Location-specific determinants of Japanese foreign direct investment in selected Asian countries.pdf

1. University of Economics International Institution of Social Studies
Ho Chi Minh City, Vietnam Eramus University of Rotterdam,
The Netherlands
VIETNAM – THE NETHERLANDS PROGRAMME
FOR MASTER OF ART IN DEVELOPMENT ECONOMICS
LOCATION SPECIFIC DETERMINANTS OF
JAPANESE FOREIGN DIRECT INVESTMENT
IN SELECTED ASIAN COUNTRIES
BY HUYNH THAO THUY VI
A thesis submitted in partial fulfillment of the requirements for the degree of
Master of Arts in Development Economics
Under the supervision of Dr. Le Cong Tru
HO CHI MINH CITY, 2014

2. 1
DECLARATION
This is to certify that the thesis entitled “Location-specific determinants of Japanese foreign
direct investment in selected Asian countries”, is submitted by me in fulfillment of the
requirement for the degree of Master of Art in Development Economics to Vietnam –
Netherlands Programme. This thesis comprises only my original work and due supervision and
acknowledgement have been made in the text to all other material used.
Huynh Thao Thuy Vi

3. 2
ACKNOWLEDGEMENT
I would not be possible to finish this thesis without the support of people surrounding me.
Firstly, I am really grateful to my supervisor, Dr. Le Cong Tru, for his guidance, comments and
supervisions.
Secondly, I would like to express my gratitude to Dr. Truong Dang Thuy for his econometric
guidance.
Thirdly, I want to acknowledge all lecturers of Vietnam-Netherlands Programme for the wide
knowledge they provided me during the time I studied here.
Next, I would like to express my gratitude to my parents for all of their sacrifice, encouragement
and support for me.
Last but not least, I would like to thank my friends and people, who supported for my thesis but
were not above-mentioned.

4. 3
ABBREVIATIONS
FE Fixed Effect
FDI Foreign Direct Investment
GDP Gross Domestic Product
JBIC Japan Bank for International Cooperation
JFDI Japanese Foreign Direct Investment
JETRO Japan External Trade Organization
MNE Multinational Enterprises
RE Random Effect

5. 4
ABSTRACT
This thesis contributes to examine the location-specific determinants influencing on
Japanese foreign direct investment. This research uses fixed effect method and panel data of ten
selected Asian countries in the period from 1995 to 2012. The determinants are classified into
three groups: policy factor, business facilitation and economic factor. In this study, except for the
variables which belong to policy factor and business facilitation, the others of economic factor
are categorized in accordance with three main motives for Japanese enterprises investing abroad.
Those motives are market-seeking, resource-seeking and efficiency-seeking. The study finds that
market size, natural resource, inflation rate, exchange rate volatility, political risk and
infrastructure development are the significant factors.
Moreover, among ten selected Asian countries, there are the differences between
intercept coefficients of Vietnam and other countries who are Thailand, Indonesia, Vietnam–
Philippines and China. In other words, except for the determinants in the regression model, there
would be other factors making those countries to be more dominant than Vietnam. Finally,
recognizing the need of Japanese foreign direct investment, the policy makers in host countries
should apply the relevant policies to improve the business environment for becoming promising
destinations and attract more Japanese foreign direct investment.
Key words: Japanese foreign direct investment, panel data, location-specific, Asian countries,
fixed effect.

6. 5
TABLE OF CONTENT
DECLARATION .......................................................................................................................... 1
ACKNOWLEDGEMENT............................................................................................................ 2
ABBREVIATIONS....................................................................................................................... 3
ABSTRACT................................................................................................................................... 4
TABLE OF CONTENT................................................................................................................ 5
LIST OF FIGURES...................................................................................................................... 7
LIST OF TABLES........................................................................................................................ 8
CHAPTER 1 INTRODUCTION.............................................................................................. 9
1.1 PROBLEM STATEMENT...........................................................................................................9
1.2 RESEARCH OBJECTIVES .......................................................................................................10
1.3 RESEARCH QUESTION...........................................................................................................10
1.4 THESIS STRUCTURE...............................................................................................................11
CHAPTER 2 LITERATURE REVIEW................................................................................ 12
2.1 THEORETICAL LITERATURE ...............................................................................................12
2.1.1 Early concepts & studies of determinants of FDI...............................................................12
2.1.2 Neoclassical Trade Theory (Heckscher-Ohlin model & MacDougall-Kemp model).........13
2.1.3 Hymer – Kindleberger Paradigm ........................................................................................13
2.1.4 Internalization theory..........................................................................................................14
2.1.5 The OLI paradigm - Eclectic theory ...................................................................................15
2.2 EMPIRICAL STUDIES..............................................................................................................17
2.3 CONCEPTUAL FRAMEWORK ...............................................................................................22
CHAPTER 3 RESEARCH METHODOLOGY.................................................................... 25
3.1 VARIABLE DEFINITION AND TESTING HYPOTHESES...................................................25
3.1.1 Market size..........................................................................................................................25
3.1.2 Natural resource..................................................................................................................25
3.1.3 Inflation rate........................................................................................................................25
3.1.4 Exchange rate volatility ......................................................................................................26
3.1.5 Trade openness....................................................................................................................26
3.1.6 Political risk ........................................................................................................................27
3.1.7 Infrastructure development .................................................................................................27
3.1.8 Labor cost............................................................................................................................28
3.2 DATA AND MODEL SPECIFICATION ..................................................................................28
3.3 RESEARCH METHODOLOGY................................................................................................31
3.3.1 Descriptive Analysis ...........................................................................................................31
3.3.2 Regression Analysis............................................................................................................32
CHAPTER 4 DATA ANALYSIS ........................................................................................... 37
4.1 THE OVERVIEW OF JAPANESE FDI IN ASIAN COUNTRIES...........................................37
4.1.1 Before the crisis in 1997 .....................................................................................................37
4.1.2 After the crisis in 1997........................................................................................................43
4.1.3 Several remarkable characteristics of recent Japanese FDI in Asia....................................45
4.2 EMPIRICAL RESULTS.............................................................................................................47
4.2.1 Descriptive analysis and some general tests .......................................................................47
4.2.2 Econometric results.............................................................................................................52
CHAPTER 5 CONCLUSION AND POLICY IMPLICATION.......................................... 57
5.1 CONCLUSION...........................................................................................................................57

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5.2 POLICY IMPLICATION ...........................................................................................................58
5.3 LIMITATION AND SUGGESTION OF FURTHER RESEARCH ..........................................59
APPENDIX A: RESULT OF HAUSMAN TEST.................................................................... 60
APPENDIX B: RESULTS OF HETEROSKEDASTICITY & .............................................. 61
SERIAL CORRELATION TEST............................................................................................. 61
Table B-1: Heteroskedasticity test..........................................................................................................61
Table B-2: Serial Correlation test ...........................................................................................................61
APPENDIX C: REGRESSION RESULTS.............................................................................. 62
REFERENCES............................................................................................................................ 63

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LIST OF FIGURES
Figure 2.1: Conceptual Framework ............................................................................................. 23
Figure 4.1: Japanese FDI by region (billion Yen) ........................................................................ 38
Figure 4.2: Japanese FDI in 10 selected Asian countries (billion Yen)........................................ 40
Figure 4.3: Japanese FDI in NIEs (billion Yen) ........................................................................... 41
Figure 4.4: Japanese FDI in ASEAN4 (billion Yen).................................................................... 42
Figure 4.5: The correlation between Political Risk (pol) and Trade Openness (TO1)................. 49
Figure 4.6: The correlation between trade and GDP .................................................................... 50
Figure 4.7: The response of Japanese enterprises considering Vietnam, Thailand, Indonesia,
Philippines and China as the promising countries. ....................................................................... 56

