UNIVERSITY OF ECONOMICS ERAMUS UNIVERSITY ROTTEDAM HO CHI MINH CITY INSTITUTE OF SCOCIAL STUDIES VIETNAM THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DIRECT, INDIRECT AND TOTAL EFFECT IN SPATIAL ANALYSIS OF PROVINCIAL FDI IN VIETNAM BY LE VAN THANG HO CHI MINH CITY, November 2016 UNIVERSITY OF ECONOMICS ERAMUS UNIVERSITY ROTTEDAM HO CHI MINH CITY INSTITUTE OF SCOCIAL STUDIES VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DIRECT, INDIRECT AND TOTAL EFFECT IN SPATIAL ANALYSIS OF PROVINCIAL FDI IN VIETNAM BY LE VAN THANG ACADEMIC SUPERVISOR DR. NGUYEN LUU BAO DOAN HO CHI MINH CITY, November 2016 DECLARATION “This is to certify that this thesis entitled “Direct, Indirect and Total effect In Spatial Analysis of Provincial FDI in Vietnam”, which is submitted by me in fulfillment of the requirements for the degree of Master of Art in Development Economics to the Vietnam – The Netherlands Programme (VNP). The thesis constitutes only my original work and due supervision and acknowledgement have been made in the text to all materials used.” Le Van Thang i ACKNOWLEDGEMENT This thesis could not be accomplished without the supporting and the motivation that I have received from many people. It is a pleasure to convey my gratitude to them all in my humble acknowledgment.
Foremost, I would like to express my sincere appreciation to Dr. Nguyen Luu Bao Doan, my supervisor. He gave me the greatest supporting, energetic assistance and valuable guidance as well as an infinite patient to encourage me to complete my very first research. Nguyen Luu Bao Doan, this study would never finish.
Besides, I also would like to give my gratitude to the Vietnam- Netherland Programme, especially to all lecturers who provided me valuable knowledge, VNP staffs for their restless assistant for the time I have been studying in VNP as well as School of Economics. I would love to express my gratefulness to Prof. Nguyen Trong Hoai and Dr. Pham Khanh Nam for the first suggestion to encourage me to deal with a novelty field of my knowledge - spatial analysis.
Moreover, I would like to give my sincere thankfullness to Dr. Pham Khanh Nam who has provided a valuable data source for me to complete this thesis. Besides that, I would like to thank all my friends, my fellows at the University of Economics, Ho Chi Minh City, my groups and all the classmates in K20-VNP. All of them are always be my side encourage and support me to complete the thesis.
Finally, I would like to send my gratefulness to my father, my mother, my two little brother, sister- Van Nam and Thuy Linh for their love, sacrifice, tremendous support for me not only to complete this thesis but also for my whole life. ii ABBREVIATION AIC: Akaike Information Criteria ESDA: Exploratory Spatial Data Analysis EU: European Union FDI: Foreign Direct Investment GDP: Gross Domestic Product GSO: General Statistical Official GRP: Gross Regional Product PCI: Provincial Competitiveness Index LM test: Lagrange Multiplier test MPI: Minister of Planning and Investment MNE: Multinational Enterprises SAR: Spatial Autoregressive Model SDM: Spatial Durbin Model SEM: Spatial Error Model USAID: The United States Agency for International Development VCCI: Chamber of commerce and industry VIF: Variance Inflation Factor iii ABSTRACT This paper investigates the spatial pattern of Foreign Direct Investment (FDI) for all 63 provinces in Vietnam from 2011 to 2014. Empirical studies on locational determinants of FDI typically neglected the spatial interaction among observations which lead to inefficient and biased estimations. Indeed, Moran’s I suggested by Moran, which is used to detect the spatial autocorrelation in data pattern of both dependent and independent variables, give hints of the necessity of spatial econometrics in analyzing the FDI determinants.
Through General To Specific approach, the Spatial Durbin Model (SDM) has been chosen as the most appropriate model, compared with other models like Non-spatial model, Spatial- Autoregressive Model (SAR) and Spatial Error Model (SEM). This study finds that the FDI flow into one province negatively spatially affects FDI inflow in remaining provinces. Moreover, by applying SDM, this paper econometrically estimates the impact of host province’s determinants and its neighbor determinants on its FDI inflow. Keywords: Foreign Direct Investment, Moran’s I, Spatial analysis iv CONTENTS DECLARATION .iv LIST OF FIGURE.
vii LIST OF TALBE. viii CHAPTER 1: INTRODUCTION .4 Scope of the study. 4 CHAPTER 2: OVERVIEW OF FDI IN VIETNAM .1 Stages of foreign direct investment in Vietnam .2 Distribution of foreign direct investment among provinces.3 Country of origin .4 Sectors of foreign direct investment. 11 CHAPTER 3: LITERATURE REVIEW .1 Theories about location choices of foreign direct investment.1 The eclectic paradigm OLI .2 Agglomeration and foreign direct investment .2 The inter-dependence of FDI between locations.1 MNE choice theory.1 Empirical studies of FDI determinants in spatial analysis.2 Empirical studies of FDI determinants in Vietnam .3 Fundamental FDI determinants.
