Determinants of foreign direct investment in malaysia

University Malaysia Sarawak
SEMESTER 2 2015/16
Class: Monday (11am-02pm)
Research Proposal
Submitted to Dr Venus Khim-Sen Liew
5/27/2016
The Determinants of Foreign
Direct Investment in Malaysia

Determinants of Foreign Direct Investment in Malaysia
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FACULTY OF ECONOMICS AND BUSINESS
EBQ2054: RESEARCH METHODOLOGY FOR ECONOMICS AND BUSINESS
SEMESTER 2 2015/16
Class: Monday (11am-02pm)
Research Proposal
TITLE: The Determinants of Foreign Direct Investment in Malaysia
Lecturer: Dr Venus Khim-Sen Liew
Group Members
No Name of Student Matric Number
1 Mohammad HasanTusher 44811
2 Viknesh Somasundram 50068
3 Koo Kang cheng 49749
4 Mohamad Noor Adam Bin Mohd Nasir 47588

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Table of Contents
CHAPTER ONE...........................................................................................................6
INTRODUCTION ........................................................................................................6
1.0 INTRODUCTION ..........................................................................................6
1.1 BACKGROUND OF THE STUDY.........................................................9
1.1.1 AN OVERVIEW OF FOREIGN DIRECT INVESTMENT..........9
1.1.2 FOREIGN DIRECT INVESTMENT IN MALAYSIA..................12
Figer 1.1: Foreign direct investment, net inflow .....................................13
1.2 PROBLEM STATEMENT.........................................................................15
Figer 1.2: Foreign direct investment, net inflows (% of GDP) .............16
1.3 SCOPE OF STUDY......................................................................................16
1.4 RESEARCH QUESTIONS .........................................................................17
1.5 RESEARCH OBJECTIVES .......................................................................17
1.5.1 GENERAL OBJECTIVE .................................................................17
1.5.2 THE SPECIFIC OBJECTIVES ARE:............................................17
1.6 TERM DEFINITION..................................................................................18
1.6.1 FOREIGN DIRECT INVESTMENT(FDI) ....................................18
1.6.2 INFRASTRUCTURE........................................................................18
1.6.3 EXCHANGE RATE..........................................................................19
1.6.4 MARKET SIZE.................................................................................19
1.6.5 GROSS DOMESTIC PRODUCT....................................................19
1.7 SIGNIFICANCE OF THE STUDY............................................................19
1.8 LIMITATION OF THE STUDY ................................................................20
1.9 ORGANIZETION OF THE STUDY .........................................................21
CHAPTER TWO........................................................................................................22
LITERATURE REVIEW..........................................................................................22

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2.0 INTRODUCTION ........................................................................................22
2.1 CONCEPTUAL FRAMWORK.............................................................22
2.1.1 EXCHANGE RATE AND FDI ........................................................23
2.1.2 MARKET SIZE AND FDI ...............................................................25
2.1.3 INFRASTRACTURE AND FDI ......................................................26
2.2 EMPAIRICAL TESTING PROCIDURE..................................................27
2.3 EMPAIRICAL RESULTS...........................................................................32
2.4 CONCLUSION REMARKES.....................................................................34
CHAPTER THREE....................................................................................................35
METHODOLOGY .....................................................................................................35
3.0 INTRODUCTION ........................................................................................35
3.1.2 SCHEMATIC DAIGRAM OF THE CONCEPTUAL
FRAMEWORK ..........................................................................................36
3.2 DATA COLLECTION.................................................................................36
3.2.1 SAMPLE OF THE STUDY..............................................................37
3.2.2 DATA AND DATA SOURCES........................................................37
3.2.3 METHOD OF ANALYSIS...............................................................37
3.3 Research Methodology.................................................................................38
3.3.1 HYPOTHESIS DEVELOPMENT...................................................39
3.3.1.1 Hypothesis 1 ....................................................................................39
3.3.1.2 Hypothesis 2 ....................................................................................39
3.3.1.3 Hypothesis 3 ....................................................................................40
3.3.2 ECONOMETRIC MODEL SPECIFICATION.............................40
3.4 ECONOMETRIC METHODOLOGY.......................................................42
3.4.1 ORDINARY LEAST SQUARE (OLS)............................................42
3.4.2 JARQUE-BERA (JB) TEST .....................................................42

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3.4.3 SERIAL CORRELATION (BREUSCH- GODFREY TEST)
43
3.4.4 WHITE’S GENERAL TEST ....................................................44
3.4.5 RAMSY’S RESET TEST.................................................................44
3.4.6 CUSUM & CUSUM SQUARES TEST ...........................................45
3.4.7 GRANGER CXAUSALITY TEST..................................................45
3.5 CONCLUTION REMARKES ....................................................................47
References....................................................................................................................49
Appendix......................................................................................................................54
Data......................................................................................................................54
Table of the literature review ……………………………………………………...55

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CHAPTER ONE
INTRODUCTION
1.0 INTRODUCTION
Over the past decade, foreign direct investment (FDI) has increased sharply as a major
form of international capital transfer. Economic phenomena such as globalization,
liberalization and economic integration are one of the significant outcomes from the flow of
FDI. It is widely recognized that FDI generate economic benefits to recipient country.
However, economists have no general consensus on the factors to determining the flow of
FDI. That means until now there have no independent variables able to consider as the correct
determinant of FDI. Many of the studies have shown mixed result of the determinant of FDI.
Main factors driving FDI like the rate of exchange, wages, corporate tax, and trade barriers
identified to have both positive and negative impact on FDI.
In classic form, FDI is a company from one country making a physical investment by
building a factory in another country. While according to the IMF’s Balance of Payments
Manual 5th edition, FDI can be defined as the investment made to acquire lasting interest in
enterprises and develop a multinational corporation (MNC) together with foreign affiliate. In
line with the definition of IMF and OECD, Malaysia has chosen an arbitrary value, holding
of at least 10 per cent of the total equity in a resident company by a non-resident direct
investor. This also include a foreign direct investment relationship which connecting the non-
resident direct investor and resident companies with subsequent transactions in financial
assets and liabilities. Generally, the motive behind foreign investors is influenced by three
groups of factor. First is the resource-seeking, this might be happen when the home economy
lack of natural resources and factor of production. The second one is market-seeking which

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aim to discovering the new markets or expanding the existing market. Third groups will be
efficiency-seeking by trying to develop economies of scale to improve the efficiency and
profit.
Global FDI dominated by United States after the Second World War and according to
the history, there have around 60% of the world FDI stock in this time period was in natural
resources. Availability of these kind resources especially minerals, agriculture product and
raw material become an important determinant of FDI for host country. Malaysia as a
medium-size, upper middle income developing economy, although it is largely urbanized but
the state continues to develop their cultural sectors actively. This is aided well by its rich
natural resources. In addition, a condition where politically stable is highly attractive to
foreign investment. Hence, FDI appears to a key driver underlying the strong growth
performance experienced by the Malaysian economy. Reformation of the policy to improve
the investment climate by Malaysia government with the introduction of Investment
Incentives Act in 1968 to promote manufacturing export such as exempt from company tax
and import duty. The next step follow by bring in the New Economy Policy (NEP) in 1970;
foreign investors owned 60% of the Malaysian corporate economy, with around 23 per cent
of the largest part of local share hold by the local Chinese business community. In order to
raise the Malay share of the corporate sector to 30%, state development agencies set up
subsidized Free Trade Zones in the early of 1970s. But this is not apply on individual
company basis and this is key element of the NEP attract foreign investor participation where
100% foreign ownership of export-oriented firms is allowed.
Generally, Malay upper and middle classes prefer foreign investment since under the
NEP’s ethnic ownership and employment quotas, foreign investment offers them with more
opportunities for employment at all level of the workforce. On the other hand, Chinese
business community generally positioned themselves well of collaborative relationships since

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foreign investment is important in technology transfer, develop new market and contributing
more to economic growth if compare with domestic investment. Chinese middle classes are
able to take advantage of getting skilled, managerial and professional jobs in foreign firm.
Nevertheless, NEP aim to remove the identification of race with economic function in
Malaysian society. Government tries to restructure by imposed restrictions on foreign
investment while selectively welcoming to reserve certain percentage of employment for
Malay. But over the years, increasing of public debt by 1980s force Malaysia government to
deregulates the FDI rules to become more transparent. More of the restrictions have been
relaxed since foreign capital is able to reduce Malaysia’s budget and balance of payments
deficits. In the late 1980s, FDI start to flood into Malaysia depends to the Chinese
connection. Presence of significant Chinese business community in Malaysia, proximity to
Singapore and fast developing East Asia countries and also the convenient production base
for relocation of labour intensive segments in response to wage rate pressure and lack of
labour force problem success to attract investors from Taiwan, Hong-Kong, Korea and also
FDI from Developed- country multinational.
Furthermore, Malaysia government recognizes that foreign investment particularly in
manufacturing helped Malaysia to improve economy growth and provide benefit of
employment opportunity. Introduction the growth triangle concept, like Singapore-Johor-
Riau (SIJORI) and Northern Growth Triangle recently is to attract more FDI and bring
Malaysia into international economy. This step provides incentive for multinational
enterprises by making wider production base with different factor endowments in each node
of the triangle. For instance, this concept had been attracting investment of US6.2 million
from Indonesia and US 2.51 billion from Singapore. However, there are many other factors to
drive the rate of FDI other than the determinant we mention above. It is believed that sound
macroeconomic management, well-functioning financial system has made Malaysia an

