0.005 0.001 0.000 0.000 0.000 0.000 0.004
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.000 0.008 0.050 0.304 1.404 1.778 1.618 2.978 1.558 1.289 1.248 0.545 0.648 1.529 1.068
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.057 0.514 0.797 0.757 0.633 0.658 1.604 1.407 2.695 2.550 2.304 1.975 0.679 1.729 1.311
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 1.616 2.520 4.513 5.504 7.652 9.659 8.954 6.355 0.037 4.496 8.141 2.790 0.093 0.091 4.459
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.301 2.233 3.588 3.168 1.530 1.350 2.738 4.399 2.641 3.494 6.862 5.931 8.089 10.415 4.053
140 Vegetable Products and Materials 0.000 0.005 0.004 0.000 0.006 0.005 0.000 0.000 0.000 0.000 0.000 0.000 0.968 0.221 0.086
Univers
ity of
Mala
ya
258
Table 4.14D: RCA Index for Vietnam-Thailand in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.008 0.009 0.000 0.032 0.002 0.011 0.028 0.025 0.051 0.117 0.022
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.063 0.063 0.024 0.007 0.079 0.160 0.110 0.045 0.036 0.493 0.236 1.898 3.342 0.504
071 Manioc, Frozen Vegetables, Dried Vegetables 0.182 0.399 0.501 0.242 0.175 0.394 0.311 0.295 0.267 0.316 0.193 0.197 0.217 0.284
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.000 0.061 0.178 1.093 1.164 1.568 1.703 1.958 1.681 5.055 2.797 2.644 2.697 1.738
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.069 0.022 0.113 0.420 2.704 6.560 5.983 6.165 2.958 4.553 2.615 1.659 2.377 2.784
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.492 0.207 0.228 0.291 0.092 0.069 0.174 2.845 0.455 2.665 2.402 2.171 1.264 1.027
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 0.011 0.089 0.093 0.069 0.015 0.096 0.000 0.109 0.066 0.042
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.366 0.067 0.053 0.096 0.058 0.027 0.014 0.042 0.011 0.011 0.038 0.118 0.188 0.084
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.038 1.603 1.894 3.364 3.540 2.115 0.960 0.632 0.442 1.940 2.458 2.558 2.384 1.840
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 79.095 72.850 56.962 30.605 23.661 21.798 28.908 16.382 12.359 26.587 9.140 2.744 4.345 29.649
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.045 0.022 0.820 0.504 0.107 0.292 0.586 0.117 0.298 0.572 0.000 0.397 0.441 0.323
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.587 0.757 0.569 0.039 0.019 0.212 0.141 0.389 0.587 0.025 0.093 0.024 0.089 0.272
140 Vegetable Products and Materials 0.911 1.202 1.358 1.089 1.195 2.070 1.022 1.642 0.736 1.017 1.034 1.125 0.936 1.180 Univers
ity of
Mala
ya
259
Table 4.15A: RCA Index for Thailand-Vietnam in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.487 0.422 0.679 0.651 0.628 0.620 0.576 0.691 0.850 0.916 0.721 0.737 0.854 0.853 0.692
070 Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.045 0.003 0.013 0.008 0.027 0.023 0.024 0.012 0.076 0.153 0.037 0.064 0.038 0.030 0.040
071 Manioc, Frozen Vegetables, Dried Vegetables 0.002 0.011 0.009 0.013 0.012 0.036 0.011 0.080 0.040 0.257 0.100 0.082 0.119 0.089 0.062
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.001 0.000 0.000 0.021 0.194 0.036 0.053 0.101 0.377 0.429 0.451 1.323 1.848 1.944 0.484
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.401 0.098 0.423 0.026 0.271 0.308 0.645 0.433 1.313 1.218 2.592 17.21 7.013 9.174 2.938
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.115 0.124 0.007 0.004 0.002 0.001 0.000 0.001 0.005 0.002 0.004 0.056 0.017 0.033 0.027
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.022 0.281 0.317 0.046 0.089 0.099 0.126 0.221 0.037 0.014 0.027 0.042 0.070 0.103 0.107
100 Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.124 0.405 0.437 0.542 0.410 0.862 0.968 0.378 1.123 0.817 0.514 0.317 0.823 0.606 0.595
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.725 0.188 0.103 0.512 0.196 1.382 0.105 0.165 0.120 0.700 0.114 0.057 0.256 0.382 0.358
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 7.654 5.700 5.230 4.277 2.241 16.976 5.591 2.396 3.418 3.505 5.549 3.825 4.420 3.122 5.279
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.082 0.599 1.340 1.514 1.292 0.998 0.938 0.831 1.205 0.967 0.385 0.962 0.930 0.731 0.912
130 Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.170 0.201 0.104 0.109 0.026 0.017 0.116 0.090 0.143 0.227 0.159 0.164 0.080 0.149 0.125
140 Vegetable Products and Materials 0.596 0.326 0.027 0.524 0.003 0.002 0.009 0.003 0.009 0.018 0.001 0.005 0.002 0.000 0.109
Univers
ity of
Mala
ya
260
Table 4.15B: RCA Index for Malaysia-Vietnam in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.033 0.014 0.000 0.000 0.046 0.035 0.006 0.000 0.024 0.000 0.000 0.000 0.000 0.011
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.023 0.025 0.029 0.040 0.017 0.066 0.004 0.015
071 Manioc, Frozen Vegetables, Dried Vegetables 0.002 0.014 0.000 0.027 0.000 0.011 0.002 0.002 0.001 0.061 0.038 0.022 0.023 0.047 0.018
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.003 0.001 0.010 0.004 0.004 0.006 0.004 0.031 0.016 0.019 0.034 0.039 0.042 0.045 0.018
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.033 0.006 0.000 0.000 0.000 0.000 0.001 0.005 0.002 0.000 0.000 0.004 0.008 0.005 0.005
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.000 0.003 0.007 0.014 0.103 0.186 0.118 0.110 0.164 0.166 0.096 0.100 0.166 0.088
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.092 0.000 0.000 0.097 0.000 0.336 0.257 0.157 0.204 0.199 0.296 0.437 0.328 0.133 0.181
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.020 0.000 0.073 0.007 0.002 0.001 0.000 0.000 0.023 0.018 0.025 0.000 0.000 0.012
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.215 0.038 0.046 0.152 0.131 0.066 0.072 0.095 0.103 0.064 0.072 0.062 0.056 0.173 0.096
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.000 0.167 0.000 0.058 0.024 1.022 1.379 2.680 2.563 1.831 3.433 2.296 2.687 1.962 1.436
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.019 0.074 0.122 0.180 0.150 0.063 0.044 0.028 0.043 0.170 0.062 0.090 0.097 0.191 0.095
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.254 0.332 0.090 0.029 0.060 0.108 0.084 0.120 0.173 0.209 0.113 0.018 0.003 0.062 0.118
140 Vegetable Products and Materials 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.468 7.014 1.777 0.000 0.045 0.196 0.964
Univers
ity of
Mala
ya
261
Table 4.15C: RCA Index for Philippines-Vietnam in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.000 0.000 0.000 0.021 0.032 0.000 0.000 0.000 0.048 0.006 0.040 0.000 0.000 0.000 0.011
070
Cabbages, Cauliflowers, Vegetables, Potatoes. Lettuce, Carrots, Turnips 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
071 Manioc, Frozen Vegetables, Dried Vegetables 0.022 0.043 0.000 0.001 0.000 0.000 0.000 0.019 0.001 0.013 0.001 0.003 0.000 0.000 0.007
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, Apples 0.040 1.005 0.928 0.122 0.507 0.467 0.115 0.006 0.023 0.178 0.080 0.988 2.221 1.274 0.568
081
Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus Fruits and Melon Peel 0.000 0.000 0.284 0.094 0.006 0.000 0.000 0.000 0.000 0.000 0.120 0.000 0.000 0.018 0.037
090
Coffee, Tea, Pepper , Capsicum, Cinnamon Flowers, Cloves, Nutmeg, Seeds of Anise, Vanilla 0.000 0.004 0.000 0.000 0.001 0.004 0.000 0.001 0.000 0.000 0.002 0.001 0.000 0.000 0.001
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.000 0.000 0.000 2.275 0.000 0.000 0.000 0.000 0.000 1.086 0.000 0.000 0.000 0.240
100
Maize (corn), Rice, Buckwheat, millet and canary seed, Oats, Barley, Wheat, Rye 0.000 0.003 0.085 0.009 0.004 0.023 0.021 0.018 0.010 0.001 0.018 0.043 0.614 0.675 0.109
110
Starches; inulin,Flour and meal of vegetables, Wheat, Cereal grain, Flour, Malt, Wheat Gluten 0.044 0.096 0.018 0.000 0.000 0.042 0.000 0.000 0.542 0.770 0.411 0.085 0.141 2.623 0.341
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 0.121 0.000 1.033 0.073 0.158 0.085 0.242 0.000 0.000 0.176 0.672 0.000 0.276 1.357 0.299
121 Locust Beans, Medicinal Plants, Swede, Mangolde etc. 0.870 0.000 0.000 0.053 0.434 4.163 3.667 1.810 3.022 3.939 2.439 1.285 0.599 1.779 1.719
130
Vegetable saps & extracts, Lac; natural gums, resins, gum‐resins & balsams 0.000 0.649 0.683 0.487 1.589 2.216 1.521 2.508 2.752 6.945 3.343 2.971 3.890
16.404 3.283
140 Vegetable Products and Materials 0.000 0.000 0.068 0.007 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.011 0.053 0.010
Univers
ity of
Mala
ya
262
Table 4.15D: RCA Index for Indonesia-Vietnam in Agriculture Industry
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
060 Cut flowers, Branch, Plants etc. 0.083 0.000 0.059 0.045 0.032 0.529 0.578 0.368 0.654 1.452 0.570 2.247 0.412 0.425 0.532
070 Cabbages, Cauliflowers, Vegetables, Potatoes. 0.046 0.014 0.000 0.004 0.000 0.783 0.175 0.227 0.493 0.037 0.186 1.481 0.278 0.234 0.283
071 Manioc, Frozen Vegetables, Dried 0.001 0.000 0.000 0.253 0.104 0.000 0.225 0.608 0.006 0.260 0.032 0.072 0.090 1.086 0.195
080 Nuts, Citrus Fruits, Banana, Melons, Grapes, Apricots, 3.137 6.272 6.904 5.613 4.773 6.177 6.986 1.900 3.566 4.606 1.609 2.144 2.478 3.893 4.290
081 Dried Fruits, Frozen Fruits, Preserved Fruits, Citrus 0.141 0.000 0.042 0.000 0.000 0.012 0.029 0.090 0.204 0.026 0.028 0.100 0.043 0.219 0.067
090 Coffee, Tea, Pepper , Capsicum, Cinnamon 0.083 0.976 4.246 2.113 2.902 2.219 1.955 2.181 2.789 5.649 3.443 6.212 6.110 4.363 3.232
091 Ginger,saffron,turmeric, thyme, bay leaves & curry 0.000 0.964 10.542 5.217 11.490 11.781 5.645 1.915 2.720 2.192 0.899 2.094 3.909 9.559 4.923
100 Maize (corn), Rice, Buckwheat, millet and 0.000 0.000 0.148 0.128 0.000 0.009 0.024 0.200 0.082 0.022 0.079 0.291 0.239 0.007 0.088
110 Starches; inulin,Flour and meal of vegetables, 0.000 0.002 0.000 0.824 0.079 0.015 0.034 0.007 0.001 0.000 0.738 0.080 0.394 0.024 0.157
120 Ground Nuts, Seeds, Oil Seeds, Soya Beans etc. 1.705 0.179 0.105 0.604 1.204 1.776 1.852 1.389 1.319 2.556 0.967 1.097 0.519 0.200 1.105
121 Locust Beans, Medicinal Plants, Swede, Mangolde 0.000 0.000 0.019 2.761 1.730 4.799 9.011 5.881 15.309 12.984 11.663 7.271 2.831 5.907 5.726
130 Vegetable saps & extracts, Lac; natural gums, resins, 0.160 0.242 0.228 0.142 0.968 0.855 0.510 1.048 1.821 1.615 1.312 2.756 2.973 3.273 1.279
140 Vegetable Products and Materials 2.965 0.335 0.136 1.091 0.000 1.039 1.027 0.134 0.841 0.129 0.200 0.269 3.769 2.696 1.045
Univers
ity of
Mala
ya
263
Table 4.17A: Thailand-Malaysia IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.350 0.443 0.502 0.405 0.307 0.384 0.286 0.252 0.235 0.261 0.266 0.307 0.377 0.396 0.341
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.995 0.912 0.380 0.312 0.266 0.255 0.433 0.528 0.791 0.454 0.233 0.463 0.217 0.347 0.470
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.239 0.437 0.243 0.284 0.256 0.308 0.452 0.357 0.229 0.289 0.320 0.340 0.320 0.250 0.309
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.17B: Indonesia-Malaysia IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.659 0.629 0.600 0.402 0.279 0.268 0.697 0.610 0.814 0.857 0.992 0.768 0.819 0.601 0.643
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.883 0.808 0.734 0.625 0.690 0.832 0.610 0.564 0.538 0.657 0.581 0.520 0.556 0.540 0.652
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.435 0.339 0.273 0.319 0.447 0.477 0.386 0.421 0.376 0.333 0.307 0.250 0.272 0.281 0.351
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
264
Table 4.17C: Philippines-Malaysia IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.605 0.470 0.397 0.284 0.366 0.393 0.576 0.469 0.665 0.574 0.506 0.722 0.941 0.881 0.561
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.570 0.269 0.274 0.230 0.021 0.155 0.001 0.002 0.050 0.045 0.042 0.060 0.162 0.015 0.135
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.544 0.905 0.750 0.609 0.560 0.455 0.351 0.312 0.643 0.995 0.771 0.914 0.838 0.003 0.618
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.17D: Vietnam-Malaysia IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.327 0.233 0.114 0.093 0.324 0.181 0.112 0.084 0.161 0.330 0.538 0.728 0.625 0.296
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.013 0.032 0.393 0.627 0.936 0.557 0.517 0.598 0.614 0.341 0.303 0.220 0.162 0.409
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.707 0.340 0.270 0.426 0.630 0.471 0.964 0.357 0.463 0.375 0.398 0.404 0.345 0.473
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
265
Table 4.18A: Malaysia-Thailand IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.350 0.443 0.502 0.405 0.307 0.384 0.286 0.252 0.235 0.261 0.266 0.307 0.377 0.396 0.341
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.995 0.912 0.380 0.312 0.266 0.255 0.433 0.528 0.791 0.454 0.233 0.463 0.217 0.347 0.470
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.239 0.437 0.243 0.284 0.256 0.308 0.452 0.357 0.229 0.289 0.320 0.340 0.320 0.250 0.309
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.18B: Indonesia-Thailand IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.616 0.576 0.422 0.422 0.359 0.445 0.358 0.375 0.495 0.430 0.360 0.464 0.460 0.551
0.452
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.227 0.297 0.377 0.429 0.382 0.476 0.183 0.133 0.119 0.267 0.263 0.450 0.443 0.357 0.314
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.397 0.295 0.410 0.591 0.668 0.533 0.785 0.915 0.924 0.875 0.814 0.831 0.696 0.574
0.664
Univers
ity of
Mala
ya
266
Table 4.18C: Philippines-Thailand IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.452 0.386 0.649 0.715 0.842 0.952 0.807 0.865 0.706 0.723 0.801 0.634 0.443 0.400 0.670
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.293 0.273 0.290 0.126 0.030 0.015 0.011 0.026 0.031 0.015 0.022 0.330 0.021 0.095 0.113
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.219 0.107 0.320 0.503 0.527 0.652 0.429 0.076 0.095 0.032 0.037 0.032 0.043 0.004 0.220
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.18D: Vietnam-Thailand IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.027 0.002 0.013 0.259 0.230 0.281 0.204 0.178 0.099 0.136 0.177 0.309 0.213 0.164
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.007 0.045 0.055 0.070 0.108 0.372 0.339 0.247 0.306 0.376 0.321 0.958 0.688 0.299
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.001 0.007 0.021 0.083 0.072 0.105 0.207 0.205 0.159 0.173 0.171 0.255 0.210 0.128
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
267
Table 4.19A: Malaysia-Philippines IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.605 0.470 0.397 0.284 0.366 0.393 0.576 0.469 0.665 0.574 0.506 0.722 0.941 0.881 0.561
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.570 0.269 0.274 0.230 0.021 0.155 0.001 0.002 0.050 0.045 0.042 0.060 0.162 0.015 0.135
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.544 0.905 0.750 0.609 0.560 0.455 0.351 0.312 0.643 0.995 0.771 0.914 0.838 0.003 0.618
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.19B: Thailand-Philippines IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.452 0.386 0.649 0.715 0.842 0.952 0.807 0.865 0.706 0.723 0.801 0.634 0.443 0.400 0.670
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.293 0.273 0.290 0.126 0.030 0.015 0.011 0.026 0.031 0.015 0.022 0.330 0.021 0.095 0.113
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.219 0.107 0.320 0.503 0.527 0.652 0.429 0.076 0.095 0.032 0.037 0.032 0.043 0.004 0.220
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
268
Table 4.19C: Indonesia-Philippines IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.724 0.823 0.962 0.865 0.965 0.703 0.777 0.715 0.631 0.677 0.597 0.407 0.287 0.319 0.675
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.023 0.282 0.348 0.328 0.293 0.145 0.179 0.200 0.362 0.136 0.128 0.113 0.136 0.112 0.199
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.028 0.004 0.042 0.069 0.066 0.015 0.057 0.044 0.022 0.041 0.093 0.072 0.008 0.000 0.040
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.19D: Vietnam-Philippines IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.029 0.024 0.022 0.028 0.023 0.310 0.209 0.164 0.258 0.224 0.175 0.347 0.440 0.173
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.898 0.018 0.002 0.007 0.057 0.009 0.003 0.007 0.002 0.005 0.044 0.014 0.004 0.082
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.823 0.288 0.588 0.999 0.641 0.728 0.613 0.592 0.519 0.304 0.336 0.127 0.031 0.507
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
269
Table 4.19A: Malaysia-Indonesia IIT Index for Automotive Industry, 2001-2014
Table 4.19B: Thailand-Indonesia IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.616 0.576 0.422 0.422 0.359 0.445 0.358 0.375 0.495 0.430 0.360 0.464 0.460 0.551
0.452
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.227 0.297 0.377 0.429 0.382 0.476 0.183 0.133 0.119 0.267 0.263 0.450 0.443 0.357 0.314
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.397 0.295 0.410 0.591 0.668 0.533 0.785 0.915 0.924 0.875 0.814 0.831 0.696 0.574
0.664
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.659 0.629 0.600 0.402 0.279 0.268 0.697 0.610 0.814 0.857 0.992 0.768 0.819 0.601 0.643
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.883 0.808 0.734 0.625 0.690 0.832 0.610 0.564 0.538 0.657 0.581 0.520 0.556 0.540 0.652
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.435 0.339 0.273 0.319 0.447 0.477 0.386 0.421 0.376 0.333 0.307 0.250 0.272 0.281 0.351
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
270
Table 4.19C: Philippines-Indonesia IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.724 0.823 0.962 0.865 0.965 0.703 0.777 0.715 0.631 0.677 0.597 0.407 0.287 0.319 0.675
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.023 0.282 0.348 0.328 0.293 0.145 0.179 0.200 0.362 0.136 0.128 0.113 0.136 0.112 0.199
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.028 0.004 0.042 0.069 0.066 0.015 0.057 0.044 0.022 0.041 0.093 0.072 0.008 0.000 0.040
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.19D: Vietnam-Indonesia IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.006 0.038 0.019 0.240 0.356 0.150 0.242 0.311 0.629 0.649 0.538 1.000 0.726 0.377
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.027 0.010 0.093 0.266 0.253 0.248 0.527 0.579 0.944 0.558 0.740 0.655 0.778 0.437
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.000 0.000 0.032 0.020 0.068 0.143 0.247 0.287 0.447 0.557 0.676 0.972 0.885 0.333
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
271
Table 4.20A: Malaysia-Vietnam IIT Index for Automotive Industry, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.327 0.233 0.114 0.093 0.324 0.181 0.112 0.084 0.161 0.330 0.538 0.728 0.625 0.296
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.013 0.032 0.393 0.627 0.936 0.557 0.517 0.598 0.614 0.341 0.303 0.220 0.162 0.409
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.707 0.340 0.270 0.426 0.630 0.471 0.964 0.357 0.463 0.375 0.398 0.404 0.345 0.473
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.20B: Thailand-Vietnam IIT Index for Automotive Industry, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.027 0.002 0.013 0.259 0.230 0.281 0.204 0.178 0.099 0.136 0.177 0.309 0.213 0.164
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.007 0.045 0.055 0.070 0.108 0.372 0.339 0.247 0.306 0.376 0.321 0.958 0.688 0.299
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.001 0.007 0.021 0.083 0.072 0.105 0.207 0.205 0.159 0.173 0.171 0.255 0.210 0.128
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
272
Table 4.20C: Indonesia-Vietnam IIT Index for Automotive Industry, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.006 0.038 0.019 0.240 0.356 0.150 0.242 0.311 0.629 0.649 0.538 1.000 0.726 0.377
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.027 0.010 0.093 0.266 0.253 0.248 0.527 0.579 0.944 0.558 0.740 0.655 0.778 0.437
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.000 0.000 0.032 0.020 0.068 0.143 0.247 0.287 0.447 0.557 0.676 0.972 0.885 0.333
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.20D: Philippines-Vietnam IIT Index for Automotive Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.029 0.024 0.022 0.028 0.023 0.310 0.209 0.164 0.258 0.224 0.175 0.347 0.440 0.173
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.898 0.018 0.002 0.007 0.057 0.009 0.003 0.007 0.002 0.005 0.044 0.014 0.004 0.082
