The effect of regional trade agreement to trade flow: evidence of trade creation and trade diversion of Asean – Japan free trade area

UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAM HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES VIETNAM THE NETHERLANDS VIETNAM –THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE EFFECT OF REGIONAL TRADE AGREEMENT TO TRADE FLOW: EVIDENCE OF TRADE CREATION AND TRADE DIVERSION OF ASEAN – JAPAN FREE TRADE AGREEMENT BY PHAM THI HIEN MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, December 2016 UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE EFFECT OF REGIONAL TRADE AGREEMENT TO TRADE FLOW: EVIDENCE OF TRADE CREATION AND TRADE DIVERSION OF ASEAN – JAPAN FREE TRADE AGREEMENT A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By PHAM THI HIEN Academic Supervisor: Prof Dr Nguyen Trong Hoai HO CHI MINH CITY, December 2016 DECLARATION This is to certify that that this thesis entitled “The effect of regional trade agreement to trade flow: Evidence of trade creation and trade diversion of ASEAN – Japan free trade agreement”, which is submitted in fulfillment of the requirements for the degree of Master of Art in Development Economics to Viet Nam – The Netherlands Program (VNP) The author hereby declares that she edit this thesis individually, using only stated resources and literatures To the best of my knowledge, my thesis does not violate anyone’s copyright as well as any proprietary rights which are fully acknowledge in accordance with the standard referencing practices HCMC, December 15th, 2016 Pham Thi Hien ACKNOWLEDGEMENT I am using this opportunity to express my gratitude to everyone who supports me during the master course time First and foremost, I would like to sincerely thank my research supervisor, Prof Dr Nguyen Trong Hoai who given to me a comprehensive guidance, great support and valuable advice during the thesis research process I am lucky person when every time I needed support or was in difficulties, he has open the door to welcome me and sent to me the prompt advice I also would like to thank my co-supervisor Dr Truong Dang Thuy for his enthusiastic support and precious suggestion, which help me overcome the challenges and difficulties in doing regression model, take me in the right direction I would like to express my gratitude to all lecturers of the Vietnam- Netherlands Program who have provided the interesting lessons to build my economic knowledge during this program In addition, I would like to express my appreciation to the VNP academic staffs for their feedback, cooperation during a long-period time I have learned here Besides, completing this work would be very difficult without the support from my best friends I am indebted to them for their help Moreover, I wish to thank all my fellow master students in VNP 21 class who share with me unforgettable memories in this program Last but not the least, there are also words of deep gratitude for my family who support spiritually and encourage continuously during my thesis writing and my life in general Table of Contents CHAPTER I: INTRODUCTION 1.1 Problem statement 1.2 Research objectives 1.3 Research questions 1.4 Research scope 1.5 Thesis structure CHAPTER LITERATURE REVIEW 2.1 Trade theories 2.2 Trade creation and trade diversion 2.2.1 Trade creation 2.2.2 Trade diversion 2.3 The gravity model in international trade 2.3.1 2.4 Theoretical framework 2.4.1 2.5 The origin of gravity model Theoretical support and theoretical equation Empirical support for effect of FTA to ASEAN 12 2.5.1 Empirical support for effect of AFTA to intra-bloc trade flow 12 2.5.2 Empirical support of effect of ASEAN + FTAs 13 2.6 Zero trade data problem 15 2.7 Chapter remark 17 CHAPTER 3: RESEARCH METHODOLOGY 18 3.1 Model specification and validity testing 18 3.1.1 Model specification 18 3.1.2 Model validity testing 22 3.2 Data and data sources 23 CHAPTER 4: RESEARCH FINDINGS AND DISCUSSION 25 4.1 Descriptive statistics of variables 25 4.2 Testing multicollinearity 28 4.3 Regression result 30 4.3.1 Comparison of estimator properties 30 4.3.2 Regression results 31 Chapter 5: Conclusion and policy