Determinants of provincial FDI in vietnam a cross section data analysis

L'N'IXYRSITY OF ECON’OMICS INSTITUTE OF SOIAL STL'DIES HO CHI MINH CITV THE HAGIJE VIETNAM THE NETHERLANDS VIETNAM-NETHERLANDS › PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DETERMINANTS OF PROVINCIAL FDI IN VIETNAM: A CROSS SECTION DATA ANALYSIS A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By NGUYEN DAI HIEP Academic Supervisor: Dr NGUYEN VAN PHUC MO CIII MINH CITY, JANUARY 2011 DECLARATION I declare that ‘Determinants of provincial FDI in Vietnam: A cross section data analysis’ is my own work, that it has not been submitted for any degree or examination at any other University, and that all sources used or quoted are indicated and knowledge by complete references January 3, 2011 NGUYEN DAI HIEP ACKNOWLEDGMENTS This thesis would never have been written if had not for the encouragement, support, and assistance which I received from large number of people Specially, I would like to thank my supervisor, Dr Nguyen Van Phuc, for his encouragement, kindness, patience and valuable advices, which helped shape and improve this thesis I would also like to thank a few anonymous referees and added explanatory variables who helped me finalize this work I would also like to sincerely thank Prof Dr Peter Calkins for his honest and valuable advices from I begin to choose the topic and TRD completion He is truly a noble teacher, who soonest feedback and detail instruction during TRD establishing I would also like to thank science committee; all the members of the VietnameseDutch Project for MA programme in Development Economics, University of Economics-HCMC, Viet Nam for their support and goodwill, and to all the lecturers, and also to my friends in the class 15.Thank you a great time! Last, I want to thank my family members, friends Any errors and omissions in this thesis are my sole responsibility TABLE OFCONTENTS Declaration Acknowledgements .3 Table of contents Table list Abstract Chapter 1: Introduction .8 1.1 Problem Statement 1.2 Research Objectives 1.3 Research questions .9 1.4 Organization of the study .9 Chapter 2: Theoretical Consideration and Literature Review 11 2.1 The regional development and competitive regionalism theory 11 2.2 FDI theories and its applicability 11 • 2.2 Capital Theory 11 2.2.2 The International Trade Arguments 12 2.2.3 Market Failures and Industrial Organization .13 2.2.4 The Eclectic Paradigm and International Investment Path 13 2.2.5 Agglomeration Effect 14 2.3 Empirical studies on the determinants of FDI 17 2.4 Geographical literature on Vietnam, China and ASEAN countries 19 Chapter 3: Research Model, Data Collection and Variable Description 24 3.1 Model Specification 24 3.2 Data Collection 25 3.3 Variables description 26 Chapter 4: Empirical Estimation and Result 34 4.1 Correlation among explanatory variables .34 4.2 Empirical estimation and result 35 Chapter 5: Conclusion and Recommendation .42 5.1 Conclusion and recommendation 42 5.2 Limitation 43 References 45 Appendices 49 , TABLE LIST Table 2.1: Theory summary .15 Table 2.2: Empirical Study Reading 22 Table 3.1 : The implementation value of provincial FDI 26 Table 3.2: FDI capital of top ten provinces .26 Table 3.3: PCI result in 2009 .27 Table 1: Matrix of Correlation among explanatory variables 34 Table 4.2: Regression Results 36 Table 4.3: Top five rank of attracting FDI in Viet Nam .38 Table 4.4: The rank of infrastructure in 2009 39 ABSTRACT FDI is of essential importance for achieving economic