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

http://en.wikipedia.org/wiki/China

http://en.wikipedia.org/wiki/South_Korea

http://en.wikipedia.org/wiki/Malaysia

http://en.wikipedia.org/wiki/Singapore


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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.

http://en.wikipedia.org/wiki/Investment

http://en.wikipedia.org/wiki/Management

http://en.wikipedia.org/wiki/Joint-venture

http://en.wikipedia.org/wiki/Transfer_of_technology

http://en.wikipedia.org/wiki/Expertise

http://en.wikipedia.org/wiki/Society

http://en.wikipedia.org/wiki/Road

http://en.wikipedia.org/wiki/Water_supply

http://en.wikipedia.org/wiki/Sewage

http://en.wikipedia.org/wiki/Power_grids

http://en.wikipedia.org/wiki/Telecommunication

http://en.wikipedia.org/wiki/Manufacturing

http://en.wikipedia.org/wiki/Good_%28economics%29

http://en.wikipedia.org/wiki/Service_%28economics%29

http://en.wikipedia.org/wiki/Raw_material

http://en.wikipedia.org/wiki/Factory

http://en.wikipedia.org/wiki/Market


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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,

http://www.investorwords.com/5752/rate.html

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http://www.investorwords.com/1797/exchange.html

http://www.investorwords.com/4643/speculation.html

http://www.investorwords.com/5030/trading.html

http://www.investorwords.com/12753/foreign_exchange_market.html

http://www.investorwords.com/10438/number.html

http://www.investorwords.com/12803/buyer.html

http://www.investorwords.com/13835/seller.html

http://www.investorwords.com/2962/market.html

http://www.investorwords.com/992/company.html

http://www.investorwords.com/2730/launch.html

http://www.investorwords.com/3874/product.html

http://www.investorwords.com/6664/service.html

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http://www.investorwords.com/4826/support.html

http://www.investorwords.com/5258/volume.html

http://www.investorwords.com/2209/goods.html

http://en.wikipedia.org/wiki/Standard_of_living

http://www.investopedia.com/terms/g/gdp.asp

http://www.investopedia.com/terms/i/indicator.asp

http://www.investopedia.com/terms/e/economy.asp


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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

FO

RE

IGN

DIR

EC

T

INV

ES

TM

EN

T(F

DI)

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:


41 | P a g e

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.


42 | P a g e

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(UNCTAD)

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

No:

Author

Variables

Sources of Data

Country

Sample

period

Data

Frequency

Methodology

Findings

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 Developing countries receiving FDI from 17 OECD countries

1984–1996

Yearly Panel Data

Regression analysis of competitiveness, 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.

62 | P a g e



period

Data

Frequency


9 James (2008)

Infrastructure development, Trade openness, Financial development, Real exchange rate, Corporate tax rate, GDP, Macroeconomics uncertainty.

World Development Indicators, World Bank

Malaysia 1960–2005

Annual data

Error correction model

The result shows that the FDI having

the positive impact and relationship

with financial development,

infrastructure development and trade

openness.

The appreciation of currency and

higher corporate tax show the negative

impact on FDI inflows.

The GDP have positively impact on

FDI inflows. The result shows that the

macroeconomics uncertainty will

encourage FDI inflows.

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period

Data

Frequency


10 Bashir, Raza and Farah (2015)

GDP Market size, (GNP) Infrastructure, 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

Secondary time series data

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.

determinants of foreign direct investment in malaysia

Economy & Finance