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.823 0.288 0.588 0.999 0.641 0.728 0.613 0.592 0.519 0.304 0.336 0.127 0.031 0.507
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
273
Table 4.21A: RCA Index of Thailand-Malaysia Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870 Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles 2.011 2.169 1.823 1.781 2.180 1.893 2.071 2.209 2.914 2.600 2.323 2.621 2.348 2.552 2.250
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.601 0.834 1.017 1.001 1.265 1.730 1.543 1.331 1.323 1.044 1.222 1.121 1.623 1.032 1.192
*401 Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber 1.564 1.710 1.670 1.554 1.757 1.704 1.558 1.506 1.569 1.491 1.355 1.592 1.675 1.742 1.603
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.21B: RCA Index of Indonesia-Malaysia Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
1.175 1.126 0.961 1.175 1.942 1.217 0.774 1.082 0.766 0.590 0.511 0.608 0.560 0.617 0.936
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.476 1.191 0.592 0.814 0.850 1.533 0.319 0.288 0.275 1.093 1.263 1.082 0.876 0.838 0.821
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.624 0.892 1.350 1.158 1.089 0.992 0.860 0.850 0.790 0.752 0.728 0.875 0.932 0.856 0.911
Univers
ity of
Mala
ya
274
Table 4.21C: RCA Index of Philippines-Malaysia Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.869 0.734 0.456 0.809 0.564 0.363 0.376 0.452 0.545 0.626 0.862 0.481 0.170 0.470 0.556
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.074 0.024 0.018 0.018 0.002 0.012 0.000 0.000 0.015 0.014 0.023 0.083 0.062 0.010 0.025
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.282 0.281 0.363 0.578 0.459 0.506 0.622 0.930 0.999 1.012 1.233 1.427 0.511 0.001 0.658
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.21D: RCA Index of Vietnam-Malaysia Automotive Industry (2001-2013)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.009 0.017 0.010 0.010 0.014 0.016 0.008 0.007 0.015 0.016 0.023 0.019 0.018 0.014
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.042 0.056 0.795 1.330 1.129 1.538 0.929 0.898 0.817 1.550 1.526 1.156 1.617 1.030
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.192 0.797 0.617 0.598 0.423 0.794 0.802 0.850 0.740 0.946 0.738 0.597 0.575 0.667
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
275
Table 4.22A: The RCA Index of Malaysia-Thailand Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.345 0.440 0.515 0.398 0.296 0.353 0.314 0.328 0.350 0.387 0.379 0.485 0.561 0.654 0.415
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.493 0.499 0.201 0.162 0.145 0.198 0.387 0.493 0.783 0.305 0.171 0.345 0.203 0.224 0.329
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.172 0.341 0.195 0.226 0.193 0.243 0.414 0.338 0.183 0.251 0.274 0.333 0.328 0.258 0.268
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.22B: The RCA Index of Indonesia-Thailand Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.986 1.636 2.323 2.935 2.228 1.742 1.756 2.183 2.291 2.393 1.950 2.816 2.433 2.716 2.170
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.766 1.935 3.143 3.084 3.713 3.223 1.087 0.831 0.711 1.305 1.104 1.582 1.938 1.072 1.821
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
1.054 1.460 1.768 1.398 1.310 1.295 1.338 0.891 0.636 0.544 0.538 0.513 0.472 0.546 0.983
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
276
Table 4.22C: The RCA Index of Philippines-Thailand Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
4.622 9.370 12.271 13.649 11.513 7.965 6.243 7.426 7.846 7.311 6.656 3.974 3.642 3.453 7.567
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.567 0.838 0.953 0.724 0.225 0.127 0.086 0.115 0.177 0.068 0.109 24.591 0.069 0.302 2.068
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.201 0.159 0.450 1.142 1.259 1.624 0.954 0.149 0.249 0.071 0.076 0.054 0.108 0.007 0.465
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.22D: The RCA Index for Vietnam-Thailand Automotive Industry (2001-2013)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.021 0.002 0.009 0.170 0.171 0.238 0.244 0.230 0.238 0.288 0.351 0.296 0.284 0.196
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.183 1.596 1.031 1.015 1.191 4.327 4.812 3.648 4.490 6.588 4.031 6.584 9.573 3.775
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.002 0.022 0.055 0.248 0.160 0.353 0.851 0.717 0.610 0.721 0.539 0.649 0.550 0.421
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
277
Table 4.23A: The RCA Index for Malaysia-Indonesia Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.657 0.585 0.458 0.291 0.326 0.190 0.410 0.493 0.730 0.736 0.812 0.478 0.394 0.266 0.488
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.686 0.915 1.136 1.764 1.673 1.103 0.721 0.760 1.038 0.889 0.835 0.479 0.342 0.311 0.904
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.197 0.206 0.237 0.216 0.325 0.314 0.204 0.235 0.254 0.250 0.213 0.158 0.149 0.140 0.221
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.23B: The RCA Index for Thailand-Indonesia Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
1.729 2.954 5.321 6.756 5.779 4.927 5.071 5.534 4.827 5.426 5.188 5.516 4.536 4.345 4.851
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 4.663 8.108 8.270 6.947 8.932 8.363 6.803 6.820 7.816 5.262 4.265 3.221 3.794 3.001 6.162
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.204 0.185 0.280 0.361 0.372 0.381 0.543 0.619 0.378 0.435 0.458 0.427 0.493 0.824 0.426
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
278
Table 4.23C: The RCA index of Philippines-Indonesia Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
9.747 9.210 8.214 6.779 5.809 3.746 3.920 3.616 5.338 5.508 5.148 2.832 1.996 3.538 5.386
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.383 1.387 1.369 1.010 1.008 1.142 0.902 1.931 3.163 2.920 2.272 1.211 1.217 1.329 1.517
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.247 0.033 0.280 0.344 0.215 0.056 0.116 0.089 0.126 0.256 0.314 0.252 0.032 0.000 0.168
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.23D: The RCA index of Vietnam-Indonesia Automotive Industry (2001-2013)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.003 0.018 0.010 0.215 0.303 0.168 0.196 0.446 0.615 0.369 0.224 0.287 0.263 0.240
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.074 0.078 0.424 1.243 0.889 0.346 0.605 0.896 1.830 1.741 2.466 1.401 1.833 1.063
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.000 0.000 0.020 0.011 0.050 0.072 0.108 0.233 0.300 0.261 0.278 0.424 0.401 0.166
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
279
Table 4.24A: The RCA Index for Malaysia-Philippines Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.325 0.274 0.193 0.143 0.157 0.107 0.150 0.093 0.187 0.113 0.090 0.082 0.084 0.117 0.151
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.161 0.186 0.197 0.149 0.244 0.177 0.410 0.241 0.415 0.278 0.326 0.803 0.308 0.417 0.308
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.091 0.283 0.373 0.270 0.221 0.179 0.131 0.115 0.326 0.459 0.238 0.361 0.311 0.292 0.261
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.24B: The RCA Index for Thailand-Philippines Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
1.585 1.904 4.485 4.418 4.770 4.473 4.402 4.247 5.887 4.713 4.085 4.312 4.912 5.544 4.267
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 3.888 4.506 4.274 6.251 8.280 8.591 7.215 3.788 4.592 3.273 4.104 2.446 2.517 2.429 4.725
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
1.925 2.409 1.799 1.977 2.008 1.712 1.670 1.637 2.035 1.579 1.650 1.686 1.862 1.507 1.818
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
280
Table 4.24C: The RCA Index of Indonesia-Philippines Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
2.796 3.461 2.774 1.570 1.820 1.791 1.744 1.909 1.843 1.521 1.981 2.511 2.510 3.631 2.276
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 5.252 2.223 2.034 1.565 1.967 3.793 2.597 5.088 2.275 5.637 5.447 4.577 3.521 4.379 3.597
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
2.795 4.420 4.072 2.910 2.100 1.865 1.111 1.165 1.801 1.726 1.058 1.522 1.600 1.757 2.136
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.24D: The RCA Index of Vietnam-Philippines Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.005 0.012 0.008 0.010 0.009 0.095 0.083 0.046 0.092 0.093 0.111 0.077 0.052 0.053
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.043 3.537 10.436 10.546 8.413 4.948 5.549 2.955 3.939 6.117 5.910 3.482 3.980 5.374
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.170 0.445 0.633 0.512 0.190 0.368 0.526 0.190 0.247 0.327 0.371 0.387 0.547 0.378
Univers
ity of
Mala
ya
281
Table 4.25A: RCA Index of Malaysia-Vietnam Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.034 0.067 0.092 0.108 0.065 0.109 0.094 0.128 0.130 0.049 0.046 0.039 0.046 0.074 0.077
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 4.502 1.810 1.789 1.596 1.138 0.410 0.217 0.323 0.277 0.188 0.197 0.168 0.168 0.229 0.929
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.075 0.086 0.053 0.089 0.173 0.169 0.576 0.156 0.171 0.129 0.133 0.178 0.141 0.101 0.159
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.25B: RCA Index of Thailand-Vietnam Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.616 0.512 0.364 0.316 0.481 0.422 0.559 0.609 1.289 0.801 0.992 0.685 1.018 1.319 0.713
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 22.155 16.709 9.699 7.770 7.610 5.495 6.128 6.712 6.995 5.752 5.795 2.562 2.144 1.815 7.667
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
1.906 1.440 1.398 1.581 1.567 1.846 1.914 1.631 1.983 1.543 1.588 1.884 2.005 2.042 1.738
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
282
Table 4.25C: RCA Index of Indonesia-Vietnam Automotive Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
0.905 0.770 1.020 1.188 0.966 1.887 1.207 1.088 0.695 0.566 0.610 0.298 0.481 0.552 0.874
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 4.474 13.622 8.681 6.096 4.241 2.225 1.438 0.988 0.849 3.313 4.209 2.981 3.004 3.259 4.241
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
1.092 0.911 1.208 0.789 0.984 0.853 0.653 0.625 0.541 0.498 0.545 0.416 0.527 0.542 0.727
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Table 4.25D: RCA Index of Philippines-Vietnam Automotive Industry (2001-2013)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Average
870
Tractors, Public Transport Vehicles, Cars, Trucks, Special Purpose Vehicles, Chassis, Body for Motor Vehicles
1.845 3.073 1.620 0.532 2.147 1.147 1.567 2.465 2.501 2.199 2.463 1.154 0.612 1.450 1.770
871 Motorcycles, Bicycles, Motorcycle Accessories, Trailers, Semi‐Trailers 0.207 0.100 0.024 0.027 0.654 0.047 0.018 0.050 0.016 0.043 0.286 0.075 0.023 0.008 0.113
*401
Conveyor or Transmission Belts, New Pneumatic Rubber Tyres, Retreaded/Used Tyres, Inner tubes of Rubber
0.701 0.229 0.617 0.375 1.073 0.466 0.514 0.378 0.346 0.175 0.160 0.082 0.028 0.000 0.368
* Consist of 4011, 4012 and 4013 relevant to Automotive Industry
Univers
ity of
Mala
ya
283
Table 4.27A: Thailand-Malaysia IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.500 0.000 0.000 0.000 0.545 0.047 0.157 0.011 0.027 0.073 0.260 0.095 0.067 0.127
500 Raw silk and silk yarn 0.051 0.381 0.000 0.000 0.000 0.065 0.000 0.028 0.422 0.181 0.000 0.160 0.000 0.250 0.110
510 Raw wool, wool yarn and animal hairs 0.150 0.146 0.078 0.129 0.053 0.967 0.067 0.059 0.085 0.434 0.197 0.167 0.022 0.007 0.183
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.421 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.030
520 Cotton, cotton yarn and woven cotton 0.361 0.390 0.256 0.239 0.299 0.051 0.055 0.161 0.160 0.253 0.789 0.288 0.493 0.815 0.329
521 Woven fabrics of cotton 0.754 0.469 0.415 0.440 0.862 0.650 0.328 0.483 0.787 0.343 0.928 0.617 0.991 0.686 0.625
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.061 0.171 0.045 0.133 0.066 0.000 0.000 0.640 0.969 0.913 0.114 0.771 0.000 0.277
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.432 0.845 0.734 0.701 0.783 0.765 0.677 0.985 0.853 0.886 0.935 0.855 0.917 0.822 0.799
550 Synthetic and artificial: filament tow, staple fibres 0.660 0.581 0.174 0.116 0.102 0.207 0.412 0.465 0.439 0.295 0.778 0.887 0.820 0.758 0.478
551 Staple fibre; man made yarn, woven fabrics 0.919 0.906 0.515 0.320 0.410 0.762 0.569 0.863 0.614 0.732 0.949 0.617 0.999 0.185 0.669
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.554 0.888 0.679 0.774 0.906 0.937 0.901 0.822 0.791 0.825 0.905 0.879 0.884 0.861 0.829
570 Carpets and other textile floor covering 0.395 0.605 0.207 0.170 0.171 0.290 0.141 0.138 0.184 0.219 0.223 0.181 0.102 0.130 0.225
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.075 0.135 0.517 0.558 0.730 0.378 0.221 0.118 0.143 0.237 0.152 0.201 0.114 0.450 0.288
581 Embroidery in the piece of strips or in motifs 0.000 0.011 0.000 0.011 0.000 0.000 0.355 0.015 0.051 0.441 0.164 0.283 0.221 0.157 0.122
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.056 0.041 0.048 0.139 0.106 0.087 0.095 0.097 0.078 0.077 0.170 0.308 0.430 0.349 0.149
591 Transmission or conveyor belts; text prod & articles for tech use 0.406 0.661 0.654 0.425 0.964 0.867 0.988 0.944 0.875 0.971 0.953 0.971 0.938 0.777 0.814
600 Fabrics, knitted/crocheted 0.021 0.104 0.112 0.108 0.158 0.031 0.149 0.392 0.284 0.552 0.613 0.610 0.147 0.242 0.252
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.382 0.582 0.665 0.662 0.774 0.847 0.972 0.630 0.414 0.340 0.434 0.461 0.443 0.424 0.574
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.337 0.302 0.471 0.656 0.730 0.908 0.708 0.892 0.879 0.930 0.526 0.515 0.789 0.456 0.650
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.331 0.307 0.378 0.237 0.417 0.464 0.381 0.444 0.415 0.321 0.476 0.623 0.908 0.887 0.471
Univers
ity of
Mala
ya
284
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.739 0.536 0.601 0.902 0.846 0.977 0.836 0.919 0.594 0.423 0.447 0.315 0.437 0.699 0.662
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.447 0.266 0.630 0.821 0.533 0.646 0.911 0.820 0.519 0.908 0.901 0.910 0.816 0.936 0.719
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.123 0.000 0.017 0.132 0.070 0.000 0.112 0.007 0.004 0.054 0.199 0.433 0.082
640 Footwear 0.842 0.966 0.658 0.486 0.675 0.533 0.514 0.441 0.515 0.503 0.473 0.451 0.506 0.703 0.590
650 Hat and Headgear etc 0.610 0.157 0.209 0.813 0.938 0.426 0.474 0.371 0.650 0.675 0.935 0.753 0.840 0.760 0.615
Table 4.27B: Indonesia-Malaysia IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.571 0.000 0.000 0.000 0.000 0.000 0.364 0.000 0.067
500 Raw silk and silk yarn 0.000 0.909 0.000 0.019 0.424 0.417 0.176 0.000 0.184 0.930 0.000 0.561 0.000 0.000 0.259
510 Raw wool, wool yarn and animal hairs 0.009 0.838 0.017 0.990 0.313 0.117 0.059 0.061 0.060 0.042 0.026 0.000 0.003 0.010 0.182
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.545 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.039
520 Cotton, cotton yarn and woven cotton 0.317 0.330 0.288 0.258 0.394 0.396 0.480 0.681 0.972 0.867 0.584 0.213 0.429 0.868 0.505
521 Woven fabrics of cotton 0.845 0.508 0.735 0.522 0.825 0.684 0.622 0.674 0.570 0.866 0.798 0.851 0.634 0.544 0.691
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.227 0.667 0.000 0.000 0.000 0.677 0.000 0.796 0.258 0.395 0.707 0.995 0.800 0.311 0.417
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.061 0.031 0.041 0.208 0.226 0.216 0.268 0.401 0.479 0.428 0.723 0.898 0.761 0.718 0.390
550 Synthetic and artificial: filament tow, staple fibres 0.516 0.611 0.688 0.568 0.563 0.416 0.488 0.708 0.850 0.875 0.628 0.812 0.775 0.970 0.676
551 Staple fibre; man made yarn, woven fabrics 0.236 0.190 0.152 0.315 0.239 0.253 0.303 0.410 0.221 0.073 0.177 0.500 0.406 0.167 0.260
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.537 0.946 0.783 0.761 0.799 0.928 0.961 0.894 0.828 0.778 0.588 0.582 0.488 0.382 0.732
570 Carpets and other textile floor covering 0.070 0.269 0.092 0.115 0.472 0.884 0.629 0.538 0.408 0.509 0.478 0.428 0.257 0.222 0.384
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.427 0.649 0.440 0.854 0.987 0.339 0.391 0.403 0.245 0.175 0.257 0.319 0.410 0.511 0.458
581 Embroidery in the piece of strips or in motifs 0.063 0.048 0.099 0.321 0.369 0.881 0.882 0.421 0.077 0.034 0.993 0.814 0.020 0.008 0.359
Univers
ity of
Mala
ya
285
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.144 0.161 0.161 0.163 0.251 0.430 0.307 0.300 0.534 0.725 0.543 0.750 0.776 0.896 0.439
591 Transmission or conveyor belts; text prod & articles for tech use 0.267 0.482 0.295 0.013 0.000 0.000 0.058 0.062 0.005 0.042 0.001 0.002 0.018 0.001 0.089
600 Fabrics, knitted/crocheted 0.278 0.912 0.690 0.918 0.308 0.380 0.245 0.189 0.296 0.395 0.216 0.435 0.563 0.476 0.450
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.120 0.146 0.152 0.331 0.212 0.128 0.032 0.818 0.241 0.286 0.417 0.720 0.263 0.273 0.296
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.520 0.297 0.721 0.461 0.525 0.739 0.487 0.967 0.775 0.918 0.715 0.657 0.782 0.876 0.674
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.121 0.041 0.012 0.027 0.037 0.088 0.159 0.224 0.057 0.054 0.086 0.129 0.108 0.074 0.087
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.882 0.910 0.375 0.143 0.160 0.582 0.067 0.095 0.105 0.120 0.146 0.160 0.088 0.273 0.293
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.770 0.893 0.588 0.956 0.937 0.766 0.930 0.756 0.723 0.714 0.557 0.623 0.460 0.277 0.711
631 Rags, scrap twine, cordage, rope 0.375 0.435 0.099 0.089 0.036 0.716 0.004 0.012 0.012 0.121 0.516 0.016 0.050 0.033 0.179
640 Footwear 0.119 0.119 0.134 0.215 0.378 0.623 0.404 0.666 0.977 0.906 0.897 0.820 0.850 0.660 0.555
650 Hat and Headgear etc 0.779 0.936 0.865 0.427 0.297 0.321 0.152 0.159 0.174 0.354 0.417 0.199 0.398 0.245 0.409
Univers
ity of
Mala
ya
286
Table 4.27C: Philippines-Malaysia IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.267 0.000 0.019
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.338 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.024
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.222 0.656 0.903 0.894 0.778 0.978 0.262 0.377 0.000 0.918 0.055 0.000 0.000 0.106 0.439
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.006 0.060 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.005
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.068 0.000 0.000 0.000 0.333 0.000 0.222 0.000 0.117 0.000 0.053
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.297 0.119 0.038 0.021 0.033 0.001 0.009 0.001 0.001 0.000 0.000 0.000 0.001 0.000 0.037
550 Synthetic and artificial: filament tow, staple fibres 0.584 0.954 0.946 0.927 0.751 0.265 0.316 0.116 0.853 0.320 0.845 0.598 0.945 0.529 0.639
551 Staple fibre; man made yarn, woven fabrics 0.039 0.049 0.000 0.002 0.449 0.186 0.093 0.000 0.029 0.000 0.504 0.000 0.000 0.000 0.096
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.241 0.563 0.795 0.853 0.598 0.627 0.239 0.161 0.169 0.100 0.060 0.127 0.052 0.101 0.335
570 Carpets and other textile floor covering 0.045 0.085 0.109 0.095 0.034 0.000 0.000 0.000 0.000 0.046 0.000 0.213 0.000 0.129 0.054
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.248 0.547 0.630 0.374 0.629 0.355 0.378 0.377 0.103 0.808 0.757 0.484 0.187 0.000 0.420
581 Embroidery in the piece of strips or in motifs 0.632 0.000 0.000 0.000 0.000 0.000 0.103 0.649 0.000 0.000 0.000 0.381 0.000 0.200 0.140
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.016 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.513 0.000 0.000 0.030 0.000 0.017 0.041
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.036 0.094 0.148 0.013 0.000 0.000 0.021
600 Fabrics, knitted/crocheted 0.053 0.114 0.115 0.302 0.204 0.153 0.465 0.731 0.411 0.000 0.000 0.000 0.649 0.115 0.237
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.305 0.903 0.706 0.672 0.858 0.541 0.785 0.849 0.715 0.728 0.729 0.815 0.747 0.824 0.727
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.414 0.405 0.868 0.429 0.861 0.587 0.869 0.704 0.387 0.320 0.997 0.430 0.405 0.111 0.556
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.217 0.453 0.238 0.315 0.035 0.022 0.356 0.795 0.619 0.241 0.172 0.508 0.824 0.550 0.382
Univers