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attractive location for FDI. A survey of electronics companies in Japan rated Malaysia as the
best host location for foreign manufacturing investment in Asia. FDI has played a crucial role
in the country’s economic development process. However, there has been a persistent decline
in the ratio of FDI inflows to GDP since the early 1990s. While for the period of 2003 to
2007, total stock of FDI increased substantially mainly due to mergers & acquisitions of
existing multinational company’s joint ventures and new investment activities. The
movement of the FDI becomes a major concern of researchers and policy maker to
investigate what are the key forces that determines FDI in Malaysia.
1.1 BACKGROUND OF THE STUDY
1.1.1 AN OVERVIEW OF FOREIGN DIRECT INVESTMENT
According to Organization for Economic Cooperation and Development (OECD)’s
Benchmark Definition of Foreign Direct Investment 3rd Edition (OECD, 1999), the
definition of foreign direct investment (FDI) is ‘the objective of obtaining a lasting interest by
a resident entity in one economy (direct investor) in an entity resident in an economy other
than that of the investor (direct investment enterprise)’’. An investment can be qualify as FDI
if it could afford the parent enterprise control over its foreign affiliate. In this case,
International Monetary Fund (IMF) defines this control as owning 10% or more of the regular
shares or voting of an incorporated firm or its equivalent for an unincorporated firm. There
have typical two types of direction for FDI. Inward investment is when foreign capital occurs
in local resource. The other type of FDI is outward direct investment, can also be referred as
direct investment abroad which means local capital is invested in foreign resources.
Generally, FDI classified into three components which is equity capital, reinvested
earnings and intra-company loans. While the FDI data on the other hand are normally

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describe in terms of stock and flow. FDI stock includes value of capital and reserve plus net
indebtedness. FDI flow refers to a foreign investor offer or accepts capital with others FDI
enterprise. Explosion of growth in FDI over time has raised the interest of economists to
examine the question about why do companies invest abroad. Basically, there have three
groups of factors that affected FDI. Firstly, foreign investor concern about the profitability of
the foreign investment project. Second, degree of the ease with which subsidiaries’ operations
can be integrated into the business strategies of foreign enterprise. Lastly, depends to overall
quality of the investment environment in host country. As a result, Dunning et al. (1977) and
Dunning (1988) combined both microeconomic and macroeconomic perspectives to develop
his theory, so-called OLI paradigm. It states that FDI is undertaken if ownership (O)
advantage like proprietary technology exists together with country specific location (L)
advantage in host country like low factor costs, and potential benefits from internalization (I)
advantage of production process abroad. The latter answer the question of why do
multinational enterprises choose to invest abroad significantly. The factors such as
availability of factor of production like natural resources, raw material, market size,
infrastructure system, factor price and certain elements of government policy are all influence
investor to selects a location for the project. This point of view provides an interesting
background in order to study the determinants of FDI.
Foreign direct investment (FDI) or foreign investment can be defined as long term
participation by country A into country B. It usually involves participation in management,
joint-venture, transfer of technology and expertise. More specifically, foreign direct
investment is a cross-border corporate governance mechanism through which a company
obtains productive assets in another country. FDI is different from other major forms of
foreign investment in that it is motivated largely by the long-term profit prospects in
production activities that investor directly control (Tsen, 2005).

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Most of the developing and least developed countries worldwide equally participated in the
process of direct investment activities . Over a long period of time, foreign direct investment
(FDI) forms a major part of investment in most industrial and some developing countries. In
the last 2 decades, foreign direct investment (FDI) flows have grown rapidly all over the
world. This is because many countries and especially developing countries see FDI as an
important element in their strategy for economic development (Adams, 2009).
The United States is the world’s largest recipient of FDI. More than $325.3 billion in
FDI flowed into the United States in 2008, which is a 37 percent increase from 2007. Some
FDI is intended to utilize local natural resources. Sometimes it is to employ relatively cheap
labour, and sometimes to produce goods near to markets.Besides, foreign direct investment
can be a significant driver of development in poor nations. It provides an inflow of foreign
capital and funds, in addition to an increase in the transfer of skills, technology, and job
opportunities. Furthermore, it would be difficult to generate this capital through domestic
savings, and even if it were not, it would still be difficult to import the necessary technology
from abroad, since the transfer of technology to firms with no previous experience of using it
is difficult, risky, and expensive. If FDI has a positive impact on economic growth, then a
host country should encourage FDI flows by offering tax incentives, infrastructure subsidies,
import duty exemptions and other measures to attract FDI ( Katerina, John and
Athanasios,2004)
Many of the East Asian tigers such as China, South Korea, Malaysia, and Singapore
benefited from investment abroad. The rise of the four Asian small dragons (Hong Kong,
Taiwan, Singapore and Korea) in the 1960s-1970s and rapid growth of China and India in
recent years all benefits from the vast inflows of FDI (Tian, Hires, Mao, Huber, Chiappe,
Chalasani, & Bargmann, 2009). At the time the government has recognised the importance of

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liberalisation and openness to FDI , effective measures are designed to attract the capital and
management expertise to transform inefficient state-dominated economies, at the same time
easing the burden of this transformation on the public budget and assumed to positively affect
local economic development.
1.1.2 FOREIGN DIRECT INVESTMENT IN MALAYSIA
Malaysia is a nation on the move and has become an economy driven by exports,
technology, capital-intensive, and knowledge-based business. Malaysia has been an
encouraging economy to foreign investors through Malaysia's strengths which include well-
developed infrastructure, industrious workforce and also a politically stable nation with a
good legal system and provides attractive incentives for investors. Foreign Direct Investment
(FDI) in Malaysia is set up following the holding of at least 10% of the total equity in a
resident company by a non-resident investor.
Foreign direct investment (FDI) has been seen as a key driver underlying the strong
growth performance experienced by the Malaysian economy .To attract a larger inflow of
FDI, the government introduced more liberal incentives including allowing a larger
percentage of foreign equity ownership in enterprise under the Promotion of Investment Act
(PIA), 1986 ( Sharif, Zulkornain, & Hook, 2009). Today, its market-oriented economy,
combined with an educated multilingual workforce and a well-developed infrastructure, has
made Malaysia one of the largest regional and global recipients of FDI (Lean, 2008).
Besides, the rapid industrialisation of the country is attributed in part to the inflow of
foreign direct investment to the manufacturing sector. Many manufacturers have taken
advantage of the country’s capabilities by outsourcing their manufacturing activities to
Malaysian companies or setting up their own operations in Malaysia. The massive influx of

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foreign investments into the manufacturing sector was pivotal in its transformation from an
agricultural economy to an industrialized economy (Rasiah, & Shahrin, (2006).
The inflow of FDI was only US$94 million in the early 1970s but increased
dramatically in 1996 with US$7,297 million. It dropped to US$2,714 million in 1998 due to
the 1997 financial crisis but recovered strongly with the highest FDI inflows of US$8,403
million in 2003 as Malaysia was able to maintain its attractiveness as a FDI location
(Shahrudin, Yusof, & Satar, 2010).
Malaysia’s foreign direct investment flows continued to contract in 2009 as a result of
the global financial crisis and economic downturn. The sharp decline reflected falling profits
and reduced financial capabilities of companies, impacted by the global crisis. But, Malaysia
FDI inflows are expected to recover gradually in 2010 and will be able to sustain its FDI in
2011. According to International Trade and Industry Minister, Datuk Seri Mustapa
Mohamed, FDIs in Malaysia leaped to RM17.1 billion for the period from January to
September 2010 compared to just RM5 billion recorded for the whole of last year.
Figer 1.1: Foreign direct investment, net inflow
Source: World Development Indicator (2015)
0
2E+09
4E+09
6E+09
8E+09
1E+10
1.2E+10
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Country: Malaysia

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However, different studies express different views related to FDI but some of these
consider the significant role of infrastructure, human capital and exchange rate along with
other determinants for attracting the FDI inflows (Chaudhry, Mehmood, & Mehmood, 2013;
Asgher, Awan, & Rehman, 2012; Rehman, Ilyas, Alam, & Akram, 2011; Asiedu, 2004; Xing
and Zhao, 2003; Noorbakhsh, Paloni, & Youssef, 2001; Moore, 1993; Wheeler and Mody
1992). The bottom line of these studies highlights that Multinational Corporations (MNCs)
are in search of such markets where they can get the advantage of low cost, high profits and
economies of scale. As inflow of foreign capital and resource creates backward and forward
linkages, MNC’s contribute technical help to promote the domestic firms. The level of
technology and productivity through both labor and capital of domestic producers will
increase (Asiedu, 2004; Shahbaz and Rehman, 2010). A number of factors gave foundation to
the increased efforts by developing countries to attract FDI inflows. A firm invests across the
border either to exploit a foreign market or to get better access to the certain inputs most
likely the better infrastructure and skilled and cheap human capital.
According to UNCTAD (1994, p. 286), the capacity building and recognition by
policy makers in terms of capabilities encompassed in FDI has the ability to contribute
directly towards the growth and development of the national economy. Secondly the other
rescue packages for the corporations are declined in such a way that they increase the level of
reliance on FDI. However, the government of these developing countries has gained
momentum in maximizing the benefits and controlling the liabilities of investment by
transitional corporations (Asiedu, 2004; Kok and Ersoy, 2009). Hence, FDI can bring vital
and potential benefits through the spillovers of management, technical skills, and information
technology and through better utilization of infrastructure.