recommendation 44 5.1 Conclusion 44 5.2 Policy implication 45 5.3 Limitations of the study 46 Reference 47 CHAPTER I: INTRODUCTION 1.1 Problem statement It is no doubt to saying that recently, regional trade agreements (RTA) have become a popular widespread trend in the international economic system, especially after Doha round of GATT/ WTO According to the definition of WTO, regional trade agreement, included free trade agreements (FTAs) and customs unions (CUs), are the negotiations of two or more parties, in which these participants agree to reduce their current custom barriers, such as tariffs, quotas Since early of the 1990s, RTAs have increased widespread According to reports of World Trade Organization (WTO), until February 2016, there are 625 notifications of RTAs and 419 in which were in force Regarding the Association of Southeast Asian Nations (ASEAN) is considered as a successful model of regionalism and the community is step by step greatly co-operating and integrating to the world economy In addition, Japan, an economy was growing rapidly, involving 17% to world economic in 2005 but reduced to only 6% in 2015 (IMF, 2015) However, her economic performance has a massive influence on the economy of the entire region For evidence, Japan is one of top three trading partners of ASEAN economies, especially Indonesia and the Philippines Before integrating into ASEAN regional economies, Japan was playing an important role in the regional development In the 1970s, 25% per total import and export values of ASEAN were doing with Japan Moreover, with lower cost in materials and labors, ASEAN markets were attractive destinations of capital investment flow from Japanese companies It generated work jobs and increased working wages, especially, with high technologies and high-trained employees, they provided a valuable opportunity for learning and transferring in this area during the 1980s to 1990s The increasingly integrated business need a major opportunity to strengthen linkages between ASEAN and Japan That is the reason for raising a needful talk about a regional agreement Since 2003, the government of Japan and the 10 countries of ASEAN completely signed the general framework of bilateral free trade agreement named ASEAN-Japan FTA (officially a comprehensive economic partnership), hereinafter referred as AJCEP At the end of December 2008, the last official round was finalized, an agreement signed among Asian countries, included: Brunei Darussalam, Cambodia, Indonesia, Laos PRD, Malaysia, Myanmar, Philippines, Singapore, Thailand, Vietnam and Japan has been forced, support multilateral trading by reducing the tariff The origin objectives of this FTA are to encourage free trade across the border in intrabloc ASEAN and Japan, strengthen Asian countries, Japan economic integration, enhance their economic in the world market, are transparent in trading procedure and maintain sustainability in the economic area It seems a major opportunity for high-tech and modern industries of Japan such as automobile, electronic, etc to enter ASEAN markets as well as encourage assembly line in regions for Japanese firms Statically, after trade agreement in force, in 2013, two-way trading volume obtained $229 billion compared with $128 billion in 2000 In this year, Japan reported 14% and 15% for import and export value to ASEAN, Thai Land ($22.5 billion), Indonesia ($ 32.2 billion) and Malaysia ($29.6 billion) are top three Asian biggest exporters to Japan (ASEAN Statistics, 2014) The notable products mainly exported from ASEAN to Japan are foods, manufactured goods, textiles, crude material Conversely, machinery and equipment transportation to gather with chemical and advanced technology manufacturing products are important to major export from Japan to ASEAN countries For example, according to Japan automobile Manufacturer Association statistics in 2014, about 47% Japanese cars, 80% truck vehicles and 85% buses were consumed as final products in ASEAN markets 1.2 Research objectives - The first research purpose of this study, in general, is to examine the effect of AJCEP to ASEAN economies in trade creation and trade