growth for developing countries, especially for Vietnam, a country which has just opened more than twenty years There were too many researches about attracting FDI for developing countries However, there are still less researches related to regional competition of FDI Therefore, this paper examines the relationship between provincial FDI in Viet Nam and explanatory variables base on variable set of PCI project in Viet Nam and other traditional variables The purpose of thesis is finding why some provinces and cities such as Binh Duong, Dong Nat, Ba Ria Vung Tau, HCMC .have had good FDI capital and others have not so From that the thesis suggests policy recommendation for provinces and cities enhancing regional system for developing economics I had a literature review on regional development, attracting regional FDI and across country, the estimated model was built with collected data and econometric analysis result, I had demonstrated that our hypotheses are right or wrong And then we answered the Tesearch questions and objectives of this study Using data collected by the General Statistical Office of Viet Nam (GSO) and Provincial Competition Index (PCI) project, estimation result shows that gross industrial output, legal institution and infrastructures statistically significant to provincial FDI at the level 1% and 5%; business support service had significance to provincial FDI at the level nearly 10% Key words: PCI, FDI impact, Provinces in Viet Nam, cross section data analysis 1.1Problem Statement The Provincial Competitiveness Index (PCI) is an effort to explain why some parts of the country perform better than others in terms of private sector dynamism, job creation and economic growth and attracting investment (FDI and local) Using new survey data from businesses that describe their perceptions of their local business environments as well as credible and comparable data from official and other sources regarding local conditions, the PCI rates provinces on a 100-point scale In 2005, the overall index is comprised of nine sub-indices that explain much of the variation in performance across provinces in Vietnam In 2006, new sub-indices were developed to capture other aspects of Provincial Government efforts to enhance the business environment However, we have not found any empirical studies to show that which are independent variables of PCI and other traditional variables effect to provincial FDI and how to impact to provincial FDI in Viet Nam I also did not find any analysis related to the independent variables of PCI whether they have internal relation 1.2Research Objectives The overall goal of this research is to investigate significant impacts of some independent variables of PCI and other traditional variables which affect provincial FDI inflows (Regional FDI) to help policy makers to focus on key points and the good points to improve their investment environment (by Provinces) and with higher level (by Government) There cxist somG previous studies related to attracting FDI to developing countries; most of these have found what factors of the country attracting FDI (across countries) However, the objectives of the thesis are to identify: (i) Independent variables of PCI and other traditional variables are significant impacts to FDI of Provinces in Vietnam; and (ii) Factors of PCI are highly correlated and we should revise PCI set (iii) PCI determinants out of the ten original factors should be included in a new, more significant subset base of PCI