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A number of studies’ bottom line has revealed that the propensity of spillovers which
takes its place is a function of absorptive capacity of the host country, which, in turn, is a
function of the development level of an economy, the education level of the human capital
and the competition level of the host economy (Blomstrom and Kokko, 1997; Resmini, 2000;
UNCTAD, 1994). Classical theory related to the international capital flow states that FDI is a
function of differences in the international rates of return on capital (Khan and Nawaz, 2010).
Overall, exchange rate, market size and Infrastructure have considerable importance
in accordance to FDI inflows. As for as Malaysia is concerned the above mentioned variables
have greater importance and emergence to point out. In this regard this study attempts to
highlight the role of exchange rate, market size and Infrastructure for attracting FDI in
Malaysia
1.2 PROBLEM STATEMENT
Over the recent years, most of the countries over the world have made their business
environment investment friendly for absorbing global opportunities by attracting more
foreign investable funds to the country. Malaysia is no exception in the implementation of
these measures. Recently, government of Malaysia is serious in transforming the economy
and will continue to undertake proactive measures to further promote FDIs to ensure that
Malaysia meets the target in the 10th Malaysia Plan. In order to make 10th Malaysia Plan
successful, the government should know the most important determinant of foreign direct
investment in Malaysia to ensure that there is no miss-step in attracting FDIs to come into
Malaysia.
Thus, the main problem statement here, although there is a increasing trends of the
FDI inflow of Malaysia mareket but there is a decreasing trends of the growth of FDI inflow
into gross domestic product so, this is important for Malaysia to attarect FDI to increase the

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FDI growth and that’s why we need to see whether those variables involve which are
infrastructure, exchange rate and market size can be classified as important instrumental in
attracting and maintaining the interest of foreign direct invesor to put their money in
Malaysia.
Figer 1.2: Foreign direct investment, net inflows (% of GDP)
Source: World Development Indicator (2016)
1.3 SCOPE OF STUDY
The research is about “The study on the relationship between foreign direct
investment and infrastructure, exchange rate and market size”. This study aims to analyse
whether the three independent variables, which are infrastructure, exchange rate and market
size have positive effect towards inflow of foreign direct investment. This study focuses on
foreign direct investment in Malaysia.
The infrastructure is measured by government development expenditure on
transportation,communication and public utilities. While for exchange rate, exchange rate
RM/US$ is used as a proxy and market size is measured by Gross Domestic Product (GDP)
0
1
2
3
4
5
6
7
8
9
10
Malaysia

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per capita. The dependent variable of foreign direct investment is measured by net inflow of
foreign direct investment(FDI).
The study of this research covers 30 years commencing from the year 1984 to 2013.
The data collection of the study is based on secondary data. All data of variables are
collected from United Nation Conference on Trade and Development(UNCTAD) Statistics,
Department of Statistics, Ministry of Finance Malaysia, Economic Report, Bank Negara
Malaysia and Datastream.
1.4 RESEARCH QUESTIONS
Is there any growth of FDI?
Is there any significant relationship between infrastructure and foreign direct investment in
Malaysia?
Is there any significant effect of exchange rate towards foreign direct investment in
Malaysia?
Is there any correlation between market size and foreign direct investment in Malaysia?
1.5 RESEARCH OBJECTIVES
1.5.1 GENERAL OBJECTIVE
The general objective of this study is to understanding the determining factors of FDI inflows
in Malaysia.
1.5.2 THE SPECIFIC OBJECTIVES ARE:
To investigate the determinant of foreign direct investment in Malaysia.
To determine the growth of FDI.

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To investigate the relationship between infrastructure and foreign direct investment in
Malaysia.
To identify the effect of exchange rate towards foreign direct investment in Malaysia.
To examine to what extent market size can influence foreign direct investment in Malaysia.
1.6 TERM DEFINITION
1.6.1 FOREIGN DIRECT INVESTMENT(FDI)
Foreign direct investment (FDI) or foreign investment refers to the net inflows
ofinvestment to acquire a lasting management interest (10 percent or more of voting stock) in
an enterprise operating in an economy other than that of the investor. It is the sum of equity
capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in
the balance of payments. It usually involves participation in management, joint-venture,
transfer of technology and expertise.
1.6.2 INFRASTRUCTURE
Infrastructure is the basic physical and organizational structures needed for the
operation of a society or enterprise, or the services and facilities necessary for an economy to
function. The term typically refers to the technical structures that support a society, such as
roads, water supply, sewers, power grids, telecommunications, and so forth . Viewed
functionally, infrastructure facilitates the production of goods and services; for example,
roads enable the transport of raw materials to a factory, and also for the distribution of
finished products to markets.

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1.6.3 EXCHANGE RATE
Rate at which one currency may be converted into another. The exchange rate is used
when simply converting one currency to another (such as for the purposes of travel to another
country), or for engaging in speculation or trading in the foreign exchange market.
1.6.4 MARKET SIZE
The number of buyers and sellers in a particular market. This is especially important
for companies that wish to launch a new product or service, since small markets are less
likely to be able to support a high volume of goods. In other words, it can be defined as the
size of a group of consumers with shared needs and their buying power.
1.6.5 GROSS DOMESTIC PRODUCT
Gross domestic product (GDP) refers to the market value of all final goods and
services produced within a country in a given period. It is often considered an indicator of a
country's standard of living. The gross domestic product (GDP) is one the primary indicators
used to gauge the health of a country's economy .
1.7 SIGNIFICANCE OF THE STUDY
The study examines the roles of exchange rate, infrastructure, and market size in
determining the FDI growth in Malaysia during the period from 1997-2013. The findings
from this study provide useful insight on the relationship between changes in the
infrastructure, interest rates and market size towards FDI inflow into Malaysia. In particular,
this study is intended to illustrate the determinants towards FDI activity.
Factors of FDI are a popular topic among the researchers. Even though, there have
been many previous studies done on the factors of FDI but less for Malaysia, in this case,

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researchers have added a relatively important variables such as exchange rate, infrastructure,
market size and gross domestic product into the model in order to find out whether the
amount exchange rate, infrastructure, market size and gross domestic product affects the FDI
inflow of Malaysia. This study will contributes to policymakers like Bank Negara Malaysia
and the Federal Government as it gives them a picture of what variables are significantly
affecting FDI inflows in Malaysia. Researchers have included some important economic
factors like exchange rate, infrastructure, market size and gross domestic product. The most
important factors are of course the gross domestic product and exchange rate. This study
results can serve as a guideline or reference to Bank Negara Malaysia and the Federal
Government in formulating monetary and fiscal policy to meet up with the preference of
direct investors who consider investing in Malaysia. Besides, these can prevent policymakers
from focusing on the unnecessary areas wasting resources in an effort to attract more FDI.
The result of this study will help to the government, policy maker and the user to have
a supporting knowledge about to find out the important determinants which is effective to
attract the foreign direct investment.
1.8 LIMITATION OF THE STUDY
As mentioned, the causes of FDI inflow to Malaysia’s and the determinants of it is
still consider an attractive area of study and relevant sources of this topic are limited for
specific Malaysia. Furthermore, majority of the information available focuses on exchange
rate, infrastructure, market size and gross domestic product that linked to a country’s FDI
growth but not on the relationship between economic growth and FDI. Hence, we have
relatively less relevant materials to refer.
We are not doing or taking any survey to collect the primary data for our research
because it needs more time and money and so we are using the secondary data which is

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collected from World Bank data and the Department of Statistics of Malaysia. Thus, if there
is any problem in the collection of the primary data it will not represent the true result and we
can’t minimise this limitations because we are dependent on secondary data in this study.
Another limitation in this study is the data collected were infrastructure, which is
measured by government development expenditure on transportation, communication and
public utilities data used in the empirical tests because we didn’t find any specific data for the
infrastructure Therefore, to ensure the continuity of the empirical tests, it was necessary to
use proxy data collected were infrastructure, which is measured by government development
expenditure on transportation, communication and public utilities which is not cover all the
infrastructure.
Besides that we only used four variables to analyse Malaysia’s FDI inflow. There are
many and more macroeconomics variables which is related or influence the factors affecting
FDI in Malaysia. The inclusion of more variables will help in providing a more accurate
study results.
1.9 ORGANIZETION OF THE STUDY
The study is divided into three chapters and the structure is as follows: Chapter one
introduces Malaysia’s economy and addresses the study’s main mechanism; Chapter two is
the literature review about exchange rate, infrastructure, market size and gross domestic
product and FDI, where views from others protagonists are briefly discussed; Chapter three
focuses on the research methodology and the theoretical framework used to test the
relationship between market size, exchange rate, infrastructure and FDI.