diversion aspects with total export data - The second research objective is to examine the effect of AJCEP on sub-catalogues in particular: food products, agricultural products, manufactured products, Machinery and equipment of transportation and clothing and accessories and textile, fabric 1.3 Research questions According to numerous studies before, the effect of RTAs has no guarantee positive effect to help its member countries integrating with the global market In many cases, RTAs actually caused some negative effects Therefore, this study aims to find the answers to these questions following: - How the trade creation and trade diversion in general total export have been caused by the free trade agreement which was signed by AJCEP to ASEAN member countries? - How the trade creation and trade diversion have been affected by the free trade agreement which is by AJCEP to ASEAN member countries in the five sub-catalogues: food products, agricultural products, manufactured products, Machinery and equipment of transportation and clothing and accessories and textile, fabric? 1.4 Research scope To estimate the effect of AJCEP, we employ a panel data set will be collected with period from 2000 – 2015 with total 5,920 observations with included 09 ASEAN countries: Brunei Darussalam, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Singapore, Thailand, Vietnam and 15 biggest trading partners of Japan 2015 include: The United State, China, South Korea (Korea Rep.), Hong Kong SAR China, Australia, Saudi Arabia, The United Arab Emirates, Russian Federation, Switzerland, New Zealand, United Kingdom, Germany, Mexico, Netherland and Japan To our knowledge, there is the rapid development in investing effect of RTAs in theoretical as well as empirical accesses However, most of them are usually focus on general questions: whether or not RTAs have affected to trade flow or created trade creation, trade diversion There are two main problems that many previous studies had The first problem is estimation challenges of the gravity model which solve around the heteroscedasticity and the frequency of zero trade observations These problems cause challenges in concerning the most suitable estimation technique to avoid biased and un-misinterpreted result The second advantage is we estimate regression model by using two sets of trade flow data The first data set is aggregated data is used to examine for bilateral total export flow The second dataset is disaggregated data is optimized to estimate the AJCEP affect to five separate subcategories: agriculture, manufacturing, chemical industry, machinery, transportation industry and clothing and accessories and textile, fabric By two different approaches, we can analyze impacts of AJCEP in general and in the specific commodity in particular as well 1.5 Thesis structure After finishing introduction chapter, the rest of this paper is arranged as follow Chapter presents the literature review in trade theories in international trade flow, theoretical support of gravity model in international trade, empirical support in order so to see the development of contribution studies of AJCEP effect to ASEAN member as well as Japan In addition, this chapter reviews empirical support of the methods to solve the popular issue of frequency of zero trade data Chapter states methodology, model construction, model estimation methods and data scope that used in the study Chapter interprets the result and findings from the regression model Chapter summaries the thesis result and recommendation suggestion as well as limitation of the study standards, technical requirements, customs procedures, sensitive list products…are added to tackle in the negotiation round gradually Therefore, ASEAN should pay attention to the new trend of international development and the competitiveness of new regional initiatives to optimize the positive effect the integration causes 5.3 Limitations of the study Before ending this paper, we would like to show out the limitation of this study for future research on the impact of AJCEP to international trade The first limitation is the in-force time of AJCEP Comparing with ACFTA, AKFTA