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LIST OF TABLES
Table 2.1: The summaries of some typical theories of FDI.......................................................... 16
Table 3.1: Summary of testing hypotheses................................................................................... 28
Table 3.2: Summary of expected signs of variables ..................................................................... 30
Table 4.1: Regional distribution of FDI by Japanese firms.......................................................... 39
Table 4.2: Promising countries for overseas business operation over the medium-term in term of
Japanese enterprises...................................................................................................................... 45
Table 4.3: Summary of variables in the study .............................................................................. 48
Table 4.4: Correlation coefficients of variables in the study........................................................ 48
Table 4.5: The VIF and TOL factors before excluding trade openness (TO1)............................. 49
Table 4.6: The VIF and TOL factors after excluding trade openness (TO1) ............................... 51
Table 4.7: Summary of Estimation Results .................................................................................. 52

10. 9
CHAPTER 1 INTRODUCTION
1.1 PROBLEM STATEMENT
For the time being, because of the immobility and long run profitability, foreign direct
investment (FDI) is one of the important factors contributing to the economic growth of
countries in the world (Nakamura & Oyama, 1998). Through FDI, the financial resources are
transferred to the host countries to set up and expand the production conditions in those
countries. Furthermore, the technological achievements and managerial knowledge are also
transferred from the investing countries to the host countries. Those factors would contribute to
the economic development of the recipients. Moreover, the host countries may also take
advantage of the networks through the sales and distribution networks of foreign investors.
As to the destination of FDI, with the available and potential advantages, Asia has been
still the leading region in attracting FDI with 3,740 projects tracked in 2012, which increases its
global market share to 31.72%. Many countries in Asia have achieved the dominant economic
growth through FDI into many specific industries, such as, business and financial services, ICT,
chemicals, plastics and rubber, etc. As to the source country or home country of FDI, Japan is
still the dominant one all over the world, especially in Asia. In spite of the decreased number of
outward FDI projects from Japan, the ratio of Japanese FDI in Asia still went up from 34.57% in
2011 to 37.37% in 2012 (Fingar, 2013). According to the survey conducted by Japan External
Trade Organization (JETRO) on 3,397 JETRO member firms and 6,403 enterprises using
JETRO services in 2013, 64.9% of firms intend to expand overseas operation by conducting new
investments going with existing operation bases whereas 91.7% set up locations in Asia Pacific.
It would be indicated that because of natural disasters and difficult domestic business
environment in Japan, for example, labor costs, tax burden, domestic regulations, etc, Japan
firms are concentrating on widening their overseas investments (JETRO, 2014). Moreover, as to
the conception of Japanese firms, the countries in Asia have been possessing advantages, which
would promote them to be promising destinations for JFDI. Those advantages can be listed as
current size of local market, inexpensive source of labor, social and political stability, etc.
Despite many motives for Japanese firms to invest in Asia, there are many issues in this
region, which raised concerns for Japanese enterprises. As indicated in the report of Japan Bank

11. 10
for International Cooperation (JBIC) in 2013, the rise in salary, difficult searching for the raw
materials, underdeveloped infrastructure, unclear legal system, etc have been the typical issues
existing in Asian countries and possibly preventing them from receiving more investment from
Japan. Combining the pros. and cons. in Asian region, we can examine the determinants
affecting JFDI inflows in Asia. In other words, the study of the important factors determining
JFDI in Asia is necessary for boosting JFDI into this region and should be based on the empirical
studies and the real situations as well. Since then, the relevant policies can be suggested for the
countries in Asia to become more attractive destinations to Japanese investors.
1.2 RESEARCH OBJECTIVES
Up to now, there are some studies about factors affecting FDI inflow in Asian countries.
It can be stated that the empirical papers presented the different and various factors to
demonstrate for the researches and got general findings. A few authors have conducted their
studies by basing on data of FDI inflow into specific sectors of specific countries to find out
what are called sector-specific determinants of FDI.
In this study, the research is concentrated on the total amount of FDI into a specific
location or host country and come to contribute to on-going researches by examining the
location-specific determinants of Japanese FDI in ten Asian countries. As to this general
objective, this study aims at the following specific objectives:
- To provide the descriptive analysis of the changes in the period of before and after
1997 crisis and some recently remarkable characteristics of JFDI in ten selected Asian
countries.
- To measure the impacts of location-specific determinants on JFDI in ten selected
Asian countries.
- To suggest some policy implications for attracting JFDI
1.3 RESEARCH QUESTION
To conduct research objectives, this study aims to answer the following questions:
- What are the characteristics of JFDI in the period of before and after 1997 crisis and
the changes in recent JFDI in ten selected Asian countries?
- What are the significant factors affecting JFDI inflow in selected Asian countries? Is
there any difference between intercept coefficients of ten selected Asian countries?

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- What are the relevant policies that can be suggested basing on the analysis to attract
JFDI inflow?
1.4 THESIS STRUCTURE
This thesis consists of five chapters. Right after Chapter 1 which aims to present the
introduction of JFDI inflows into Asian countries, Chapter 2 will synthesize the remarkable
theories about determinants of FDI. There are five typical theories presented in this chapter from
the one with the basic concept to the wider one. They are early studies of FDI, Neoclassical trade
theory, Hymer – Kindleberger Paradigm, Internalization theory and OLI paradigm - Eclectic
theory. Moreover, some typically empirical studies will also be reviewed in Chapter 2. By
considering the combination of theories and empirical studies, the analytical framework of this
thesis will be drawn at the end of Chapter 2.
Following Chapter 2, Chapter 3 concentrates on variables definitions and eight testing
hypothesis. Furthermore, going with the introduction of empirical model used in this thesis, the
source for data and the expected signs of eight variables will be summarized in one table. The
final part in Chapter 3 is the research methodology which describes the methods and typical tests
in panel data regression.
In Chapter 4, an overview of JFDI in Asian countries will be presented to describe the
changes in JFDI in the period of before and after the-1997-crisis. Moreover, the recent trends and
characteristics of JFDI in ten selected Asian countries will be also analyzed. The next in this
chapter is the findings obtained from the estimation results, which will provide the answers for
each hypothesis stated in Chapter 2. Since then, the question of significant factors determining
JFDI in selected Asian countries will be also discussed.
Basing on the findings in Chapter 4, some conclusion remarks and policies
recommendations for attracting JFDI into Asian countries will be presented in Chapter 5 which is
the last chapter in this thesis. Moreover, Chapter 5 will also point out some limitations of thesis
and suggest some further research for the study of JFDI.

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CHAPTER 2 LITERATURE REVIEW
This chapter includes three main parts. The first section provides some typical FDI theories
whose combinations will be the theoretical basis for this thesis. The next part contains the
summaries of some empirical studies. Finally, basing on the theories and empirical studies, the
conceptual framework for this thesis will be presented in the last section.
2.1 THEORETICAL LITERATURE
The rise in FDI has led to the extensive research and the development of many theories to
explain the determinants of FDI flow. To study FDI, it should be the combination of many
theories, not just basing on any single one (Faeth, 2009). Therefore, in this study, some theories
will be presented from the early to the latest one. At the end of this section, the Table 2.1 will
provide the summary of these theories.
2.1.1 Early concepts & studies of determinants of FDI
The early researches of determinants of FDI were mostly based on the questionnaires.
The companies in the survey or research were asked to realize and indicate the reasons or factors
which encouraged them investing abroad. Some major researchers contributing to the initially
general building of FDI’s determinants would be mentioned such as Robinson (1961), Behrman
(1963), Basi (1966), etc. (in (Faeth, 2009). In these early studies, a diversification of factors,
indicated as the encouraging ones in multinational enterprises’ investment decisions, included
cost factors, trade openness factors, marketing factors and investment climate. The degree of
significance of those factors were various in every study’s analysis result. In some researches,
marketing factors whose proxies were market size and market growth were the major
determinants of FDI. However, in other studies, the availability of low labor and natural resource
were considered as the important factors. On the other hand, according to the research of Basi
(1966), political stability was the most significant determinant. It would be said that through the
early studies with the researches in specific economies, the initial concepts of FDI’s determinants
have been taken into account.