determinants (iv) Interaction effects between PCI improvement and FDI growth 1.3 Research questions The thesis focus on studying the determinants of provincial FDI in Viet Nam base on the independence variable set of the Provincial Competitiveness Index (PCI) and other some traditional variables could be attracting FDI of provinces in Viet Nam We found economic theory, and empirical studies related to FDI (chapter 2), the description of each independence variable which PCI project in Viet Nam use to survey (chapter 3) We build research model (specification) and collect the data from PCI project (www.pcivietnam.org) and statistical yearbook of Vietnam from General Statistics Office (www.gso.gov.vn) to answer some research questions as following: (1)Which independent variables of PCI and other traditional variables are significant impacts to FDI of Provinces in Vietnam? (2) Factors of PCI are highly correlated and we should revise PCI set? (3) Which PCI determinant out of the ten original factors should be included in a new more significant subset base of PCI determinants? (4) Are interaction effects between PCI improvement and FDI growth? 1.4 Organization of the study This thesis has five chapters, while the chapter one has presented as above explain the purpose chose the theme The rest of this thesis is organized as follows: Chapter two briefly provides the regional development and FDI theory, and then we also have summarized the empirical researches related to attracting FDI, specially related to attracting FDI across to provinces of the country Chapter three is presented how to build the research model base on chapter two, the way to choose the data It is important to explain dependent and independent variables which PCI project have used to survey yearly, also including some traditional variables Chapter four is the econometric analysis and finding The last chapter will be conclusion and recommendation of the research survey yearly, point—I to 10 2006-2009 projectViet Nam Proactivity of Provincial Leadership of PPL 1l TAI TCRC 13 MS PCI each province, survey yearly, point-1 to 2006-2009 project- 10 Viet Nam Transparency and Access to Average from PCI Information of each province, survey 2006-2009 project- yearly, point-1 to 10 Viet Nam Time Costs of Regulatory Compliance 12 Average from Average from PCI of each province, survey yearly, point=1 2006-2009 project- to 10 Viet Nam Retail sales of goods and services at Average from current prices by province 2006-2009 50 GSO Table 2: Expected effect of independent variables No Notation Name of Variables AL Access to Land of each province + BSS Business Support Service of each province, + EC Entry Costs of each province IC Informal Charge of each province INF IP Gross output of industry LI Legal Institution of each province LT Labour Training of each province PPL Infrastructure of each province Proactivity of Provincial Leadership of each province 10 TAI Transparency and Access to Information of each province lI TCRC Time Costs of Regulatory Compliance of each province 12 MS Market Size Expected sign Table R3.1 OLS result: General Estimation , Dependent Variable: FDI Method: Least Squares Date: 11/28/10 Time: 07:52 Sample: 63 Included observations: 63 Variable Coefficient Std Error t-Statistic Prob c -549.2492 473.3872 -1.160254 0.2515 AL -58.81156 40.52070 -1.451395 0.1529 BSS -56.72349 42.86048 -1.323445 0.1917 EC 27.09780 45.87978 0.590626 0.5574 IC 23.66403 60.37637 0.391942 0.6968 INF 6.806537 3.462824 1.965603 0.0549 