ity of
Mala
ya
287
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.196 0.266 0.801 0.492 0.160 0.590 0.874 0.347 0.730 0.044 0.865 0.632 0.933 0.562 0.535
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.247 0.425 0.272 0.304 0.533 0.120 0.100 0.161 0.161 0.122 0.123 0.074 0.123 0.341 0.222
631 Rags, scrap twine, cordage, rope 0.083 0.059 0.273 0.021 0.163 0.449 0.875 0.533 0.270 0.606 0.208 0.000 0.126 0.015 0.263
640 Footwear 0.371 0.610 0.021 0.040 0.051 0.122 0.091 0.245 0.234 0.062 0.161 0.152 0.881 0.922 0.283
650 Hat and Headgear etc 0.818 0.417 0.625 0.769 0.308 0.933 0.522 0.162 0.364 0.000 0.057 0.333 0.915 0.078 0.450
Table 4.27D: Vietnam-Malaysia IIT Index for Textile and Clothing Industry, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.167 0.118 0.838 0.948 0.568 0.409 0.566 0.335 0.286 0.420 0.918 0.582 0.985 0.549
521 Woven fabrics of cotton 0.063 0.005 0.081 0.002 0.058 0.001 0.003 0.016 0.025 0.003 0.000 0.001 0.000 0.020
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.000 0.500 0.000 0.790 0.000 0.000 0.000 0.800 0.161
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.046 0.077 0.076 0.116 0.154 0.195 0.284 0.534 0.397 0.374 0.225 0.337 0.436 0.250
550 Synthetic and artificial: filament tow, staple fibres 0.915 0.300 0.628 0.647 0.663 0.661 0.402 0.888 0.742 0.790 0.825 0.409 0.608 0.652
551 Staple fibre; man made yarn, woven fabrics 0.343 0.457 0.503 0.154 0.116 0.213 0.312 0.259 0.259 0.249 0.023 0.072 0.003 0.228
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.096 0.102 0.333 0.255 0.210 0.043 0.213 0.247 0.140 0.262 0.344 0.477 0.354 0.237
570 Carpets and other textile floor covering 0.387 0.114 0.014 0.027 0.000 0.051 0.038 0.000 0.399 0.708 0.720 0.405 0.580 0.265
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.352 0.543 0.776 0.829 0.538 0.832 0.410 0.379 0.152 0.433 0.442 0.149 0.028 0.451
581 Embroidery in the piece of strips or in motifs 0.733 0.324 0.383 0.759 0.200 0.000 0.000 0.125 0.000 0.000 0.000 0.173 0.049 0.211
Univers
ity of
Mala
ya
288
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.630 0.965 0.682 0.529 0.882 0.337 0.266 0.252 0.238 0.141 0.200 0.284 0.326 0.441
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.040 0.003 0.782 0.683 0.153 0.000 0.000 0.004 0.035 0.000 0.003 0.010 0.132
600 Fabrics, knitted/crocheted 0.267 0.249 0.449 0.434 0.193 0.341 0.183 0.348 0.376 0.744 0.482 0.376 0.297 0.364
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.004 0.086 0.004 0.039 0.031 0.026 0.100 0.101 0.089 0.156 0.202 0.444 0.462 0.134
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.027 0.039 0.199 0.102 0.747 0.323 0.417 0.157 0.273 0.400 0.746 0.313 0.630 0.336
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.001 0.000 0.001 0.011 0.010 0.017 0.050 0.410 0.100 0.066 0.027 0.042 0.141 0.067
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.250 0.153 0.062 0.429 0.326 0.424 0.331 0.434 0.779 0.954 0.450 0.337 0.355 0.406
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.028 0.069 0.146 0.671 0.620 0.321 0.338 0.588 0.991 0.908 0.594 0.754 0.571 0.508
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.000 0.000 0.000 0.059 0.000 0.070 0.000 0.200 0.116 0.000 0.034
640 Footwear 0.091 0.007 0.042 0.108 0.080 0.040 0.064 0.203 0.144 0.191 0.134 0.154 0.200 0.112
650 Hat and Headgear etc 0.455 0.000 0.140 0.655 0.545 0.867 0.336 0.708 0.314 0.783 0.519 0.589 0.519 0.495
Univers
ity of
Mala
ya
289
Table 4.28A: Malaysia-Thailand IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.500 0.000 0.000 0.000 0.545 0.047 0.157 0.011 0.027 0.073 0.260 0.095 0.067 0.127
500 Raw silk and silk yarn 0.051 0.381 0.000 0.000 0.000 0.065 0.000 0.028 0.422 0.181 0.000 0.160 0.000 0.250 0.110
510 Raw wool, wool yarn and animal hairs 0.150 0.146 0.078 0.129 0.053 0.967 0.067 0.059 0.085 0.434 0.197 0.167 0.022 0.007 0.183
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.421 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.030
520 Cotton, cotton yarn and woven cotton 0.361 0.390 0.256 0.239 0.299 0.051 0.055 0.161 0.160 0.253 0.789 0.288 0.493 0.815 0.329
521 Woven fabrics of cotton 0.754 0.469 0.415 0.440 0.862 0.650 0.328 0.483 0.787 0.343 0.928 0.617 0.991 0.686 0.625
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.061 0.171 0.045 0.133 0.066 0.000 0.000 0.640 0.969 0.913 0.114 0.771 0.000 0.277
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.432 0.845 0.734 0.701 0.783 0.765 0.677 0.985 0.853 0.886 0.935 0.855 0.917 0.822 0.799
550 Synthetic and artificial: filament tow, staple fibres 0.660 0.581 0.174 0.116 0.102 0.207 0.412 0.465 0.439 0.295 0.778 0.887 0.820 0.758 0.478
551 Staple fibre; man made yarn, woven fabrics 0.919 0.906 0.515 0.320 0.410 0.762 0.569 0.863 0.614 0.732 0.949 0.617 0.999 0.185 0.669
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.554 0.888 0.679 0.774 0.906 0.937 0.901 0.822 0.791 0.825 0.905 0.879 0.884 0.861 0.829
570 Carpets and other textile floor covering 0.395 0.605 0.207 0.170 0.171 0.290 0.141 0.138 0.184 0.219 0.223 0.181 0.102 0.130 0.225
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.075 0.135 0.517 0.558 0.730 0.378 0.221 0.118 0.143 0.237 0.152 0.201 0.114 0.450 0.288
581 Embroidery in the piece of strips or in motifs 0.000 0.011 0.000 0.011 0.000 0.000 0.355 0.015 0.051 0.441 0.164 0.283 0.221 0.157 0.122
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.056 0.041 0.048 0.139 0.106 0.087 0.095 0.097 0.078 0.077 0.170 0.308 0.430 0.349 0.149
591 Transmission or conveyor belts; text prod & articles for tech use 0.406 0.661 0.654 0.425 0.964 0.867 0.988 0.944 0.875 0.971 0.953 0.971 0.938 0.777 0.814
600 Fabrics, knitted/crocheted 0.021 0.104 0.112 0.108 0.158 0.031 0.149 0.392 0.284 0.552 0.613 0.610 0.147 0.242 0.252
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.382 0.582 0.665 0.662 0.774 0.847 0.972 0.630 0.414 0.340 0.434 0.461 0.443 0.424 0.574
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.337 0.302 0.471 0.656 0.730 0.908 0.708 0.892 0.879 0.930 0.526 0.515 0.789 0.456 0.650
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.331 0.307 0.378 0.237 0.417 0.464 0.381 0.444 0.415 0.321 0.476 0.623 0.908 0.887 0.471
Univers
ity of
Mala
ya
290
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.739 0.536 0.601 0.902 0.846 0.977 0.836 0.919 0.594 0.423 0.447 0.315 0.437 0.699 0.662
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.447 0.266 0.630 0.821 0.533 0.646 0.911 0.820 0.519 0.908 0.901 0.910 0.816 0.936 0.719
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.123 0.000 0.017 0.132 0.070 0.000 0.112 0.007 0.004 0.054 0.199 0.433 0.082
640 Footwear 0.842 0.966 0.658 0.486 0.675 0.533 0.514 0.441 0.515 0.503 0.473 0.451 0.506 0.703 0.590
650 Hat and Headgear etc 0.610 0.157 0.209 0.813 0.938 0.426 0.474 0.371 0.650 0.675 0.935 0.753 0.840 0.760 0.615
Table 4.28B: Indonesia-Thailand IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.857 0.000 0.175 0.000 0.000 0.000 0.000 0.000 0.000 0.074
500 Raw silk and silk yarn 0.067 0.333 0.833 0.353 0.079 0.175 0.278 0.500 0.658 0.059 0.000 0.000 0.441 0.085 0.276
510 Raw wool, wool yarn and animal hairs 0.023 0.000 0.036 0.593 0.014 0.077 0.065 0.544 0.591 0.000 0.000 0.000 0.000 0.000 0.139
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.004 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.995 0.988 0.844 0.707 0.904 0.881 0.618 0.977 0.870 0.962 0.855 0.833 0.790 0.737 0.854
521 Woven fabrics of cotton 0.876 0.708 0.870 0.838 0.672 0.739 0.644 0.782 0.994 0.933 0.979 0.726 0.992 0.397 0.797
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.741 0.805 0.000 0.414 0.351 0.000 0.000 0.827 0.000 0.000 0.051 0.966 0.381 0.000 0.324
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.150 0.184 0.290 0.310 0.315 0.357 0.399 0.447 0.523 0.552 0.571 0.811 0.605 0.665 0.441
550 Synthetic and artificial: filament tow, staple fibres 0.275 0.272 0.249 0.218 0.225 0.274 0.195 0.296 0.270 0.254 0.328 0.422 0.439 0.448 0.297
551 Staple fibre; man made yarn, woven fabrics 0.475 0.400 0.424 0.614 0.442 0.515 0.594 0.589 0.487 0.419 0.352 0.699 0.811 0.868 0.549
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.360 0.122 0.205 0.158 0.119 0.284 0.210 0.130 0.180 0.087 0.123 0.168 0.142 0.148 0.174
570 Carpets and other textile floor covering 0.826 0.756 0.520 0.666 0.884 0.908 0.576 0.852 0.860 0.674 0.807 0.805 0.577 0.824 0.753
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.680 0.520 0.406 0.845 0.900 0.903 0.890 0.849 0.978 0.894 0.975 0.921 0.694 0.608 0.790
581 Embroidery in the piece of strips or in motifs 0.183 0.291 0.774 0.296 0.228 0.351 0.540 0.730 0.904 0.664 0.133 0.208 0.436 0.376 0.437
Univers
ity of
Mala
ya
291
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.392 0.352 0.491 0.878 0.715 0.998 0.578 0.756 0.836 0.559 0.909 0.910 0.279 0.282 0.638
591 Transmission or conveyor belts; text prod & articles for tech use 0.852 0.057 0.411 0.156 0.272 0.680 0.245 0.429 0.899 0.768 0.880 0.504 0.815 0.870 0.560
600 Fabrics, knitted/crocheted 0.882 0.343 0.565 0.434 0.418 0.322 0.488 0.487 0.585 0.632 0.421 0.445 0.493 0.460 0.498
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.573 0.643 0.959 0.827 0.827 0.984 0.926 0.718 0.697 0.994 0.713 0.634 0.917 0.681 0.792
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.689 0.563 0.456 0.132 0.523 0.821 0.794 0.931 0.920 0.818 0.822 0.965 0.547 0.750 0.695
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.972 0.809 0.866 0.592 0.919 0.503 0.463 0.344 0.363 0.360 0.517 0.489 0.365 0.696 0.590
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.908 0.466 0.399 0.541 0.358 0.485 0.846 0.284 0.557 0.251 0.290 0.382 0.442 0.359 0.469
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.433 0.796 0.698 0.686 0.470 0.511 0.424 0.580 0.450 0.347 0.543 0.590 0.383 0.451 0.526
631 Rags, scrap twine, cordage, rope 0.667 0.000 0.000 0.000 0.250 0.359 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.091
640 Footwear 0.111 0.155 0.303 0.112 0.353 0.487 0.493 0.455 0.489 0.301 0.827 0.783 0.437 0.344 0.404
650 Hat and Headgear etc 0.773 0.413 0.055 0.079 0.218 0.238 0.768 0.576 0.500 0.083 0.308 0.636 0.633 0.272 0.396
Univers
ity of
Mala
ya
292
Table 4.28C: Philippines-Thailand IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.040 0.000 0.081 0.000 0.000 0.013 0.000 0.000 0.200 0.000 0.000 0.190 0.000 0.000 0.037
510 Raw wool, wool yarn and animal hairs 0.000 0.017 0.749 0.361 0.043 0.066 0.064 0.229 0.000 0.000 0.000 0.000 0.000 0.000 0.109
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.071
520 Cotton, cotton yarn and woven cotton 0.041 0.417 0.222 0.284 0.116 0.154 0.003 0.000 0.000 0.033 0.069 0.000 0.000 0.000 0.096
521 Woven fabrics of cotton 0.017 0.000 0.037 0.016 0.012 0.006 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.006
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.909 0.000 0.000 0.629 0.917 0.000 0.542 0.000 0.000 0.000 0.138 0.000 0.541 0.262
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.154 0.000 0.011
540 Man‐made:filaments yarn and synthetic yarn 0.000 0.004 0.009 0.004 0.011 0.001 0.000 0.002 0.000 0.001 0.000 0.000 0.002 0.001 0.002
550 Synthetic and artificial: filament tow, staple fibres 0.031 0.027 0.018 0.007 0.006 0.002 0.015 0.031 0.011 0.044 0.051 0.040 0.028 0.011 0.023
551 Staple fibre; man made yarn, woven fabrics 0.000 0.002 0.002 0.000 0.000 0.002 0.000 0.000 0.019 0.063 0.278 0.803 0.122 0.000 0.092
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.810 0.308 0.350 0.209 0.125 0.072 0.007 0.006 0.014 0.006 0.039 0.019 0.064 0.024 0.147
570 Carpets and other textile floor covering 0.000 0.000 0.077 0.291 0.137 0.082 0.094 0.031 0.000 0.014 0.004 0.004 0.000 0.006 0.053
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.532 0.704 0.964 0.475 0.399 0.462 0.687 0.453 0.348 0.303 0.223 0.410 0.620 0.607 0.513
581 Embroidery in the piece of strips or in motifs 0.004 0.028 0.002 0.008 0.003 0.000 0.002 0.000 0.001 0.007 0.000 0.000 0.000 0.000 0.004
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.000 0.000 0.000 0.000 0.140 0.000 0.211 0.027 0.164 0.041 0.550 0.121 0.948 0.001 0.157
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.255 0.000 0.000 0.780 0.447 0.340 0.014 0.000 0.000 0.131
600 Fabrics, knitted/crocheted 0.641 0.102 0.104 0.071 0.177 0.085 0.139 0.142 0.030 0.002 0.000 0.001 0.009 0.000 0.107
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.004 0.003 0.003 0.024 0.151 0.022 0.056 0.129 0.268 0.104 0.176 0.148 0.690 0.349 0.152
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.000 0.000 0.000 0.571 0.037 0.004 0.080 0.032 0.071 0.102 0.378 0.116 0.579 0.380 0.168
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.006 0.120 0.096 0.056 0.039 0.045 0.406 0.069 0.102 0.073 0.094 0.153 0.292 0.029 0.113
Univers
ity of
Mala
ya
293
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.035 0.031 0.022 0.036 0.069 0.082 0.527 0.965 0.683 0.070 0.241 0.999 0.590 0.230 0.327
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.805 0.562 0.986 0.625 0.552 0.747 0.904 0.988 0.260 0.075 0.031 0.518 0.634 0.890 0.613
631 Rags, scrap twine, cordage, rope 1.000 0.000 0.269 0.010 0.020 0.009 0.020 0.000 0.144 0.527 0.143 0.007 0.000 0.000 0.154
640 Footwear 0.019 0.022 0.018 0.026 0.018 0.022 0.028 0.103 0.107 0.122 0.063 0.032 0.099 0.129 0.058
650 Hat and Headgear etc 0.000 0.000 0.204 0.000 0.316 0.006 0.094 0.033 0.068 0.000 0.000 0.000 0.023 0.351 0.078
Table 4.28D: Vietnam-Thailand IIT Index for Textile and Clothing Industry, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.852 0.759 0.062 0.123 0.329 0.057 0.466 0.784 0.800 0.506 0.000 0.222 0.000 0.382
500 Raw silk and silk yarn 0.129 0.041 0.142 0.212 0.240 0.276 0.750 0.732 0.452 0.077 0.224 0.156 0.042 0.267
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.200 0.000 0.000 0.000 0.000 0.000 0.000 0.834 0.262 0.100
520 Cotton, cotton yarn and woven cotton 0.205 0.428 0.364 0.086 0.135 0.271 0.168 0.581 0.289 0.790 0.726 0.587 0.310 0.380
521 Woven fabrics of cotton 0.033 0.055 0.059 0.142 0.101 0.214 0.117 0.058 0.057 0.029 0.027 0.047 0.009 0.073
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.130 0.000 0.000 0.340 0.000 0.000 0.000 0.000 0.036
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.248 0.078 0.106 0.179 0.839 0.875 0.990 0.986 0.924 0.887 0.955 0.898 0.761 0.671
550 Synthetic and artificial: filament tow, staple fibres 0.832 0.717 0.450 0.137 0.124 0.336 0.098 0.147 0.124 0.234 0.253 0.219 0.152 0.294
551 Staple fibre; man made yarn, woven fabrics 0.117 0.118 0.056 0.025 0.003 0.010 0.033 0.063 0.081 0.096 0.049 0.102 0.047 0.062
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.016 0.138 0.024 0.018 0.004 0.054 0.053 0.052 0.151 0.129 0.081 0.105 0.117 0.072
570 Carpets and other textile floor covering 0.889 0.067 0.023 0.020 0.011 0.034 0.006 0.018 0.022 0.018 0.036 0.049 0.028 0.094
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.072 0.132 0.225 0.183 0.124 0.156 0.183 0.253 0.110 0.135 0.141 0.192 0.150 0.158
581 Embroidery in the piece of strips or in motifs 0.000 0.020 0.014 0.000 0.140 0.650 0.677 0.543 0.204 0.015 0.002 0.000 0.000 0.174
Univers
ity of
Mala
ya
294
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.113 0.050 0.039 0.146 0.129 0.496 0.892 0.904 0.498 0.519 0.528 0.698 0.528 0.426
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.518 0.000 0.046 0.023 0.502 0.520 0.496 0.362 0.959 0.263
600 Fabrics, knitted/crocheted 0.001 0.022 0.009 0.030 0.040 0.402 0.140 0.125 0.082 0.118 0.211 0.177 0.257 0.124
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.520 0.690 0.331 0.441 0.587 0.861 0.642 0.833 0.875 0.598 0.848 0.638 0.539 0.646
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.429 0.729 0.540 0.506 0.323 0.477 0.921 0.601 0.779 0.789 0.904 0.638 0.999 0.664
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.451 0.704 0.981 0.353 0.858 0.885 0.906 0.781 0.675 0.585 0.636 0.857 0.900 0.736
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.284 0.960 0.747 0.170 0.287 0.643 0.659 0.534 0.580 0.463 0.459 0.582 0.837 0.554
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.360 0.080 0.091 0.079 0.171 0.222 0.120 0.237 0.190 0.201 0.519 0.454 0.376 0.238
631 Rags, scrap twine, cordage, rope 0.024 0.000 0.286 0.480 0.000 0.000 0.571 0.103 0.029 0.000 0.643 0.000 0.005 0.165
640 Footwear 0.414 0.442 0.600 0.792 0.765 0.680 0.725 0.519 0.806 0.826 0.551 0.475 0.417 0.616
650 Hat and Headgear etc 0.214 0.185 0.706 0.263 0.689 0.886 0.048 0.985 0.644 0.894 0.982 0.840 0.683 0.617
Univers
ity of
Mala
ya
295
Table 4.29A: Malaysia-Indonesia IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.571 0.000 0.000 0.000 0.000 0.000 0.364 0.000 0.067
500 Raw silk and silk yarn 0.000 0.909 0.000 0.019 0.424 0.417 0.176 0.000 0.184 0.930 0.000 0.561 0.000 0.000 0.259
510 Raw wool, wool yarn and animal hairs 0.009 0.838 0.017 0.990 0.313 0.117 0.059 0.061 0.060 0.042 0.026 0.000 0.003 0.010 0.182
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.545 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.039
520 Cotton, cotton yarn and woven cotton 0.317 0.330 0.288 0.258 0.394 0.396 0.480 0.681 0.972 0.867 0.584 0.213 0.429 0.868 0.505
521 Woven fabrics of cotton 0.845 0.508 0.735 0.522 0.825 0.684 0.622 0.674 0.570 0.866 0.798 0.851 0.634 0.544 0.691
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.227 0.667 0.000 0.000 0.000 0.677 0.000 0.796 0.258 0.395 0.707 0.995 0.800 0.311 0.417
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.061 0.031 0.041 0.208 0.226 0.216 0.268 0.401 0.479 0.428 0.723 0.898 0.761 0.718 0.390
550 Synthetic and artificial: filament tow, staple fibres 0.516 0.611 0.688 0.568 0.563 0.416 0.488 0.708 0.850 0.875 0.628 0.812 0.775 0.970 0.676
551 Staple fibre; man made yarn, woven fabrics 0.236 0.190 0.152 0.315 0.239 0.253 0.303 0.410 0.221 0.073 0.177 0.500 0.406 0.167 0.260
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.537 0.946 0.783 0.761 0.799 0.928 0.961 0.894 0.828 0.778 0.588 0.582 0.488 0.382 0.732
570 Carpets and other textile floor covering 0.070 0.269 0.092 0.115 0.472 0.884 0.629 0.538 0.408 0.509 0.478 0.428 0.257 0.222 0.384
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.427 0.649 0.440 0.854 0.987 0.339 0.391 0.403 0.245 0.175 0.257 0.319 0.410 0.511 0.458
581 Embroidery in the piece of strips or in motifs 0.063 0.048 0.099 0.321 0.369 0.881 0.882 0.421 0.077 0.034 0.993 0.814 0.020 0.008 0.359
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.144 0.161 0.161 0.163 0.251 0.430 0.307 0.300 0.534 0.725 0.543 0.750 0.776 0.896 0.439
591 Transmission or conveyor belts; text prod & articles for tech use 0.267 0.482 0.295 0.013 0.000 0.000 0.058 0.062 0.005 0.042 0.001 0.002 0.018 0.001 0.089
600 Fabrics, knitted/crocheted 0.278 0.912 0.690 0.918 0.308 0.380 0.245 0.189 0.296 0.395 0.216 0.435 0.563 0.476 0.450
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.120 0.146 0.152 0.331 0.212 0.128 0.032 0.818 0.241 0.286 0.417 0.720 0.263 0.273 0.296
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.520 0.297 0.721 0.461 0.525 0.739 0.487 0.967 0.775 0.918 0.715 0.657 0.782 0.876 0.674
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.121 0.041 0.012 0.027 0.037 0.088 0.159 0.224 0.057 0.054 0.086 0.129 0.108 0.074 0.087
Univers
ity of
Mala
ya
296
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.882 0.910 0.375 0.143 0.160 0.582 0.067 0.095 0.105 0.120 0.146 0.160 0.088 0.273 0.293
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.770 0.893 0.588 0.956 0.937 0.766 0.930 0.756 0.723 0.714 0.557 0.623 0.460 0.277 0.711
631 Rags, scrap twine, cordage, rope 0.375 0.435 0.099 0.089 0.036 0.716 0.004 0.012 0.012 0.121 0.516 0.016 0.050 0.033 0.179
640 Footwear 0.119 0.119 0.134 0.215 0.378 0.623 0.404 0.666 0.977 0.906 0.897 0.820 0.850 0.660 0.555
650 Hat and Headgear etc 0.779 0.936 0.865 0.427 0.297 0.321 0.152 0.159 0.174 0.354 0.417 0.199 0.398 0.245 0.409
Table 4.29B: Thailand-Indonesia IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.857 0.000 0.175 0.000 0.000 0.000 0.000 0.000 0.000 0.074
500 Raw silk and silk yarn 0.067 0.333 0.833 0.353 0.079 0.175 0.278 0.500 0.658 0.059 0.000 0.000 0.441 0.085 0.276