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2.1.2 Neoclassical Trade Theory (Heckscher-Ohlin model & MacDougall-Kemp
model)
As to the Neoclassical Trade Theory, Heckscher – Ohlin (HO hereafter) model was
considered as the first theory attempting to explain the essence and factors of FDI. Two Swedish
economists, Eli Heckscher and Bertil Ohlin, put the foundation of FDI in HO model through
some basic assumptions: no trade barriers, no transportation cost, perfect competition & full
employment, no specialization, the same constant return to scale production function, the
existence of domestic factor mobility & international factor immobility and the identical
technology between countries. HO model was based on 2x2x2 model, standing for two countries
(home and host country), two factors (capital and labor) and two commodities. In HO model, the
only difference in relative factor endowment would lead to the comparative advantage and
international factor price differentials. The key concept in HO model is that the home country
would export to the host or foreign country the good, which uses the factor that the home country
is relatively abundant. MacDougall-Kemp (MK hereafter) model was one of the earliest theories
of FDI. The assumptions in this model were also the full employment, perfect competition and
constant return to scale. Like HO model, the capital would move from the home country to the
host country that has the higher capital rate of returns. However, as to MK model, the host
country can apply the tax on the capital flow and manage the capital return. It could be said that
the researches in MK model had took into account the barriers toward the trade or the capital
inflow.
2.1.3 Hymer – Kindleberger Paradigm
Besides the Neoclassical Trade Theory, after the World War II, the theory of portfolio
investment, which is one of the oldest theories of FDI, was used to explain for FDI flows. The
basis of this theory is interest rate. Under this concept, the investors will invest where brings
more profits. However, this theory was developed by the assumptions of no risks, uncertainties,
or barriers that cannot exist in the reality. Therefore, Stephen Hymer devoted his 1960
dissertation to develop another clearer theory of FDI. It is called Hymer – Kindleberger
paradigm. As to Hymer’s theory, besides the unrealistic assumptions, in the interest-rate theory
or portfolio investment theory, there is still a theoretical limitation which is called shortage of
explanation of control (Hymer, 1976). As to the portfolio investment theory, the investor would
invest his money in a foreign enterprise whose interest rate is higher than domestic one’s.

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However, he cannot control the enterprise he invested in. Therefore, Hymer built two types of
direct investment to explain for the reasons why the investors would like to seek the control.
Since then, the theory of direct investment was formed.
In the direct investment of Type 1, Hymer indicated that the investor seeks the control
because they would like to make sure that the capital was used prudently. Because of the
different nationalities, the conflict would happen between the investors about the ratio of
reserves that should be kept in particular currency. Meanwhile, Hymer also emphasized the
difference between international transaction and intra-national one, which would lead to the
distrust and consideration among investors. Generally, although direct investment of Type 1 is
nearly similar to the portfolio investment theory, in which the core concept is interest rate, it
would supplement in portfolio investment theory the concept of the necessity of control in the
case that there is unbelief between investors and the high fear of expropriation and the exchange
rate risk. As a result, direct investment of Type 1 can replace the portfolio investment theory.
As to the direct investment of Type 2, the other reason for operating the foreign
enterprise is the possibility of removal of competition between the firms (Hymer, 1976). It is a
very normal phenomenon that in the same market, the competition between foreign enterprises
would happen. In the case of imperfect market, the combination by gathering the foreign firms
and giving the right of control for one firm would be one of the profitable collusion. In addition,
the ability of enterprise to build the international operation is rather different. It would depend on
the each firm’s specific advantage in particular industry. Furthermore, the firm would have two
choices: the first one is to rent or sell its skills or technologies; the other is setting up the
international operation and undertaking by itself.
2.1.4 Internalization theory
The internalization theory, which was developed by Buckley and Casson in 1976, was
considered as a general paradigm explaining for FDI. Due to the market imperfection, the
internalization would happen. Under this theory, the firm internalizes its globally foreign
businesses to benefit from the internal network and prevent its operation from the disadvantages
of resource allocation (Buckley & Casson, 2009).
In reality, most enterprises have to buy the inputs from independent suppliers, who would
be international ones. In this situation, one question was raised that whether the enterprises
should produce inputs by themselves or not. This kind of question belongs to what is called

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“make or buy decision” in business management or “backward integration” in economics
studies. This issue also leads to one kind of direct investment, which is called “resource-seeking
investment”. It means that a global company would like to set up the international operations in a
foreign country; and via its subsidiaries in that country, it would use raw materials that could not
be found in any elsewhere to produce intermediate goods. In addition, along with “backward
integration”, “forward integration” issue was also arisen to mention to the question that whether
the enterprise should build its foreign subsidiaries to control the distribution of its goods in
foreign markets or not. By establishing these subsidiaries, instead of using independent
distributors, the enterprise itself can supervise the oversea distribution network.
Moreover, Buckley and Casson emphasized in their studies that the multinational
enterprises (MNEs) specializing in research and development industries would have higher
internalization than the others (Faeth, 2009). On the other hand, MNEs only invested in some
countries with specific characteristics going with MNEs’ investment plans. As to the study of
Buckley and Casson (2009) through literature of development economics, the importance of
encouraging-foreign direct investment factors would be analyzed and classified. It was stated in
the study of Buckley and Casson that as to the MNEs planning to broaden their consuming
market into any country, the factors of local market size and local standard of living were the
important ones. In addition, with the plan of widen markets not only in host country, but also in
host country’s neighboring ones, the infrastructure development was the outweighed factor. Or
with the engagement of constructing focusing-export plants in host country, the MNEs would
pay their attention to the factor of labor cost.
2.1.5 The OLI paradigm - Eclectic theory
By combining and developing from previous theories, Dunning raised the eclectic theory
that is also called OLI paradigm. The OLI paradigm is the combination of three factors: O-L-I
which in turn stands for Ownership advantages, Location advantages and Internalization
advantages.
When entering the abroad location for production, the multinational firms have to face
the additional costs, which are caused by the diversity of legal, cultural, language system, the
lack of knowledge of domestic market; etc, would reduce their benefits. As to the first factor of
OLI paradigm, FDI happens when the multinational enterprises have Ownership advantages or
firm specific advantages that can offset the additional costs. These advantages can be tangible

