FDI Malaysia

8/11/2019 FDI Malaysia

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DETERMINANTS OF FOREIGN DIRECT

INVESTMENT IN MALAYSIA

Presented by

Yee Nee TEOH

090051064

ECM010 DISSERTATION

MSc Business Economics

Supervisor: Professor Saqib Jafarey

September 2010


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CONTENTS

ACKNOWLEDGEMENTS3

ABSTRACT.4

CHAPTER 1: INTRODUCTION..5

1.1BACKGROUND.5

1.2PROBLEM STATEMENT..7

1.3CONCEPTS AND THEORIES..9

1.4RECENT TRENDS...10

1.5OBJECTIVE OF THE STUDY10

1.6SIGNIFICANT OF THE STUDY11

CHAPTER 2: LITERATURE REVIEW12

CHAPTER 3: METHODOLOGY...19

3.1 DATA SOURCES.19

3.2 EMPIRICAL MODEL...21

3.3 EXPECTED RESULT...22

CHAPTER 4: EMPIRICAL RESULTS..23

4.1 AUGMENTED DICKEY FULLER TEST ..24

4.2 CORRELATION MATRIX .25

4.3 ORDINARY LEAST SQUARES ESTIMATION ...26

4.4 BREUSCH-GODFREY LM TEST ..28

4.5 RAMSEY RESET TEST...28

4.6 THE WHITES TEST29

4.7 DESCRIPTIVE TEST30


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CHAPTER 5: CONCLUSION.31

5.1 SUMMARY...31

5.2 MAJOR FINDINGS..31

5.3 POLICY IMPLICATIONS33

5.4 LIMITATION OF THE STUDY...34

5.5 RECOMMENDATION FOR THE FUTURE STUDY.35

REFERENCES...36

List of Figures

Figure 1: Net inflow of foreign direct investment (FDI) in Malaysia..10

List of Tables

Table 1: Data source and units of measurement...20

Table 2: ADF unit root test results...24

Table 3: Correlation matrix..25

Table 4: OLS estimation results...26

Table 5: Breusch-Godfrey LM test results...28

Table 6: Ramsey RESET test results28

Table 7: Whites test results.29

Table 8: Descriptive test results...30


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ACKNOWLEDGEMENTS

With the deepest gratitude I wish to thank my supervisor Professor Saqib Jafarey, for

giving me this opportunity to involve in this Study and his superb guidance to guide me

completed this work. The project is fully supervised by him during the past 3 months.

I would also like to thank my parents for their advices, financial and moral support

throughout this academic year and help me to overcome the obstacles when the things do not

turn out as expected.


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ABSTRACT

This study using quarterly time series data for the period 1997 2007 to examines the

determinants of foreign direct investment (FDI) in Malaysia. The study uses the Ordinary

Least Square (OLS) method to identify the variable in explaining the FDI in Malaysia.

Empirical results suggest that FDI flows in Malaysia are positively influenced by market size

and corporation tax rate while negatively affected by degree of openness in economy, real

exchange rate and labour cost. All variables are statistically significant except for the degree

of openness and corporate tax rate.


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CHAPTER 1: INTRODUCTION

1.1BACKGROUND

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 IMFs 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 economylack of natural resources and factor of production. The second one is market-seeking which

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


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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

NEPs ethnic ownership and employment quotas, foreign investment offers them with more

opportunities for employment at all level of the workforce. On the other hand, Chinesebusiness community generally positioned themselves well of collaborative relationships since

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 try 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 Malaysias 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


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success to attract investors from Taiwan, Hong Kong, Korea and also FDI from Developed-

country multinational.

Furthermore, Malaysia government recognize 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 multination 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 have made Malaysia an

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 countrys 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 companys joint ventures and new investment activities. Themovement of the FDI becomes a major concern of researchers and policy maker to

investigate what are the key forces that determines FDI in Malaysia.