IP 0.011343 0.001623 6.990285 0.0000 LI 98.75612 42.98600 2.297402 0.0258 LT -33.07042 31.26290 -1.057817 0.2952 PPL -6.798794 27.04513 -0.251387 0.8025 TAI 22.33385 38.06656 0.586705 0.5600 TCRC 21.30427 35.70395 0.596692 0.5534 KEA -14.45187 77.72050 -0.185947 0.8532 R-squared 0.756475 Mean dependent var 109.6462 Adjusted R-squared 0.698029 S.D dependent var 277.7646 S.E of regression 152.6369 Akaike info criterion 13.07559 Sum squared resid 1164902 Schwarz criterion 13.51782 -398.8810 Hannan-Quinn criter 13.24952 F-statistic 12.94314 Durbin-Watson stat 1.524842 Prob(F-statistic) 0.000000 Log likelihood 52 Table R3.2 Regression No.02 , Dependent Variable: FDI Method: Least Squares Date: 1/28/10 Time: 07:55 Sample: 63 Included observations: 63 Coefficient Std Error t-Statistic Prob Variable c AL -480.5299 410.8795 -1.169515 0.2475 -60.00294 38.17154 -1.571929 0.1220 BSS -56.41570 41.12630 -1.371767 0.1760 EC 27.22179 44.93207 0.605843 0.5473 IC 14.95326 53.10300 0.281590 0.7794 INF 6.579613 2.760459 2.383522 0.0208 IP 0.011124 0.001394 7.978977 0.0000 LI 94.10527 37.40989 2.515519 0.0150 LT -32.71414 30.16600 -1.084470 0.2832 TAI 19.48059 35.97586 0.541491 0.5905 TCRC 21.93116 34.88220 0.628721 0.5323 R-squared 0.755947 Mean dependent var 109.6462 Adjusted R-squared 0.709013 S.D dependent var 277.7646 S.E of regression 149.835 I 13.01426 Sum squared resid 1167428 Schwarz criterion Log likelihood -398.9493 F-statistic 16.10682 Prob(F-statistic) 0.000000 Akaike info criterion 13.38846 Hannan-Quinn criter 13 16144 Durbin-Watson stat 1.508808 Table R3.3 Regression No.03 Dependent Variable: FDI Method: Least Squares Date: l 1/28/10 Time: 07:57 Sample: 63 Included observations: 63 Variable Coefficient Std Error t-Statistic Prob c AL -447.5560 -47.88471 368.1538 31.23973 -1.215677 -1.532815 0.2294 0.1312 BSS -42.86376 33.25264 -1.289033 0.2029 EC 28.52452 43.85878 0.650372 0.5182 INF 6.318169 2.689276 2.349394 0.0225 IP 0.011003 0.001360 8.091305 0.0000 LI 94.53679 35.26903 2.680447 0.0097 LT -28.45041 28.98503 -0.981555 0.3307 TCRC 24.79147 33.98543 0.729474 0.4689 R-squared 0.754023 Mean dependent var 109.6462 Adjusted R-squared 0.717582 S.D dependent var 277.7646 S.E of regression 147.6124 Akaike info criterion 12.95862 Sum squared resid 1176629 Schwarz criterion 13.26478 Log likelihood -399.1965 Hannan-Quinn criter 13.07904 F-statistic 20.69163 Durbin-Watson stat 1.493211 Prob(F-statistic) 0.000000 54 Table R3.4 Regression No.04 Dependent Variable: FDI Method: Least Squares Date: 11/28/10 Time: 07:58 Sample: 63 Included observations: 63 Variable , - Coefficient Std Error t-Statistic Prob c -211.4629 203.2044 -1.040641 0.3025 AL -44.83035 30.53984 -1.467930 0.J 477 BSS -37.33395 32.30533 -1.155659 0.2527 INF 6.596859 2.579005 2.557909 0.0133 IP 0.010739 0.001296 8.283895 0.0000 LI 101.1162 34.01125 2.973022 0.0043 LT -19.93587 27.10756 -0.735436 0.4651 R-squared 0.750307 Mean dependent var 109.6462 Adjusted R-squared 0.723554 S.D dependent var 277.7646 S.E of regression 146.0434 Akaike info criterion 12.910 12 Sum squared resid 1194406 Schwarz criterion Lop likelihood 13.14825 -399.6689 Hannan-Quinn criter 13.00378 F-statistic 28.04590 Durbin-Watson stat 1.467836 Prob(F-statistic) 0.000000 Table R3.5 Regression No.05 Dependent Variable: FDI Method: Least Squares Date: 11/28/10 Time: 08:00 Sample: 63 Included observations: 63 Variable Coefficient Std Error I-Statistic Prob c -218.1488 202.1817 -1.078974 0.2851 AL -44.00827 30.39622 -1.447821 0.1531 BSS -48.13647 