were in force 2002 and 2007 respectively, AJCEP was in force in December 2008 Therefore, with the limited time during the period from beginning 2008 to 2015, we can-not estimate the full long-term effects of AJCEP to ASEAN and Japan In addition, the target elimination time of AJCEP has been still lasted to 2018, we not have an overview of AJCEP effect The second limitation is the construction of the database We could not include some variables that would effect to bilateral trade significantly such as control variables for nontrade barriers, administration cost, RoOs, foods and safety standards… The last but not least limitation is the considering of precise of AJCEP content For many FTAs in general and AJCEP in particular, they have commitment schedule of elimination/ removal of FTAs tariffs rather than immediately after in force FTAs These phasing schedules should be incorporated to the analysis processing of impact of AJCEP as well as FTAs to have deeply understood the effect of tariff elimination gradually 46 Reference Aiken, D E 1973 Proecdysis, setal development, and molt prediction in the American lobster (Homarus americanus) J Fish Res Board Can 30: 1337–1344 Anderson, J E., & Marcouiller, D (2002) Insecurity and the pattern of trade: An empirical investigation Review of Economics and statistics, 84(2), 342-352 Anderson, J.E and E Van 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Std Err 0.0206301 0.0209659 0.0267363 0.0226067 0.0425662 0.0574424 0.1270826 0.127256 0.1215723 0.1025836 0.078642 0.0642604 0.7466247 Source: author’s estimation 51 t P>|t| 54.25 56.95 -0.19 -4.63 -36.56 15.82 3.55 2.17 -6.46 -7.37 -6.73 -14.19 -34.22 0.000 0.000 0.853 0.000 0.000 0.000 0.000 0.030 0.000 0.000 0.000 0.000 0.000 = 0.0000 = 0.7351 = 1.6441 [95% Conf Interval] 1.07882 1.152829 -0.0573625 -0.1489121 -1.639715 0.7961627 0.2018216 0.0270812 -1.023822 -0.9573927 -0.6837698 -1.037557 -27.01394 1.15971 1.235035 0.0474687 -0.0602726 -1.472816 1.021391 0.700105 0.5260444 -0.5471436 -0.5551685 -0.375419 -0.7855958 -24.08647 Table 16: Fixed effect model regression estimation result (Total export) Number of obs = 4701 Number of groups = Fixed-effects (within) regression Group variable: id Obs per group: = avg = 14.5 max = 16 F(7,324) = 93.90 Prob > F = 0.0000 R-sq: within = 0.4742 between = 0.4601 overall = 0.4847 Log total export Log GDP exporting country Log GDP importing country Log Population exporting country Log Population importing country Log distance Common language Colony Border Land-locked FTA_1 FTA_2 FTA_3 Constant 325 Coefficient 0.6690951 0.7029839 -0.1416827 0.3526593 0 0 -0.1692733 -0.1405741 0.0403717 -19.71186 Robust Std Err 0.0903103 0.105047 0.6214666 0.4283095 (omitted) (omitted) (omitted) (omitted) (omitted) 0.1030317 0.0614709 0.0662626 10.22266 Source: author’s estimation 52 t P>|t| [95% Conf Interval] 7.41 6.69 -0.23 0.82 -1.64 -2.29 0.61 -1.93 0.000 0.000 0.820 0.411 0.4914264 0.4963237 -1.364302 -0.4899595 - - - - - - - - - - - - - - - 0.101 0.023 0.543 0.055 -0.3719689 -0.2615066 -0.0899876 -39.82303 0.8467637 0.9096442 1.080936 1.195278 0.0334223 -0.0196415 0.1707311 0.3993135 Table 17: Random effect model regression estimation result (Total export) Number of obs = 4701 Number of groups = Obs per group: = avg = 14.5 max = 16 F(7,324) = 93.90 Prob > F = 0.0000 Random-effects GLS regression Group variable: id R-sq: within = 0.4721 between = 0.7068 overall = 0.6977 corr(u_i, X) = (assumed) Log total export Log GDP exporting country Log GDP importing country Log Population exporting country Log Population importing country Log distance Common language Colony Border Land-locked FTA_1 FTA_2 FTA_3 Constant Source: author’s estimation 325 Wald chi2(12) = 985.13 Prob > chi2 = 0.0000 Coefficient 0.6727227 0.7788964 0.2721261 0.1555137 -1.188552 1.517583 0.3895419 0.2126746 -1.727995 -0.2616835 -0.2035819 -0.0504345 -15.67725 Robust Std Err 0.0589658 0.0647758 0.1347648 0.1111275 0.1448908 0.2430654 0.5480772 0.5017454 0.4592858 0.1016957 0.0608571 0.0701266 2.774299 53 t P>|t| 11.41 12.02 2.02 1.4 -8.2 6.24 0.71 0.42 -3.76 -2.57 -3.35 -0.72 -5.65 0.000 0.000 0.043 0.162 0.000 0.000 