1.2PROBLEM STATEMENT

Increased globalization has lead to strong growth of international economy activity and

foreign direct investment (FDI) over past two decades. Hence, there have extensive of the

studies and literatures on the phenomena of FDI and to identify the determinants and impacts

of FDI. Past studies commonly approved that FDI will promote economic growth.

Advantages of FDI always outweigh the disadvantage shown that FDI affect economic

growth positively. However, large number of studies conducted by economists to identify

determinants of FDI but end up with quite chaotic empirical findings and reflects a lack of


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robustness. That means there is no general consensus has emerged and it is difficult to say

which explanatory variables can be consider as true determinant of FDI.

As the enormous increase in FDI flows across countries over past 20 years, an important

determinant among the factors that attract foreign investment are particularly the

characteristics of host country. Investment environment in host country such as political risk,

infrastructure system, regulatory framework, red tape and degree of corruption always

regarded have negative effect or maybe have mixed effect on FDI inflow. According to

Chakrabarti (2001), the relation between FDI and many of the controversial variables namely

tax, wages, exchange rate and trade balance are highly sensitive to small alterations in the

conditioning information set. Ngie and Yol (2009) concluded that determinants of FDI inflow

group into three major categories which is economic condition, host country policies and

Multinational Enterprises (MNE) strategies. Economic condition means availability of natural

resource and market size. Host country policies include macroeconomic policies and different

policies related to trade and industry. While MNE strategies will be concern about location,

sourcing and integration transfer. Large number of research has been conducted to identify

the effect of these three major categories mention above. For instance, Clegg and Scott-Green

(1999) argue that market size and growth variable have positive impact on FDI inflow. On

the other hand, Kristtjansdottir (2005) argue that FDI inflow are more significantly affect bywealth effects if compare with the effect of market size. Past research works and studies

shown quite different empirical finding, are all of these cross-countries evidences applicable

in Malaysia case?


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1.3CONCEPTS AND THEORIES

According to Organization for Economic Cooperation and Development (OECD)s

Benchmark Definition of Foreign Direct Investment 3rdEdition (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 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 locational (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


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investor to selects a location for the project. This point of view provides an interesting

background in order to study the determinants of FDI.

1.4RECENT TRENDS

According to Statistic Department of Malaysia 2003, foreign direct investment (FDI) in

Malaysia decline by 8.6% per annum from year 1997 to 2001. This is due to Malaysia

suffered a great hit from the 1997 Asian Financial Crisis. Figure 1 shows the net inflow of

FDI as U.S. dollar spanning 1997-2007. Substantial surges of FDI inflows were reported in

year 1999, 2002, 2004 and 2006. For the period of 2003 to 2007, manufacturing, financial

intermediation, mining and services become main four sectors of FDI recipients. Total stock

of FDI increased substantially in year 2006 and 2007 mainly due to mergers and acquisitions

(M&A) by multinational enterprises (MNE). The largest proportion of FDI in Malaysia

contributes by manufacturing sector and most of the FDI flow from Singapore, USA and

Japan.

Figure 1

Data source: Obtained from World Development Indicators (WDI)

1.5OBJECTIVE OF THE STUDY


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The general objective of this study is to understanding the determining factors of FDI

inflows in Malaysia from year 1997 to 2007. Specifically, the study in this paper is to

examine the determinants of FDI for Malaysia.

1.6SIGNIFICANT OF THE STUDY

Since the 1960s, capital inflows to Malaysia have been dominated by foreign direct

investment (FDI). However, introduction of New Economic Policy (NEP) in1970 was a tool

for Malaysia government to increase the share of Malays in corporate sector and reserve a

specific percentage of employment in foreign venture for Malays. The constraints of NEP and

government intervention in almost every business level create anxiety in the mind of foreign

investors. Although government have taking step to make the policy stance towards FDI

unambiguous, the slowdown in FDI inflow since the early 1990s was due to the financial

crisis. The speculative attack on the Thai baht in 1997 results in East Asia financial crisis.