28.65678 -1.679759 0.0985 INF 6.159920 2.499510 2.464451 0.0168 IP 0.010838 0.001284 8.440153 0.0000 LI 95.47022 32.99978 2.893056 0.0054 R-squared 0.747895 Mean dependent var 109.6462 Adjusted R-squared 0.725781 S.D dependent var 277.7646 S.E of regression 145.4540 Akaike info criterion 12.88799 Sum squared resid 1205942 Schwarz criterion 13.09210 Log likelihood -399.9717 Hannan-Quinn criter F-statistic 33.81932 Prob(F-statistic) 0.000000 Durbin-Watson stat 56 12.96827 1.467968 Table R3.6 Regression J's'o.06 Dependent Variable: FDI Method: Least Squares Date: 11/28/10 Time: 08:03 Sample: 63 Included observations: 63 Variable Coefficient Std Error t-Statistic Prob c BSS -425.0812 -47.33038 144.3463 28.92085 -2.944870 -1.636549 0.0046 0.1071 INF 5.968698 2.519495 2.369006 0.0212 IP 0.011305 0.001255 9.009201 0.0000 LI 80.02072 31.52059 2.538681 0.0138 R-squared 0.738624 Mean dependent var Adjusted R-squared 0.720598 S.D dependent var 277.7646 S.E of regression 146.8221 12.89236 Sum squared resid 1250291 Schwarz criterion Akaike info criterion 109.6462 13.06245 Lop likelihood -401 1093 Hannan-Quinn criter 12.95926 F-statistic 40.97567 1.480202 Prob(F-statistic) 0.000000 Durbin-Watson stat 57 Table 4: The White Heteroskedasticity Test (No cross terms) , White Heteroskedasticity Test: F-statistic 1.655384 Probability 0.080879 Obs*R-squared 31.12148 Probability 0.119838 Test Equation: Dependent Variable: RESID‘2 Method: Least Squares Date: 11/28/10 Time: 23:25 Sample: 63 Included observations: 63 Variable , Coefficient Std Error Prob C AL 1181520 224840.1 3221604 310916.5 0.366749 0.723153 0.7158 0.4739 AL°2 -18251.90 25041.06 -0.728879 0.4704 BSS 173714.7 17 ld 10.6 1.012261 0.3177 BSS°2 -24185.85 18183.94 -1.330066 0.1912 EC -239308.0 704856.2 -0.339513 0.7360 EC°2 15750.55 44351.78 0.355128 0.7244 Ic 236931.9 439033.8 0.539667 0.5925 IC°2 -16971.77 33208.46 -0.511068 0.6122 INF - 15587.33 14130.50 -1.103099 0.2767 INFº2 162.7767 141.7105 1.148656 0.2577 IP 5.496573 2.822001 1.947757 0.0587 IP°2 -1.84E-05 2.27E-05 -0.811153 0.4222 LI -258417.7 227961.7 -1.133601 0.2639 LIº2 32203.45 24910.96 1.292742 0.2037 LT 73823.70 103656.9 0.712193 0.4806 LT°2 -7511.556 10190.74 -0.737097 0.4655 PPL 70854.75 91090.23 0.777852 0.4413 PPL°2 -8628.330 8108.898 -1.064057 0.2938 TAI -133598.0 126110.8 -1.059370 0.2959 TA1º2 15280.56 11649.50 1.311693 0.1973 TCRC -496289.2 238223.7 -2.083291 0.0438 TCRC°2 48021.71 21844.30 198363 0.0339 KEA -19626.68 51982.02 -0.377567 0.7078 R-squared Adjusted R-squared 0.493992 195577 Mean dependent var S.D dependent var 18490.50 94593 17 S.E of regression 84840.28 Akaike info criterion 25.81726 Sum squared resid 2.81E+ 11 Schwarz criterion 26.63369 Log likelihood -789.2437 F-statistic 1.655384 Prob(F-statistic) 0.080879 Durbin-Watson stat 1.501341 P-val ue — I 19> 5% , No HET in this model 59 Table 5: The Wald Test Wald Test: Equation: Untitled Test Statistic Value df Probability F-statistic 1.319975 (8, 50) 0.2555 Chi-square 10.55980 0.2279 Value Std Err C(l) -549.2492 C(3) -56.72349 473.3872 42.86048 C(4) 27.09780 45.87978 C(8) 98.75612 42.98600 C(9) -33.07042 31.26290 C(I 0) -6.798794 27.04513 Null Hypothesis Summary: Normalized Restriction (= 0) • C(11) 22.33385 38.06656 C(12) 21.30427 35.70395 Restrictions are linear in coefficients P-value F = 0.2279 > 5% —-• Fail to reject Ho —-• Sellecting the simple model 60 Tilblé 6: Correlogram Q-Statistics Date: I/29/I Time: 00: 19 Sample: 63 Included observations: 63 Autocorrelation Partial Correlation