17. 16
(superior technology, products, economies of scale and scope, etc) or intangible (brand name,
trademark, etc) (Hosseini, 2005).
As to the second factor in OLI paradigm, a particular country’s characteristics, which are
considered as the Location advantages or country specific advantages by foreign firms, would be
the drivers of FDI inflows. The multinational enterprises tend to combine its ownership
advantages and location advantages endowed in host countries to make their investment more
beneficial. Location advantages can be divided into three groups: economic advantages
(including qualitative and quantitative factors related to economics, for example, transport and
communication costs, market size, market growth, etc); political advantages (consisting all
government policies related to FDI inflows, international trade and production, etc) and social &
cultural advantages (including the attitude toward foreign enterprises, the diversity in culture,
etc).
The final factor in OLI paradigm is Internalization advantages that would be exploited
when the multinational enterprises realize the benefit of using Ownership advantages and
investing abroad instead of export or other contractual agreements, such as, licensing, joint
ventures, etc (Hosseini, 2005). This is the third leg of OLI paradigm in making clear the scale
and geography of foreign activities of multinational enterprises (Dunning, 2001) .
Table 2.1: The summaries of some typical theories of FDI
Theoretical approach Determinants/Concepts Authors
Early studies Cost factors, trade openness factors,
marketing factors and investment climate
Robinson (1961),
Behrman (1963),
Basi (1966), etc.
Neoclassical Trade Theory:
- Heckscher – Ohlin Model
- MacDougall – Kemp Model
Higher return on investment, lower labor
cost
Heckscher & Ohlin
(1933)
Hymer – Kindleberger
Paradigm
Market imperfection, Ownership
advantages
Hymer (1976) &
Kindleberger (1969)
Internalization theory Market failure Buckley and Casson
(1976)
OLI paradigm - Eclectic
theory
Ownership advantages, Location
advantages, Internalization advantages.
Dunning (1977,
1979)

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2.2 EMPIRICAL STUDIES
Up to now, there are many studies researching about determinants of FDI. The study of
FDI spreads from the FDI inflows to FDI outflows, from locational determinants to sectorial
ones of FDI. Basing on three conceptions of capital imperfection, special ownership advantages
and institutional factors, Buckley et al. (2007) investigated the determinants of foreign direct
investment by Chinese multinational enterprises. The study was based on official data from 1984
– 2001. The authors collected data of forty-nine host countries receiving Chinese FDI, in which,
there are twenty-two countries belonging to Organization for Economic Cooperation and
Development (OECD). Two models were used in this study: pooled ordinary least squares
(POLS) and random effects (RE). Moreover, the authors conducted Lagrangian multiplier (LM)
test to conclude that RE is the better model. Basing on the general and specific theories of FDI,
Buckley et al used fourteen independent variables to be the determinants of Chinese FDI
outflows. These are market size, market size per capita, market growth, natural resource
endowment, host country’s endowment of ownership advantages, political risk, cultural
proximity, policy liberalization, exchange rate, inflation rate, geographic distance from China,
export & import and openness to FDI. Basing on the empirical theories, with the expectation of
nonlinear relationship, the authors transformed data into the natural logarithms. The results of
this study emphasized the important role of host market characteristics, cultural and political
factors on FDI inflows. In host market factors, market size was the only one having significantly
positive influence on Chinese FDI outflow. On the other hand, the exchange rate, geographic
distance and openness to FDI are all insignificant.
In the study of Kinoshita, Campos, and Pankki (2004), the host country’s characteristics,
which would be the drivers of FDI, were analyzed by using 1990 – 1998 panel data of 25
transition countries, which include Central and Eastern European and Baltic (CEEB) countries
and the Commonwealth of Independent States (CIS) consists of all former Soviet Union
countries. These two authors used fixed effects and random effects model to find out the
importance of host country’s factors in FDI inflows. However, the Hausman test rejected random
effects model. They divided the determinants into four groups. Group 1 – Classical Source of
Comparative Advantage – referred to the host country’s advantages considered as the motivation
for FDI inflows. The variables in Group 1 were market size, low labor cost, labor quality and
infrastructure. The second Group included Macroeconomic Policy and Reform variables in

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which inflation rate was the typical one to emphasize the stability of host country’s economy. As
to the authors, the lower average inflation rate, the more profit can be brought by investment
projects. Next, the third Group emphasized the important role of host country institutions. To
make the investment decisions, the MNEs have to consider not only the economic cost, but also
the non-economic one. The authors used the “Rule of Law” variable whose data was collected
from International Country Risk Guide to measure the corruption of host country. In the last
Group, the variable of agglomeration was used to demonstrate the feedback effect of past FDI on
the current and future FDI. Through the estimation results, the authors found that market size,
labor cost and natural resource were the important FDI’s determinants. In addition, good
institution or lower political risk, higher trade openness were also the drivers of FDI inflow.
Nevertheless, the variable of education and infrastructure were likely to be insignificant.
The same results were also demonstrated in the study of Farrell, Gaston, and Sturm
(2004). These authors used panel data from 1984 to 1995 of 16 countries and applied pooled and
fixed effects model to indicate the important determinants of Japanese FDI. They found that
market size and labor cost of host country were extremely significant. Moreover, the
macroeconomic conditions also highly affected JFDI inflow. As to the variable of exchange rate,
basing on the statistically insignificant results, another finding of the author was that the strength
of Japanese Yen was not likely to be the main determinant of JFDI. According to the authors,
this finding was also similar to other studies.
Using the same type of data from 1979 to 1997 for Japanese FDI and data from 1982 to
1997 for the United States (US) FDI, the research of Nakamura and Oyama (1998) focused on
indicating the macroeconomic determinants of FDI from Japan and US to eight East Asian
countries. They were Taiwan, Korea, Indonesia, Philippines, China, Malaysia, Singapore and
Thailand. The reason that these two Japanese authors chose to investigate Japan and US as the
home countries is that FDI from Japan and US occupied about 50 percent of the total FDI flow
into the above-referred East Asian countries. According to these authors, although there were
many factors influencing on FDI, in their study, they just concentrated on macroeconomic ones,
especially the real exchange rate. Before conducting the regression analysis, eight host countries
were also classified into many different groups basing on their FDI elasticity to macroeconomic
variables. Remarkably, this classification was similar to the countries’ economic characteristics
and development process. The study applied fixed effects and random effects method for the

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analysis. Like the others, Hausman test was also used to decide which method was better. As to
the regression result, Japanese FDI into eight countries was significantly influenced by the
change of exchange rate whereas US FDI was not. Moreover, as to both Japanese FDI and US
FDI, the coefficient of host country’ GDP was found to be significant in most host countries. On
the other hand, this study also indicated the link between FDI and trade. In other words, FDI
strongly affect the export from host countries to Japan and the import of host countries from
Japan.
Another typical study investigating the factors of Japanese FDI belonged to Urata and
Kawai (2000). By using data of 117 countries that were divided into three groups: developed,
developing and Asian countries, these two authors found out the importance of host country’s
factors in JFDI inflows. The independent variables include exchange rate, wage rate, market size,
macroeconomic stability, labor quality, infrastructure, agglomeration and governance.
Accompanied with the analysis of relationship between those factors and JFDI, the authors also
used SME dummy to indicate the difference between small, medium-sized enterprises (SMEs)
and the large ones in the way of making investment decisions. The results of this analysis
showed that low wage labor, good infrastructure, factors related to local market have the
significant meanings on JFDI inflows. When investing in developing countries, Japanese
multinational enterprises aim the export production that is the reason why they consider much
more about the production conditions. On the other hand, investing in developed countries,
Japanese firms would be interested in the local sales. As a result, market-related factors would be
always the decisive ones. Moreover, industrial agglomeration was found to be very significant in
attracting JFDI. Japanese investors always consider the inter-firm relationship between Japanese
enterprises. As to their conception, this relationship would bring them benefits in procurement
and sales. The other finding referred in the study is the SMEs are more sensitive to the change of
locational conditions than the large ones. Therefore, with the investment tendency from Japanese
SMEs, the countries, who want to attract JFDI inflows, need to build, maintain and enhance local
business environment.
Similarly, with the dataset from 1975 to 2007, Vijayakumar, Sridharan, and Rao (2010)
contributed one more study to the research of FDI’s determinants. In their study, a new term was
generated – BRICS standing for Brazil, Russia, India, China and South Africa. This term
represented for the world’s four continents whose economies were considered significant. The