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CHAPTER TWO
LITERATURE REVIEW
2.0 INTRODUCTION
There are different results obtained from previous studies about the relationship
between FDI and Market size, Infrastructure and Exchange rate based on the different
method, different variables and also different countries. The empirical result from the
previous researchers has shown the different relationship among the FDI, Market size,
Infrastructure and Exchange rate. . In this study we are going to show some of the previous
literature conceptual framework, testing procedure and the empirical findings. Section 2.1
presents conceptual framework by variables, Section 2.2 reviews the testing procedure,
Section 2.3 presents the empirical results and Section 2.4 is the conclusion for literature
review and summary table.
2.1 CONCEPTUAL FRAMWORK
FDI is a concept of the globalization. Froeign direct investment or FDI means one
country business man invest another country. It can be FDI inflow or FDI outflow. FDI
inflow is a very good effect for any country economic growth. Almsafir, Latif and Bekhet
(2011); Mughal and Akram (2011); Bashir, Raza and Farah (2015) postulates that FDI is the
key role for the developing country for growth and integrate with the global business
especially in economics and capital flow. For this reason almost all country invite the
investor to invest their country. There are many factors that attract investors to come with
FDI. Five main reason for FDI, capital flow, advantages of oligopolistic, cost advantages,
currency effects, and political stability (Awan, Khan, & Zaman, 2011).
According to the concept of FDI, firstly, capital flow wealthy country to poor country
and provides a win-win situation for both country. This is mostly from developing country,

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due to the diminishing return of the capital because investor can get the biggest return from
their investment in abroad (Awan et al, 2011). Secondly, take the advantages of oligopolistic
by acquisition of foreign firm because foreign investor acquire the local firm and dominate
the international business (Kedron & Bagchi, 2012) Thirdly, cost advantages of production
factors because of the low cost location means the cheap labor cost and the cheap raw
materials (Barrell, & Pain,1997). Fourth, appreciation the host and home country currency
effect. It means appreciation of the home country encourage the FDI outflow because of the
increasing demand of home currency and more purchasing power form the host country (Lily,
Kogid, Mulok, Sang & Asid, 2014) and fifth, political stability encourage the FDI because
promoting liberal policy, security, quality institution and degree of the protection of property
right are the key influencing factors that effects the returns of the investor (Baek, &Qian,
2011).
In the next section, we will discuss about the effect of exchange rate, market size and
fixed capital formation on FDI from the previous studies to find out concept and general
ideas that are related to our research problem.
2.1.1 EXCHANGE RATE AND FDI
Exchange rate of a country has remained a debatable and controversial topic for
researchers and policy makers. Different researches show different opinions in this regard as
Kohlhagen (1977) conducted a study which reveals that MNEs converge toward increasing
their production capacity in foreign countries, and the motive behind this is to serve their
domestic market in case the foreign currencies depreciate. Appreciation of exchange rate
decrease the FDI (Tsen, 2005) because it decrease the wealth of the investor by paying the
higher cost for factors of production. Blomstrom and Kokko (1997) conclude that the host
country market size, local regulations, infrastructure and technological capacity of local firms
influence the extent of linkages are. He argues that over time the connection between these

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ingredients will enhance as the level of skills of the local investors grows economies of scale
increases.
Benassy, Fontagne, and Lahreche (2001) explain that depreciation in exchange rate
and its volatility in terms of their effects on FDI. However, the fluctuations in exchange rate
have much concern in decision making related to FDI. Currencies with higher depreciation
trend are considered more alarming to foreign investor as their investment declines over
periods. Dianchun, & Yu, (2008) and Blonigen (1997) also declare negative impact of
exchange rate on FDI inflows. Xing and Zhao (2003) conducted a study to analyze the
linkage among imports, FDI, and exchange rates in the situation of imperfect competition. He
also suggest that product differentiation is the major reason that MNEs indulge in imports.
However they got extra benefits from the devaluation in the currency of host country than
local firms.
The phenomena that the exchange rates affect FDI flows shows its influence in a few
theoretical studies, e.g., Froot and Stein (1991), Kohlhagen (1977),and Benassy et al., (2001).
Most of these studies conclude that due to the devaluation in hosting country’s currency host
country’s FDI inflows become boost up, however, an appreciation in turns leads towards the
reduction in FDI inflows. Basically, there are two major channels through which exchange
rates reflect its impact on FDI: the first one is channel of wealth effect and the second one is
channel of relative production cost (Froot and Stein, 1991; Xing and Zhao, 2003). Reduction
in the value of the currency of FDI’s host countries includes a reduction in cost of production
in terms of foreign currency which in turn boosting up the profit of export oriented foreign
investors. However, the higher return attracts more inflows of FDI. Empirical investigation in
perspective of exchange rate and FDI nexus is an important icon for the making of both FDI
and exchange rate policies. However, Malaysia is also playing its role in this regard.

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2.1.2 MARKET SIZE AND FDI
The market size and FDI’s relationship is elaborated by Resmini (2000), that market
size is positively associated with FDI. By applying gravity models on bilateral FDI flow from
G54countries to 22 emerging markets over the period 1992–2000, Frenkel,
Funke,&Stadtmann, (2004) claims that host country GDP matters while considering all home
and host countries. However, when regionally separating the emerging markets into Asia,
Central Europe and Latin America, this study finds that GDP matters only in Central Europe
and Latin America. Hence, the most widely used measures of market size are GDP, GDP per
capita and growth in GDP. Moosa and Cardak (2006) conducted a study on how the domestic
market size and differences in factor costs can relate to the location of FDI. However, this
study states that foreign investors who operate in industries characterized by relatively large
economies of scale, the market size and its growth have considerable impact in this regard as
they can exploit scales economies only after the market attains a certain threshold size.
The impudence of market size on the inflows of FDI in the empirical literature depicts
its positive image. The spillovers of FDI are attracted to those markets where the MNC’s can
achieve reduction in the costs of production and get economies of scale. Blonigen (1997),
Chakrabarti (2001), and Moosa and Cardak (2006) postulate that influence of market size in
the game of attracting FDI. By using cross-section data of 135 countries, Chakrabarti (2001)
conducts an extreme bound analysis and finds that market size attracts FDI. Mina (2007)
determines the location advantages in GCC countries. This study concludes that the location
advantages gain their emergence from the assets that foreign markets supply and these assets
include abundant natural resources, cheap factors of production, large market size, and
appropriate business environment. However, these factors attract the firms to produce and
trade across the border. Khan and Nawaz (2010) conclude that foreign investors invest in

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those countries where they got new opportunities. However, the foreign investors tap the
domestic market and thus the market size has considerable importance in this regard. The
larger the market size, the higher will be the opportunities and economies of scale.
2.1.3 INFRASTRACTURE AND FDI
According to Zunaidah and Dagus (2005), their study has supported the view that
infrastructure is always associated with foreign direct investment. According to them,
Malaysia is making successful efforts to upgrade the level of infrastructure and the
developments of telecommunication, which are very important elements in attracting more
foreign investors because they help create, knit together and integrate large national
economies and provide critical infrastructure for the global networks of multinational
companies (Shapiro, 2011). This is supported by Aw, & Tang, (2009). As referred to them,
infrastructure plays a crucial role in FDI flows in the short-run, but not in the long-run, after
considering the event of China joining the WTO in 2001 and the inclusion of corruption
variables.
Hasan (2004) has the same view with this theory as he stated that one prerequisite for
an economy to stimulate FDI inflow is the expansion of various sort of infrastructural
facilities, including means of transportation and communication,power supply,educated skill
worker ,accomodation and the like. As he expected, development expenditure which has been
used as a proxy for infrastructure has a positive relationship with fdi inflow and the
coefficient too is not small.
As referred to Demirhan, & Masca, (2008), the relationship between infrastructure and
foreign direct investment has also received positive support from them, as they claim that the
effect of infrastructure on FDI is positive and significant. This result shows that investors are
attracted to a country with better infrastructure. It means that better infrastructure is an

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important determinant in attractingFDI to developing countries. As referred to Tsen (2005),
he has stated that the better the infrastructure of the host country, the more attractive it is to
FDI. A good infrastructure will facilitate production activities as well as distribution of
output.
2.2 EMPAIRICAL TESTING PROCIDURE
Mughal and Akram (2011) use the ARDL Model to estimate the impact of foreign direct
investment with market size, exchange rate and corporate tax. The model they used as flowes:
ln(FDIt) = β0 + β1ln(MSt) + β2ln(ERt) + β3(CTt) + Ut, …………………(1)
where,
FDIt , = foreign direct investment;
MSt, = market size;
ERt = exchange rate;
CTt = corporate tax rate;
Ut = the error term, expected value of other variables
t= time series
In=logarithm
Here, β0 the intercept means the FDI unknown value while all other variable are zero.
β1 is the positive coefficient unknown value MS which means that the 1 unit increase of MS
will increase the FDI is β1 unit because the bigger market size welcome more MNC’s due to
economic scale of production (Resmini 2000). β2 is the positive coefficient unknown value
ER which means that the 1% depreciate of ER will increase the FDI is β2 % due to the
increase of purchasing power of foreign currency (Tsen, 2005) and β3 is the positive