510 Raw wool, wool yarn and animal hairs 0.023 0.000 0.036 0.593 0.014 0.077 0.065 0.544 0.591 0.000 0.000 0.000 0.000 0.000 0.139
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.004 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.995 0.988 0.844 0.707 0.904 0.881 0.618 0.977 0.870 0.962 0.855 0.833 0.790 0.737 0.854
521 Woven fabrics of cotton 0.876 0.708 0.870 0.838 0.672 0.739 0.644 0.782 0.994 0.933 0.979 0.726 0.992 0.397 0.797
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.741 0.805 0.000 0.414 0.351 0.000 0.000 0.827 0.000 0.000 0.051 0.966 0.381 0.000 0.324
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.150 0.184 0.290 0.310 0.315 0.357 0.399 0.447 0.523 0.552 0.571 0.811 0.605 0.665 0.441
550 Synthetic and artificial: filament tow, staple fibres 0.275 0.272 0.249 0.218 0.225 0.274 0.195 0.296 0.270 0.254 0.328 0.422 0.439 0.448 0.297
551 Staple fibre; man made yarn, woven fabrics 0.475 0.400 0.424 0.614 0.442 0.515 0.594 0.589 0.487 0.419 0.352 0.699 0.811 0.868 0.549
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.360 0.122 0.205 0.158 0.119 0.284 0.210 0.130 0.180 0.087 0.123 0.168 0.142 0.148 0.174
570 Carpets and other textile floor covering 0.826 0.756 0.520 0.666 0.884 0.908 0.576 0.852 0.860 0.674 0.807 0.805 0.577 0.824 0.753
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.680 0.520 0.406 0.845 0.900 0.903 0.890 0.849 0.978 0.894 0.975 0.921 0.694 0.608 0.790
581 Embroidery in the piece of strips or in motifs 0.183 0.291 0.774 0.296 0.228 0.351 0.540 0.730 0.904 0.664 0.133 0.208 0.436 0.376 0.437
Univers
ity of
Mala
ya
297
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.392 0.352 0.491 0.878 0.715 0.998 0.578 0.756 0.836 0.559 0.909 0.910 0.279 0.282 0.638
591 Transmission or conveyor belts; text prod & articles for tech use 0.852 0.057 0.411 0.156 0.272 0.680 0.245 0.429 0.899 0.768 0.880 0.504 0.815 0.870 0.560
600 Fabrics, knitted/crocheted 0.882 0.343 0.565 0.434 0.418 0.322 0.488 0.487 0.585 0.632 0.421 0.445 0.493 0.460 0.498
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.573 0.643 0.959 0.827 0.827 0.984 0.926 0.718 0.697 0.994 0.713 0.634 0.917 0.681 0.792
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.689 0.563 0.456 0.132 0.523 0.821 0.794 0.931 0.920 0.818 0.822 0.965 0.547 0.750 0.695
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.972 0.809 0.866 0.592 0.919 0.503 0.463 0.344 0.363 0.360 0.517 0.489 0.365 0.696 0.590
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.908 0.466 0.399 0.541 0.358 0.485 0.846 0.284 0.557 0.251 0.290 0.382 0.442 0.359 0.469
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.433 0.796 0.698 0.686 0.470 0.511 0.424 0.580 0.450 0.347 0.543 0.590 0.383 0.451 0.526
631 Rags, scrap twine, cordage, rope 0.667 0.000 0.000 0.000 0.250 0.359 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.091
640 Footwear 0.111 0.155 0.303 0.112 0.353 0.487 0.493 0.455 0.489 0.301 0.827 0.783 0.437 0.344 0.404
650 Hat and Headgear etc 0.773 0.413 0.055 0.079 0.218 0.238 0.768 0.576 0.500 0.083 0.308 0.636 0.633 0.272 0.396
Univers
ity of
Mala
ya
298
Table 4.29C: Philippines-Indonesia IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
510 Raw wool, wool yarn and animal hairs 0.000 0.333 0.000 0.000 0.000 0.531 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.062
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.018 0.176 0.138 0.128 0.209 0.242 0.329 0.009 0.000 0.000 0.013 0.064 0.002 0.000 0.095
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.011 0.199 0.750 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.697 0.822 0.177
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.101 0.026 0.010 0.016 0.020 0.014 0.002 0.126 0.003 0.000 0.000 0.001 0.000 0.000 0.023
550 Synthetic and artificial: filament tow, staple fibres 0.008 0.004 0.089 0.017 0.051 0.032 0.053 0.036 0.000 0.000 0.000 0.005 0.000 0.000 0.021
551 Staple fibre; man made yarn, woven fabrics 0.000 0.000 0.008 0.002 0.000 0.032 0.004 0.000 0.000 0.000 0.016 0.019 0.005 0.004 0.006
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.799 0.975 0.363 0.311 0.046 0.081 0.193 0.160 0.127 0.117 0.602 0.983 0.876 0.640 0.448
570 Carpets and other textile floor covering 0.000 0.000 0.005 0.011 0.003 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.010 0.010 0.003
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.408 0.151 0.365 0.829 0.957 0.699 0.422 0.607 0.131 0.098 0.860 0.539 0.285 0.070 0.459
581 Embroidery in the piece of strips or in motifs 0.817 0.044 0.168 0.205 0.000 0.667 0.471 0.082 0.000 0.742 0.779 0.000 0.000 0.000 0.284
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.036 0.000 0.001 0.000 0.011 0.009 0.002 0.002 0.205 0.000 0.000 0.160 0.061 0.000 0.035
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.358 0.000 0.000 0.026
600 Fabrics, knitted/crocheted 0.164 0.440 0.071 0.121 0.107 0.361 0.352 0.131 0.051 0.065 0.000 0.042 0.087 0.000 0.142
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.184 0.003 0.062 0.595 0.082 0.977 0.710 0.686 0.250 0.219 0.358 0.365 0.828 0.506 0.416
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.463 0.000 0.771 0.859 0.260 0.048 0.114 0.086 0.075 0.206 0.116 0.130 0.387 0.046 0.254
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.349 0.269 0.618 0.499 0.596 0.739 0.710 0.825 0.064 0.212 0.809 0.363 0.284 0.055 0.457
Univers
ity of
Mala
ya
299
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.570 0.416 0.637 0.024 0.198 0.089 0.178 0.194 0.292 0.073 0.009 0.375 0.339 0.064 0.247
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.238 0.003 0.010 0.308 0.599 0.098 0.006 0.044 0.443 0.510 0.144 0.155 0.461 0.512 0.252
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.029 0.000 0.000 0.000 0.000 0.000 0.011 0.020 0.007 0.000 0.000 0.005
640 Footwear 0.035 0.002 0.034 0.002 0.005 0.006 0.028 0.031 0.030 0.020 0.021 0.001 0.009 0.007 0.017
650 Hat and Headgear etc 0.000 0.000 0.000 0.165 0.000 0.000 0.000 0.000 0.000 0.000 0.006 0.070 0.017 0.024 0.020
Table 4.29D: Vietnam-Indonesia IIT Index for Textile and Clothing Industry, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.769 0.000 0.000 0.059
500 Raw silk and silk yarn 0.000 0.016 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.040 0.430 0.000 0.214 0.000 0.000 0.000 0.012 0.054
520 Cotton, cotton yarn and woven cotton 0.017 0.090 0.047 0.015 0.061 0.165 0.208 0.292 0.265 0.866 0.973 0.529 0.662 0.322
521 Woven fabrics of cotton 0.338 0.481 0.125 0.355 0.699 0.497 0.386 0.071 0.059 0.025 0.030 0.705 0.391 0.320
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.671 0.000 0.000 0.000 0.000 0.000 0.005 0.000 0.052
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.041 0.114 0.202 0.195 0.166 0.231 0.142 0.229 0.446 0.538 0.640 0.865 0.991 0.369
550 Synthetic and artificial: filament tow, staple fibres 0.095 0.129 0.056 0.025 0.100 0.214 0.460 0.450 0.212 0.697 0.943 0.738 0.869 0.384
551 Staple fibre; man made yarn, woven fabrics 0.343 0.331 0.292 0.517 0.138 0.218 0.258 0.092 0.479 0.363 0.263 0.260 0.201 0.289
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.296 0.139 0.448 0.554 0.757 0.740 0.984 0.960 0.687 0.502 0.384 0.604 0.719 0.598
570 Carpets and other textile floor covering 0.009 0.083 0.000 0.000 0.000 0.123 0.000 0.000 0.000 0.016 0.000 0.000 0.004 0.018
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.042 1.000 0.653 0.673 0.886 0.839 0.928 0.611 0.613 0.487 0.323 0.421 0.541 0.617
581 Embroidery in the piece of strips or in motifs 0.000 0.919 0.104 0.059 0.386 0.000 0.000 0.000 0.000 0.000 0.154 0.764 0.349 0.210
Univers
ity of
Mala
ya
300
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.093 0.097 0.173 0.156 0.052 0.956 0.771 0.572 0.319 0.224 0.168 0.201 0.289 0.313
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.698 0.800 0.000 0.000 0.000 0.092 0.509 0.381 0.278 0.109 0.151 0.232
600 Fabrics, knitted/crocheted 0.146 0.018 0.900 0.046 0.055 0.700 0.711 0.370 0.245 0.249 0.270 0.576 0.507 0.369
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.942 0.000 0.159 0.105 0.264 0.959 0.872 0.721 0.671 0.921 0.984 0.769 0.577 0.611
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.000 0.000 0.549 0.182 0.109 0.749 0.703 0.267 0.237 0.879 0.888 0.949 0.717 0.479
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.272 0.084 0.281 0.394 0.737 0.896 0.685 0.674 0.633 0.467 0.304 0.320 0.348 0.469
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.774 0.943 0.750 0.286 0.469 0.276 0.780 0.747 0.650 0.849 0.663 0.418 0.488 0.623
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.826 0.762 0.634 0.089 0.040 0.039 0.164 0.973 0.268 0.051 0.229 0.081 0.034 0.322
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.749 0.245 0.139 0.087
640 Footwear 0.900 0.581 0.883 0.890 0.754 0.347 0.232 0.179 0.224 0.285 0.273 0.188 0.158 0.453
650 Hat and Headgear etc 1.000 0.000 0.000 0.667 0.571 0.000 0.818 0.700 0.235 0.146 0.133 0.026 0.026 0.333
Univers
ity of
Mala
ya
301
Table 4.30A: Malaysia-Philippines IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.267 0.000 0.019
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.338 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.024
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.222 0.656 0.903 0.894 0.778 0.978 0.262 0.377 0.000 0.918 0.055 0.000 0.000 0.106 0.439
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.006 0.060 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.005
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.068 0.000 0.000 0.000 0.333 0.000 0.222 0.000 0.117 0.000 0.053
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.297 0.119 0.038 0.021 0.033 0.001 0.009 0.001 0.001 0.000 0.000 0.000 0.001 0.000 0.037
550 Synthetic and artificial: filament tow, staple fibres 0.584 0.954 0.946 0.927 0.751 0.265 0.316 0.116 0.853 0.320 0.845 0.598 0.945 0.529 0.639
551 Staple fibre; man made yarn, woven fabrics 0.039 0.049 0.000 0.002 0.449 0.186 0.093 0.000 0.029 0.000 0.504 0.000 0.000 0.000 0.096
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.241 0.563 0.795 0.853 0.598 0.627 0.239 0.161 0.169 0.100 0.060 0.127 0.052 0.101 0.335
570 Carpets and other textile floor covering 0.045 0.085 0.109 0.095 0.034 0.000 0.000 0.000 0.000 0.046 0.000 0.213 0.000 0.129 0.054
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.248 0.547 0.630 0.374 0.629 0.355 0.378 0.377 0.103 0.808 0.757 0.484 0.187 0.000 0.420
581 Embroidery in the piece of strips or in motifs 0.632 0.000 0.000 0.000 0.000 0.000 0.103 0.649 0.000 0.000 0.000 0.381 0.000 0.200 0.140
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.016 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.513 0.000 0.000 0.030 0.000 0.017 0.041
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.036 0.094 0.148 0.013 0.000 0.000 0.021
600 Fabrics, knitted/crocheted 0.053 0.114 0.115 0.302 0.204 0.153 0.465 0.731 0.411 0.000 0.000 0.000 0.649 0.115 0.237
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.305 0.903 0.706 0.672 0.858 0.541 0.785 0.849 0.715 0.728 0.729 0.815 0.747 0.824 0.727
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.414 0.405 0.868 0.429 0.861 0.587 0.869 0.704 0.387 0.320 0.997 0.430 0.405 0.111 0.556
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.217 0.453 0.238 0.315 0.035 0.022 0.356 0.795 0.619 0.241 0.172 0.508 0.824 0.550 0.382
Univers
ity of
Mala
ya
302
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.196 0.266 0.801 0.492 0.160 0.590 0.874 0.347 0.730 0.044 0.865 0.632 0.933 0.562 0.535
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.247 0.425 0.272 0.304 0.533 0.120 0.100 0.161 0.161 0.122 0.123 0.074 0.123 0.341 0.222
631 Rags, scrap twine, cordage, rope 0.083 0.059 0.273 0.021 0.163 0.449 0.875 0.533 0.270 0.606 0.208 0.000 0.126 0.015 0.263
640 Footwear 0.371 0.610 0.021 0.040 0.051 0.122 0.091 0.245 0.234 0.062 0.161 0.152 0.881 0.922 0.283
650 Hat and Headgear etc 0.818 0.417 0.625 0.769 0.308 0.933 0.522 0.162 0.364 0.000 0.057 0.333 0.915 0.078 0.450
Table 4.30B: Thailand-Philippines IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.040 0.000 0.081 0.000 0.000 0.013 0.000 0.000 0.200 0.000 0.000 0.190 0.000 0.000 0.037
510 Raw wool, wool yarn and animal hairs 0.000 0.017 0.749 0.361 0.043 0.066 0.064 0.229 0.000 0.000 0.000 0.000 0.000 0.000 0.109
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.071
520 Cotton, cotton yarn and woven cotton 0.041 0.417 0.222 0.284 0.116 0.154 0.003 0.000 0.000 0.033 0.069 0.000 0.000 0.000 0.096
521 Woven fabrics of cotton 0.017 0.000 0.037 0.016 0.012 0.006 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.006
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.909 0.000 0.000 0.629 0.917 0.000 0.542 0.000 0.000 0.000 0.138 0.000 0.541 0.262
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.154 0.000 0.011
540 Man‐made:filaments yarn and synthetic yarn 0.000 0.004 0.009 0.004 0.011 0.001 0.000 0.002 0.000 0.001 0.000 0.000 0.002 0.001 0.002
550 Synthetic and artificial: filament tow, staple fibres 0.031 0.027 0.018 0.007 0.006 0.002 0.015 0.031 0.011 0.044 0.051 0.040 0.028 0.011 0.023
551 Staple fibre; man made yarn, woven fabrics 0.000 0.002 0.002 0.000 0.000 0.002 0.000 0.000 0.019 0.063 0.278 0.803 0.122 0.000 0.092
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.810 0.308 0.350 0.209 0.125 0.072 0.007 0.006 0.014 0.006 0.039 0.019 0.064 0.024 0.147
570 Carpets and other textile floor covering 0.000 0.000 0.077 0.291 0.137 0.082 0.094 0.031 0.000 0.014 0.004 0.004 0.000 0.006 0.053
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.532 0.704 0.964 0.475 0.399 0.462 0.687 0.453 0.348 0.303 0.223 0.410 0.620 0.607 0.513
581 Embroidery in the piece of strips or in motifs 0.004 0.028 0.002 0.008 0.003 0.000 0.002 0.000 0.001 0.007 0.000 0.000 0.000 0.000 0.004
Univers
ity of
Mala
ya
303
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.000 0.000 0.000 0.000 0.140 0.000 0.211 0.027 0.164 0.041 0.550 0.121 0.948 0.001 0.157
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.255 0.000 0.000 0.780 0.447 0.340 0.014 0.000 0.000 0.131
600 Fabrics, knitted/crocheted 0.641 0.102 0.104 0.071 0.177 0.085 0.139 0.142 0.030 0.002 0.000 0.001 0.009 0.000 0.107
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.004 0.003 0.003 0.024 0.151 0.022 0.056 0.129 0.268 0.104 0.176 0.148 0.690 0.349 0.152
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.000 0.000 0.000 0.571 0.037 0.004 0.080 0.032 0.071 0.102 0.378 0.116 0.579 0.380 0.168
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.006 0.120 0.096 0.056 0.039 0.045 0.406 0.069 0.102 0.073 0.094 0.153 0.292 0.029 0.113
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.035 0.031 0.022 0.036 0.069 0.082 0.527 0.965 0.683 0.070 0.241 0.999 0.590 0.230 0.327
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.805 0.562 0.986 0.625 0.552 0.747 0.904 0.988 0.260 0.075 0.031 0.518 0.634 0.890 0.613
631 Rags, scrap twine, cordage, rope 1.000 0.000 0.269 0.010 0.020 0.009 0.020 0.000 0.144 0.527 0.143 0.007 0.000 0.000 0.154
640 Footwear 0.019 0.022 0.018 0.026 0.018 0.022 0.028 0.103 0.107 0.122 0.063 0.032 0.099 0.129 0.058
650 Hat and Headgear etc 0.000 0.000 0.204 0.000 0.316 0.006 0.094 0.033 0.068 0.000 0.000 0.000 0.023 0.351 0.078
Univers
ity of
Mala
ya
304
Table 4.30C: Indonesia-Philippines IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008
2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000
510 Raw wool, wool yarn and animal hairs 0.000 0.333 0.000 0.000 0.000 0.531 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.062
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.018 0.176 0.138 0.128 0.209 0.242 0.329 0.009
0.000 0.000 0.013 0.064 0.002 0.000 0.095
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.011 0.199 0.750 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.697 0.822 0.177
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.101 0.026 0.010 0.016 0.020 0.014 0.002 0.126
0.003 0.000 0.000 0.001 0.000 0.000 0.023
550 Synthetic and artificial: filament tow, staple fibres 0.008 0.004 0.089 0.017 0.051 0.032 0.053 0.036
0.000 0.000 0.000 0.005 0.000 0.000 0.021
551 Staple fibre; man made yarn, woven fabrics 0.000 0.000 0.008 0.002 0.000 0.032 0.004 0.000
0.000 0.000 0.016 0.019 0.005 0.004 0.006
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.799 0.975 0.363 0.311 0.046 0.081 0.193 0.160
0.127 0.117 0.602 0.983 0.876 0.640 0.448
570 Carpets and other textile floor covering 0.000 0.000 0.005 0.011 0.003 0.000 0.003 0.000
0.000 0.000 0.000 0.000 0.010 0.010 0.003
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.408 0.151 0.365 0.829 0.957 0.699 0.422 0.607
0.131 0.098 0.860 0.539 0.285 0.070 0.459
581 Embroidery in the piece of strips or in motifs 0.817 0.044 0.168 0.205 0.000 0.667 0.471 0.082
0.000 0.742 0.779 0.000 0.000 0.000 0.284
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.036 0.000 0.001 0.000 0.011 0.009 0.002 0.002
0.205 0.000 0.000 0.160 0.061 0.000 0.035
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.358 0.000 0.000 0.026
600 Fabrics, knitted/crocheted 0.164 0.440 0.071 0.121 0.107 0.361 0.352 0.131
0.051 0.065 0.000 0.042 0.087 0.000 0.142
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.184 0.003 0.062 0.595 0.082 0.977 0.710 0.686
0.250 0.219 0.358 0.365 0.828 0.506 0.416
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.463 0.000 0.771 0.859 0.260 0.048 0.114 0.086 0.075 0.206 0.116 0.130 0.387 0.046 0.254
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.349 0.269 0.618 0.499 0.596 0.739 0.710 0.825
0.064 0.212 0.809 0.363 0.284 0.055 0.457
Univers
ity of
Mala
ya
305
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.570 0.416 0.637 0.024 0.198 0.089 0.178 0.194
0.292 0.073 0.009 0.375 0.339 0.064 0.247
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.238 0.003 0.010 0.308 0.599 0.098 0.006 0.044 0.443 0.510 0.144 0.155 0.461 0.512 0.252
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.029 0.000 0.000 0.000 0.000
0.000 0.011 0.020 0.007 0.000 0.000 0.005
640 Footwear 0.035 0.002 0.034 0.002 0.005 0.006 0.028 0.031
0.030 0.020 0.021 0.001 0.009 0.007 0.017
650 Hat and Headgear etc 0.000 0.000 0.000 0.165 0.000 0.000 0.000 0.000
0.000 0.000 0.006 0.070 0.017 0.024 0.020
Table 4.30D: Vietnam-Philippines IIT Index for Textile and Clothing Industry, 2001-2013
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.000 0.000 0.857 0.000 0.000 0.031 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.068
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.000 0.114 0.356 0.270 0.370 0.327 0.141 0.025 0.004 0.039 0.098 0.648 0.461 0.220
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.424 0.000 0.000 0.130 0.150 0.236 0.072
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.020 0.720 0.627 0.977 0.384 0.111 0.056 0.625 0.039 0.153 0.216 0.017 0.139 0.314
550 Synthetic and artificial: filament tow, staple fibres 0.052 0.000 0.072 0.028 0.008 0.008 0.000 0.005 0.002 0.000 0.000 0.005 0.005 0.014
551 Staple fibre; man made yarn, woven fabrics 0.000 0.000 0.004 0.845 0.301 0.008 0.000 0.016 0.000 0.036 0.124 0.535 0.019 0.145
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.035 0.194 0.396 0.189 0.223 0.938 0.684 0.967 0.276 0.597 0.580 0.517 0.330 0.456
570 Carpets and other textile floor covering 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.112 0.147 0.167 0.540 0.257 0.291 0.467 0.553 0.469 0.750 0.319 0.008 0.016 0.315
581 Embroidery in the piece of strips or in motifs 0.000 0.011 0.750 0.000 0.000 0.000 0.200 0.000 0.000 0.000 0.000 0.000 0.051 0.078
Univers
ity of
Mala
ya
306
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.000 0.016 0.123 0.184 0.061 0.062 0.000 0.000 0.000 0.002 0.000 0.024 0.006 0.037
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
600 Fabrics, knitted/crocheted 0.000 0.318 0.706 0.802 0.798 0.677 0.359 0.186 0.117 0.031 0.034 0.006 0.005 0.311
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.000 0.057 0.671 0.000 0.108 0.003 0.021 0.121 0.409 0.061 0.270 0.076 0.381 0.168
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.475 0.623 0.552 0.740 0.026 0.000 0.063 0.091 0.146 0.040 0.022 0.021 0.289 0.238
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.050 0.148 0.792 0.808 0.066 0.281 0.000 0.000 0.261 0.168 0.223 0.078 0.154 0.233