21. 20
FDI inflow into those regions was extremely complex. In this study, the authors used three
methods for analysis: OLS pooled regression, fixed effects and random effects. The fixed effects
method was also rejected by Hausman test. The variables were classified into seven groups. They
were market size, labor cost, trade openness, currency value, infrastructure facilities, gross
capital formation and economic stability & growth prospect. The analysis results showed that
most variables had the important influence on FDI. Nevertheless, the economic stability &
growth prospect measured by inflation rate and trade openness measured by the ratio of total
export plus import to GDP were found to be insignificant determinants of FDI in BRICS
countries.
Basing on the OLI framework of Dunning, Wadhwa and Reddy (2011) conducted the
study about the impact of market-seeking, resource-seeking and efficiency-seeking factors of
host countries on FDI inflows into those countries. The study used panel data from 1991 to 2008
of ten developing countries, which are Bangladesh, China, India, Indonesia, Iran, Malaysia,
Pakistan, Thailand, Turkey and Vietnam. The author classified the determinants into three kinds
of factors. As to market-seeking factor, GDP and population growth were used as the proxies of
market size. In efficiency-seeking factor, the author used inflation rate and exchange rate to be
the variables in this category. Infrastructure indexes including internet users, mobile subscribers
and roads paved were used to demonstrate for the resource-seeking factor. In this study, the
author used fixed effect model with some necessary tests, for instance, Augmented Dickey-Fuller
test checking the stationary of data and multicollinearity test. The regression results showed that
all the factors have the significant impacts on FDI inflows into ten Asian countries referred
above.
Basing on the data sets from 1992 to 2009 of provinces of China, Xin-Zhong (2005) also
conducted panel model to investigate the location determinants affecting to FDI inflow into
provinces in China. The author classified these determinants into three categories. They were
investment environment improving, macro-economic and investment cost factors. The group of
investment environment improving factors included many determinants in which the typical ones
are openness level of economics, policy index and infrastructure level. The factors of macro-
economics included market size, growth rate of economy, economic developing level and human
capital. The final group related to investment cost included labor cost and the exchange rate. The
empirical results indicated that all variables were statistically significant. However, as to the

22. 21
wrong signs of the variables of economic developing level and human capital, this author
considered the existence of collinearity among variables. As a result, this author chose the
method of eliminating these two variables and recombining the independent variables to create
more models and remove the collinearity. The derived results showed the good performance of
these two variables and the highly statistic significance of other variables. Basing on the results,
some policy implications were also suggested to attract more FDI inflows. According to this
author, the policy should concentrate on promoting GDP, liberal trade and re-educational
projects. Moreover, besides applying the basic education, it is really important for the
government to pay attention to research and development (R&D) policy to achieve the
productive labor force.
Another research about FDI was conducted by Delaunay and Torrisi (2012). These
authors studied about determinants of FDI in Vietnam by using time-series data which was from
1991 to 2008 and collected from the reliable sources, for instance, IMF, UNCTAD, Vietnamese
GSO, etc. According to these authors, the models of FDI determinants concentrated on two
groups. They are economic and non-economic factors. In this study, the authors classified
political stability, institutional efficiency and corruption indicators into the group of non-
economic factors whereas market size, market growth, trade openness, etc belonged to economic
factors. On the other hand, because the research object was Vietnam whose figures or measures
of these factors were not available, this study just examined the impact of economic factors.
Moreover, the authors used ASIAN dummy variable to measure the impact of Vietnam’s
membership in Asian trading zone on FDI into Vietnam. The results derived were similar with
other studies. GDP, labor cost and exchange rate are predictably significant to FDI in Vietnam
whereas GDP growth rate was not significant. Furthermore, according to the results, the impact
of Vietnam’s membership in Asian trading zone on FDI into Vietnam was not clear. The authors
explained that although the intra-trade increased when Vietnam join Asian, this intra-trade has
been rather low. That is the reason why the re-export from Vietnam to ASIAN market is limited,
which would reduce the attractiveness for FDI inflows. It could be concluded fairly that ASIAN
has not succeeded in being a trade integration mechanism yet.
Different from previous studies, the joint research of Vuong and Yokoyama (2011)
brought the variety and interest in researching FDI’s determinants, especially JFDI’s. In the
study, they used Importance Performance Analysis (IPA) method to investigate the factors that

23. 22
stimulating JFDI inflow. Since then, the authors evaluated and compared the attractiveness of
Vietnam with China and Thailand in the process of being the dominant destination of Japanese
enterprises. The study was conducted by IPA method, which has been using not only in
economic planning for strategic management problem, but also in forming framework for
demonstrating changes. Conducting qualitative research methods as referred by Dunning and
Lundan (2008), these two authors carried out the survey and research based on the participation
of 1500 Japanese companies: 900 companies located in 15 districts in Japan and 600 companies
set the operation in Vietnam. Through the research, the attributes whose means were higher than
four (>4), were considered as the determining factors of JFDI in Asia. They were political
stability, availability of skilled labor, infrastructure conditions, labor cost, access to raw material,
etc. Furthermore, the authors also indicated the important difference in between two group
countries in the way that Japanese companies evaluated Vietnamese factors motivating JFDI. As
to the enterprises investing in Vietnam, they paid attention and appreciated the political stability
and the strength of Japanese Yen toward Vietnam Dong. As to the companies not having projects
in Vietnam, they were found to be optimistic about Vietnamese investment environment and the
quality of labor. On the other hand, in making investment decisions, they also considered the
easy access to raw material, infrastructure development and the corruption condition. According
to the findings in this study, Vietnam was considered to be more advantageous than China and
Thailand in production cost and labor characteristics. However, to attract more JFDI, Vietnam
should pay attention to the factors related to macroeconomic conditions and investment
environment.
2.3 CONCEPTUAL FRAMEWORK
Based on the literature review presented in the previous sections, the location-specific
determinants affecting to FDI inflow are classified and described in the following figure:

24. 23
Figure 2.1: Conceptual Framework
Following the World Investment Report (UNCTAD, 1998), the location-specific or host
country determinants of FDI are classified into three groups. They are policy factor, business
facilitation and economic factor. The policy factor refers to the index measuring the stability of
politics and economics, the rules related to the entry and operation of multinational enterprises
and the trade policy related to the trade openness, which is the necessary factor for the host
countries to receive FDI inflows from foreign countries. While the policy factor aims at creating
the framework for the operation of foreign investors, the factors belonging to business
facilitation are considered to facilitate their businesses in host countries. The measures in
business facilitation group are mostly new, in which the reduction of “hassle cost” is really
Location-specific (Host country)
determinants
Business facilitation
- Hassle cost (related to
administrative and
government effectiveness
Economic factors
Policy factors
- Economic, political and
social stability
- Rules regarding entry
and operations
- Trade openness
Type of FDI classified by motives of Principle economic determinants in
Japanese enterprises host countries
1. Market – seeking - Market size
2. Resource/Asset – seeking - Raw materials, natural resource
- Physical infrastructure (power,
energy, telecommunication)
3. Efficiency - seeking - Lower labor cost
- Exchange rate
- Inflation rate