26 CHAPTER 4: DATA AND METHODOLOGY .2 Spatial econometric model .1 Spatial Autoregressive Model .2 Spatial Error Model .3 Spatial Durbin Model .4 Marginal effect in Spatial Durbin Model .3 Pre-test for spatial existent with Moran’s I .4 Spatial weight matrix .5 Comparisons of models. 46 CHAPTER 5: EMPIRICAL RESULT.3 Limitation and future research. 64 vi LIST OF FIGURE Figure 2.1: Registered, implement FDI (million USD) and Number of FDI projects .2: The distribution of FDI in Vietnam from 1988 to 2014 .3: The sector distribution of FDI .1: Analytical framework of FDI and determinants.1: General to Specific strategy .1: The Local Moran’s I of FDI inflow Vietnam in 2011-2012-2014. 49 vii LIST OF TALBE Table 2.1: Sharing of FDI in Vietnam from 1988 to 2014 .2: Top ten countries of origin of FDI in Vietnam .1: Multinational Enterprise Motivation .1: The variable descriptive .2: The summary statistics of variables .1: The Moran’s I coefficient of FDI .2: The Moran’s I coefficient of explanatory variables .3: The AIC value.4: The Marginal effect of Spatial Durbin Model.
52 viii CHAPTER 1: INTRODUCTION 1.1 Problem statement Foreign Direct Investment (FDI) plays a major role in the countries’s growth, especially in developing countries, thank to its benefits, including technological transferring, management skill, job creations, and other positive externalities. Moreover, the FDI is considered as one of the essential elements for economic development (Cave, 1996; Nwaogu, 2012). Aware of these positive effects, nations have implemented several manners to promote the FDI inflow such as issuing supportive law and policies, opening their market, enhancing the human capital or improving the infrastructure capability. Particular to Vietnam, since the “Doi Moi” in 1986, the economy system was reconstructed from planned economy into the market economy.
The foreign sector is accepted as a component of the economy. Vietnam started its new policies to attract the FDI inflow and become an attractive destination for investment from abroad. Due to the growth of FDI activities, researchers has paid considerable attention into finding the FDI determinants in recent years. Blanc-Brude et al.
(2014) have reviewed hundred previous studies on FDI determinants with varying scales: countries within a region or sub-national in a country. For sub-national level, there are some remarkable studies such as Cheng and Kwan (2000), Sun, Tong and Yu (2002), Kang and Lee (2007) for China, Crozet et al. Regarding to Vietnam, the examining on FDI’s determinants at the provincial level are relatively inadequate. There is only few papers in this field, like Pham (2002), Meyer and Nguyen (2005), Anwar and Nguyen (2010).
Nonetheless, the similarities of above studies is that they have assumed each region is isolated and have no impact on the others. With this assumption, the amount of FDI inflow to each region are functioned by its characteristic only and therefore, these researchers just explored the disparity of FDI in term of locational determinants. However, according to the Tobler’s law (1970): “Everything is related to everything else, but near things are more related than distant things”. To illustrate for the Tolber’s Law, Neumayer and Plumper (2010) gave an example of a person in attempt to avoid the traffic jam to arrive the destination as quick as possible.
One conclusion might be obtained from this example is that the time travel for this person to reach the destination would be a function of the vehicle used, the velocity, the road route utilized. Also, the amount of time 1 depends on the time of others to arrive their destination. Besides, his travelling time also depends on the other’s options such as their vehicle, their velocity, and their road route. The Tolber’s law is also applied in examining the FDI determinants.
For instance, if Ha Noi attracts more FDI would possibly boost or deteriorate the FDI inflow of its nearby neighbors, or if Ha Noi holds a good infrastructure or a high level of human capital, then it would not only assist to attract more FDI inflow itself but also possibly make positive externalities on nearby provinces such as Ninh Binh or Hai Duong. More comprehensive, this implies that the level of FDI inflow in one province not only depends on its determinants but also influenced by the FDI inflow of other nearby provinces as well as their determinants. Alternatively, the geographical proximity between provinces in Vietnam also contributes a particular effect on the level of FDI inflow and the closer proximity-the stronger effect. The impact caused by the proximity between regions is known as spatial effect.
Therefore, due to the existence of spatial effect, the reliability of previous studies on FDI determinants with assumption that regions are distinct, is in doubt. According to Anselin (1988), the omission of spatial effect lead to biased, inconsistent or inefficient parameter estimates. As a result, these spatial effects should be controlled to yield a more accurate estimation. Nevertheless, previous works on FDI determinants of Vietnam provided a useful suggestion for selecting potential determinants.
Currently, there are only two empirical studies of Hoang and Goujon (2014), Esiyok and Ugur (2015), which embraced the spatial effect. By applying two different models, they stated that the FDI inflow to provinces in Vietnam has impact on one another with different signs. However, the restraint of using two basic spatial models does not allow them to distinguish the real impact of characteristics from nearby provinces on the host province. Thereby, this study is expected to partially fulfill the drawbacks in previous studies by accounting for the spatial interaction between provinces in investigating the FDI determinants, which might offer more precise results.
Especially, by applying recent spatial econometric techniques, this study aims to reveal not only the spatial dependence of FDI in Vietnam but also the effect of alternative provinces determinants on the FDI flow into one province. Research objective As discussed above, the FDI inflow to each province does not simply rely on its determinants but also be mutually affected by the FDI inflow to other provinces and their determinants through the spatial interaction. Followed by that, this study is designed to analyze the FDI determinants at provincial level and examine the spatial interaction between provinces in attracting FDI. Research questions In order to reach the research goal, this study focuses on answering two main research questions: (1) Does the spatial dependence of FDI inflow between provinces in Vietnam exist? (2) Which determinants would affect the FDI inflow at the provincial level? 1.4 Scope of the study This study adopts the panel data at the provincial level for all 63 provinces in Vietnam from 2010 to 2014.
The amount of registered FDI in US dollars as the dependent variable is collected from Vietnam Statistical Year Book by the General Statistical Official of Vietnam (GSO) and the Provinces Statistical Yearbook from 2011 to 2014. The Gross Domestic Product (GDP) proxy for the market size, the sum of export and import over the GDP proxy for the degree of openness and the proportion of employment in foreign firms over the total employment proxy for the agglomeration. These data are collected from the Provinces Statistical Yearbook from 2010 to 2013.