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.078 0.038 0.121 0.034 0.208 0.724 0.514 0.701 0.812 0.178 0.432 0.448 0.299 0.353
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.044 0.584 0.715 0.130 0.681 0.897 0.772 0.479 0.608 0.588 0.722 0.307 0.124 0.512
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.015 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.173 0.014
640 Footwear 0.090 0.006 0.006 0.010 0.005 0.000 0.009 0.003 0.001 0.004 0.000 0.007 0.000 0.011
650 Hat and Headgear etc 0.000 0.000 0.146 0.125 0.813 0.000 0.000 0.258 0.000 0.000 0.000 0.000 0.133 0.113
Univers
ity of
Mala
ya
307
Table 4.31A: Malaysia-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.167 0.118 0.838 0.948 0.568 0.409 0.566 0.335 0.286 0.420 0.918 0.582 0.985 0.549
521 Woven fabrics of cotton 0.063 0.005 0.081 0.002 0.058 0.001 0.003 0.016 0.025 0.003 0.000 0.001 0.000 0.020
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.000 0.500 0.000 0.790 0.000 0.000 0.000 0.800 0.161
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.046 0.077 0.076 0.116 0.154 0.195 0.284 0.534 0.397 0.374 0.225 0.337 0.436 0.250
550 Synthetic and artificial: filament tow, staple fibres 0.915 0.300 0.628 0.647 0.663 0.661 0.402 0.888 0.742 0.790 0.825 0.409 0.608 0.652
551 Staple fibre; man made yarn, woven fabrics 0.343 0.457 0.503 0.154 0.116 0.213 0.312 0.259 0.259 0.249 0.023 0.072 0.003 0.228
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.096 0.102 0.333 0.255 0.210 0.043 0.213 0.247 0.140 0.262 0.344 0.477 0.354 0.237
570 Carpets and other textile floor covering 0.387 0.114 0.014 0.027 0.000 0.051 0.038 0.000 0.399 0.708 0.720 0.405 0.580 0.265
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.352 0.543 0.776 0.829 0.538 0.832 0.410 0.379 0.152 0.433 0.442 0.149 0.028 0.451
581 Embroidery in the piece of strips or in motifs 0.733 0.324 0.383 0.759 0.200 0.000 0.000 0.125 0.000 0.000 0.000 0.173 0.049 0.211
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.630 0.965 0.682 0.529 0.882 0.337 0.266 0.252 0.238 0.141 0.200 0.284 0.326 0.441
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.040 0.003 0.782 0.683 0.153 0.000 0.000 0.004 0.035 0.000 0.003 0.010 0.132
600 Fabrics, knitted/crocheted 0.267 0.249 0.449 0.434 0.193 0.341 0.183 0.348 0.376 0.744 0.482 0.376 0.297 0.364
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.004 0.086 0.004 0.039 0.031 0.026 0.100 0.101 0.089 0.156 0.202 0.444 0.462 0.134
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.027 0.039 0.199 0.102 0.747 0.323 0.417 0.157 0.273 0.400 0.746 0.313 0.630 0.336
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.001 0.000 0.001 0.011 0.010 0.017 0.050 0.410 0.100 0.066 0.027 0.042 0.141 0.067
Univers
ity of
Mala
ya
308
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.250 0.153 0.062 0.429 0.326 0.424 0.331 0.434 0.779 0.954 0.450 0.337 0.355 0.406
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.028 0.069 0.146 0.671 0.620 0.321 0.338 0.588 0.991 0.908 0.594 0.754 0.571 0.508
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.000 0.000 0.000 0.059 0.000 0.070 0.000 0.200 0.116 0.000 0.034
640 Footwear 0.091 0.007 0.042 0.108 0.080 0.040 0.064 0.203 0.144 0.191 0.134 0.154 0.200 0.112
650 Hat and Headgear etc 0.455 0.000 0.140 0.655 0.545 0.867 0.336 0.708 0.314 0.783 0.519 0.589 0.519 0.495
Table 4.31B: Thailand-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.852 0.759 0.062 0.123 0.329 0.057 0.466 0.784 0.800 0.506 0.000 0.222 0.000 0.382
500 Raw silk and silk yarn 0.129 0.041 0.142 0.212 0.240 0.276 0.750 0.732 0.452 0.077 0.224 0.156 0.042 0.267
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.200 0.000 0.000 0.000 0.000 0.000 0.000 0.834 0.262 0.100
520 Cotton, cotton yarn and woven cotton 0.205 0.428 0.364 0.086 0.135 0.271 0.168 0.581 0.289 0.790 0.726 0.587 0.310 0.380
521 Woven fabrics of cotton 0.033 0.055 0.059 0.142 0.101 0.214 0.117 0.058 0.057 0.029 0.027 0.047 0.009 0.073
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.130 0.000 0.000 0.340 0.000 0.000 0.000 0.000 0.036
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.248 0.078 0.106 0.179 0.839 0.875 0.990 0.986 0.924 0.887 0.955 0.898 0.761 0.671
550 Synthetic and artificial: filament tow, staple fibres 0.832 0.717 0.450 0.137 0.124 0.336 0.098 0.147 0.124 0.234 0.253 0.219 0.152 0.294
551 Staple fibre; man made yarn, woven fabrics 0.117 0.118 0.056 0.025 0.003 0.010 0.033 0.063 0.081 0.096 0.049 0.102 0.047 0.062
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.016 0.138 0.024 0.018 0.004 0.054 0.053 0.052 0.151 0.129 0.081 0.105 0.117 0.072
570 Carpets and other textile floor covering 0.889 0.067 0.023 0.020 0.011 0.034 0.006 0.018 0.022 0.018 0.036 0.049 0.028 0.094
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.072 0.132 0.225 0.183 0.124 0.156 0.183 0.253 0.110 0.135 0.141 0.192 0.150 0.158
581 Embroidery in the piece of strips or in motifs 0.000 0.020 0.014 0.000 0.140 0.650 0.677 0.543 0.204 0.015 0.002 0.000 0.000 0.174
Univers
ity of
Mala
ya
309
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.113 0.050 0.039 0.146 0.129 0.496 0.892 0.904 0.498 0.519 0.528 0.698 0.528 0.426
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.518 0.000 0.046 0.023 0.502 0.520 0.496 0.362 0.959 0.263
600 Fabrics, knitted/crocheted 0.001 0.022 0.009 0.030 0.040 0.402 0.140 0.125 0.082 0.118 0.211 0.177 0.257 0.124
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.520 0.690 0.331 0.441 0.587 0.861 0.642 0.833 0.875 0.598 0.848 0.638 0.539 0.646
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.429 0.729 0.540 0.506 0.323 0.477 0.921 0.601 0.779 0.789 0.904 0.638 0.999 0.664
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.451 0.704 0.981 0.353 0.858 0.885 0.906 0.781 0.675 0.585 0.636 0.857 0.900 0.736
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.284 0.960 0.747 0.170 0.287 0.643 0.659 0.534 0.580 0.463 0.459 0.582 0.837 0.554
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.360 0.080 0.091 0.079 0.171 0.222 0.120 0.237 0.190 0.201 0.519 0.454 0.376 0.238
631 Rags, scrap twine, cordage, rope 0.024 0.000 0.286 0.480 0.000 0.000 0.571 0.103 0.029 0.000 0.643 0.000 0.005 0.165
640 Footwear 0.414 0.442 0.600 0.792 0.765 0.680 0.725 0.519 0.806 0.826 0.551 0.475 0.417 0.616
650 Hat and Headgear etc 0.214 0.185 0.706 0.263 0.689 0.886 0.048 0.985 0.644 0.894 0.982 0.840 0.683 0.617
Univers
ity of
Mala
ya
310
Table 4.31C: Indonesia-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.769 0.000 0.000 0.059
500 Raw silk and silk yarn 0.000 0.016 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.040 0.430 0.000 0.214 0.000 0.000 0.000 0.012 0.054
520 Cotton, cotton yarn and woven cotton 0.017 0.090 0.047 0.015 0.061 0.165 0.208 0.292 0.265 0.866 0.973 0.529 0.662 0.322
521 Woven fabrics of cotton 0.338 0.481 0.125 0.355 0.699 0.497 0.386 0.071 0.059 0.025 0.030 0.705 0.391 0.320
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.671 0.000 0.000 0.000 0.000 0.000 0.005 0.000 0.052
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.041 0.114 0.202 0.195 0.166 0.231 0.142 0.229 0.446 0.538 0.640 0.865 0.991 0.369
550 Synthetic and artificial: filament tow, staple fibres 0.095 0.129 0.056 0.025 0.100 0.214 0.460 0.450 0.212 0.697 0.943 0.738 0.869 0.384
551 Staple fibre; man made yarn, woven fabrics 0.343 0.331 0.292 0.517 0.138 0.218 0.258 0.092 0.479 0.363 0.263 0.260 0.201 0.289
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.296 0.139 0.448 0.554 0.757 0.740 0.984 0.960 0.687 0.502 0.384 0.604 0.719 0.598
570 Carpets and other textile floor covering 0.009 0.083 0.000 0.000 0.000 0.123 0.000 0.000 0.000 0.016 0.000 0.000 0.004 0.018
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.042 1.000 0.653 0.673 0.886 0.839 0.928 0.611 0.613 0.487 0.323 0.421 0.541 0.617
581 Embroidery in the piece of strips or in motifs 0.000 0.919 0.104 0.059 0.386 0.000 0.000 0.000 0.000 0.000 0.154 0.764 0.349 0.210
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.093 0.097 0.173 0.156 0.052 0.956 0.771 0.572 0.319 0.224 0.168 0.201 0.289 0.313
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.698 0.800 0.000 0.000 0.000 0.092 0.509 0.381 0.278 0.109 0.151 0.232
600 Fabrics, knitted/crocheted 0.146 0.018 0.900 0.046 0.055 0.700 0.711 0.370 0.245 0.249 0.270 0.576 0.507 0.369
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.942 0.000 0.159 0.105 0.264 0.959 0.872 0.721 0.671 0.921 0.984 0.769 0.577 0.611
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.000 0.000 0.549 0.182 0.109 0.749 0.703 0.267 0.237 0.879 0.888 0.949 0.717 0.479
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.272 0.084 0.281 0.394 0.737 0.896 0.685 0.674 0.633 0.467 0.304 0.320 0.348 0.469
Univers
ity of
Mala
ya
311
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.774 0.943 0.750 0.286 0.469 0.276 0.780 0.747 0.650 0.849 0.663 0.418 0.488 0.623
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.826 0.762 0.634 0.089 0.040 0.039 0.164 0.973 0.268 0.051 0.229 0.081 0.034 0.322
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.749 0.245 0.139 0.087
640 Footwear 0.900 0.581 0.883 0.890 0.754 0.347 0.232 0.179 0.224 0.285 0.273 0.188 0.158 0.453
650 Hat and Headgear etc 1.000 0.000 0.000 0.667 0.571 0.000 0.818 0.700 0.235 0.146 0.133 0.026 0.026 0.333
Table 4.31D: Philippines-Vietnam IIT Index for Textile and Clothing Industry, 2001-2014
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.000 0.000 0.857 0.000 0.000 0.031 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.068
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.000 0.114 0.356 0.270 0.370 0.327 0.141 0.025 0.004 0.039 0.098 0.648 0.461 0.220
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.424 0.000 0.000 0.130 0.150 0.236 0.072
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.020 0.720 0.627 0.977 0.384 0.111 0.056 0.625 0.039 0.153 0.216 0.017 0.139 0.314
550 Synthetic and artificial: filament tow, staple fibres 0.052 0.000 0.072 0.028 0.008 0.008 0.000 0.005 0.002 0.000 0.000 0.005 0.005 0.014
551 Staple fibre; man made yarn, woven fabrics 0.000 0.000 0.004 0.845 0.301 0.008 0.000 0.016 0.000 0.036 0.124 0.535 0.019 0.145
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.035 0.194 0.396 0.189 0.223 0.938 0.684 0.967 0.276 0.597 0.580 0.517 0.330 0.456
570 Carpets and other textile floor covering 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.112 0.147 0.167 0.540 0.257 0.291 0.467 0.553 0.469 0.750 0.319 0.008 0.016 0.315
581 Embroidery in the piece of strips or in motifs 0.000 0.011 0.750 0.000 0.000 0.000 0.200 0.000 0.000 0.000 0.000 0.000 0.051 0.078
Univers
ity of
Mala
ya
312
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.000 0.016 0.123 0.184 0.061 0.062 0.000 0.000 0.000 0.002 0.000 0.024 0.006 0.037
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
600 Fabrics, knitted/crocheted 0.000 0.318 0.706 0.802 0.798 0.677 0.359 0.186 0.117 0.031 0.034 0.006 0.005 0.311
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.000 0.057 0.671 0.000 0.108 0.003 0.021 0.121 0.409 0.061 0.270 0.076 0.381 0.168
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.475 0.623 0.552 0.740 0.026 0.000 0.063 0.091 0.146 0.040 0.022 0.021 0.289 0.238
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.050 0.148 0.792 0.808 0.066 0.281 0.000 0.000 0.261 0.168 0.223 0.078 0.154 0.233
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.078 0.038 0.121 0.034 0.208 0.724 0.514 0.701 0.812 0.178 0.432 0.448 0.299 0.353
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.044 0.584 0.715 0.130 0.681 0.897 0.772 0.479 0.608 0.588 0.722 0.307 0.124 0.512
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.015 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.173 0.014
640 Footwear 0.090 0.006 0.006 0.010 0.005 0.000 0.009 0.003 0.001 0.004 0.000 0.007 0.000 0.011
650 Hat and Headgear etc 0.000 0.000 0.146 0.125 0.813 0.000 0.000 0.258 0.000 0.000 0.000 0.000 0.133 0.113
Univers
ity of
Mala
ya
313
Table 4.32A: RCA Index for Thailand-Malaysia Textile and Clothings Industry (2001-2014)
HS Product 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.013 0.020 0.027 0.026 0.110 0.438 0.796 0.070 0.077 0.248 0.157 0.453 0.036 0.177
500 Raw silk and silk yarn 0.115 0.107 0.029 0.126 0.071 0.121 0.266 0.115 0.093 0.108 0.056 0.034 0.056 0.010 0.093
510 Raw wool, wool yarn and animal hairs 3.395 2.787 3.671 2.646 2.335 0.509 0.017 0.016 0.010 0.068 0.023 0.030 0.001 0.000 1.108
511 Woven fabrics of wool or animal hair carded or combed 0.667 0.000 0.026 0.000 0.104 0.060 0.000 0.000 0.021 0.386 0.011 1.706 0.476 0.738 0.300
520 Cotton, cotton yarn and woven cotton 0.795 0.890 0.844 0.632 0.900 0.820 1.008 1.082 0.899 0.575 0.511 0.225 0.222 0.135 0.681
521 Woven fabrics of cotton 0.470 0.337 0.283 0.188 0.276 0.665 0.580 0.183 0.519 0.716 0.052 0.194 0.128 0.066 0.333
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.403 0.608 0.662 0.439 0.545 0.456 0.375 0.117 0.061 0.092 0.060 0.016 0.018 0.120 0.284
531 Woven fabrics of jute, vegetable fibre 2.123 0.452 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.042 0.000 0.000 0.000 0.187
540 Man‐made:filaments yarn and synthetic yarn 0.230 0.292 0.264 0.251 0.273 0.277 0.357 0.351 0.265 0.267 0.269 0.264 0.235 0.234 0.273
550 Synthetic and artificial: filament tow, staple fibres 0.452 0.421 0.732 0.763 0.676 0.636 0.385 0.307 0.222 0.273 0.124 0.149 0.236 0.262 0.403
551 Staple fibre; man made yarn, woven fabrics 0.262 0.176 0.295 0.218 0.248 0.154 0.068 0.082 0.094 0.038 0.035 0.045 0.074 0.147 0.138
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 1.301 1.559 1.852 1.297 1.270 1.159 1.278 1.237 1.276 1.233 1.148 1.193 1.238 1.227 1.305
570 Carpets and other textile floor covering 0.681 0.756 1.339 0.677 1.030 0.950 1.389 1.324 1.453 1.379 1.420 1.540 1.689 1.404 1.216
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 1.011 0.809 0.643 0.509 0.651 0.583 0.353 0.317 0.352 0.259 0.247 0.233 0.284 0.228 0.463
581 Embroidery in the piece of strips or in motifs 0.091 0.278 0.281 0.335 0.211 0.156 0.134 0.215 0.186 0.113 0.093 0.102 0.086 0.102 0.170
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 4.284 4.276 2.319 1.708 1.999 1.769 2.094 1.776 1.437 1.103 0.500 0.338 0.512 0.752 1.776
591 Transmission or conveyor belts; text prod & articles for tech use 0.105 0.208 0.143 0.109 0.357 0.342 0.283 0.423 0.300 0.378 0.378 0.395 0.624 1.011 0.361
600 Fabrics, knitted/crocheted 1.277 1.341 1.750 1.468 1.864 1.834 1.328 0.878 0.954 0.800 0.694 0.592 0.581 0.650 1.143
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.053 0.052 0.054 0.045 0.037 0.025 0.025 0.029 0.051 0.062 0.065 0.052 0.045 0.039 0.045
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.047 0.051 0.042 0.037 0.054 0.039 0.030 0.034 0.023 0.017 0.015 0.014 0.018 0.016 0.031
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.028 0.032 0.028 0.040 0.034 0.022 0.032 0.033 0.039 0.046 0.054 0.049 0.035 0.023 0.035
Univers
ity of
Mala
ya
314
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.059 0.051 0.082 0.118 0.117 0.108 0.157 0.097 0.193 0.293 0.188 0.240 0.140 0.084 0.138
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.066 0.117 0.119 0.158 0.146 0.067 0.094 0.171 0.142 0.211 0.225 0.218 0.182 0.258 0.155
631 Rags, scrap twine, cordage, rope 0.048 0.746 0.714 0.628 0.714 0.422 0.428 0.389 0.526 1.423 1.028 0.065 0.046 0.078 0.518
640 Footwear 0.054 0.047 0.031 0.022 0.026 0.024 0.022 0.016 0.025 0.017 0.015 0.016 0.014 0.017 0.025
650 Hat and Headgear etc 0.031 0.056 0.041 0.029 0.032 0.055 0.036 0.039 0.019 0.030 0.032 0.014 0.025 0.024 0.033
Univers
ity of
Mala
ya
315
Table 4.32B: RCA Index for Indonesia-Malaysia Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.178 0.302 0.181 0.086 0.000 0.040 0.000 0.000 0.000 0.000 0.000 0.039 0.004 0.059
500 Raw silk and silk yarn 0.002 0.095 0.300 1.017 0.157 0.007 0.004 1.349 0.156 0.019 0.006 0.071 0.103 0.357 0.260
510 Raw wool, wool yarn and animal hairs 0.001 0.056 0.014 0.854 0.214 0.084 0.061 0.066 0.047 0.026 0.019 0.000 0.002 0.003 0.103
511 Woven fabrics of wool or animal hair carded or combed 0.511 0.000 0.000 2.876 10.313 0.146 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.024 1.062
520 Cotton, cotton yarn and woven cotton 2.679 2.789 2.356 2.181 1.932 2.618 2.319 1.740 0.829 0.464 0.324 0.268 0.178 0.300 1.498
521 Woven fabrics of cotton 2.712 1.119 1.744 1.147 2.085 1.900 1.386 1.301 1.088 1.661 1.783 2.546 2.470 2.235 1.798
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.194 0.023 0.379 0.467 0.000 0.069 0.083 0.070 0.048 0.044 0.054 0.068 0.111 0.081 0.121
531 Woven fabrics of jute, vegetable fibre 0.354 0.000 0.000 0.000 0.259 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.044
540 Man‐made:filaments yarn and synthetic yarn 2.707 3.762 3.421 2.643 2.315 1.580 2.223 1.775 1.201 1.055 1.044 1.219 1.280 1.422 1.975
550 Synthetic and artificial: filament tow, staple fibres 1.130 1.080 0.884 0.830 0.668 0.621 0.777 0.481 0.290 0.273 0.238 0.284 0.261 0.351 0.583
551 Staple fibre; man made yarn, woven fabrics 1.920 2.447 2.633 1.720 2.224 1.496 1.177 0.710 0.533 0.880 0.944 0.670 0.861 0.871 1.363
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.714 1.071 1.601 0.753 1.030 1.085 0.924 0.950 0.803 0.646 0.551 0.540 0.404 0.365 0.817
570 Carpets and other textile floor covering 5.944 5.787 6.679 3.407 1.459 1.131 0.773 0.818 0.931 0.856 1.178 1.347 1.535 1.618 2.390
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 1.317 1.601 0.984 1.134 0.921 0.985 1.317 0.995 0.540 0.390 0.347 0.451 0.379 0.332 0.835
581 Embroidery in the piece of strips or in motifs 0.183 1.153 1.102 1.453 0.306 0.208 0.181 0.117 0.289 0.277 0.188 0.211 8.658 11.752 1.863
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 6.506 6.804 8.380 6.142 3.503 2.336 0.724 0.881 0.235 0.127 0.136 0.131 0.123 0.142 2.584
591 Transmission or conveyor belts; text prod & articles for tech use 0.107 0.267 0.139 0.012 0.000 0.000 0.041 0.070 0.002 0.015 0.000 0.001 0.012 0.001 0.048
600 Fabrics, knitted/crocheted 1.627 1.289 1.450 0.634 0.293 0.472 0.293 0.353 0.442 0.482 0.180 0.298 0.536 0.499 0.632
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.136 0.153 0.160 0.082 0.112 0.138 0.114 0.076 0.112 0.150 0.146 0.090 0.114 0.129 0.122
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.052 0.032 0.043 0.071 0.056 0.040 0.027 0.023 0.013 0.019 0.021 0.033 0.070 0.141 0.046
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.304 0.411 0.398 0.311 0.255 0.220 0.303 0.368 0.370 0.228 0.252 0.291 0.304 0.326 0.310
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.047 0.053 0.183 0.257 0.548 0.307 0.366 0.671 0.696 0.672 0.537 0.386 0.411 0.279 0.387
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.896 1.040 1.025 0.960 1.112 0.869 1.111 0.758 0.489 0.410 0.342 0.437 0.269 0.211 0.709
Univers
ity of
Mala
ya
316
631 Rags, scrap twine, cordage, rope 0.074 0.426 0.186 0.311 0.089 0.716 6.586 4.249 7.195 1.376 0.010 4.010 0.728 0.900 1.918
640 Footwear 0.690 0.372 0.434 0.319 0.294 0.184 0.186 0.101 0.053 0.060 0.070 0.076 0.087 0.085 0.215
650 Hat and Headgear etc 0.056 0.236 0.111 0.039 0.052 0.053 0.035 0.057 0.051 0.099 0.139 0.066 0.149 0.084 0.088
Table 4.32C: RCA Index for Philippines-Malaysia Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.029 0.000 0.000 0.232 0.086 0.025
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.013 0.000 0.021 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 5.838 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.417
520 Cotton, cotton yarn and woven cotton 0.035 0.174 0.091 0.124 0.146 0.079 0.011 0.011 0.000 0.012 0.016 0.000 0.000 0.003 0.050
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.001 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.850 0.016 0.006 0.000 0.070 0.000 0.045 0.065 3.911 1.068 0.431
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.312 0.000 0.000 0.000 0.022
540 Man‐made:filaments yarn and synthetic yarn 0.026 0.008 0.004 0.008 0.013 0.000 0.004 0.001 0.001 0.000 0.001 0.000 0.001 0.001 0.005
550 Synthetic and artificial: filament tow, staple fibres 0.184 0.265 0.231 0.224 0.146 0.086 0.075 0.019 0.045 0.026 0.103 0.147 0.071 0.082 0.122