AC PAC Q-Stat -0.085 0.018 -0.085 0.010 0.4809 0.5015 0.488 0.778 -0.004 -0.002 0.5028 0.918 0.110 0.ll0 1.3456 0.854 0.091 0.112 1.9306 0.859 -0.027 -0.012 1.9811 0.921 -0.046 -0.054 2.1372 0.952 -0.088 -0.115 2.7181 0.951 -0.008 -0.051 2.7230 0.974 10 0.013 0.006 2.7353 0.987 11 0.053 0.080 2.9587 0.991 12 -0.027 0.025 3.0153 0.995 l3 -0.164 -0.150 5.2269 0.970 14 0.056 0.016 5.4903 0.978 IS -0.023 -0.044 5.5359 0.987 16 -0.036 -0.065 5.6495 0.991 17 -0.043 -0.011 5.8136 0.994 18 -0.246 -0.235 11.319 0.880 19 -0.010 -0.060 11.329 0.912 20 -0.042 -0.044 11.500 0.932 21 0.004 -0.012 11.501 0.952 22 -0.142 -0.097 13.523 0.918 23 -0.037 -0.028 13.661 0.936 24 0.084 0.096 14.408 0.937 25 0.078 0.071 15.067 0.940 26 -0.033 -0.068 15.190 0.954 27 0.001 0.004 15.190 0.967 28 0.076 0.041 15.863 0.968 AR does not exist in this model 61 Prob Table 7: Matrix of Correlation among Explanatory variables AL BSS AL l 000000 -0.06113 BSS -0.060361 EC LI LT PPL TAl TCRC MS 0.339452 0.018306 0.456193 11.232489 156726 -0.252539 127156 0.5873 44 -0.023645 -0.279 786 1.000000 0.2 14889 185477 0.755183 0.6 10939 0.302026 0.728165 0.509042 0.752013 0.543298 0.527710 127156 0.214889 1.000000 155114 109491 -0 126805 0.338421 0.336528 0.289464 0.2977 0.0825 89 -0 161585 IC 0.587344 185477 155114 1.000000 156503 -0 130 I l 0.477916 0.280546 0.629927 0.370366 0.343537 -0 133767 INF -0.023645 0.755183 109491 156503 1.000000 0.543 151 0.274197 0.651423 0.3503 88 0.532088 0.566604 0.442 128 IP -0.279786 0.610939 -0 126805 -0 113011 0.543151 1.000000 0.012219 0.383837 0.196515 0.315223 0.272102 0.885623 LI 0.339452 0.302026 0.338421 0.477916 0.274197 0.012219 1.000000 0.392201 0.643586 0.316825 0.343543 -0.0452 19 LT 0.0 18306 0.728165 0.336528 0.280546 0.651423 0.383837 0.392201 1.000000 0.515889 0.652770 0.57006 I 0.324225 PPL 0.456193 0.509042 0.289464 0.629927 0.350388 196515 0.643586 0.515889 I 000000 0.628578 0.436839 188026 TAI 0.232489 0.7520 13 0.297717 0.370366 0.532088 0.315223 0.3 16825 0.652770 0.628578 1.000000 0.502590 0.281665 TCRC 156726 0.543298 0.0825 89 0.343537 0.566604 0.272 102 0.343543 0.570061 0.436839 0.502590 1.000000 108097 MS -0.252539 0.5277 10 -0 161585 -0.13 3767 0.442 128 0.885623 -0.045219 0.324225 188026 0.281665 108097 1.000000 62 Table 8: log estimation b42tw en PCI and pFDI Dependent Variable: Log(FDI) Method: Least Squares Date: l l/18/10 Time: 23: 18 Sample (adjusted): 62 Included observations: 62 after adjustments Variable Coefficient Std Error t-Statistic Prob * i c -35.88196 8.563074 -4.190313 0.0001 Log(PCI) 9.593381 2.136220 4.490821 0.0000 R-squared 0.251567 Mean dependent var 2.555023 Adjusted R-squared 0.239093 S.D dependent var 2.380918 S.E of regression 2.076874 Akaike info criterion 4.331331 Sum squared resid 258.8044 Schwarz criterion 4.399949 F-statistic 20.16747 Prob(T-statistic) 0.000033 Log likelihood Durbin-Watson stat ' -132.2713 0.451771 63 ...DECLARATION I declare that ? ?Determinants of provincial FDI in Vietnam: A cross section data analysis? ?? is my own work, that it has not been submitted for any degree or examination at any other... relationship of FDI in Malaysia are the community, availability of raw materials and fuel 21 , Table 2.2: Empirical Study Reading Xu et Spatial Determinants of Inward agglomeration al FDI in China: Evidence... provincial FDI and attracting FDI of Vietnam Vietnam’s supporting industries were far less developed than other ASEAN countries like Thailand, Malaysia and Indonesia, he said Vietnamese firms are