25. 24
important. Demonstrating the reduction of “hassle cost” includes measuring the improvement of
government effectiveness or the reduction of corruption. In this study, in term of policy factor
and business facilitation, we use the variables of trade openness, the average figure of Rule of
Law, Regulatory Quality and Government Effectiveness to be the proxies.
The third group of host country determinant is the economic factor. The economic factor
includes many determinants belonging to the host country’s economic indexes that can have
negative or positive effects on FDI inflow. As indicated in World Investment Report (UNCTAD,
1998), the potential destinations for FDI belong to the host countries which have the advantages
sought by the foreign countries. However, to consider and decide which country is suitable for
investment, the foreign firms from home countries also base on their strategies and motives.
According to the study of Dunning and Lundan (2008), there are three primary motives for the
multinational enterprises to decide investing abroad. They are market-seeking, resource/asset-
seeking and efficiency-seeking FDI. According to the above conceptual framework, the
economic determinants are divided and classified relatively into each type of FDI motive. As
indicated in the study of Dunning and Lundan (2008), the prerequisite reason for market-seeking
FDI is that a multinational enterprise finds it necessary to set the business operation in the
important markets in which its competitors are serving. When engaging market-seeking FDI, the
foreign firms consider their affiliates to be independent production units rather than a part of
network of cross-border activities. The output will be mostly consumed in host country, so the
market size of host country is top leading determinant that the Japanese firms always appreciate
(JBIC, 2013). Next, the resource-seeking FDI, as it name, would happen when the multinational
enterprises aim to acquire the source of physical infrastructure and raw materials (Buckley et al.,
2007). Furthermore, because Japan is the country with limited natural resource, natural resource
endowment is always considered to be significant determinant (Urata, 1993). The purpose of the
last motive, efficiency-seeking FDI, is the lower cost reduction and the more efficient business
operation. As a result, the lower labor cost is classified in this type of FDI motive. Moreover, in
this group, inflation rate and exchange rate are the determinants highly evaluated. While the
inflation rate implies the macroeconomic stability, the exchange rate is the factor that the foreign
investors would take advantage to reduce the cost of production (Wadhwa & Reddy, 2011).

26. 25
CHAPTER 3 RESEARCH METHODOLOGY
This chapter includes three parts. Basing on the conceptual framework discussed in the previous
chapter, the first part introduces the independent variables used in this thesis. Going with the
definition of variables, each specific hypothesis is also derived. The second section is data and
model specification. In this section, the way of calculating and the source of dependent variables
are illustrated. The final part is research methodology which consists of descriptive analysis and
regression analysis.
3.1 VARIABLE DEFINITION AND TESTING HYPOTHESES
3.1.1 Market size
According to UNCTAD (1998), market size is one of the important traditional
determinants influencing on FDI flows. The developed or home countries look at the size of host
country’s economy to decide whether they should conduct FDI or not. The larger scale of
economy, the more markets and more benefit the foreign enterprises can get. Therefore, market
size is the cardinal factor reckoned by multinational enterprises when they aim to seek markets
through FDI. Since then, the hypothesis can be derived as follow:
Hypothesis 1: Host country’s market size will have a positive impact on JFDI
3.1.2 Natural resource
Japan is a country with the limited natural resource. This is the reason why Japanese FDI
has been concentrating on host country’s natural resource to ensure the provision of raw
materials for the production, for example, petroleum drilling in Indonesia; iron ore mining in
Malaysia; copper mining in Philippines, etc (Urata, 1993). Moreover, in the research of
Kinoshita et al. (2004), the abundance of natural resources is regarded as the driver of FDI
inflows. Thus, I derive the following hypothesis:
Hypothesis 2: Host country’s natural resource will have a positive impact on JFDI
3.1.3 Inflation rate
Unpredictable and instable inflation rate can be the disadvantage for host country to attract
FDI. It is clearly stated that profit expectation of foreign firms would not be ensured because of
volatile inflation rate. In addition, high inflation rate can be one of main reasons leading to the
lowered real earnings in domestic currency of foreign firms. As a result, the study of Wadhwa

27. 26
and Reddy (2011) indicated the negative relationship between inflation rate and FDI. In this
study, inflation rate was classified into the group of efficiency-seeking factors, which concentrate
on the motives of lower cost reduction and the more efficient business operation of foreign firms.
Hereby, it can be concluded the third hypothesis as follows:
Hypothesis 3: Host country’s inflation rate will have a negative impact on JFDI
3.1.4 Exchange rate volatility
As to economic theory, because of the depreciation of host country’s currency, the
foreign firms can reduce the costs of buying the local inputs that leading to the lower production
costs. In the study of Xing (2006), the role of exchange rate is referred as the critical variable
affecting Japanese FDI in China. Under this author’s research, the appreciation in the Yen
associated with the increase in FDI into China and vice versa. Specifically, the author found that
the fluctuation of Japanese FDI in China can be explained by the fluctuation of real bilateral
exchange rate between China and Japan. Moreover, in the study of Urata and Kawai (2000), the
exchange rate does not have the important influence on FDI inflows whereas the exchange rate
volatility has negative impact on JFDI inflows. Therefore, the fourth hypothesis can be derived
as followings:
Hypothesis 4: Host country’s exchange rate volatility will have a negative impact on JFDI
3.1.5 Trade openness
In many studies, trade openness has been referred as one of the important determinants of
FDI inflows. A country who has high degree of trade openness would be the more attractive
destination for FDI. As to Yanikkaya (2003), there are two ways for measuring trade openness,
one of them is measuring trade volumes, and the other is measuring trade restriction. Yanikkaya
showed that trade restriction includes total import duties, total export duties and tax on
international trade, bilateral payments arrangements and measure of trade barriers. However,
with the available data, in this study, we use the indicator of trade volume measured by the ratio
of total export plus import to GDP to demonstrate the degree of trade openness. The fifth
hypothesis is as follows:
Hypothesis 5: Host country’s trade openness will have a positive impact on JFDI

28. 27
3.1.6 Political risk
According to Buckley et al. (2007), in the host countries with the higher rate of political
risk, the multinational firms who want to find markets would choose to substitute exporting or
licensing for owing production in local area. Moreover, in the study of finding out the linkages
between political risk, institution and foreign direct investment, Busse and Hefeker (2007)
analyzed the relative importance of twelve indicators standing for political risk of a particular
country on FDI inflows. The result of this study shows that FDI inflows are significantly
sensitive to the change in host country’s indicators of political risk such as government stability,
internal and external conflict, law and order, quality of bureaucracy, corruption and ethnic
tensions and democratic accountability of government. The higher value of political risk index
demonstrates the higher political stability. In this study, we use the average of Rule of Law,
Regulatory Quality and Government Effectiveness. The sixth hypothesis can be derived as
follows:
Hypothesis 6: The increase in host country’s political risk will have a negative impact on JFDI
3.1.7 Infrastructure development
By statistical analysis, Urata and Kawai (2000) examined and emphasized the importance
of the availability of infrastructure in attracting FDI by Japanese small and medium-sized
enterprises. For the time being, in some developing countries, it is rather hard for them to solve
the problems related to infrastructure development because of the lack of finance. The
insufficient infrastructure is one of the main problems that Japanese firms would encounter and
consider when investing in a particular country. As to the study of Urata and Kawai (2000), most
Japanese firms, who want to enter and set the investment in any country, always pay attention to
the availability of electricity because it is considered as the significant factors to produce high
quality products. However, as to Vijayakumar et al. (2010), there are some indicators used to
measure infrastructure development, for example, the availability of transportation,
telecommunications, electricity and water. The combination of those indicators is necessary to
reflect the host country’s infrastructure development. Therefore, after considering the availability
of data, in this study, the infrastructure development index is built by indexing the level of
electricity generation per person, the telephone lines (per 100 people) and the energy use (kg of
oil equivalent per capita). The seventh hypothesis is set as following:
Hypothesis 7: Host country’s infrastructure development will have a positive impact on JFDI