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coefficient unknown value CT which means that the 1 % decrease of CT will increase the
FDI is β3 %. The lower the corporate tax the grater the profit so increase the FDI.
Awan et al., (2011) also examine the variables of foreign direct investment in
commodity producing sector at current market price, gross domestic product (GDP), real
GDP growth rate, gross fixed capital formation, foreign exchange reserves, trade openness,
income per capita. To test co-integration and Error correction model (ECM) for Pakistan by
using Quarterly data from year 1996Q1 to 2008Q4 and the data are collected from World
Development Indicators (WDI), World Investment Reports (WIR), Economic Survey of
Pakistan, Board of Investment (BOI), Statistic Year Book 2005, Statistic Bulletin of State
Bank of Pakistan, International Financial Statistic (IMS)). The following model has been
formulated to estimate the results:
LFDIP = β0 + β1 LGDPMP + β2 LGRP+ β3 LGFCF + β4 LFOREX+ β5 LTO +
β6LPC + μt, ……………………………………… (2)
where,
LFDIP = Foreign Direct Investment in Commodity Producing Sector;
LGDPMP = Gross Domestic Product at Current Market price;
LGRP = Real GDP growth rate in commodity producing sector (in %);
LGFCF = Gross Fixed Capital Formation;
LFOREX = Foreign Exchange Reserves;
LTO = Trade Openness;
LPC = Per Capita Income;
μt = the error term, expected value of other variables

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Here, “L” refers the logarithm, β0 the intercept means the LFDIP unknown value
while all other variable are zero. β1 is the positive coefficient unknown value LGDPMP
which means that the 1 % increase of LGDPMP will increase the LFDIP is β1%. It means
increase in GDP in the current market increase the FDI because higher GDP in the current
market refers the higher consumption and that’s why it’s welcome the FDI (Lumber, 2006).
β2 is the positive unknown coefficient value of LGRP which means that the 1% increase of
LGRP will increase the LFDIP is β2 %. GDP growth rate is positively related but only
increase in GDP growth not really increase the FDI but along with the technology effect. The
β3 is the positive coefficient unknown value LGFCF which means that the 1% increase of
LGFCF will increase the LFDIP is β3%. Gross Fixed Capital Formation formally known as
Gross Fixed Investment which is used to development of the infrastructure which is welcome
FDI with cost efficiency in the production (World Bank 2015). β4 is the positive coefficient
unknown value of LFOREX which means that the 1% depreciate of LFOREX will increase
the LFDIP is β4%. Because depreciation of the host currency is give the strong purchasing
power to the foreign currency. β5 is the positive coefficient unknown value LTO which
means that the 1% increase of LTO will increase the LFDIP is β5%. Trade openness means
removing the tariff and non tariff barriers in the flow of international trade so, naturally in
increase the FDI. β6 is the positive coefficient unknown value LPC which means that the 1%
increase of LPC will increase the LFDIP is β6%. The increase in the labor force participation
rate shows there has sufficient skill labor which is one of the factors of production. So, the
availability of the factors of production increases the FDI.
Almsafir et al., (2011) use ARDL bound test. Johansen co-integration and Error
correction model (ECM) methodology for Malaysia for the year 1970 to 2009 annual data
from Bank Negara, Department of Statistic to test the variables Foreign direct investment,
real GDP growth rate, exchange rate (RM/US$), money supply, gross fixed capital formation,

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corporate tax, electricity generation. Examine short run relationship with the FDI and flowing
variables with this model.
lnFDIt= + GRt+ ERt+ InM2t + InGFCFt+ lnCTAXt+ lnEGt+ , ………………….(3)
where,
FDIt = Foreign Direct Investment for the Malaysia;
GRt = real GDP growth rate;
ERt= exchange rate;
M2t = money supply, as a proxy for financial development;
GFCFt= gross fixed capital formation and is used as a proxy for domestic investment;
CTAXt= company tax;
EGt= electricity generation and is used as a proxy of energy supply;
In= logarithm
t= time series
ε = the error term, expected value of other variables.
β1 is the positive coefficient unknown value GR which means that the 1 % increase ofGR
will increase the FDI is β1%. β2 is the positive coefficient unknown value GR which means
that the 1 % increase of GR will increase the FDI is β1%. β3 is the positive coefficient
unknown value ER which means that the 1 % depreciate of ER will increase the FDI is β1%.
β4 is the positive coefficient unknown value M2 which means that the 1 % increase ofM2
will increase the FDI is β1%. β5 is the positive coefficient unknown value CTAX which
means that the 1 % decrease of CTAX will increase the FDI is β1%.
β6 is the positive coefficient unknown value EG which means that the 1 % increase of EG
will increase the FDI is β1%.

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Bashir et al., (2015) examine that the variables of foreign direct investment in
Pakistan having the positive impacts on FDI but at the same also having the negative
relationship in FDI. The log log model, least square method (OLS) and regression model
have been used to test the secondary time series data sample from year 1970-2010 which
collected from Federal beaureu of Statistics, State Bank of Pakistan, International Monetary
Fund (IMF), World Bank, South Asian Bank, Economic Survey of Pakistan, Hand book of
Statistics 2005-2006, Center of Economic Research in Pakistan and South Asian Terrorism
Portal. The following model has been formulated to finds the results as below:
LnFDI = β0+β1lnGDP+ β2lnM+ β3lnI+ β4lnT+ β5lnEX +U ……………. (4)
where,
FDI = Foreign Direct Investment (in million rupees);
Ex = Exchange Rate (in million rupees);
I = Infrastructure (length of high type roads in km);
T = Terrorism (no of deaths due to violence);
GDP = Gross Domestic Product;
M = Market size (as GNP in million rupees);
In= logarithm
U = the error term, expected value of other variables.
β1 is the positive coefficient unknown value GDP which means that the 1 % increase of GDP
will increase the FDI is β1%. GDP is positively related to the FDI because it refes the higher
consumption. β2 is the positive coefficient unknown value M which means that the 1 %
increase of M will increase the FDI is β2%. Increase in market size increase the FDI due to
economic scale of production. β3 is the positive coefficient unknown value I which means
that the 1 % increase of I will increase the FDI is β3%. Batter infrastructures like

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transportation facility and the telecommunication facility increase due to cost efficiency. the
β4 is the positive coefficient unknown value T which means that the 1 % decrease of T will
increase the FDI is β1%. Because the increase of the terrorism shows the less security of the
investor which is discourage the FDI. β5 is the positive coefficient unknown value EX which
means that the 1 % depreciate of EX will increase the FDI is β1%. The depreciation in the
host country exchange rate will increase the FDI inflow since it reduces the cost of capital
investment.
According to Solomon, Islam, & Bakar, (2015) examine the dependent variable FDI with
the independent variables financial market development Market size of the economy,
Governmental infrastructure expenditure, Real exchange rate, Economics openness, and
corporate tax and Inflation rate in attraction the foreign direct investment in Malaysia. The
method used for this research is one-tailed pearson correlation. The test was used to assess
the discriminate validity of the variables. The data used for this test is from 1990 to 2010
taken from World Bank.
2.3 EMPAIRICAL RESULTS
Gross domestic product, real GDP growth rate, gross fixed capital formation, foreign
exchange reserves, trade openness and income per capita are the major determinants of
Pakistan FDI in commodity-producing sector. High GDP at current market price means
greater economic size for investors to invest. Trade openness attract FDI inflows massively
where foreign exchange reserves means stable macroeconomic (Awan et al., 2011). At the
same time Mughal and Akram (2011), the study result shows that market size is the main
factor to attract FDI inflows in the long run in Pakistan. Besides, exchange rate has shown
significant negative impact determinant in the short and long run. However, corporate tax rate
did not show any influence in the long run. The major determinants of FDI in Pakistan are

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GDP, infrastructure, market size (GNP), exchange rate and terrorism discover by Bashir et
al., (2015). The results show that the GDP, exchange rate and market size (GNP) have the
positive relationship between FDI. When the GDP and market size (GNP) increased and
currency is good condition, the FDI will increase. On the other hand, the results also indicate
that the terrorism and infrastructure have the negative relationship between FDI. During the
terrorism rises in an economic, the FDI will decrease. In contrast, the implementation of
policy is very important in order to increase the FDI and incentives should be given to the
investor to encourage investment.
As reviewed by Tsen (2005) foreign direct investment (FDI), is much different
compared to the foreign investment that bonded with the long term profit in production
activities that investors directly control. Manufacturing is the important element in the
economic growth of Malaysia whereby the FDI played the crucial role by exporting the
manufacturing products such as semiconductor. Based on it, the studies mainly focus on the
relationship of the long run between FDI and the location-related determinants in
manufacturing industry of Malaysia. Besides, the results give the positive effect in which FDI
attracts by the infrastructure and education. In order to that a hypothesis is made, the larger
the market size, the more it is expected to attract the FDI on the other hand inflation and
appreciation of exchange rate discourage the FDI. There is long run relationship between
FDI, GDP growth rate, exchange rate, money supply, gross fixed capital formation, corporate
tax and electricity generation exist in Malaysia. The authors suggested focusing on financial
development to attract FDI in the short and long run. (Almsafir et al., 2011). On another
research Solomon, Islam and Bakar (2015) the result, financial market development and
market size are the most affecting factors compare to others variables in FDI inflows into
Malaysia which are positively significant. In the other hands, corporate tax is negatively
significant independent variables