Malaysian government attempt to prevent further pressure on domestic currency by restricted

the short-term capital inflow and use of ringgit outside country had been influence economic

performance adversely. Vision 2020 then developed in order to stimulate the economy topropel Malaysia economy by increase foreign investment.

Previous studies shown there have no consensus view about the determinants of FDI and

there is no widely accepted set of explanatory variable can regarded as true determinants of

FDI. The determinants of FDI vary across countries depending on typological characteristic

of the host country. This can explain why some countries are more successful than others in

attracting FDI with their own policies. Hence, this study will be examine which of the

variables that are truly influential and robust in term of their effect on FDI in Malaysia base

on the unique structure features and the historical settings of the Malaysia economy.


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CHAPTER 2: LITERATURE REVIEW

Strong growth of international economy activity and foreign direct investment (FDI) over

the last two decades led to extensive research on this topic and become prime concern for

policy maker especially regarding the determinants of FDI inflows. This chapter aim to

provide a survey of the major theoretical and empirical studies on this issue from the past

literature review.

Early empirical studies such as Robinson (1961), Basi (1966), Wilkins (1970) and

Forsyth (1972) shown variety of factor including market factors, in particular market size,

market growth and maintaining market share, trade barriers, cost factors and investment

climate were the main determinants of FDI. Dunnings (1977) developed a theory so-called

OLI paradigm states that FDI is undertaken if ownership specific advantage (O) exist

together with location specific advantages (L) in host countries and potential benefits from

internalisation (I) of the production process abroad. (Frenkel, et al. 2004). The most

important factor is the selection of location for a project including the availability of local

input, factor prices, market size, and position of the economy and certain elements of the

economic policy of the government. This is supported by Asiedu (2002) and Edwards (1990),

they argue that an efficient environment that comes with more openness to trade is likely to

attract foreign investment. Kok and Ersoy, (2009) had been investigate whether FDI

determinants affect FDI based on both panel of data and cross section SUR (seemingly

unrelated regression) for 24 developing countries over the period 1983 to 2005 and from

1976 to 2885 respectively. Time series combine with cross sections able to enhance the

quality and quantity of data and the empirical result found that domestic policies help to

attract FDI and maximize the benefits by reduced restriction, removed obstacles to local

business. The finding also shows that foreign company pursue only the good business


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environment. The other determinants have significant affect FDI inflow including trade, gross

capital formation and GDP per capita growth.

Chakrabarti (2001) argue that the relation between FDI and many of the controversial

variables such as tax, wages, openness, exchange rate, growth and trade balance are highly

sensitive to small alteration in the conditioning information set. Many potential determinants

found to be statistically significant in cross-sectional studies depend on specific variable are

included in the regression equation. Chakrabarti (2001) give the example like tariffs have

positive effect on FDI if combine with growth rate and openness but provide negative effect

when including wage rates and real exchange rate have positive effect when combine with

openness, domestic investment and government consumption. Hufbauer, Lakdawalla and

Malani (1994) use the ratio of trade to GDP as a measure of the degree of openness and test

on the relationship between trade and FDI in an UNCTAD study. On the other hand, Wang

and Swain (1995) used the tariff rate as an alternative measure of the openness in the host

country. They argued that the coefficient have insignificant effect to the FDI although it had

the expected positive sign. However, as mention above the reliable of the empirical results

are depends to some question given the small number of observations researchers work with.

There is a variety of results regarding the empirical work in area of the openness of the host

countrys economy. Thus, Bajo-Rubio and Sosvilla-Rivero (1994) examined the relationshipbetween the degree of openness and FDI flows by using the tariff rate as a proxy and the

result shown both have a significant coefficient and also the expected sign. Jeannie, et al.