29. 28
3.1.8 Labor cost
With the purpose of seeking efficiency and market in host countries, the firms from
developed countries outweighed the labor-related issues. Among them, Mirza and Giroud (2004)
referred in their study the significant role of labor cost in attracting FDI into Vietnam. Because
of the pressure from other countries that have been in process of exploiting advantages for FDI
inflows, it is really necessary for Asian developing countries to base on its endowment, such as,
low labor cost, largely potential markets, a degree of innovatory capacity, etc. Thus:
Hypothesis 8: Host country’s labor cost will have a negative impact on JFDI
In summary, the below table indicates eight hypotheses that will be tested in this thesis:
Table 3.1: Summary of testing hypotheses
Hypotheses Description
H1 Host country’s market size will have a positive impact on JFDI
H2 Host country’s natural resource will have a positive impact on JFDI
H3 Host country’s inflation rate will have a negative impact on JFDI
H4 Host country’s exchange rate volatility will have a negative impact on JFDI
H5 Host country’s trade openness will have a positive impact on JFDI
H6 The increase in host country’s political risk will have a negative impact on JFDI
H7 Host country’s infrastructure development will have a positive impact on JFDI
H8 Host country’s labor cost will have a negative impact on JFDI
3.2 DATA AND MODEL SPECIFICATION
The dataset includes yearly observations from 1995 to 2012 for ten Asian countries:
Vietnam, Thailand, Indonesia, Malaysia, Philippines, Hong Kong, Korea, Singapore, India and
China. The dependent variable in this study is the Log of Japanese FDI (LJFDI) inflow in billion
Yen. The independent variables, chosen thoroughly basing on the previous studies and the
consideration of the availability of dataset, include Purchasing Power Parity adjusted Gross
Domestic Product (GDP), natural resource (NRE), inflation rate (IFL), exchange rate volatility
(EXCV), political risk (POL), trade openness (TO1), infrastructure development (INFRA2) and
labor cost (ARWAG).

30. 29
To archive the second objective, which indicates the determinants of Japanese FDI in ten
selected Asian countries, a panel data econometric model for this study was constructed based on
the basic theories, the empirical studies and the availability of data as follows:
LnJFDIit = α
α
α
α0 + β
β
β
β1 GDPit + β
β
β
β2NREit + β
β
β
β3 IFLit + β
β
β
β4 LnEXCVit + β
β
β
β5 POLit + β
β
β
β6TO1it + β
β
β
β7
INFRA2it + β
β
β
β8 ARWAGit + εit
Where:
LnJFDIit is the Log of Japanese Foreign Direct Investment in billion Yen for country i at time t.
GDPit is Purchasing Power Parity adjusted Gross Domestic Product in constant 2005
international $ for country i at time t and is the proxy of market size (Billion US dollars).
NREit is Natural Resource and is measured by the ratio of ore and metal exports to merchandize
exports for country i at time t (%)
IFLit is the inflation rate for country i at time t (%).
LnEXCVit is the Log of exchange rate index between Japanese Yen and host country i’s currency
at time t. The simple exchange rate index is constructed for selected countries as:
Yt = Xt / X1995
X1995 is the value of exchange rate in 1995 for each country
Xt is the value of exchange rate at time t for each country
Yt is the index value of exchange rate at time t for each country
TO1it is Trade Openness for country i at time t and is measured by the ratio of total import and
export to GDP (%).
POLit is Political Risk for country i at time t and is measured by the average of Rule of Law,
Regulatory Quality and Government Effectiveness. Those data are collected from Worldwide
Governance Indicators (WGI). This is the source of dataset produced by Revenue Watch and
Brookings Institution, World Bank Development Research Group and World Bank Institute.
There are six aggregate WGI measures, whose data are in a standard normal distribution, mean
of zero, standard deviation of one and run from -2.5 to 2.5. The higher values stand for better
governance.
POLit = ∑
3
3
Yjt /
j
Yjt is the value of the jth
indicator at time t for each country

31. 30
INFRA2it is Infrastructure Development Index for country i at time t. This is the average of the
index of the level of electricity generation per person, the telephone lines (per 100 people) and
the energy use (kg of oil equivalent per capita). Those data are collected from data source of
World Bank. The simple Infrastructure Development Index is constructed for selected countries
as:
Yjt = Xjt / Xj1995
Xj1995 is the value of jth
indicator in 1995 for each country
Xjt is the value of jth
indicator at time t for each country
Yjt is the index value of the jth
indicator at time t for each country. Then we take the average
of the above Yjt to get the Infrastructure Development Index for each country i as follows:
INFRA2it = ∑
3
3
Yjt /
j
ARWAGit is the Average Real Wage in USD for country i at time t and is the proxy of labor cost.
This data is collected from the International Labor Organization (ILO).
eit is the error time over the time t.
Table 3.2: Summary of expected signs of variables
Variables Proxy Unit Expected
Sign
Source
JFDI
(dependent
variables)
Annual Japanese FDI in host countries billion
Yen
Japan
Ministry of
Finance
Market size GDP: Host country’s GDP Billion
US
dollars
+
World Bank
Natural
resource
NRE: The ratio of ore and metal
exports to merchandize exports of host
countries
%
+
World Bank
Inflation rate IFL: Host countries’ annual inflation
rate
%
-
World Bank
Exchange rate
volatility
EXCV: Annual exchange rate index of
host countries’ currency against JPY
%
-
World Bank

32. 31
Trade
Openness
TO1: The ratio of total export plus
import to GDP
%
+
World Bank
Political risk POL: the average of Rule of Law
Index, Regulatory Quality Index and
Government Effectiveness Index
Index
+
Worldwide
Governance
Indicators
Infrastructure
development
INFRA2: The average of the index of
the level of electricity generation per
person, the telephone lines (per 100
people) and the energy use (kg of oil
equivalent per capita)
%
+
World Bank
Labor cost ARWAG: The Average Real Wage in
USD
US
dollar -
International
Labor
Organization
3.3 RESEARCH METHODOLOGY
3.3.1 Descriptive Analysis
In this section, by applying the method of descriptive statistics, the overview of JFDI
before and after the crisis in 1997 will be presented. The year of 1997 is chosen because it was
the first threshold on which JFDI underwent the large change. The descriptive analysis is
conducted by going from the whole context to the detailed selected Asian countries. By
describing the changes of JFDI towards the crisis in 1997, this part aims to synthesize and
analyze the specific factors of each selected Asian countries, which made them to be more or less
attractive destinations of Japanese firms in this period.
In the second section of this part, the ranking table of promising countries for JFDI from
2009 to 2013 will be also given with the purpose of discussing about the recent characteristics of
JFDI in ten selected Asian countries. By combining the figures, empirical studies and recent
surveys, the analysis in both two sections partially contributes for the outline of determinants of
JFDI.