0.477 0.672 0.000 0.01 0.001 0.472 0.000 [95% Conf Interval] 0.5571518 0.6519382 0.007992 -0.0622922 -1.472533 1.041184 -0.6846697 -0.7707282 -2.628179 -0.4610033 -0.3228597 -0.1878801 -21.11478 0.7882937 0.9058546 0.5362601 0.3733197 -0.9045712 1.993983 1.463754 1.196077 -0.8278114 -0.0623636 -0.0843042 0.0870112 -10.23972 Table 18: Hausman-Taylor estimator (Total export) Number of obs = 4701 Number of groups = Obs per group: = avg = 14.5 max = 16 Wald chi2(12) = 4267.28 Prob > chi2 = 0.0000 Hausman-Taylor estimation Group variable: id Random effects u_i ~ i.i.d Log total export Time-variant exogenous Log Population exporting country Log Population importing country Time-variant endogenous Log GDP exporting country Log GDP importing country FTA_1 FTA_2 FTA_3 Time-invariant exogenous Log distance Common language Colony Border Land-locked Constant 325 Coefficient Robust Std Err t P>|t| 0.4296208 0.4026711 0.0912479 0.0969341 4.71 4.15 0.000 0.000 0.2507782 0.2126838 0.6084634 0.5926584 0.6226404 0.6962608 -0.2003355 -0.1683645 0.0034543 0.0415624 0.0407571 0.0488492 0.0391921 0.0367949 14.98 17.08 -4.1 -4.3 0.09 0.000 0.000 0.000 0.000 0.925 0.5411796 0.6163784 -0.2960781 -0.2451797 -0.0686623 0.7041013 0.7761432 -0.1045929 -0.0915494 0.0755709 -0.7013101 1.566991 1.378114 0.5571814 -1.517171 -23.45649 0.1988263 0.3876302 0.5930089 0.6188225 0.4912172 3.456517 -3.53 4.04 2.32 0.9 -3.09 -6.79 0.000 0.000 0.020 0.368 0.002 0.000 -1.091002 0.8072493 0.2158382 -0.6556885 -2.479939 -30.23114 -0.3116177 2.326732 2.54039 1.770051 -0.554403 -16.68184 Source: author’s estimation 54 [95% Conf Interval] Table 19: Hausman-Taylor estimator (Total agricultural goods export) Number of obs = 4464 Number of groups = Obs per group: = avg = 13.9 max = 16 Wald chi2(12) = 2443.55 Prob > chi2 = 0.0000 Hausman-Taylor estimation Group variable: id Random effects u_i ~ i.i.d Log total agricultural goods export Time-variant exogenous Log Population exporting country Log Population importing country Time-variant endogenous Log GDP exporting country Log GDP importing country FTA_1 FTA_2 FTA_3 Time-invariant exogenous Log distance Common language Colony Border Land-locked Constant Source: author’s estimation 320 Coefficient Robust Std Err t P>|t| 0.8664666 0.3368013 0.1329026 0.1333158 6.52 2.53 0.000 0.012 0.6059823 0.075507 1.126951 0.5980956 0.484432 0.655748 0.015511 0.1813875 0.1650885 0.0592005 0.0576299 0.0685457 0.0551759 0.051858 8.18 11.38 0.23 3.29 3.18 0.000 0.000 0.821 0.001 0.001 0.3684011 0.5427955 -0.1188361 0.0732446 0.0634487 0.6004629 0.7687006 0.1498581 0.2895303 0.2667284 -0.5584736 1.715421 1.700751 1.274802 -2.069866 -29.59842 0.2702073 0.4988783 0.8022823 0.801647 0.6751415 4.890198 -2.07 3.44 2.12 1.59 -3.07 -6.05 0.039 0.001 0.034 0.112 0.002 0.000 -1.08807 0.7376376 0.1283065 -0.2963977 -3.393119 -39.18304 -0.0288771 2.693205 3.273195 2.846001 -0.7466133 -20.01381 55 [95% Conf Interval] Table 20: Hausman-Taylor estimator (Total manufactured products export) Number of obs = 4685 Number of groups = Hausman-Taylor estimation Group variable: id Obs per group: = avg = 14.4 max = 16 Wald chi2(12) = 3849.05 Prob > chi2 = 0.0000 Random effects u_i ~ i.i.d Log total manufactured goods export Time-variant exogenous Log Population exporting country Log Population importing country Time-variant endogenous Log GDP exporting country Log GDP importing country FTA_1 FTA_2 FTA_3 Time-invariant exogenous Log distance Common language Colony Border Land-locked Constant Source: author’s estimation 325 Coefficient Robust Std Err t P>|t| [95% Conf Interval] 0.960844 0.4045739 0.0949099 0.101675 10.12 3.98 0.000 0.000 0.774824 0.2052945 1.146864 0.6038534 0.5008785 0.8018104 -0.1799028 -0.1323354 -0.1204445 0.0454678 0.044832 0.0537679 0.0429367 0.0402769 11.02 17.88 -3.35 -3.08 -2.99 0.000 0.000 0.001 0.002 0.003 0.4117632 0.7139412 -0.2852859 -0.2164897 -0.1993857 0.5899938 0.8896795 -0.0745196 -0.048181 -0.0415033 -0.3342723 1.676608 2.747449 0.3562068 -0.7940927 -35.95877 0.1988127 0.3861688 0.5998992 0.6161129 0.4937604 3.551777 -1.68 4.34 4.58 0.58 -1.61 -10.12 0.093 0.000 0.000 0.563 0.108 0.000 -0.7239381 0.9197311 1.571668 -0.8513523 -1.761845 -42.92012 0.0553934 2.433485 3.92323 1.563766 0.1736599 -28.99741 56 Table 21: Hausman-Taylor estimator (Total chemical products export) Number of obs = 4450 Number of groups = Hausman-Taylor estimation Group variable: id Obs per group: = avg = 13.8 max = 16 Wald chi2(12) = 2367.84 Prob > chi2 = 0.0000 Random effects u_i ~ i.i.d Log total chemical product export Time-variant exogenous Log Population exporting country Log Population importing country Time-variant endogenous Log GDP exporting country Log GDP importing country FTA_1 FTA_2 FTA_3 Time-invariant exogenous Log distance Common language Colony Border Land-locked Constant Source: author’s estimation 323 Coefficient Robust Std Err t P>|t| [95% Conf Interval] 0.6695428 0.1067314 0.1531909 0.1565314 4.37 0.68 0.000 0.495 0.3692943 -0.2000645 0.9697914 0.4135274 0.7474003 0.8092239 0.0870771 0.0139498 -0.1381347 0.0671749 0.065669 0.0776045 0.0627119 0.0588048 11.13 12.32 1.12 0.22 -2.35 0.000 0.000 0.262 0.824 0.019 0.6157399 0.680515 -0.065025 -0.1089633 -0.2533899 0.8790607 0.9379328 0.2391791 0.136863 -0.0228794 -0.703089 1.877265 1.501016 0.6925626 -1.807243 -32.21257 0.3273248 0.6160669 0.9659669 0.9893473 0.8052378 5.73397 -2.15 3.05 1.55 0.7 -2.24 -5.62 0.032 0.002 0.120 0.484 0.025 0.000 -1.344634 0.669796 -0.3922442 -1.246522 -3.38548 -43.45095 -0.0615441 3.084734 3.394276 2.631648 -0.2290058 -20.9742 57 Table 22: Hausman-Taylor estimator (Total machinery and transport equipment products export) Number of obs = 4576 Number of groups = Hausman-Taylor estimation Group variable: id Obs per group: = avg = 14.2 max = 16 Wald chi2(12) = 2726.95 Prob > chi2 = 0.0000 Random effects u_i ~ i.i.d Log total machinery and transport equipment product export Time-variant exogenous Log Population exporting country Log Population importing country Time-variant endogenous Log GDP exporting country Log GDP importing country FTA_1 FTA_2 FTA_13 Time-invariant exogenous Log distance Common language Colony Border Land-locked Constant Source: author’s estimation 323 Coefficient Robust Std Err 0.7917668 0.1260856 0.2625055 0.1336605 t P>|t| [95% Conf Interval] 6.28 1.96 0.000 0.050 0.5446435 0.0005358 1.03889 0.5244752 0.747688 0.7255829 -0.3006256 -0.0042431 -0.105 0.0583981 0.0574021 0.0685096 0.0548692 0.0516781 12.8 12.64 -4.39 -0.08 -2.03 0.000 0.000 0.000 0.938 0.042 0.6332299 0.6130769 -0.4349019 -0.1117849 -0.2062871 0.8621462 0.8380888 -0.1663492 0.1032986 -0.0037128 -0.5284197 2.303365 2.244035 0.4113427 -0.9729046 -34.55316 0.2689517 0.5102003 0.7983332 0.8165978 0.6595691 4.777025 -1.96 4.51 2.81 0.5 -1.48 -7.23 0.049 0.000 0.005 0.614 0.140 0.000 -1.055555 1.303391 0.679331 -1.189159 -2.265636 -43.91596 -0.0012841 3.303339 3.808739 2.011845 0.319827 -25.19037 58 Table 23: Hausman-Taylor estimator (Total Cloth, accessories and textiles and fabric products export) Number of obs = 4506 Number of groups = Hausman-Taylor estimation Group variable: id Obs per group: = avg = 14.0 max = 16 Wald chi2(12) = 710.61 Prob > chi2 = 0.0000 Random effects u_i ~ i.i.d Log total Cloth, accessories and textile and fabric products export Time-variant exogenous Log Population exporting country Log Population importing country Time-variant endogenous Log GDP exporting country Log GDP importing country FTA_1 FTA_2 FTA_3 Time-invariant exogenous Log distance Common language Colony Border Land-locked Constant Source: author’s estimation 322 Coefficient Robust Std Err t P>|t| [95% Conf Interval] 0.7173523 0.3196175 0.1402635 0.1452437 5.11 2.2 0.000 0.028 0.4424409 0.0349451 0.9922636 0.6042899 0.2999062 0.5369363 -0.2615986 -0.2361215 -0.2030816 0.0638324 0.0625458 0.0746417 0.0595095 0.056752 4.7 8.58 -3.5 -3.97 -3.58 0.000 0.000 0.000 0.000 0.000 0.1747969 0.4143488 -0.4078937 -0.3527579 -0.3143135 0.4250154 0.6595239 -0.1153035 -0.119485 -0.0918497 -0.6758808 1.463656 1.444672 0.396464 -1.983899 -18.45476 0.3024518 0.5880272 0.9001723 0.9414727 0.7800677 5.189873 -2.23 2.49 1.6 0.42 -2.54 -3.56 0.025 0.013 0.109 0.674 0.011 0.000 -1.268675 0.3111436 -0.3196331 -1.448789 -3.512804 -28.62672 -0.0830861 2.616168 3.208978 2.241717 -0.4549947 -8.282795 59 60