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2.4 CONCLUSION REMARKES
From the above discussion we found that Exchange rate, market size and Infrastructure
has the much more influence on attracting the foreign direct investment (FDI). Based on
previous research that conducted to examine the relationship among the FDI, Market size,
Infrastructure and Exchange rate, there are mainly 3 types of findings. The main findings
include positive relationships means bigger market size welcome investor due to economic
scale of production, batter infrastructure increase the FDI because of the cost efficient of
production and depreciation of exchange rate also increase the FDI by providing strong
purchasing power to the foreign currency. Also noticeable the existence of long run
relationship and bidirectional relationship among the FDI, Market size, Infrastructure and
Exchange rate. The testing procedure that mainly use in previous study to examine the
relationship among the FDI, Market size, Infrastructure and Exchange rate are unit root test,
counteraction test and Granger Causality test. Many researchers have suggested that the
determinants of foreign direct investment for country have different result compare with
different country. In order to have a precise result in our study, we decide to do the OLS
regression test, diagnostic test, stability test and the casualty test which explain more in the
methodology part conduct in our study based on the consideration of background of our
country.

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CHAPTER THREE
METHODOLOGY
3.0 INTRODUCTION
This study is focusing on the FDI, Infrastructure, market size and real exchange rate
in Malaysia from year 1984 until 2013. The main objective of conducting this research study
is to find the impact of the determinant’s which consists of Infrastructure, market size and
real exchange rate on FDI in Malaysia. At the same time, the impact of the real exchange rate
on FDI will be examined. This study is a time-series study which the data is collected over
discrete interval of time. There are four sections in this chapter such as estimation model,
definition of dependent variable, definition of independent variables and statistical analysis.
The first section 3.1 in this section is about the data. A multiple regression model
which is appropriate to be use in this study is going to form for the purpose of analyzing the
relationship between the dependent variable and the independent variables. In sections 3.2 of
this chapter, is explain the methodology for this study, hypothesis and also the econometric
model specification of the study. And lastly section 3.3, this section will identify the
appropriate test to be used to examine the effect of independent variables on dependent
variable in Malaysia. Few tests will be chosen and described for the use of this research
study.
3.1 STUDY CONCEPT
3.1.1 CONCEPTUAL FRAMEWORK
In this study, the conceptual framework is needed in order to know the relationship
from one variable to the other variables. A variable is anything that can take on differing or
varying value.

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 Dependent variable (criterion variable) - is the primary interest to the researcher.
 Independent variable (predictor variable) – is one that influence the dependent
variable in either a positive or negative way.
The schematic diagram below shows the relationship between independent variables and
dependent variable
3.1.2 SCHEMATIC DIAGRAM OF THE CONCEPTUAL FRAMEWORK
DEPENDANT VARIABLE INDEPENDENT VARIABLES
The relation of the infrastructure, exchange rate and market size towards the foreign
direct investment (FDI) is shows in the schematic diagram. The dependent variable is the
foreign direct investment (FDI) which is positively related with the independent variables
infrastructure, exchange rate and market size. According to the previous literature review we
expect that the infrastructure, exchange rate and market size will positive effect on the
foreign direct investment that means the unit increase in infrastructure and market size will
increase the foreign direct investment (FDI) and in percent depreciating the Malaysian
FOREIGNDIRECT
INVESTMENT(FDI)
INFRASTRUCTURE
EXCHANGE RATE
MARKET SIZE

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currency against foreign currency will led to increase the foreign direct investment (FDI) to
Malaysia.
3.2 DATA COLLECTION
3.2.1 SAMPLE OF THE STUDY
In completing this study, the samples that have been used are based on 30 years
(1984-2013) data in yearly basis. The data collected were infrastructure, which is measured
by government development expenditure on transportation, communication and public
utilities. While for exchange rate, exchange rate RM/US$ is used as a proxy and market size
is measured by Gross Domestic Product (GDP) per capita. The dependent variable of foreign
direct investment is measured by net inflow of foreign direct investment (FDI). All the
variables are in terms of Malaysian Ringgit (RM).
3.2.2 DATA AND DATA SOURCES
Data that are collected to be analyzed in this study is secondary data. Secondary
data can be referred to the information gathered from sources already existing. All
the data and information are collected from United Nation Conference on Trade and
Development (UNCTAD), Economic Report, Department of Statistics and Ministry of
Finance, Malaysia, World Bank, Bank Negara Malaysia and DataStream. The other sources
of secondary data are obtained from internet search, journals, and newspapers.
3.2.3 METHOD OF ANALYSIS
For this study, E-views is used to analyze all the data collection and interpret the
result findings. The raw data collected in the field must be transformed into information that
will answer the researcher’s questions in order to identify the relationship and correlation
between foreign direct investment with infrastructure, exchange rate and market size.

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3.3 Research Methodology
In this study, the time series data always required the three standard procedures. First
least squares regression (OLS) for specification the model and then normality test is a test
used to decide whether a data set used in the model is normal distributed or not. According to
Gujarati and Porter (2009) there are 3 normality tests in general. The tests include histogram
of residuals, normal probability plot, a graphical device and the Jarque-Bera test. In this
study, the test for normality will first show by the histogram of residuals.. Another
consideration is the p-value for the test. The p-value should higher than the critical values in
order to conclude for do not rejecting the null hypothesis. On the other hand, this study also
considers the Jarque-Beratest. This test is based on the OLS residuals and an asymptotic test.
The condition for a normally distributed variable is the skewness coefficient should be zero
and the kurtosis should be three (Gujarati and Porter, 2009).
One of the CLRM assumptions is that different observations of stochastic error term
are uncorrelated with each other. In short, autocorrelation or serial correlation implies that the
error term from one time period depends in some systematic way on error terms from other
time periods. If the error term in time period, there is first-order autocorrelation. Two ways
for detecting autocorrelation, there are informal test and formal test. In informal test, there
have two ways which are graphical method and runs tests. For formal test, there have three
ways which are Durbin-Watson d Test, Durbin-Watson h Test and Breusch-Godfrey (BG)
Test. At this study we only use the formal test which is Breusch-Godfrey test. Besides that,
the higher order moving averages of white noise error terms also allows to use this testing.
BG test also known as LM test. Heteroscedasticity appear when a critical assumption of the
classical linear regression model is that the error terms have a different variance. There are
several methods to test for the presence of heteroscedasticity. In this study, Autoregressive
Conditional Heteroscedasticity (ARCH) is chosen to test the presence of the

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heteroscedasticity. Ramsey RESET test was proposed by Ramsey himself and it act as a
general test of specification error called (regression specification error test) RESET. The
main idea in this test is when the estimated dependent variable was introduce in the
regression, if the increase in R2
is statistically significant, this suggest that the function is
miss-specified. Granger Causality test suggested by Wiener is use to find out the causation
between the studied variable. (Gujarati and Porter, 2009, pp 653-655).
3.3.1 HYPOTHESIS DEVELOPMENT
From the research questions above there are 3 hypotheses developed for this research.
3.3.1.1 Hypothesis 1
According to concept of FDI batter infrastructure increase the FDI because the batter
transportation facility and the batter telecommunication facilities increase the business in the
country due to cost efficient in the production as a result increase the FDI. Malaysia is
making successful efforts to upgrade the level of infrastructure and the development of
telecommunication, which are very important elements in attracting more foreign investors
because they help create, knit together and integrate large national economies and provide
critical infrastructure for the global networks of multinational companies (Shapiro, 2011).
So, in the hypothesis one we need to see whether there is a relationship between
infrastructure and foreign direct investment in Malaysia.
H1: There is a relationship between infrastructure and foreign direct investment in
Malaysia.
Tsen (2005) explain that appriciating the exchange rate decrasing the FDI inflow
because it decrase the walth of the investor by paying the higher cost for factors of

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production. So, we make our hypothesis 2 to evaluate in our stutdy whether exchange rate
and foreign direct investment has a relation or not.
H2: There is a relationship between exchange rate and foreign direct investment in
Malaysia.
Moosa and Cardak (2006) conducted a study on how the domestic market size and
differences in factor costs can relate to the location of FDI. However, this study states that
foreign investors who operate in industries characterized by relatively large economies of
scale, the market size and its growth have considerable impact means to have more profit to
produce in the large market in this regard as they can exploit scales economies only after the
market attains a certain threshold size. As on our study we want to find the relationship
between market size and foreign direct investment in Malaysia. So, we make our hypothesis 3
as flowes.
H3: There is a relationship between market size and foreign direct investment in
Malaysia.
3.3.2 ECONOMETRIC MODEL SPECIFICATION
The aim of this study is to investigate the motivators of FDI inflows in case of
Malaysia. There is an application of Log-linear model in this study – as Layson (1983)
concludes that the log-linear form provides more reliable and comprehensive results than
linear form. However, Shahbaz and Rahman (2010) also conclude that the findings with a
log-linear specification are more authenticated than linear specification. Hence, functional
form of log-log is quoted below:

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log(FDIt)= β0+ β1log(EXCRt)+ β2log(MRKTSZt)+ β3log(INFRAt)+εt
wheres,
FDIt=Foreign Direct Investment in time
EXCRt=Exchange Rate in time
MARKSZt=Market Size in time
INFRAt= Infrastructure in time
εt= Error Term
Here, “log” represents logarithmic form of series. Whereas, β1, β2 and β3are the
elasticity’s of FDI net inflows with respect to EXGR, MARKTSZ and INFRA. Expected sign
can be explain more from the equation above, the expected sign for Exchange Rate, Foreign
Direct Investment, and Market Size towards Foreign Direct Investment are positive. This
means all of the explanatory variables have positive relationships to the response variable.
The relationship between Foreign Direct Investment and Infrastructure estimate to be positive
when government spends money on upgrading the Infrastructure, the Foreign Direct
Investment will increase because it helps producer to be cost efficient. When the Foreign
Direct Investment increases, this will contribute to the increase in output. Next, Market Size
is the positive relation toward the Foreign Direct Investment, means the increase in Market
Size increase the Foreign Direct Investment due to it helps to producer to produce in
economic of scale and more profitable and lastly Exchange Rate and the Foreign Direct
Investment has a positive relation means, depreciating the Malaysia currency against the
foreign currency will increase the Foreign Direct Investment because foreign currency holder
can buy more cheaper goods in Malaysia market.

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3.4 ECONOMETRIC METHODOLOGY
3.4.1 ORDINARY LEAST SQUARE (OLS)
T-test is used to test the significance level about the regression coefficient. The main
idea of this test is that of attest statistic (estimator) and the sampling distribution of such a
statistic under the null hypothesis. The equation for t value is as follows:
t = ( b2–β2)/se (b2), (Note : β2= 0)
Where; b2 is the estimator of the true population (β) and se (b2) is the standard error of
b2. In the significance test, when the value of the test statistic lies in the critical region, the
statistic is said to be statistically significant, and in this situation the null hypothesis is
rejected. On the other hand, when the test statistic lies in the acceptance region, the statistic is
said to be statistically insignificant, and in this case the null hypothesis is not rejected
(Gujarati and Porter, 2009, pp 115-118).
F-test is used when T-test cannot test the joint hypothesis that the true partial slope
coefficients are zero simultaneously. The null hypothesis the true slope coefficients are
simultaneously zero. If the F value is more than the critical F value from F table, we reject
Ho. On the contrary, when the F value computed does not exceed the critical F value from the
F table, we do not reject the null hypothesis(Gujarati and Porter, 2009, pp 237-248).
3.4.2 JARQUE-BERA (JB) TEST
Normality test is normally used to test whether the underlying random variable in the
model is normally distributed or not. Histogram (bellshaped) is used to explain the normality
test. The normal distribution should be bell-shaped and the p-value should be higher than the
critical value for do not reject the null hypothesis. The null and alternative hypothesis as
shown as below:

43 | P a g e
H0 : The error term is normally distributed.
Ha: The error term is not normally distributed.
Besides that, the Jarque-Bera test for this decision will be taken into account in this
study. If the data is normally distributed, the JB test of normality is an asymptotic which has
a chi- square distribution with degree of freedom of two. For a normal distribution, skewness
coefficient must be zero and the kurtosis must be three (Gujarati and Porter, 2009).
By using the rejection rule, the null hypothesis will be rejected when the level of significant
(5%) is larger than the p-value. The error term is considered not correctly distributed if the
computed probability is larger than the critical value. Therefore, the null hypothesis will be
rejected which also means that it is statistically significant.
3.4.3 SERIAL CORRELATION (BREUSCH- GODFREY TEST)
The serial correlation has been employed to test the error term on one period depend
on another error term of other time period which are correlated. The serial correlation exists
when the OLS estimates are remain unbiased and consistent, but they are inefficient
(Williams, 2015). Breusch- Godfrey test is applied to run the test of autocorrelation. The null
and alternative hypothesis as stated below:
H0 : The error term does not exhibit serial correlation problem.
Ha : The error term exhibit serial correlation problem.
If the result shows that P-value > 0.05, we do not reject null hypothesis, H0, at 5% of
significant level. This indicates that the error term is uncorrelated. There is no first order
autocorrelation. So, the OLS estimates model does Best Linear Unbiased Estimator (BLUE)
and are inefficient.

44 | P a g e
3.4.4 WHITE’S GENERAL TEST
Heteroskedasticity happens when the variance of the error terms are not constant
throughout the period even though the mean value is constant. Goldfeld-Quandt test and
White's General test are formal statistical tests for the errors of heteroskedasticity. In this
study, we used White's General test of heteroskedasricity test. If it is heteroscedastic, the OLS
estimators thus are no longer minimum variance estimators even they unbiased and consistent
(Gujarati and Porter, 2009). The null and alternative hypothesis are shown as below:
H0 : The error term is homoscedastic.
Ha : The error term is heteroscedastic.
If the result shows that the level of significant (0.05) is less than probability, we do not reject
the null hypothesis. It is not statistically significant. Therefore, the error term is
homoscedastic.
3.4.5 RAMSY’S RESET TEST
In classical linear regression model, one of the assumptions is that the regression
model of the model is linear. Ramsey’s RESET Test is a form of test that is used to test for
the linearity of the functional form. At the same time, it analyse the misspecification of the
regression model. F test is used in running the Ramsey’s RESET test. The null and
alternative hypothesis is:
H0: The model is correctly specified.
Ha: The model is not correctly specified.
By using the rejection rule, the null hypothesis will be rejected when the level of significant
(5%) is larger than the p-value. The model is considered not correctly specified if the

45 | P a g e
computed F-value is larger than the critical value. Therefore, the null hypothesis will be
rejected which also means that it is statistically significant.
3.4.6 CUSUM & CUSUM SQUARES TEST
Both CUSUM and CUSUM squares test is stability test for the OLS regression model.
CUSUM and CUSUM squares test is obtain from the residuals of the recursive estimation.
There will be graph with line that is fluctuates and the line is used to determine whether or
not the OLS regression model is stable and whether or not reject the null hypothesis.
H0: The model is stable.
Ha: The model is not stable.
If the line is in between the range of 5% significant level, the OLS regression model is stable.
Therefore, the null hypothesis is not rejected. However, if the line or any part of the line is
exceeding the range of 5% significant level, the OLS regression model will be determined as
not stable at that particular periods. Hence, the null hypothesis is rejected.
3.4.7 GRANGER CAUSALITY TEST
Granger Causality test suggested by Wiener is use to find out the causation between
the studied variable. The granger causality test is designed to test whether A cause B, or the
other way round. To test this hypothesis, the F test is applied as follows,
F= − /
/ −�
Equation follows the F distribution with m and (n-k) df. Where, number of lagged M terms is
represent by M and the number of parameters estimated in the unrestricted regression
represented by k. If the calculated F value is more than the critical F value at the chosen level

46 | P a g e
of significance, the null hypothesis will be rejected, in which case the lagged M terms belong
in the regression (Gujarati and Porter, 2009, pp 653-655).
Granger causality test is very sensitive to the number of lags that used in the analysis.
Therefore, caution should be applied when implementing the test. The Granger Causality test
is conducted for identify the short run relationship between the variables. If the variables are
significant at 1%, 5%, 10% level where p-value is smaller than the significance level, the null
hypothesis is rejected. Therefore, it can conclude the independent variables cause the
dependent variables. In contrast, if the variables are insignificance at 1%, 5% or 10% where
p-value is greater than the significance level, the null hypothesis is failed to reject. It
concludes that there are not causality linkage between the independent variable and
dependent variables. The test involves the following estimation regression:
After the co integration test is detected, we used Granger causality test to find out the
short-run causality relationship. The Granger causality was used to determine the co
integration between two variables either it is univariate or bivariate. In fact, the causality test
also functions as verifying the change in other two series.The study tests three hypotheses;
the FDI has impact on MRKTSZ,EXCR and INFRA;MRKTSZ,INFRA and EXCR have
impacts on FDI; and both sides impact each other, using Granger causality. Thus the causality
test helps to verify whether change in any series can be explained by the other series. This
approach to study the direction of causality based on following equation:
� �� = � + ∑ � �� −��= + ∑ � �� −��= +��,
� �� = � + ∑ � �� −��= + ∑ � �� −��= +��,