(2000) investigates the determinants of aggregate FDI inflows into Australia since the mid-

1980s. They measure the openness of the economy by the traditional measure of the sum of

imports and exports as a percentage of GDP and the result come out with a negative

coefficient. This is contradicting with the earlier argument that greater openness of the

economy attracts capital inflow. However, it is in some extent support some of the literature

view that FDI inflows are substitute for trade and thus decreasing in trade flows or

economys openness might have to come together with an increasing in FDI inflows.

On the other hand, Moosa, et al. (2006) examines eight determining variables if FDI

inflows by using extreme bounds analysis to a cross-sectional sample cover 138 countries

over the period 1998 to 2000. The empirical evidence shows that countries which are

developed countries with large economies, high degree of openness and low country risk are

able to attract more FDI. This is also supported by Nunnenkamp, et al. (2002) and Wheeler,


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et al. (1992), they find that the size of the market and the market potentiality, typically

proxies by the level of GDP and GDP growth rate affect FDI inflow significantly.

Measurement for the size of the host market in great majority of empirical studies is real GDP.

Wang and Swain (1995) found that the market size as a significant determinant of FDI flows

by using the real GDP. Nevertheless, the rate of growth of real GDP and GDP per capital can

be an alternative measure of the size of host market. Domestic market size and market

potentiality become important factor in attracting foreign investment since some of the

foreign investors invest to host countries mainly serve the market in host country. Mottaleb

(2007) examines the factor of size and growth rate of GDP in affect the inflow of FDI in the

developing countries by using the panel data from 60 developing countries. He then identified

that FDI mostly flows towards the developed country with higher per capita GDP and higher

GDP growth rate and only a small portion of FDI flows to a limited number of developing

countries. The highly significant and positive coefficient conclude that only those countries

with large market size, high market potentials and the greater contribution of industries to

GDP will more likely to increasing the FDI inflow. This argument is again consistent with the

founding from Kok and Ersoy, (2009) that GDP per capita growth has positive effect on the

flow of FDI.

Existing empirical studies focused on the role of different tax treatment as determiningthe source and location of foreign direct investment (FDI). Hartman (1984) examined the

impact of corporate tax rate on FDI flows and it is largely ignored home country tax rates. He

includes the tax rate on U.S. capital owned by foreign investor relative to those owned by

local investor as the explanatory variable during the estimation of the effect to the change in

the after tax rates of return on FDI. The result had shown that dependent variable, log of the

ration of FDI to U. S. gross national product (GNP) increase when the after tax rates of return

rise and lower as the foreign investors relative tax rate decrease. This finding is supported by

Boskin and Gale (1987) where they re-examine Hartmans model with the refinement of the

data cover period from 1956 to 1984 and come with the result consistent with Hartmans

original finding, which is taxes are an important determinant of FDI. On the other side,

Newlon (1987) found the results that is away from Hartman (1984), Boskin and Gale (1987).

He extends their studies by using better data from the Bureau of Economics Analysia for

period of 1965 to 1973 and found there have no estimated coefficient that explains FDI

finance by transfer of fund statistically significant from zero. As the first study to examine the

determinant related to tax policy on the foreign direct investment (FDI) by using micro data,


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Cummins and Hubbard (1994) investigate the effects of taxation on FDI using panel data on

outbound FDI by subsidiaries of U.S. multinational firms collected by Compustats

Geographic Segment file project and they find that there is a significant doubt on the simplest

notion that taxes dont matter for the FDI investment of the U.S. firms.