33. 32
3.3.2 Regression Analysis
Data used for estimating the econometric model in this study is a panel dataset. The panel
data will be in the period of 1995 to 2012 and consist of 10 selected Asian countries, including
Vietnam, Thailand, Indonesia, Malaysia, Philippines, Hong Kong, Korea, Singapore, India and
China.
There are three common methods used to analyze panel data. They are Common Constant
Method, Fixed Effects Method (FEM) and Random Effects Method (REM). Theoretically,
increasing the accuracy in calculation is the main advantage of panel data, which can be easy to
realize. As to each individual, by the combination of many periods of data, the number of
observations is accelerated. The second benefit of panel data is in FEM, which allows the
researchers to consider unobserved heterogeneity that may be correlated with the regressors. On
the other hand, one more advantageous method referred in panel data is REM, which manages
the unobserved heterogeneity to be independent with the regressors. Nevertheless, if the model
includes the fixed effects, REM and Common Constant Method seem to be
inappropriate.(Cameron & Trivedi, 2005).
The general model for panel data can be presented as follows:
Yit = α it + Xitβ it + uit, i = 1,....,N; t = 1,....,T
Where i stands for cross section or individual, t stands for the time, Yit is a dependent variable,
Xit is a Kx1 vector of independent variables, uit is disturbance term.
The common constant method
The Common Constant Method is also called as Pooled OLS method. This method is
conducted under the basic assumption that there is no difference among data matrices of cross
section dimensions. In this model, the coefficients and intercepts are the same. Therefore, the
model of Pooled OLS method is as follow:
Yit = α + Xitβ + uit
Despite being a simple method in panel data, Pooled OLS method still has the drawbacks. It is
very common that each individual i has time-invariant but unique effects whereas Pooled
regression model ignores the heterogeneity between individuals and assumes the same
coefficients for all of them, and then, the above-referred effects will be included in the error term

34. 33
uit. However, the regressors are not correlated with the error term. Since then, the regression
results from Pooled OLS would be inconsistent.
The fixed effects method
The general model of FEM can be written as following:
Yit = α i + Xitβ + εit
It is clearly stated that the intercept with the subscript i means that the intercept of each
individual would be different. The meaning of the term “fixed effects” is that even though the
intercept may be different between individuals, it does not vary across time. It is called as “time-
invariant”. Then, the main idea of FEM is removing the effects of time-invariant characteristics,
such as culture, religion, gender, etc from the predictor variables. The unobserved heterogeneity,
which is correlated with the regressors, can be measured by the individual-specific effects α1 ….
αN. Therefore, if fixed effects existed and correlated with the observed regressors, the estimation
of Pooled OLS method would be biased and inconsistent.
The way of estimation in FEM is least square dummy variables (LSDV) method. By
generating as many dummies as individuals, we can measure the different characteristics of each
individual. However, it is really important to subtract one dummy variable for one individual to
avoid dummy variable trap or perfect multicollinearity. Under this concept, the general model of
LSDV method can be presented as follows:
Yit = α1 + α 2D2i + …. + αND Ni + Xitβ + εit
Applying the above method in this study, we have nine dummies used to represent for ten
countries. Therefore, the specific model demonstrating the study of determinants of Japanese
FDI in ten selected Asian countries can be written in the following equation:
LnJFDIit = α
α
α
α 1 + α
α
α
α 2D2i + α
α
α
α 3D3i + α
α
α
α 4D4i + α
α
α
α 5D5i + α
α
α
α 6D6i + α
α
α
α 7D7i + α
α
α
α 8D8i + α
α
α
α 9D9i + β
β
β
β1 GDPit
+ β
β
β
β2 NREit + β
β
β
β3 IFLit + β
β
β
β4 LnEXCVit + β
β
β
β5TO1it + β
β
β
β6 POLit + β
β
β
β7 INFRA2it + β
β
β
β8 ARWAGit + εit
Where: α1 is the intercept of Vietnam
D2i, D3i, D4i, D5i, D6i, D7i, D8i and D9i represent for Thailand, Indonesia, Malaysia, Philippines,
Hong Kong, Korea, Singapore, India and China
D2i = 1 for Thailand, 0 otherwise; D3i = 1 for Indonesia, 0 otherwise; and so on.
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35. 34
The random effects method
Unlike FEM, in REM, the unobserved heterogeneity is assumed to be random variables
and uncorrelated with the regressors included in the model. The advantage of REM is that REM
can estimate the coefficient of time-invariant variables which is explicitly introduced in the
model. The general model for REM can be written as follows:
Yit = µ + Xitβ + αi + εit
or we can rewrite the above equation as: Yit = µ + Xitβ + uit where the error term uit includes two
components: The first one is individual-specific error component αi, which varies across
individuals but consistent over time. The second one is the combined cross-section and time
series error component εit, which varies over individuals and time.
The Hausman test
As to two above-mentioned sections, the basic difference between FEM and REM is the
assumption that whether there is the correlation between individual-specific error component αi
and the X regressors or not. Clearly, if αi and the regressors were not correlated, REM would be
appropriate, otherwise, FEM would be the more suitable model.
Based on that concept, a test called Hausman test is built and used to decide whether
FEM or REM is better. The statistic test of Hausman test can be presented as follows:
(βFE – βRE)’[Var(βFE) - Var(βRE)]-1
(βFE – βRE) ~ χ2
(k)
Where βFE and βRE are the vectors of coefficients from FEM and REM. The Hausman test is set
with the null hypothesis that the individual-specific effects are uncorrelated with the regressors
or REM is supported. Basing on the very low p value of estimated chi-square statistics, Hausman
test rejects the null hypothesis. It means that the regression results from REM are not consistent
and FEM is the more appropriate model.
Test for Heteroskedasticity
One of the important assumptions related to the error term ui in the regression model is
the existence of equal variance or homoscedasticity across observations. In the case that this
assumption is not satisfied, it leads to the heteroskedasticity or unequal variance. This is the
common problem in cross-sectional data (Gujarati & Handelshøyskolen, 2011). On the other
hand, according to Juhl and Sosa-Escudero (2014), linear panel model contains many features
with standard linear regressions. As a result, the cross-sectional domain heteroskedasticity would
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happen to most panel models and it requires the detection tests and the remedial measures as
well.
In this study, we use the “xttest3” command in Stata to calculate the modified Wald test
for groupwise heteroskedasticity (Baum, 2001). The null hypothesis indicating that: α
2
i
=
α
2
with i = 1,…, N where N is the number of cross-sectional units means that the existence of
homoscedasticity across observations. The null hypothesis is rejected when the estimated chi-
square statistic is larger than the critical value of χ2
distribution for some level of significance. At
that time, we can conclude that the heteroskedasticity exists in the model. In Stata, the option
“robust” can be used to control for heteroskedasticity in fixed and random effects.
Test for serial correlation
Another common problem related to the error term ut is the correlation between the error
term at time t with the error term at time (t-1) or the one in the past. This problem is called as
autocorrelation or serial correlation. In the case of autocorrelation, although the OLS estimators
are consistent, they are not efficient because the autocorrelation in panel data models bias the
standard errors (Drukker, 2003).
There are many tests proposed to detect the serial correlation in panel-data models. In this
study, we use the “xtserial” command in Stata to conduct the Wooldridge’s test and find out
whether serial correlation exists in the model. According to Drukker, Wooldridge’s test is easy to
conduct because it requires relatively few assumptions. Under this test, the calculations in
different cases can be conducted, such as, the cases of fixed and random effects model, with or
without homoskedasticity, with balanced data or with unbalanced data. On the other hand, with
fewer assumptions, the Wooldridge’s test seems to be less powerful than other tests.
Nevertheless, it has good size and power properties. The null hypothesis is no serial correlation.
Based on the estimated statistic, we can conclude whether the data does not have first-order
correlation or not.
Test for multicollinearity
Another important assumption in linear regression model is no linear relationship among
the regressors. If there is only one relationship between two regressors, it is called as collinearity.
In the case that there is more than one, we call it as “multicollinearity”. Because of the
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