551 Staple fibre; man made yarn, woven fabrics 0.010 0.007 0.000 0.000 0.569 0.018 0.007 0.000 0.001 0.000 0.022 0.000 0.000 0.000 0.045
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 2.445 0.734 0.579 0.550 0.538 0.503 0.165 0.228 0.341 0.221 0.174 0.342 0.106 0.264 0.514
570 Carpets and other textile floor covering 0.002 0.008 0.007 0.009 0.002 0.000 0.000 0.000 0.000 0.005 0.000 0.042 0.000 0.026 0.007
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 1.050 0.709 0.342 0.602 0.367 0.228 0.216 0.346 0.177 0.249 0.434 0.677 0.635 1.769 0.557
581 Embroidery in the piece of strips or in motifs 0.297 0.000 0.000 0.000 0.000 0.000 0.003 0.025 0.000 0.000 0.000 0.194 0.000 0.004 0.037
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.004 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.087 0.000 0.000 0.007 0.000 0.005 0.007
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.012 0.045 0.072 0.012 0.000 0.000 0.010
600 Fabrics, knitted/crocheted 0.027 0.028 0.014 0.016 0.018 0.031 0.060 0.023 0.050 0.016 0.000 0.000 0.046 0.005 0.024
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.008 0.008 0.004 0.007 0.009 0.008 0.015 0.021 0.023 0.060 0.096 0.037 0.076 0.080 0.032
Univers
ity of
Mala
ya
317
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.002 0.014 0.006 0.040 0.018 0.014 0.029 0.012 0.050 0.119 0.040 0.026 0.014 0.011 0.028
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.039 0.021 0.023 0.021 0.026 0.045 0.067 0.062 0.028 0.059 0.190 0.125 0.051 0.025 0.056
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.863 0.496 0.033 0.055 0.008 0.029 0.148 0.445 0.191 0.006 0.223 0.441 0.160 0.079 0.227
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.303 0.369 0.122 0.164 0.259 0.054 0.060 0.133 0.148 0.135 0.229 0.172 0.207 0.611 0.212
631 Rags, scrap twine, cordage, rope 19.934 4.796 3.194 4.654 3.273 5.658 1.813 2.519 2.774 6.355 6.026 4.541 5.473 2.446 5.247
640 Footwear 0.004 0.007 0.000 0.000 0.000 0.001 0.001 0.005 0.008 0.001 0.007 0.005 0.038 0.041 0.009
650 Hat and Headgear etc 0.035 0.017 0.003 0.003 0.003 0.005 0.013 0.003 0.048 0.000 0.002 0.002 0.072 0.345 0.039
Table 4.32D: RCA Index for Vietnam-Malaysia Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.999 0.000 0.000 0.000 0.000 0.000 0.000 0.077
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.187 0.000 0.000 0.000 0.017 0.000 0.000 0.000 0.016
510 Raw wool, wool yarn and animal hairs 0.006 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.450 0.000 0.000 0.000 0.035
520 Cotton, cotton yarn and woven cotton 0.145 0.082 1.056 1.555 1.434 2.319 1.994 2.862 2.933 3.281 3.120 1.253 1.165 1.785
521 Woven fabrics of cotton 0.071 0.018 0.350 0.004 0.168 0.007 0.016 0.139 0.251 0.024 0.000 0.003 0.001 0.081
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 0.011 0.029 0.000 0.237 0.508 0.098 0.059 0.005 0.073
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.276 0.539 0.454 0.465 0.397 0.609 0.800 1.131 0.721 0.695 0.535 0.453 0.421 0.577
550 Synthetic and artificial: filament tow, staple fibres 0.712 2.713 3.237 2.902 1.546 1.654 3.620 1.472 0.625 1.201 0.741 0.434 0.504 1.643
551 Staple fibre; man made yarn, woven fabrics 0.592 0.811 0.973 0.282 0.135 0.249 0.327 0.189 0.100 0.097 0.010 0.033 0.002 0.292
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.200 0.348 1.064 0.552 0.386 0.317 0.401 0.461 0.209 0.371 0.407 0.428 0.439 0.429
570 Carpets and other textile floor covering 0.375 0.159 0.018 0.028 0.000 0.025 0.011 0.000 0.212 0.262 0.242 0.115 0.165 0.124
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.436 1.155 1.808 0.811 0.214 0.244 0.112 0.146 0.070 0.097 0.091 0.073 0.012 0.405
581 Embroidery in the piece of strips or in motifs 0.100 0.189 0.050 0.183 0.003 0.000 0.000 0.004 0.000 0.000 0.000 0.028 0.003 0.043
Univers
ity of
Mala
ya
318
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 1.636 1.777 1.561 2.599 0.853 1.884 2.864 3.165 3.503 4.073 2.374 1.037 0.969 2.177
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.026 0.004 0.200 0.277 0.024 0.000 0.000 0.001 0.008 0.000 0.001 0.001 0.042
600 Fabrics, knitted/crocheted 0.135 0.341 1.232 0.922 0.556 1.536 0.796 1.362 1.028 1.571 1.130 0.540 0.418 0.890
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.298 0.323 0.135 0.450 0.300 0.320 0.168 0.173 0.131 0.175 0.167 0.081 0.113 0.218
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.394 0.331 0.187 0.090 0.024 0.091 0.075 0.089 0.060 0.056 0.082 0.110 0.171 0.135
620 Women and man:overcoat, jacket, dresses, undergarments etc 1.632 1.913 1.505 1.077 0.740 0.705 0.238 0.089 0.178 0.202 0.240 0.187 0.174 0.683
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.964 1.773 1.343 0.421 0.258 0.314 0.343 0.220 0.228 0.193 0.249 0.156 0.127 0.507
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 1.020 0.777 1.172 0.843 0.785 1.321 1.808 1.652 1.022 0.825 0.636 0.443 0.610 0.993
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.000 0.000 0.000 0.429 0.000 0.049 0.000 0.036 0.009 0.000 0.040
640 Footwear 0.560 0.719 0.755 0.666 0.518 0.847 0.840 0.677 0.703 0.633 0.552 0.304 0.354 0.625
650 Hat and Headgear etc 0.511 0.009 0.814 0.246 0.061 0.137 0.086 0.132 0.543 0.190 0.143 0.126 0.146 0.242
Univers
ity of
Mala
ya
319
Table 4.33A: RCA Index for Malaysia-Thailand Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.027 0.000 0.000 0.000 0.032 0.009 9.660 11.608 5.651 6.942 1.074 9.343 1.065 3.244
500 Raw silk and silk yarn 0.002 0.018 0.000 0.000 0.000 0.003 0.000 0.002 0.022 0.011 0.000 0.003 0.000 0.001 0.004
510 Raw wool, wool yarn and animal hairs 0.224 0.157 0.126 0.160 0.048 0.427 0.452 0.562 0.208 0.242 0.222 0.341 0.117 0.113 0.243
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.021 0.000 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002
520 Cotton, cotton yarn and woven cotton 0.142 0.154 0.104 0.075 0.119 0.017 0.026 0.098 0.071 0.083 0.354 1.361 0.697 0.203 0.250
521 Woven fabrics of cotton 0.630 0.787 0.910 0.585 0.274 0.251 0.103 0.593 0.304 0.148 0.063 0.088 0.129 0.132 0.357
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.014 0.052 0.009 0.029 0.012 0.000 0.000 0.117 0.097 0.075 0.272 0.030 0.000 0.050
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.051 0.153 0.129 0.119 0.131 0.134 0.166 0.352 0.321 0.333 0.251 0.360 0.285 0.349 0.224
550 Synthetic and artificial: filament tow, staple fibres 0.180 0.123 0.059 0.041 0.027 0.058 0.091 0.096 0.056 0.047 0.084 0.121 0.169 0.166 0.094
551 Staple fibre; man made yarn, woven fabrics 0.180 0.151 0.086 0.036 0.048 0.074 0.025 0.111 0.038 0.022 0.034 0.020 0.076 0.016 0.066
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.404 0.888 0.801 0.721 0.787 1.032 0.952 0.891 0.754 0.861 1.007 0.954 1.007 0.961 0.859
570 Carpets and other textile floor covering 0.136 0.234 0.130 0.055 0.072 0.126 0.096 0.101 0.133 0.169 0.189 0.156 0.093 0.101 0.128
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.032 0.042 0.189 0.173 0.280 0.107 0.040 0.020 0.024 0.035 0.022 0.027 0.018 0.069 0.077
581 Embroidery in the piece of strips or in motifs 0.000 0.001 0.000 0.002 0.000 0.000 0.026 0.002 0.004 0.032 0.009 0.017 0.011 0.009 0.008
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.100 0.063 0.048 0.112 0.084 0.063 0.095 0.094 0.053 0.044 0.049 0.063 0.144 0.165 0.084
591 Transmission or conveyor belts; text prod & articles for tech use 0.334 0.300 0.248 0.356 0.287 0.205 0.264 0.391 0.349 0.354 0.440 0.427 0.566 0.666 0.371
600 Fabrics, knitted/crocheted 0.011 0.053 0.088 0.073 0.120 0.023 0.097 0.221 0.142 0.303 0.326 0.265 0.047 0.093 0.133
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.010 0.015 0.022 0.020 0.018 0.027 0.021 0.014 0.012 0.013 0.019 0.016 0.013 0.011 0.016
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.008 0.007 0.011 0.016 0.023 0.026 0.050 0.028 0.016 0.020 0.044 0.041 0.028 0.058 0.027
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.005 0.004 0.006 0.005 0.007 0.005 0.007 0.010 0.009 0.009 0.018 0.023 0.030 0.030 0.012
Univers
ity of
Mala
ya
320
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.081 0.100 0.161 0.127 0.064 0.081 0.102 0.085 0.074 0.078 0.057 0.046 0.040 0.047 0.082
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.015 0.013 0.046 0.200 0.040 0.110 0.102 0.254 0.368 0.253 0.291 0.267 0.272 0.304 0.181
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.039 0.000 0.004 0.023 0.014 0.000 0.028 0.005 0.002 0.002 0.005 0.022 0.010
640 Footwear 0.032 0.036 0.053 0.059 0.038 0.052 0.057 0.058 0.065 0.051 0.051 0.058 0.042 0.033 0.049
650 Hat and Headgear etc 0.011 0.003 0.004 0.017 0.021 0.012 0.010 0.009 0.008 0.015 0.030 0.024 0.035 0.015 0.015
Table 4.33B: RCA Index for Indonesia-Thailand Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.883 0.000 0.011 0.068 0.000 0.148 0.435 0.018 0.000 0.000 0.015 0.000 0.113
500 Raw silk and silk yarn 0.003 0.009 0.018 0.118 0.766 0.188 0.022 0.011 0.064 0.011 0.000 0.000 0.190 0.348 0.125
510 Raw wool, wool yarn and animal hairs 0.004 0.153 0.012 1.787 0.032 0.075 0.023 0.638 0.198 0.001 0.000 0.000 0.000 0.000 0.209
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.086 0.036 0.000 9.427 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.682
520 Cotton, cotton yarn and woven cotton 0.943 0.815 1.342 1.050 0.881 0.796 0.726 1.006 0.568 0.626 0.388 0.438 0.481 0.384 0.746
521 Woven fabrics of cotton 0.855 0.549 1.872 1.635 2.041 2.038 1.414 1.341 1.409 0.966 0.919 0.643 0.711 0.362 1.197
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.283 0.330 0.000 0.020 0.041 0.000 0.000 0.097 0.002 0.000 0.040 0.084 0.021 0.006 0.066
531 Woven fabrics of jute, vegetable fibre 0.000 8.004 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.572
540 Man‐made:filaments yarn and synthetic yarn 3.808 3.778 3.393 2.587 2.881 2.927 3.258 3.565 2.895 2.549 2.094 1.609 2.435 2.624 2.886
550 Synthetic and artificial: filament tow, staple fibres 1.162 0.875 0.948 0.747 0.772 0.771 0.603 0.958 0.816 0.737 0.790 1.448 1.713 1.811 1.011
551 Staple fibre; man made yarn, woven fabrics 2.672 3.161 3.637 2.323 2.176 1.857 1.122 1.114 0.909 0.851 1.278 0.310 0.550 0.730 1.621
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 1.367 0.531 0.928 0.542 0.402 0.445 0.378 0.260 0.329 0.188 0.280 0.345 0.338 0.440 0.484
570 Carpets and other textile floor covering 0.797 0.836 1.121 1.623 1.275 1.401 1.054 0.991 0.788 0.497 0.698 0.634 0.576 0.837 0.938
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.892 0.759 0.711 1.565 2.262 1.785 2.273 1.822 1.781 1.759 1.330 1.411 1.164 0.793 1.451
581 Embroidery in the piece of strips or in motifs 0.272 0.575 1.502 0.371 0.268 0.495 0.505 0.794 0.845 1.127 1.399 1.679 2.081 1.650 0.969
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.813 1.531 1.304 1.436 1.721 1.481 2.486 1.873 1.019 0.690 1.675 2.528 0.702 0.831 1.435
Univers
ity of
Mala
ya
321
591 Transmission or conveyor belts; text prod & articles for tech use 0.434 1.035 0.518 0.198 0.105 0.166 0.130 0.334 0.130 0.188 0.134 0.346 0.275 0.424 0.315
600 Fabrics, knitted/crocheted 1.824 1.009 1.808 1.280 1.559 1.212 1.633 1.834 2.543 2.415 1.269 1.523 1.921 2.347 1.727
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.068 0.061 0.039 0.033 0.053 0.037 0.038 0.035 0.032 0.052 0.025 0.027 0.049 0.033 0.042
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.023 0.004 0.013 0.016 0.014 0.014 0.020 0.015 0.022 0.013 0.029 0.021 0.047 0.020 0.019
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.024 0.037 0.022 0.012 0.011 0.039 0.045 0.049 0.050 0.043 0.022 0.026 0.031 0.029 0.031
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.044 0.063 0.039 0.030 0.037 0.352 0.229 0.550 0.426 0.430 0.231 0.165 0.140 0.093 0.202
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.123 0.072 0.058 0.157 0.083 0.084 0.064 0.083 0.097 0.067 0.109 0.114 0.088 0.089 0.092
631 Rags, scrap twine, cordage, rope 0.082 0.000 0.019 0.000 0.053 0.043 0.060 0.015 0.000 0.000 0.007 8.461 5.407 0.517 1.047
640 Footwear 0.164 0.173 0.225 0.335 0.154 0.254 0.200 0.197 0.214 0.152 0.096 0.083 0.120 0.146 0.179
650 Hat and Headgear etc 0.185 0.119 0.020 0.055 0.030 0.024 0.027 0.024 0.003 0.150 0.004 0.004 0.012 0.046 0.050
Univers
ity of
Mala
ya
322
Table 4.33C: RCA Index for Philippines-Thailand Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.006 0.000 0.012 0.000 0.000 0.004 0.000 0.000 0.020 0.000 0.000 0.008 0.000 0.000 0.004
510 Raw wool, wool yarn and animal hairs 0.007 0.391 1.331 1.315 2.600 0.835 3.496 1.228 0.000 0.000 0.000 0.000 0.000 0.000 0.800
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.040 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.003
520 Cotton, cotton yarn and woven cotton 0.015 0.250 0.112 0.273 0.098 0.082 0.003 0.000 0.000 0.041 0.053 0.000 0.000 0.000 0.066
521 Woven fabrics of cotton 0.003 0.000 0.020 0.017 0.012 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.004
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.086 0.006 0.144 0.188 0.068 0.070 0.156 0.155 0.000 0.006 0.082 0.365 0.257 0.113
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.757 0.000 0.000 0.180 0.240 0.741 0.692 0.186
540 Man‐made:filaments yarn and synthetic yarn 0.000 0.004 0.009 0.005 0.022 0.002 0.000 0.003 0.001 0.001 0.000 0.000 0.002 0.001 0.004
550 Synthetic and artificial: filament tow, staple fibres 0.034 0.041 0.024 0.013 0.012 0.003 0.031 0.054 0.023 0.094 0.101 0.071 0.053 0.018 0.041
551 Staple fibre; man made yarn, woven fabrics 0.000 0.003 0.002 0.000 0.000 0.003 0.000 0.000 0.013 0.039 0.136 1.141 0.046 0.000 0.099
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 1.295 0.494 0.671 0.402 0.211 0.155 0.014 0.014 0.034 0.014 0.093 0.030 0.098 0.031 0.254
570 Carpets and other textile floor covering 0.000 0.000 0.052 0.243 0.128 0.120 0.148 0.056 0.000 0.015 0.005 0.006 0.000 0.020 0.057
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 2.230 3.737 2.757 4.243 5.104 4.338 7.532 8.498 6.167 6.418 7.873 4.925 4.730 5.964 5.323
581 Embroidery in the piece of strips or in motifs 0.004 0.027 0.002 0.012 0.011 0.000 0.006 0.000 0.003 0.017 0.000 0.000 0.000 0.000 0.006
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.000 0.000 0.000 0.000 0.101 0.000 0.095 0.006 0.040 0.012 0.094 1.396 0.390 0.000 0.152
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.038 0.000 0.000 0.432 0.288 0.352 0.005 0.000 0.000 0.080
600 Fabrics, knitted/crocheted 0.092 0.074 0.079 0.103 0.291 0.071 0.083 0.112 0.040 0.002 0.000 0.001 0.017 0.000 0.069
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.000 0.000 0.000 0.004 0.034 0.002 0.004 0.010 0.025 0.013 0.019 0.012 0.078 0.022 0.016
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.000 0.000 0.000 0.013 0.001 0.000 0.001 0.001 0.002 0.004 0.022 0.012 0.024 0.007 0.006
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.000 0.011 0.011 0.007 0.005 0.004 0.045 0.007 0.011 0.007 0.009 0.010 0.036 0.003 0.012
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves 0.004 0.003 0.003 0.007 0.014 0.017 0.152 0.223 0.197 0.023 0.059 0.654 0.170 0.022 0.111
Univers
ity of
Mala
ya
323
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.133 0.075 0.116 0.089 0.466 0.140 0.128 0.210 0.034 0.046 0.023 0.060 0.182 0.210 0.136
631 Rags, scrap twine, cordage, rope 0.064 0.887 2.432 7.541 10.223 13.294 15.458 9.472 6.367 1.379 0.097 0.407 0.632 0.193 4.889
640 Footwear 0.000 0.001 0.001 0.001 0.001 0.001 0.001 0.004 0.005 0.005 0.003 0.001 0.003 0.002 0.002
650 Hat and Headgear etc 0.000 0.000 0.021 0.000 0.151 0.003 0.043 0.016 0.039 0.000 0.000 0.000 0.030 0.032 0.024
Table 4.33D: RCA Index for Vietnam-Thailand Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 33.563 69.332 7.805 13.298 25.726 1.467 10.634 28.160 2.595 0.721 0.000 0.009 0.000 14.870
500 Raw silk and silk yarn 1.584 9.031 8.300 4.019 1.479 1.393 1.089 0.623 0.605 5.934 8.226 2.312 9.058 4.127
510 Raw wool, wool yarn and animal hairs 0.199 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.015
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.092 0.000 0.000 0.000 0.000 0.000 0.000 4.528 4.167 0.676
520 Cotton, cotton yarn and woven cotton 0.260 1.645 0.830 0.200 0.211 0.604 0.467 2.443 0.891 3.757 3.120 1.206 0.670 1.254
521 Woven fabrics of cotton 0.146 0.317 0.391 0.673 0.392 1.440 0.780 0.270 0.261 0.224 0.177 0.229 0.048 0.411
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.549 0.000 0.000 0.085 0.000 0.000 0.189 0.000 0.000 0.000 0.000 0.063
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2.170 0.000 0.000 0.167
540 Man‐made:filaments yarn and synthetic yarn 0.382 0.214 0.236 0.419 2.575 4.037 6.039 6.848 5.900 9.632 6.807 5.081 4.400 4.044
550 Synthetic and artificial: filament tow, staple fibres 0.970 2.443 1.288 0.709 0.587 2.198 0.843 1.127 0.819 2.137 1.732 1.009 0.669 1.272
551 Staple fibre; man made yarn, woven fabrics 0.402 0.468 0.214 0.062 0.007 0.029 0.096 0.147 0.167 0.215 0.097 0.159 0.047 0.162
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.080 1.407 0.249 0.094 0.014 0.210 0.209 0.194 0.566 0.567 0.271 0.282 0.298 0.342
570 Carpets and other textile floor covering 1.275 0.094 0.048 0.030 0.014 0.042 0.010 0.039 0.049 0.057 0.072 0.106 0.045 0.145
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.345 0.916 1.757 0.857 0.472 0.835 1.154 1.470 0.584 1.062 0.827 0.843 0.931 0.927
581 Embroidery in the piece of strips or in motifs 0.000 0.019 0.015 0.000 0.709 1.977 3.708 2.909 0.920 0.090 0.011 0.000 0.000 0.797
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.199 0.115 0.108 0.419 0.183 1.511 7.418 7.125 3.858 4.040 3.439 3.445 6.167 2.925
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.054 0.000 0.052 0.026 0.362 0.656 0.405 0.234 0.900 0.207
Univers
ity of
Mala
ya
324
600 Fabrics, knitted/crocheted 0.004 0.243 0.071 0.124 0.135 1.748 0.782 0.735 0.629 1.750 2.781 1.633 2.728 1.028
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.035 0.080 0.047 0.035 0.038 0.091 0.134 0.060 0.061 0.055 0.102 0.097 0.129 0.074
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.011 0.047 0.019 0.015 0.010 0.043 0.064 0.086 0.042 0.088 0.147 0.131 0.144 0.065
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.088 0.091 0.023 0.088 0.033 0.042 0.064 0.037 0.034 0.039 0.035 0.058 0.065 0.054
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.412 0.265 0.172 0.027 0.028 0.406 0.428 0.116 0.231 0.367 0.337 0.222 0.295 0.254
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 1.050 3.413 4.664 3.927 2.842 2.547 4.624 2.188 2.036 2.718 1.964 1.354 1.086 2.647
631 Rags, scrap twine, cordage, rope 10.969 3.171 0.463 0.236 0.138 0.240 0.098 0.029 0.050 0.000 0.139 0.397 1.690 1.355
640 Footwear 0.322 0.427 0.268 0.342 0.261 0.312 0.305 0.385 0.333 0.415 0.458 0.400 0.468 0.361
650 Hat and Headgear etc 0.098 0.033 0.028 0.230 0.039 0.097 0.128 0.106 0.252 0.210 0.089 0.074 0.082 0.113
Univers
ity of
Mala
ya
325
Table 4.34A: RCA Index for Malaysia-Indonesia Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.293 0.016 0.000 0.012 0.000 0.044 0.014 0.009 0.000 0.028
500 Raw silk and silk yarn 0.000 0.090 0.000 0.010 0.044 0.025 0.041 0.000 0.022 0.036 0.000 0.230 0.000 0.000 0.035
510 Raw wool, wool yarn and animal hairs 0.281 0.088 1.760 0.858 1.198 1.369 1.992 2.189 2.113 1.990 2.315 3.452 1.603 0.697 1.565
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.392 0.354 0.000 0.000 0.279 0.000 0.000 0.000 0.000 0.073
520 Cotton, cotton yarn and woven cotton 0.575 0.626 0.440 0.318 0.491 0.652 0.724 0.931 1.215 1.009 1.271 2.844 0.660 0.231 0.856
521 Woven fabrics of cotton 2.257 3.724 3.332 3.200 3.073 3.694 3.042 2.656 3.779 3.614 4.337 4.334 5.402 5.996 3.746
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.028 0.013 0.000 0.000 0.022 0.036 0.000 0.048 0.448 0.018 0.048 0.086 0.170 0.015 0.067
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 4.594 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.128 0.337
540 Man‐made:filaments yarn and synthetic yarn 0.098 0.068 0.080 0.302 0.305 0.193 0.341 0.461 0.525 0.478 0.956 1.253 0.798 0.798 0.475
550 Synthetic and artificial: filament tow, staple fibres 0.447 0.539 0.515 0.324 0.271 0.165 0.248 0.274 0.298 0.583 0.840 0.524 0.418 0.374 0.416