47 | P a g e
� � � = � + ∑ � �� −��= + ∑ � �� −��= +��,
� �� = � + ∑ � �� −��= + ∑ � �� −��= + ��,
� �� = � + ∑ � �� −��= + ∑ � �� −��= + ��,
� � � = � + ∑ � �� −��= + ∑ � �� −��= + ��,
� � �� = � + ∑ � �� −��= + ∑ � �� −��= +��,
� � �� = � + ∑ � �� −��= + ∑ � �� −��= +��,
� �� = � + ∑ � �� −��= + ∑ � �� −��= +��,
� �� = � + ∑ � �� −��= + ∑ � �� −��= +��,
� � � = � + ∑ � �� −��= + ∑ � �� −��= +��,
� � �� = � + ∑ � �� −�
�=
+ ∑ � �� −�
�=
+��,
3.5 CONCLUTION REMARKES
For this study, E-views 8 will be used to analyze all the data collection and interpret
the result findings. The raw data collected in the field will be transformed into information
that will answer the researcher’s questions in order to identify the relationship and correlation
between foreign direct investment with infrastructure, exchange rate and market size. The

48 | P a g e
ordinary least square (OLS) will be used to analyze significant level of the independent
variables toward the dependent variable FDI and theresidual diagnostic test such as Jarque-
Bera (JB) test to see the normality, Breush-Godfrey test to identify the serial correlation and
White’s General test use to identify the heteroscedasticity. Furthermore, Ramsey’s RESET
test and CUSUM and CUSUM Squares test also use to find the stability and lastly Granger
casualty test will be used to see the causal relation of the variables. This study is focusing on
the FDI, Infrastructure, market size and real exchange rate in Malaysia from year 1984 until
2013. As conclusion, the main objective of conducting this research study is to find the
impact of the determinant’s which consists of Infrastructure, market size and real exchange
rate on FDI in Malaysia. At the same time, the impact of the real exchange rate on FDI will
be examined. This study is a time-series study which the data is collected over discrete
interval of time.

49 | P a g e
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Appendix
Data
Year FDI Infra Mrktsz EXCR
1984 7974.769 4940 2254 2.343642
1985 6947.125 4700 2015 2.483042
1986 4888.741 4630 1741 2.581442
1987 4226.797 4790 1926 2.519638
1988 7194.181 5020 2050 2.618783
1989 16678.72 5460 2193 2.708842
1990 7088.332 6070 2417 2.704875
1991 12151.29 6730 2626 2.750067
1992 15752.23 7700 3079 2.547383
1993 15212.15 8450 3395 2.574095
1994 13194.73 9140 3685 2.624257
1995 12697.67 10990 4286 2.504404
1996 15433.3 11200 4743 2.515943
1997 15609.87 10790 4593 2.813192
1998 6574.578 7050 3228 3.924375
1999 11837.7 8700 3456 3.8
2000 11510.61 9530 4004 3.8
2001 5539.474 11170 3877 3.8
2002 9735.197 13070 4130 3.8
2003 7515.927 14290 4427 3.8
2004 14052.98 15690 4918 3.8
2005 12052.71 16470 5554 3.787092
2006 18465.33 18170 6179 3.668177
2007 25691 22390 7218 3.437569
2008 22415.38 26570 8460 3.335833
2009 4216.289 26390 7277 3.524503
2010 10885.61 30260 8754 3.221087
2011 15119.37 37630 10058 3.060003
2012 9733.616 41220 10432 3.088801
2013 11582.68 42430 10514 3.150909

55 | P a g e
Table 2.1 the summary of literature review
No: Author Variables Sources of Data Country Sample
period
Data
Frequency
Methodology Findings
1 Awan, Khan
& Zaman
(2011).
Foreign direct
investment in
commodity
producing sector
at current
market price,
Gross domestic
product (GDP),
real GDP
growth rate,
Gross fixed
capital
formation,
Foreign
exchange
reserves,
Trade openness,
Income per
capita.
World
Development
Indicators (WDI),
World Investment
Reports (WIR),
Economic Survey
of Pakistan,
Board of
Investment
(BOI),
Statistic Year
Book 2005,
Statistic Bulletin
of State Bank of
Pakistan,
International
Financial Statistic
(IMS).
Pakistan. From
year
1996Q1
to
2008Q4.
Quarterly
data.
Co-integration
and Error
correction
model (ECM).
Gross domestic product, real GDP
growth rate, gross fixed capital
formation, foreign exchange reserves,
trade openness and income per capita are
the major determinants of Pakistan FDI
in commodity-producing sector.
High GDP at current market price means
greater economic size for investors to
invest. Trade openness attract FDI
inflows massively where foreign
exchange reserves means stable
macroeconomic.

56 | P a g e
Table 2.1 the summary of literature review (continued)
period
Data
Frequency
2 Bashir, Raza
and Farah
(2015).
GDP
Market size
(GNP),
Infrastructures,
Terrorism,
Exchange rate.
Federal beaureu
of Statistics
State Bank of
Pakistan
International
Monetary Fund
(IMF)
World Bank
South Asian
Bank
Economic
Survey of
Pakistan
Hand book of
Statistics 2005-
2006
Center of
Economic
Research in
Pakistan
South Asian
Terrorism Portal
Pakistan 1970-
2010
Annually Log-Log
model,
Least square
method (OLS)
Regression
model.
The results show the GDP, exchange rate
and market size (GNP) have the positive
relationship between FDI.
The results also indicate that the
terrorism and infrastructure have the
negative relationship between FDI.
The policy is also important because
having the positive impact on FDI.

57 | P a g e
period
Data
Frequency
3 Tsen (2005). Location-related
determinates
Production cost,
Infrastructure,
Human capital,
and market size
Ministry of
Finance of
Malaysia
United Nations
Conference on
Trade and
Development(U
NCTAD)
Malaysia 1980-
2002
Annually Empirical
estimation
Unit root test
Co-integration
analysis
Good education and infrastructure
attracts FDI
Important factors are the availability of a
pool of relatively cheap and well trained
labour
Technology, innovative capacity and
pool of capital are major attracting
elements
4 Almsafir,
Latif &
Bekhet
(2011).
Foreign direct
investment,
Real GDP
growth rate,
Exchange rate
(RM/US$),
Money supply,
gross fixed
capital
formation,
Corporate tax,
electricity
generation.
Bank Negara,
Department of
Statistic
Malaysia From
year 1970
to 2009
Annual
data
ARDL bound
test.
Johansen co-
integration and
Error
correction
model (ECM).
There is long run relationship between
FDI, GDP growth rate, exchange rate,
money supply; gross fixed capital
formation, corporate tax and electricity
generation exist in Malaysia.
The authors suggested focusing on
financial development to attract FDI in
the short and long run.

58 | P a g e
period
Data
Frequency
5 Mughal &
Akram
(2011).
Foreign direct
investment,
Exchange rate,
corporate tax.
Various financial
bills of the
Government of
Pakistan,
World
Development
Indicators,
World Bank
Pakistan. 1984 to
2008.
Annual ARDL Model. The result shows that market size is the
main factor to attract FDI inflows in the
long run in Pakistan.
Besides, exchange rate has shown
significant negative impact determinant
in the short and long run.
However, corporate tax rate did not show
any influence in the long run.

59 | P a g e
period
Data
Frequency
6 Solomon,
Islam and
Bakar
(2015)
FDI
Financial
market
development
Market size
of the
economy
Government
infrastructure
expenditure
Real
exchange
rate
Economics
openness
Corporate tax
Inflation rate
World Development
Indicators, World Bank
Malaysia 1991-
2010
Yearly One-tailed
pearson
correlation
Financial market development and
market size are the most affecting
factors in FDI inflows which are
positively significant.
Corporate tax is negatively significant
independent variables.

60 | P a g e
period
Data
Frequency
7 George
and
Harandi
(2013)
Political
stability
Governmenta
l and legal
Social and
cultural
Economics
Financial
Location
World Development
Indicators, World Bank
Malaysia 1990-
2011
Yearly Qualitative
method
The analyses show that in political,
governmental and legal factors the
most effective variables are country
image, environmental law and conflict
resolution.
In cultural and social factors, religion
and level of education have the most
influence and the less impact in FDI.
In the location factors, level of
technology has the main influence in
attracting FDI and
Immigration skilled workforce has the
minimum impact on FDI.
Accesses to capital and exchange rate
fluctuation have the maximum and
minimum impact on FDI
Results show that technology
availability and human development
are the effective and ineffective
variables impact on FDI.

61 | P a g e
period
Data
Frequency
8 Benassy,
Fontagne,
and
Lahrech
(2001)
Nominal
exchange-
rate;
Real
exchange
rate ,
Stock of FDI
received
by the
emerging
country
ifrom the
OECD
country k
Investment;
currency
blocks
GDP growth
rate,
Trade
Openness
IMF, International
Financial Statistics
42
Developi
ng
countries
receiving
FDI from
17 OECD
countries
1984–
1996
Yearly
Panel Data
Regression
analysis of
competitivenes
s, volatility,
correlation,
proximity
DISTk
i , OPENi t D
100 ¢ (Xi t C
Mi t )=GDPi t
The trade-off between depreciation in
exchange rate and its volatility in
terms of their effects on FDI.
However, the fluctuations in exchange
rate have much concern in decision
making related to FDI.
Currencies with higher depreciation
trend are considered more alarming to
foreign investor as their investment
declines over periods.

Determinants of foreign direct investment in malaysia

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