551 Staple fibre; man made yarn, woven fabrics 0.293 0.292 0.241 0.317 0.313 0.219 0.208 0.190 0.092 0.056 0.148 0.282 0.223 0.080 0.211
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 2.211 1.089 1.144 1.208 1.605 1.266 0.845 1.220 1.575 1.688 2.141 1.659 1.271 1.553 1.463
570 Carpets and other textile floor covering 0.247 1.019 0.359 0.205 0.466 0.906 0.351 0.312 0.331 0.486 0.597 0.463 0.230 0.202 0.441
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.407 0.871 3.880 1.499 0.980 4.870 5.363 4.094 5.365 6.752 3.803 3.001 1.494 0.969 3.096
581 Embroidery in the piece of strips or in motifs 0.007 0.032 0.063 0.274 0.072 0.165 0.141 0.032 0.016 0.008 0.301 0.182 0.090 0.049 0.102
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.573 0.677 0.818 0.536 0.521 0.646 0.130 0.161 0.119 0.120 0.082 0.099 0.079 0.176 0.338
591 Transmission or conveyor belts; text prod & articles for tech use 0.792 0.953 0.894 1.697 1.295 1.316 1.367 2.259 1.101 1.188 1.653 1.458 1.331 2.148 1.389
600 Fabrics, knitted/crocheted 0.299 1.225 0.848 0.736 1.664 2.028 2.080 3.505 3.528 3.255 2.401 1.354 1.389 1.601 1.851
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.010 0.014 0.015 0.016 0.014 0.010 0.002 0.055 0.021 0.042 0.062 0.064 0.017 0.020 0.026
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.021 0.006 0.027 0.021 0.020 0.024 0.083 0.023 0.029 0.038 0.061 0.085 0.112 0.110 0.047
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.022 0.010 0.003 0.004 0.005 0.010 0.026 0.048 0.015 0.011 0.018 0.025 0.018 0.013 0.016
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.042 0.072 0.047 0.019 0.049 0.127 0.013 0.034 0.054 0.072 0.069 0.042 0.019 0.044 0.050
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 1.627 1.463 2.736 1.032 1.015 1.413 0.955 1.295 1.197 1.228 1.431 1.218 0.915 1.313 1.346
Univers
ity of
Mala
ya
326
631 Rags, scrap twine, cordage, rope 0.364 0.134 3.988 6.604 5.064 1.296 0.012 0.027 0.062 0.147 0.048 0.040 0.019 0.015 1.273
640 Footwear 0.050 0.027 0.035 0.038 0.071 0.084 0.047 0.052 0.077 0.083 0.092 0.067 0.065 0.042 0.059
650 Hat and Headgear etc 0.101 0.236 0.161 0.141 0.310 0.279 0.418 0.678 0.735 0.767 0.855 0.757 0.607 0.601 0.475
Table 4.34B: RCA Index for Thailand-Indonesia Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.324 0.000 0.000 0.018 0.000 0.073 0.774 0.900 0.000 0.000 0.007 0.002 0.000 0.001 0.150
500 Raw silk and silk yarn 0.058 0.032 0.016 0.016 0.018 0.015 0.087 0.019 0.090 0.233 0.015 0.044 0.030 0.009 0.049
510 Raw wool, wool yarn and animal hairs 0.238 0.000 0.396 2.609 2.575 1.529 0.423 0.140 0.327 0.000 0.000 0.001 0.000 0.003 0.588
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.010 0.100 0.146 0.000 0.052 0.000 0.028 0.000 0.735 0.617 0.121
520 Cotton, cotton yarn and woven cotton 0.744 0.610 0.599 0.353 0.605 0.820 1.020 0.617 0.511 0.360 0.304 0.185 0.175 0.136 0.503
521 Woven fabrics of cotton 0.856 0.732 0.882 0.727 0.586 0.969 0.423 0.504 0.965 0.526 0.516 0.217 0.391 0.891 0.656
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.130 0.162 0.141 0.048 0.109 0.106 0.138 0.040 0.000 0.001 0.001 0.046 0.003 0.000 0.066
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 1.326 0.418 0.000 0.000 0.000 0.000 0.000 0.000 0.125
540 Man‐made:filaments yarn and synthetic yarn 0.242 0.279 0.352 0.292 0.305 0.515 0.510 0.600 0.711 0.604 0.489 0.650 0.589 0.795 0.495
550 Synthetic and artificial: filament tow, staple fibres 5.699 4.068 4.086 3.765 3.446 3.939 3.517 3.234 3.621 3.148 2.361 3.204 3.401 3.814 3.664
551 Staple fibre; man made yarn, woven fabrics 0.649 0.577 0.598 0.634 0.351 0.522 0.298 0.272 0.203 0.140 0.159 0.099 0.209 0.341 0.361
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 4.855 6.002 4.980 3.890 3.592 2.174 2.026 2.187 2.308 2.559 2.489 2.233 2.460 3.358 3.222
570 Carpets and other textile floor covering 0.437 0.372 0.241 0.499 0.913 0.943 0.268 0.431 0.412 0.607 0.603 0.557 0.792 0.726 0.557
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 1.351 1.580 1.709 1.316 1.567 1.757 1.145 1.447 1.291 0.884 0.740 0.979 1.222 1.104 1.292
581 Embroidery in the piece of strips or in motifs 2.111 2.474 1.456 1.315 1.180 1.887 0.858 0.809 0.710 0.349 0.058 0.115 0.323 0.233 0.991
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 2.607 5.244 2.454 1.129 1.755 1.194 0.635 0.667 0.508 1.107 1.176 1.250 2.411 3.074 1.801
591 Transmission or conveyor belts; text prod & articles for tech use 0.457 0.022 0.082 0.010 0.009 0.069 0.587 0.717 0.074 0.073 0.100 0.069 0.105 0.198 0.184
600 Fabrics, knitted/crocheted 1.804 3.560 2.810 2.840 3.341 5.119 3.183 3.334 4.265 3.247 2.787 3.150 3.269 4.778 3.392
Univers
ity of
Mala
ya
327
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.021 0.021 0.026 0.029 0.021 0.031 0.020 0.037 0.042 0.032 0.026 0.034 0.032 0.039 0.029
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.009 0.007 0.002 0.001 0.003 0.008 0.008 0.010 0.018 0.012 0.012 0.012 0.010 0.020 0.009
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.017 0.018 0.017 0.017 0.007 0.010 0.009 0.006 0.008 0.006 0.005 0.005 0.004 0.009 0.010
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.041 0.152 0.096 0.050 0.095 0.091 0.105 0.053 0.114 0.038 0.023 0.023 0.022 0.012 0.066
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.027 0.035 0.019 0.051 0.153 0.198 0.150 0.119 0.232 0.197 0.171 0.162 0.207 0.185 0.136
631 Rags, scrap twine, cordage, rope 0.032 0.000 0.000 0.159 0.004 0.159 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.025
640 Footwear 0.008 0.011 0.025 0.012 0.019 0.066 0.041 0.034 0.048 0.017 0.040 0.032 0.019 0.018 0.028
650 Hat and Headgear etc 0.229 0.335 0.431 0.832 0.139 0.142 0.027 0.006 0.001 0.004 0.000 0.005 0.003 0.004 0.154
Univers
ity of
Mala
ya
328
Table 4.34C: RCA Index for Philippines-Indonesia Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
500 Raw silk and silk yarn 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.097 0.000 0.000 0.000 0.000 0.007
510 Raw wool, wool yarn and animal hairs 0.000 0.450 0.000 0.071 0.000 0.113 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.045
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 0.191 1.992 1.111 0.880 1.606 2.230 2.273 0.046 0.001 0.000 0.043 0.152 0.005 0.000 0.752
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 7.600 4.303 4.792 16.436 1.347 0.990 1.389 1.114 1.216 0.238 0.000 0.953 0.496 0.766 2.974
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.438 0.000 0.000 1.191 0.252 0.134
540 Man‐made:filaments yarn and synthetic yarn 0.510 0.096 0.041 0.039 0.071 0.111 0.007 0.136 0.004 0.000 0.000 0.001 0.000 0.000 0.073
550 Synthetic and artificial: filament tow, staple fibres 0.153 0.034 0.347 0.108 0.284 0.216 0.207 0.135 0.001 0.000 0.000 0.007 0.000 0.000 0.107
551 Staple fibre; man made yarn, woven fabrics 0.000 0.000 0.024 0.003 0.000 0.029 0.012 0.000 0.000 0.000 0.009 0.006 0.002 0.003 0.006
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 8.771 4.275 4.145 6.018 7.049 6.070 0.081 0.155 0.194 0.227 1.124 1.734 1.332 0.718 2.992
570 Carpets and other textile floor covering 0.000 0.000 0.007 0.015 0.004 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.013 0.012 0.004
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 18.589 11.594 7.361 2.427 3.650 2.206 1.956 1.078 0.371 0.103 0.446 1.556 3.399 7.578 4.451
581 Embroidery in the piece of strips or in motifs 0.388 0.062 0.068 0.068 0.000 0.025 0.296 0.474 0.847 0.630 0.716 0.243 0.006 0.000 0.273
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.306 0.000 0.011 0.003 0.088 0.103 0.009 0.010 0.709 0.000 0.000 0.088 0.016 0.000 0.096
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.003 0.224 0.006 0.000 0.145 0.000 0.000 0.072 0.000 0.000 0.032
600 Fabrics, knitted/crocheted 0.729 1.543 0.296 0.322 0.309 1.204 0.697 0.280 0.108 0.056 0.000 0.045 0.123 0.000 0.408
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.026 0.000 0.014 0.031 0.005 0.076 0.052 0.044 0.035 0.035 0.047 0.049 0.134 0.098 0.046
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.018 0.000 0.111 0.047 0.022 0.006 0.009 0.008 0.006 0.012 0.008 0.014 0.049 0.008 0.023
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.088 0.045 0.116 0.049 0.092 0.135 0.214 0.166 0.019 0.059 0.249 0.046 0.041 0.006 0.095
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 5.474 4.349 3.365 0.036 0.295 0.118 0.074 0.048 0.120 0.018 0.003 0.123 0.088 0.012 1.009
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.544 0.003 0.004 0.108 0.116 0.030 0.002 0.021 0.162 0.110 0.033 0.020 0.085 0.137 0.098
Univers
ity of
Mala
ya
329
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 3.749 0.000 0.000 0.000 0.000 0.000 10.828 9.078 2.702 2.005 3.518 2.277
640 Footwear 0.019 0.001 0.007 0.000 0.001 0.002 0.009 0.011 0.010 0.010 0.010 0.000 0.003 0.002 0.006
650 Hat and Headgear etc 0.000 0.000 0.000 0.026 0.000 0.000 0.000 0.000 0.000 0.000 0.007 0.202 0.084 0.064 0.027
Table 4.34D: RCA Index for Vietnam-Indonesia Textile and Clothing Industry (2001-2013)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 18.170 1.071 0.085 0.052 0.000 0.000 1.491
500 Raw silk and silk yarn 0.000 0.011 0.011 0.000 0.265 2.520 0.336 0.000 0.000 0.000 0.000 0.000 0.000 0.242
510 Raw wool, wool yarn and animal hairs 0.186 0.000 0.000 0.000 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.015
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.591 13.598 3.128 106.478 35.953 5.586 8.563 7.493 12.939 14.948
520 Cotton, cotton yarn and woven cotton 0.052 0.269 0.119 0.047 0.197 0.353 0.351 1.035 0.566 1.811 1.575 2.811 2.473 0.897
521 Woven fabrics of cotton 1.197 1.939 0.547 1.542 3.559 1.329 0.696 0.229 0.258 0.087 0.045 2.159 1.024 1.124
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.000 0.000 3.045 6.969 16.362 0.600 2.093 6.609 10.421 6.401 4.038
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.134 0.450 0.629 0.818 0.781 0.770 0.412 1.370 2.433 2.299 1.783 2.919 3.818 1.432
550 Synthetic and artificial: filament tow, staple fibres 0.245 0.250 0.077 0.026 0.151 0.210 0.729 1.026 0.271 1.160 1.708 1.190 1.676 0.671
551 Staple fibre; man made yarn, woven fabrics 0.764 0.417 0.499 0.987 0.333 0.203 0.244 0.241 1.325 0.730 0.616 0.445 0.302 0.546
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.397 0.252 0.568 0.781 1.433 0.939 1.258 2.898 4.362 4.332 2.857 2.765 2.779 1.971
570 Carpets and other textile floor covering 0.028 0.122 0.000 0.000 0.000 0.239 0.000 0.000 0.000 0.027 0.000 0.000 0.007 0.033
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.006 0.437 0.393 0.280 1.216 0.827 0.878 3.832 3.346 3.999 3.265 3.496 2.229 1.862
581 Embroidery in the piece of strips or in motifs 0.000 0.856 0.112 0.133 0.471 0.000 0.000 0.000 0.000 0.000 0.002 0.104 0.061 0.134
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.364 0.402 0.422 0.433 0.274 3.149 9.645 21.317 22.737 15.488 7.717 6.291 7.766 7.385
591 Transmission or conveyor belts; text prod & articles for tech use 0.093 0.000 0.352 0.544 0.000 0.000 0.000 0.053 0.142 0.137 0.102 0.082 0.149 0.127
600 Fabrics, knitted/crocheted 0.307 0.029 3.183 0.122 0.208 5.331 9.142 27.610 29.031 22.854 15.449 17.070 15.576 11.224
Univers
ity of
Mala
ya
330
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.037 0.000 0.059 0.091 0.004 0.006 0.009 0.039 0.035 0.022 0.029 0.032 0.061 0.033
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.000 0.000 0.036 0.007 0.010 0.018 0.055 0.050 0.022 0.044 0.031 0.027 0.034 0.026
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.003 0.001 0.097 0.010 0.016 0.002 0.009 0.032 0.030 0.069 0.106 0.098 0.101 0.044
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.024 0.067 0.224 0.091 0.048 0.018 0.078 0.088 0.108 0.114 0.101 0.223 0.070 0.096
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.106 0.223 0.373 0.709 1.260 1.145 0.564 0.483 1.952 1.239 0.084 0.381 0.864 0.722
631 Rags, scrap twine, cordage, rope 0.496 0.000 0.000 0.090 0.000 0.000 0.000 0.000 0.000 0.000 11.242 1.894 0.446 1.090
640 Footwear 0.338 0.194 0.367 0.268 0.460 0.646 0.667 1.462 1.259 1.083 0.879 1.081 1.078 0.753
650 Hat and Headgear etc 0.125 0.000 0.010 0.006 0.007 0.000 0.042 0.074 0.036 0.052 0.048 0.256 0.165 0.063
Univers
ity of
Mala
ya
331
Table 4.35A: RCA Index for Malaysia-Philippines Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.016 0.000 0.001
500 Raw silk and silk yarn 0.000 0.000 0.000 0.019 0.000 0.000 0.005 0.000 0.322 0.000 0.000 0.000 0.014 0.000 0.026
510 Raw wool, wool yarn and animal hairs 0.016 0.108 0.391 0.068 0.105 0.000 0.000 0.000 0.072 0.000 0.000 0.008 0.000 0.000 0.055
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.151 0.000 0.000 0.000 0.000 0.011
520 Cotton, cotton yarn and woven cotton 0.242 0.103 0.188 0.107 0.115 0.091 0.074 0.031 0.029 0.005 0.171 0.006 0.023 0.016 0.086
521 Woven fabrics of cotton 0.681 0.442 0.236 0.204 0.197 0.225 0.258 0.038 0.087 0.007 0.025 0.051 0.039 0.040 0.181
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.783 0.212 0.000 0.000 0.037 0.000 0.000 0.000 0.010 0.004 0.002 0.000 0.106 0.000 0.082
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.128 0.149 0.364 0.741 0.946 0.937 0.876 0.897 1.004 0.947 0.819 0.937 1.235 1.043 0.787
550 Synthetic and artificial: filament tow, staple fibres 0.385 0.294 0.355 0.276 0.301 0.679 0.394 0.213 0.023 0.062 0.044 0.019 0.028 0.072 0.225
551 Staple fibre; man made yarn, woven fabrics 0.445 0.351 0.295 0.324 0.204 0.209 0.152 0.038 0.037 0.029 0.020 0.043 0.052 0.039 0.160
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.289 0.350 0.654 0.436 1.564 1.325 1.198 1.754 2.531 1.888 1.712 1.521 1.761 1.573 1.325
570 Carpets and other textile floor covering 0.062 0.213 0.195 0.198 0.154 0.111 0.034 0.034 0.051 0.103 0.032 0.107 0.052 0.118 0.105
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.128 0.324 0.269 0.147 0.209 0.059 0.050 0.054 0.007 0.076 0.081 0.065 0.029 0.000 0.107
581 Embroidery in the piece of strips or in motifs 0.118 0.126 0.135 0.173 0.143 0.059 0.058 0.035 0.048 0.044 0.017 0.014 0.005 0.011 0.071
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.456 0.854 0.355 0.332 0.354 0.209 0.530 0.219 0.174 0.113 0.147 0.148 0.201 0.172 0.304
591 Transmission or conveyor belts; text prod & articles for tech use 0.645 0.585 0.408 0.504 0.397 0.405 0.258 0.688 0.448 0.413 0.277 0.550 0.529 0.653 0.483
600 Fabrics, knitted/crocheted 0.854 0.562 0.385 0.096 0.200 0.448 0.194 0.027 0.009 0.000 0.014 0.003 0.042 0.025 0.204
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.001 0.011 0.013 0.014 0.015 0.025 0.023 0.019 0.029 0.015 0.017 0.016 0.020 0.018 0.017
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.006 0.004 0.008 0.011 0.029 0.040 0.022 0.014 0.008 0.010 0.012 0.028 0.024 0.059 0.020
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.004 0.008 0.005 0.004 0.001 0.001 0.014 0.028 0.009 0.004 0.005 0.013 0.032 0.021 0.011
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.081 0.093 0.085 0.181 0.117 0.084 0.114 0.063 0.228 0.124 0.052 0.061 0.080 0.064 0.102
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 1.854 1.660 1.329 0.976 0.882 1.009 1.119 1.022 1.165 0.934 1.074 1.348 1.382 0.936 1.192
Univers
ity of
Mala
ya
332
631 Rags, scrap twine, cordage, rope 0.747 0.177 0.863 0.053 0.359 1.976 2.297 4.663 0.298 1.240 0.215 0.000 0.161 0.006 0.932
640 Footwear 0.015 0.019 0.022 0.019 0.015 0.019 0.022 0.025 0.043 0.019 0.024 0.019 0.021 0.011 0.021
650 Hat and Headgear etc 0.021 0.006 0.012 0.006 0.018 0.007 0.004 0.025 0.007 0.001 0.019 0.003 0.027 0.004 0.011
Table 4.35B: RCA Index for Thailand-Philippines Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.220 0.000 0.000 0.083 1.015 0.846 0.366 0.066 0.048 0.239 0.069 0.043 0.214
500 Raw silk and silk yarn 0.346 0.240 0.221 0.336 0.133 0.323 0.174 0.223 0.074 0.032 0.015 0.036 0.076 0.090 0.166
510 Raw wool, wool yarn and animal hairs 0.000 0.003 0.606 0.169 0.033 0.015 0.055 0.069 0.052 0.021 0.146 0.207 0.007 0.000 0.099
511 Woven fabrics of wool or animal hair carded or combed 0.031 1.701 0.031 1.759 0.232 0.435 0.000 0.000 0.000 0.000 0.000 0.027 0.040 0.000 0.304
520 Cotton, cotton yarn and woven cotton 0.828 0.807 0.685 0.959 0.912 0.499 0.732 0.744 1.121 0.892 0.616 0.753 0.625 0.449 0.759
521 Woven fabrics of cotton 0.348 1.044 0.800 1.238 1.190 1.244 1.057 0.994 1.552 1.559 1.122 0.991 0.911 0.913 1.069
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.375 0.061 0.000 0.000 0.049 0.029 0.000 0.182 0.000 0.000 0.000 0.003 0.000 0.038 0.053
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.896 0.681 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.024 0.000 0.114
540 Man‐made:filaments yarn and synthetic yarn 1.326 1.577 1.536 1.712 2.247 1.703 2.119 1.904 1.217 0.929 0.724 0.822 0.767 0.826 1.386
550 Synthetic and artificial: filament tow, staple fibres 2.521 2.558 2.044 2.258 2.181 2.000 2.005 1.490 1.651 1.547 1.586 1.727 1.445 1.262 1.877
551 Staple fibre; man made yarn, woven fabrics 2.026 2.423 1.985 1.663 1.607 1.118 0.550 0.569 0.575 0.438 0.346 0.385 0.271 0.286 1.017
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 2.238 2.307 2.403 2.003 1.803 2.105 1.772 1.876 1.975 1.706 1.916 1.611 1.147 1.002 1.847
570 Carpets and other textile floor covering 1.703 0.884 0.997 0.830 0.993 1.433 1.428 1.539 1.342 0.768 1.052 1.493 1.585 2.449 1.321
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.949 1.726 1.949 0.769 0.726 0.665 1.883 1.085 0.532 0.419 0.406 0.638 0.816 1.043 0.972
581 Embroidery in the piece of strips or in motifs 2.439 1.660 1.457 1.670 4.089 2.428 2.200 2.233 4.232 1.674 2.117 1.337 0.713 0.740 2.071
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 5.305 5.694 1.720 0.525 0.767 0.258 0.387 0.188 0.183 0.208 0.101 0.045 0.166 0.227 1.127
591 Transmission or conveyor belts; text prod & articles for tech use 0.069 0.056 0.176 0.142 0.148 0.132 0.188 0.249 0.277 0.365 0.706 0.367 0.419 0.566 0.276
600 Fabrics, knitted/crocheted 0.230 1.169 1.093 1.636 1.713 0.817 0.534 0.641 1.075 0.817 1.206 1.172 1.348 1.145 1.042
Univers
ity of
Mala
ya
333
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.141 0.129 0.165 0.205 0.239 0.102 0.067 0.065 0.067 0.086 0.080 0.074 0.057 0.041 0.108
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.014 0.022 0.022 0.019 0.022 0.026 0.017 0.027 0.024 0.029 0.039 0.101 0.023 0.012 0.028
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.099 0.148 0.163 0.140 0.139 0.081 0.083 0.080 0.085 0.070 0.071 0.059 0.082 0.074 0.098
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.240 0.141 0.182 0.227 0.230 0.202 0.203 0.104 0.155 0.227 0.178 0.328 0.155 0.069 0.189
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.105 0.164 0.091 0.114 0.101 0.042 0.074 0.089 0.093 0.426 0.584 0.087 0.150 0.105 0.159
631 Rags, scrap twine, cordage, rope 0.076 0.000 0.287 0.022 0.058 0.032 0.076 0.000 0.202 0.180 0.003 0.001 0.000 0.000 0.067
640 Footwear 0.051 0.072 0.059 0.058 0.060 0.052 0.047 0.035 0.034 0.031 0.036 0.029 0.021 0.014 0.043
650 Hat and Headgear etc 0.130 0.149 0.142 0.318 0.457 0.453 0.414 0.401 0.445 0.221 0.508 1.486 1.018 0.061 0.443
Table 4.35C: RCA Index for Indonesia-Philippines Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.232 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.017
500 Raw silk and silk yarn 0.000 0.000 0.000 0.010 0.000 0.797 0.000 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.058
510 Raw wool, wool yarn and animal hairs 0.000 0.024 0.284 0.000 0.008 0.081 0.033 0.027 0.054 0.387 0.000 0.000 0.001 0.000 0.064
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 12.357 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.883
520 Cotton, cotton yarn and woven cotton 3.400 5.414 4.674 3.898 4.612 4.187 3.263 2.981 1.500 0.970 1.065 1.035 0.935 0.966 2.779
521 Woven fabrics of cotton 0.919 0.325 0.206 1.104 2.018 3.598 5.844 6.528 3.725 3.382 2.716 3.800 3.101 3.249 2.894
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.008 0.553 0.271 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.195 0.214 0.089
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.699 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.050
540 Man‐made:filaments yarn and synthetic yarn 1.566 1.917 2.497 1.466 2.407 3.970 2.247 0.595 0.477 0.542 0.383 0.324 0.405 0.509 1.379
550 Synthetic and artificial: filament tow, staple fibres 6.308 4.743 2.341 3.728 3.620 3.478 2.134 2.134 1.063 1.146 0.761 0.581 0.643 0.755 2.388
551 Staple fibre; man made yarn, woven fabrics 0.779 1.031 1.952 0.796 0.621 0.460 1.695 0.783 0.279 0.222 0.187 0.129 0.171 0.248 0.668
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 2.146 1.070 0.287 0.337 0.056 0.066 0.214 0.523 0.455 0.515 0.428 0.379 0.219 0.297 0.499
570 Carpets and other textile floor covering 0.425 0.323 0.823 0.856 0.850 0.542 0.653 0.549 0.366 0.260 0.419 0.498 0.546 0.477 0.542
Univers
ity of
Mala
ya
334
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.775 0.248 0.514 1.041 1.124 1.063 2.072 0.726 0.844 0.281 0.097 0.130 0.119 0.053 0.649
581 Embroidery in the piece of strips or in motifs 0.091 0.725 0.230 0.180 0.002 0.013 0.026 0.006 0.000 0.052 0.075 0.000 0.000 0.000 0.100
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 2.752 3.100 4.923 6.729 5.607 5.751 2.531 2.904 0.989 0.159 0.209 0.228 0.109 0.153 2.582
591 Transmission or conveyor belts; text prod & articles for tech use 0.002 0.994 0.645 0.154 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.075 0.118 0.084 0.148
600 Fabrics, knitted/crocheted 1.329 1.440 2.514 1.514 1.836 1.415 0.922 1.175 0.648 0.238 0.144 0.472 0.572 1.368 1.113
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.042 0.062 0.141 0.022 0.043 0.019 0.026 0.025 0.039 0.041 0.035 0.050 0.040 0.057 0.046
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.010 0.024 0.022 0.019 0.049 0.062 0.042 0.055 0.024 0.015 0.021 0.044 0.043 0.065 0.035
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.068 0.075 0.081 0.045 0.013 0.020 0.033 0.069 0.092 0.070 0.060 0.047 0.052 0.039 0.055
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.355 0.300 0.492 0.894 0.900 0.652 0.214 0.131 0.112 0.067 0.097 0.121 0.091 0.072 0.321
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.654 0.591 0.251 0.180 0.091 0.149 0.216 0.280 0.090 0.045 0.070 0.053 0.059 0.078 0.201
631 Rags, scrap twine, cordage, rope 0.161 0.000 0.000 0.016 0.000 0.035 0.120 0.000 0.000 0.008 0.015 0.002 0.000 0.000 0.026
640 Footwear 0.176 0.154 0.135 0.161 0.136 0.204 0.169 0.196 0.101 0.147 0.155 0.154 0.118 0.102 0.151
650 Hat and Headgear etc 0.002 0.153 0.023 0.087 0.039 0.037 0.004 0.010 0.009 0.079 0.358 1.256 2.047 1.017 0.366
Table 4.35D: RCA Index for Vietnam-Philippines Textile and Clothing Industry (2001-2013)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.067 0.005
500 Raw silk and silk yarn 0.428 0.000 0.357 0.000 0.000 0.007 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.061
510 Raw wool, wool yarn and animal hairs 0.195 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.015
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 1.312 0.000 0.000 15.549 2.852 0.000 0.000 1.516
520 Cotton, cotton yarn and woven cotton 0.258 0.539 1.418 2.304 1.760 3.250 2.758 3.450 2.559 1.464 1.032 0.389 0.575 1.673
521 Woven fabrics of cotton 0.552 0.477 1.065 0.401 0.264 0.540 0.353 0.110 0.006 0.000 0.010 0.008 0.064 0.296
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.024 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002
Univers
ity of
Mala
ya
335
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
540 Man‐made:filaments yarn and synthetic yarn 0.148 0.073 0.076 0.098 0.233 0.618 0.290 0.086 0.087 0.263 0.343 0.325 0.234 0.221
550 Synthetic and artificial: filament tow, staple fibres 0.610 0.560 1.240 2.535 2.400 4.164 6.544 2.441 3.942 3.493 3.592 2.536 2.563 2.817
551 Staple fibre; man made yarn, woven fabrics 0.497 0.120 0.491 0.086 0.083 0.349 0.444 0.028 0.149 0.297 0.722 0.177 0.026 0.267
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 0.042 0.191 0.344 0.107 0.074 0.232 0.073 0.054 0.261 0.292 0.420 0.467 0.876 0.264
570 Carpets and other textile floor covering 0.000 0.000 0.000 0.000 0.000 0.005 0.000 0.000 0.022 0.000 0.000 0.001 0.000 0.002
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.149 0.377 0.342 0.960 0.305 0.254 0.515 0.257 0.067 0.090 0.588 2.289 1.064 0.558
581 Embroidery in the piece of strips or in motifs 0.000 1.211 0.022 0.000 0.000 0.000 0.037 0.000 0.000 0.000 0.000 0.199 0.297 0.136
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.512 3.372 2.716 1.667 1.477 3.334 2.524 2.289 2.990 2.281 1.670 0.651 0.934 2.032
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.085 0.000 0.000 0.000 0.000 0.000 0.245 0.000 0.007 0.000 0.000 0.020 0.027
600 Fabrics, knitted/crocheted 0.000 0.070 0.657 0.191 0.427 1.045 3.130 1.810 3.955 2.314 2.437 3.758 5.167 1.920
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.149 0.023 0.039 0.056 0.050 0.070 0.062 0.061 0.064 0.100 0.104 0.109 0.204 0.084
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.035 0.030 0.027 0.028 0.013 0.032 0.053 0.065 0.137 0.101 0.161 0.159 0.382 0.094
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.003 0.014 0.013 0.006 0.023 0.047 0.033 0.034 0.030 0.057 0.116 0.115 0.123 0.047
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.055 0.029 0.218 0.007 0.021 0.220 0.142 0.053 0.226 0.109 0.149 0.204 0.114 0.119
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.140 0.103 0.217 0.055 0.015 0.023 0.037 0.154 0.071 0.059 0.109 0.462 0.793 0.172
631 Rags, scrap twine, cordage, rope 0.356 0.000 0.000 0.082 0.041 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.064 0.042
640 Footwear 0.200 0.643 0.572 0.378 0.251 0.328 0.307 0.201 0.230 0.282 0.615 0.576 0.637 0.402
650 Hat and Headgear etc 0.000 0.014 0.172 0.042 0.037 0.066 0.182 0.134 0.239 0.298 0.361 0.321 0.223 0.161
Univers
ity of
Mala
ya
336
Table 4.36A: RCA Index for Malaysia-Vietnam Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.104 0.000 0.000 0.000 0.206 0.000 0.000 0.044 0.000 0.025
500 Raw silk and silk yarn 0.000 0.970 0.190 0.609 0.036 0.000 0.146 0.471 0.118 0.000 0.000 0.048 0.037 0.006 0.188
510 Raw wool, wool yarn and animal hairs 0.000 0.091 0.112 0.004 0.170 0.288 0.399 0.000 0.000 0.006 0.000 0.007 0.031 0.000 0.079
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
520 Cotton, cotton yarn and woven cotton 1.135 0.688 0.805 0.944 0.504 0.413 0.527 0.485 0.374 0.515 1.922 3.595 1.417 0.428 0.982
521 Woven fabrics of cotton 1.544 3.874 4.587 2.733 4.981 6.849 7.718 14.208 15.133 10.407 10.310 10.656 11.202 10.376 8.184
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.037 0.023 0.000 0.000 0.000 0.000 0.006 0.017 0.278 0.000 0.000 0.000 0.004 0.000 0.026
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.055 0.000 0.000 0.000 0.000 0.004
540 Man‐made:filaments yarn and synthetic yarn 8.291 7.031 6.326 4.135 4.229 3.905 3.239 2.614 2.227 1.786 3.059 2.637 1.777 1.708 3.783
550 Synthetic and artificial: filament tow, staple fibres 0.428 0.251 0.814 0.761 0.679 0.564 0.609 0.992 0.811 0.462 0.377 0.132 0.260 0.239 0.527
551 Staple fibre; man made yarn, woven fabrics 2.031 1.431 1.591 1.850 1.945 1.441 1.183 1.070 0.518 0.402 0.597 1.036 1.778 2.434 1.379
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 2.824 3.376 2.926 2.071 2.921 10.051 2.251 2.760 2.126 1.454 1.422 1.610 2.403 2.724 2.923
570 Carpets and other textile floor covering 1.112 1.384 1.378 1.096 0.998 0.655 0.381 0.386 0.650 0.282 0.312 0.533 0.476 0.776 0.744
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 1.453 1.619 0.630 0.628 0.516 0.236 0.291 0.525 0.653 0.207 0.233 1.060 0.962 0.727 0.696
581 Embroidery in the piece of strips or in motifs 0.041 0.019 0.115 0.061 0.026 0.014 0.024 0.051 0.038 0.011 0.053 0.353 0.127 0.092 0.073
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.535 0.866 0.444 0.512 0.596 0.264 0.293 0.384 0.361 0.183 0.192 0.202 0.223 0.171 0.373
591 Transmission or conveyor belts; text prod & articles for tech use 1.189 0.664 1.265 0.170 0.474 0.196 0.417 1.040 0.314 0.273 0.624 0.653 0.302 0.438 0.573
600 Fabrics, knitted/crocheted 0.625 1.251 2.341 1.824 4.616 5.168 5.281 5.453 3.392 1.564 2.584 2.746 2.825 2.674 3.025
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.000 0.008 0.000 0.005 0.004 0.003 0.006 0.008 0.005 0.009 0.014 0.027 0.040 0.034 0.012
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.004 0.003 0.011 0.003 0.036 0.012 0.013 0.006 0.007 0.008 0.036 0.024 0.093 0.019 0.020
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.001 0.000 0.000 0.003 0.003 0.004 0.004 0.019 0.007 0.004 0.002 0.005 0.016 0.031 0.007
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.098 0.077 0.024 0.063 0.045 0.058 0.046 0.051 0.111 0.125 0.052 0.037 0.032 0.031 0.061
Univers
ity of
Mala
ya
337
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.010 0.015 0.051 0.233 0.313 0.175 0.246 0.580 0.768 0.585 1.091 0.862 0.288 0.210 0.388
631 Rags, scrap twine, cordage, rope 0.000 2.529 0.157 0.000 0.117 0.319 0.009 6.016 1.043 0.832 0.234 0.174 0.081 0.080 0.828
640 Footwear 0.019 0.001 0.009 0.021 0.019 0.012 0.019 0.064 0.042 0.039 0.029 0.030 0.046 0.050 0.029
650 Hat and Headgear etc 1.234 0.000 0.034 0.065 0.144 0.073 0.285 0.061 0.077 0.072 0.036 0.062 0.060 0.039 0.160
Table 4.36B: RCA Index for Thailand-Vietnam Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 10.086 27.201 64.310 55.991 47.850 14.489 9.114 4.711 0.486 0.431 0.133 0.030 0.016 0.025 16.777
500 Raw silk and silk yarn 0.044 0.045 0.168 0.132 0.074 0.065 0.170 0.280 0.050 0.048 0.285 0.083 0.082 0.012 0.110
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.145 0.021 0.052 0.088 0.134 0.077 0.314 0.059
511 Woven fabrics of wool or animal hair carded or combed 0.000 0.000 0.236 13.686 0.302 0.043 0.394 0.106 0.000 0.403 0.560 2.681 11.798 8.014 2.730
520 Cotton, cotton yarn and woven cotton 0.921 1.452 0.988 1.236 1.062 1.118 1.325 1.551 1.482 1.164 1.505 1.229 1.560 1.153 1.268
521 Woven fabrics of cotton 3.479 2.713 3.415 2.435 2.712 3.497 3.277 2.345 2.527 3.073 3.588 4.063 4.545 4.576 3.303
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.022 0.000 0.000 0.241 0.054 0.354 0.006 0.068 0.011 0.037 0.092 0.091 0.039 0.001 0.073
531 Woven fabrics of jute, vegetable fibre 1.054 0.150 0.000 0.000 0.047 0.235 0.000 0.132 0.236 0.000 0.000 0.000 0.000 0.049 0.136
540 Man‐made:filaments yarn and synthetic yarn 1.095 1.272 1.119 1.177 1.305 1.507 1.602 1.828 1.931 2.446 2.044 2.640 3.060 2.609 1.831
550 Synthetic and artificial: filament tow, staple fibres 0.279 0.328 1.177 2.667 3.266 3.160 4.241 3.685 3.476 3.260 3.281 3.471 3.480 2.867 2.760
551 Staple fibre; man made yarn, woven fabrics 2.626 1.786 1.958 1.337 1.626 1.668 1.496 1.182 1.109 0.862 1.048 1.252 0.846 1.374 1.441
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 4.078 4.557 5.366 2.871 2.485 2.209 2.007 1.877 1.945 1.663 1.767 2.152 2.054 2.180 2.658
570 Carpets and other textile floor covering 0.413 0.646 1.111 0.802 0.947 0.703 0.832 1.108 1.270 1.300 1.073 1.790 1.364 1.377 1.053
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 3.769 3.110 3.678 2.352 2.622 2.860 2.973 2.635 2.816 2.961 3.004 3.361 4.905 4.284 3.238
581 Embroidery in the piece of strips or in motifs 0.480 0.446 0.557 1.498 3.441 1.192 1.885 2.029 2.280 2.437 2.725 3.271 2.211 1.300 1.839
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 1.340 1.077 1.441 1.473 0.969 1.331 2.396 2.245 3.268 2.331 2.631 2.724 0.946 0.575 1.768
Univers
ity of
Mala
ya
338
591 Transmission or conveyor belts; text prod & articles for tech use 0.031 0.087 0.082 0.108 0.057 0.050 0.582 0.565 0.303 0.378 0.337 0.449 0.418 0.646 0.292
600 Fabrics, knitted/crocheted 5.178 5.335 4.104 2.288 2.418 2.020 2.695 2.874 4.156 5.657 6.484 7.101 7.895 8.835 4.789
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.040 0.036 0.063 0.034 0.033 0.020 0.017 0.022 0.022 0.026 0.021 0.019 0.020 0.026 0.029
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.016 0.020 0.013 0.012 0.018 0.039 0.020 0.052 0.018 0.027 0.033 0.026 0.062 0.061 0.030
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.010 0.012 0.006 0.005 0.009 0.010 0.014 0.015 0.019 0.019 0.021 0.018 0.023 0.019 0.014
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.028 0.069 0.076 0.082 0.060 0.056 0.055 0.083 0.158 0.247 0.310 0.229 0.176 0.138 0.126
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.093 0.034 0.059 0.045 0.097 0.092 0.077 0.076 0.060 0.061 0.189 0.168 0.108 0.152 0.094
631 Rags, scrap twine, cordage, rope 0.055 0.000 0.020 0.207 0.000 0.000 0.010 0.138 0.937 3.218 0.018 0.000 0.002 0.036 0.331
640 Footwear 0.034 0.029 0.030 0.062 0.059 0.047 0.045 0.035 0.063 0.059 0.048 0.053 0.053 0.046 0.047
650 Hat and Headgear etc 0.329 0.078 0.013 0.010 0.027 0.022 1.352 0.028 0.034 0.053 0.024 0.023 0.018 0.019 0.145
Univers
ity of
Mala
ya
339
Table 4.36C: RCA Index for Indonesia-Vietnam Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.169 1.433 0.000 0.000 0.030 0.000 0.000 0.000 0.084 0.000 0.000 0.000 0.123
500 Raw silk and silk yarn 0.000 1.097 0.000 0.097 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.085
510 Raw wool, wool yarn and animal hairs 0.000 0.136 0.039 0.045 0.057 0.000 0.037 0.000 0.000 0.000 0.437 0.000 0.000 0.002 0.054
511 Woven fabrics of wool or animal hair carded or combed 0.000 1.076 0.000 0.000 0.000 0.253 0.729 0.000 2.239 0.000 0.000 0.000 0.083 0.000 0.313
520 Cotton, cotton yarn and woven cotton 4.955 4.797 4.887 4.683 4.324 3.575 2.566 2.717 1.920 1.746 1.665 1.048 1.274 1.409 2.969
521 Woven fabrics of cotton 4.829 5.174 8.217 5.379 4.583 3.662 2.473 2.787 4.367 5.085 2.936 4.108 4.391 6.401 4.599
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.714 0.000 0.188 0.762 0.000 5.486 0.000 0.000 0.000 0.000 0.000 0.026 0.000 0.002 0.513
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.282 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.020
540 Man‐made:filaments yarn and synthetic yarn 5.277 6.268 5.583 5.709 5.950 5.374 4.596 4.762 4.402 4.597 3.793 3.970 4.055 4.529 4.919
550 Synthetic and artificial: filament tow, staple fibres 4.042 3.070 2.652 1.538 1.988 1.595 2.078 1.585 1.185 1.596 1.918 2.112 2.272 2.873 2.179
551 Staple fibre; man made yarn, woven fabrics 3.023 1.779 2.914 2.130 3.094 1.514 1.402 2.254 2.182 2.426 4.074 3.082 2.817 6.054 2.767
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 1.877 2.852 1.962 1.537 1.627 1.458 1.037 1.411 1.184 1.071 0.680 1.242 1.625 1.701 1.519
570 Carpets and other textile floor covering 5.042 2.374 3.409 4.338 3.686 3.325 3.376 2.858 2.842 2.586 2.632 2.861 3.383 3.177 3.278
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 0.236 0.369 0.190 0.415 1.057 0.545 0.647 0.757 0.767 0.949 0.630 0.967 0.862 1.052 0.675
581 Embroidery in the piece of strips or in motifs 0.028 0.615 2.050 3.304 1.361 0.185 0.282 1.491 6.278 0.965 0.028 0.174 0.302 0.098 1.226
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 6.103 6.644 4.437 3.864 7.102 3.131 5.149 3.833 2.237 1.438 0.707 0.729 1.368 1.007 3.411
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.977 0.654 0.273 0.097 0.177 0.299 0.492 0.215 0.427 0.629 1.481 1.910 2.334 0.712
600 Fabrics, knitted/crocheted 3.203 2.723 3.880 3.890 5.114 2.612 4.295 2.813 2.101 2.388 2.413 7.157 5.510 10.203 4.164
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.034 0.023 0.005 0.004 0.020 0.005 0.006 0.031 0.036 0.019 0.028 0.054 0.026 0.059 0.025
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.132 0.137 0.096 0.055 0.117 0.010 0.086 0.145 0.086 0.025 0.024 0.031 0.020 0.028 0.071
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.018 0.021 0.016 0.002 0.019 0.002 0.004 0.007 0.007 0.015 0.019 0.019 0.022 0.019 0.014
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.012 0.051 0.134 0.408 0.109 0.102 0.103 0.066 0.116 0.114 0.050 0.061 0.225 0.172 0.123
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.124 0.307 0.173 0.025 0.018 0.021 0.043 0.206 0.157 0.024 0.011 0.017 0.016 0.026 0.083
Univers
ity of
Mala
ya
340
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 0.000 0.025 0.000 2.354 4.018 16.491 20.273 6.743 14.073 6.243 2.398 5.187
640 Footwear 0.227 0.401 0.289 0.162 0.192 0.123 0.075 0.065 0.082 0.133 0.139 0.116 0.097 0.092 0.157
650 Hat and Headgear etc 0.102 0.104 0.000 0.002 0.012 0.005 0.025 0.018 0.003 0.003 0.003 0.004 0.002 0.001 0.020
Table 4.36D: RCA Index for Philippines-Vietnam Textile and Clothing Industry (2001-2014)
HS Products 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total
Average
430 Furskins raw, tanned or dressed and artificial apparel and furs 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.253 0.018
500 Raw silk and silk yarn 0.000 0.000 1.116 0.000 0.000 0.978 0.000 0.041 0.226 0.291 0.000 0.124 0.048 0.000 0.202
510 Raw wool, wool yarn and animal hairs 0.000 0.000 0.000 0.039 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.003
511 Woven fabrics of wool or animal hair carded or combed 0.000 2.567 0.000 4.578 70.513 49.164 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 9.059
520 Cotton, cotton yarn and woven cotton 0.000 0.100 0.721 0.263 1.064 1.403 0.464 0.206 0.022 0.088 0.114 0.587 0.570 0.824 0.459
521 Woven fabrics of cotton 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.141 0.000 0.020 0.295 0.314 1.576 1.979 0.309
530 Flax raw, hemp, jute, vegetables, yarn of jute and vegetables 0.000 0.000 0.000 0.029 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.212 0.172 0.179 0.042
531 Woven fabrics of jute, vegetable fibre 0.000 0.000 0.000 0.000 0.000 0.000 0.492 0.000 0.000 0.688 0.000 0.000 0.000 0.000 0.084
540 Man‐made:filaments yarn and synthetic yarn 0.009 0.126 0.081 0.075 0.147 0.081 0.019 0.186 0.007 0.065 0.089 0.009 0.058 0.098 0.075
550 Synthetic and artificial: filament tow, staple fibres 0.097 0.000 0.108 0.027 0.026 0.039 0.000 0.031 0.015 0.000 0.001 0.020 0.023 0.015 0.029
551 Staple fibre; man made yarn, woven fabrics 0.000 0.000 0.002 0.086 0.039 0.003 0.000 0.001 0.000 0.016 0.102 0.204 0.001 0.355 0.058
560 Wadding of textiles, rubber thread, metalized and gimped yarn etc 13.763 5.449 3.271 0.753 1.579 0.453 0.084 0.239 0.167 0.370 0.367 0.514 0.573 1.238 2.059
570 Carpets and other textile floor covering 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.008 0.000 0.001
580 Woven, pile & chenille fabrics, towelling, gauze, tulles, label, etc 14.835 14.590 8.824 1.899 5.495 3.292 3.741 3.190 0.879 0.162 0.238 0.029 0.029 0.010 4.087
581 Embroidery in the piece of strips or in motifs 0.057 0.021 0.086 0.000 0.000 0.000 0.009 0.095 0.159 0.097 0.000 0.000 0.026 0.000 0.039
590 Textile fabrics ctd, nylon etc, linoleum etc, text wall, rubberized text etc. 0.000 0.084 0.418 0.123 0.124 0.237 0.000 0.000 0.000 0.005 0.000 0.025 0.009 0.000 0.073
591 Transmission or conveyor belts; text prod & articles for tech use 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.044 0.000 0.000 0.000 0.000 0.000 0.003
600 Fabrics, knitted/crocheted 0.589 1.127 0.841 0.094 0.754 1.182 1.513 0.880 0.985 0.108 0.090 0.033 0.044 1.684 0.709
Univers
ity of
Mala
ya
341
610 Women and man: coat,jacket, suits, undergarments, knitted/croch etc 0.000 0.002 0.047 0.000 0.008 0.000 0.001 0.019 0.066 0.009 0.035 0.014 0.159 0.076 0.031
611 Jerseys, babies garments, track suits, swimwear kintted/croch etc 0.664 0.042 0.024 0.035 0.000 0.000 0.004 0.015 0.043 0.006 0.004 0.005 0.214 0.032 0.078
620 Women and man:overcoat, jacket, dresses, undergarments etc 0.000 0.004 0.020 0.006 0.002 0.017 0.000 0.000 0.018 0.016 0.031 0.015 0.034 0.004 0.012
621 Track suits, ski suits and swimwear, handkerchief, tie, gloves etc 0.013 4.522 7.911 0.318 0.006 0.276 0.108 0.462 0.619 0.032 0.088 0.186 0.066 0.083 1.049
630 Blankets and travelling rugs, bed, table, curtains, sacks and bags, tents 0.019 0.130 0.915 0.576 0.020 0.041 0.131 0.230 0.125 0.073 0.132 0.264 0.174 0.072 0.207
631 Rags, scrap twine, cordage, rope 0.000 0.000 0.000 8.090 0.000 0.140 0.046 0.816 2.685 1.719 0.673 1.785 2.240 0.000 1.300
640 Footwear 0.056 0.006 0.004 0.001 0.002 0.000 0.003 0.001 0.000 0.002 0.000 0.006 0.000 0.000 0.006
650 Hat and Headgear etc 0.000 0.000 0.032 0.002 0.067 0.000 0.000 0.094 0.000 0.000 0.000 0.000 0.052 0.355 0.043
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