Foreign direct investment (FDI) determine by the potential interrelationship of the

taxation policies between home country and host country since foreign investor are subject to

corporate income tax in host country and follow by the another tax to their after-tax

expatriated profits in their home country. Furthermore, some of the countries adopt tax

exemption system and thus will be more sensitive to any changes of the taxes policies in host

country. Slemrod (1990) investigate that if FDI from exemption countries should be at least

as sensitive to U. S. tax rates as FDI from tax credit countries by using the FDI time series

data from 3 credit countries and 4 exemption countries. However, the result comes out with

no convincing evidence with the original hypothesis. The other studies like Hines (1996)

argue that foreign investors from tax exemption countries are considerably more responsive

to U.S. states tax than foreign investors from tax credit countries. On the other hand, Desai et

al. (2002) conclude that the tax sensitivity of FDI will affect by the different tax systems in

different countries. This is about same to the view of Mooji and Ederveen (2001), when

different studies put at the same format, investor from tax exemption country are moresensitive to changes in host country tax if compare with those investors from tax credit

country. Hence, Wijeweera, et al. (2007) try to capture all significant changes in tax policies

over past two decade by using the data for nine countries over the period 1982 to 2000 to

examine the impact of corporate taxed on FDI in the U.S. They found that corporate income

tax give a significant negative impact on U.S. FDI and another finding is investors from

exemption countries are more sensitive to taxes policies than investors from credit countries.

This result is consistent with the studies from Hines (1996).

Although many empirical results shown corporate tax rate as an important determinant of

foreign direct investment (FDI), but the role of other non-tax determinants of FDI should not

be underestimate. It already well documented in the past literature that there have a

significant relationship between FDI and the bilateral exchange rate between home countries

and host countries. Wakasugi (1994) argue that the exchange rate and the relative rent

between Japan and U.S. affected the relative ratio of exports to FDI significantly in his

analysis of the determinants of production for Japanese manufacturing companies in the two


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countries. Froot and Stein (1991) whose had been highly influence by Kohlhagen (1977)

about the theory of FDI and exchange rate linkages , used an imperfect capital market

approach to argue that FDI flow into the U.S. over the period of 1973 to 1988 were

negatively related to the real value of the dollar. This is because the borrowing costs become

more expensive than the internal cost of capital in firm due to the imperfect information

about capital markets. Hence, the wealth of foreigner rises automatically and they are able to

make higher bids for assets. Thus, it is expected that the depreciation of the host country will

give a positive effect on inbound FDI. This finding also consistent with the investigation

from Klein and Rosengren (1994), they examine the significant importance of the wealth

which caused by the imperfect information in capital markets across countries on to FDI from

seven industrial countries to the U.S. for the period of 1979 to 1991. The result shows that

there is strong evidence where the relative wealth is affecting the FDI significantly. While

when the exchange rate of the dollar face the appreciation, all kind of the FDI were decreased

significantly except for the acquisition of land.

According to Choi (1989), corporate international investment was aimed to diversify risk

together with operational cash flow and also the real exchange rate. Theoretically, the

covariance of exchange rates with output and input prices in a stochastic market will always

give significant result in foreign investment decision. This implies that the gains from realexchange risk diversification attract foreign investment. To further explaining the link

between FDI and exchange rate, Baek and Okawa, (2001) examine the Japanese FDI of their

manufacturing sector in Asia by focusing on the various type of exchange rates, such as the

yen against the Asian currencies, the yen against the US dollar and also the US dollar against

the Asian currencies which cover the period from 1983 to 1992 for six countries. The study

finds that the exchange rate variables are significant factor in determining FDI in

manufacturing sector. The nominal exchange rates variable exert a significant effect on FDI

even it is decomposed in to PPP rates or convert into the real exchange rate and this results

are all consistent with the prediction before.

Past empirical and theoretical work have no consensus regarding the nature of the

relationship between exchange rate and foreign direct investment (FDI). Risk averse investors

will attempt to reduce the effect of uncertainty on profit by exploiting exchange rate

correlations between locations during decide the alternative location to do the foreign

investment. This is due to the exchange risk will come out when there have the timing


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differences between investment and profit. This is so-called exchange rate volatility if the

expected return gains by foreign investors are equal to the cost plus payment for the degree of

risk. Cushman (1985) found that when a risk adjusted expected real exchange rate appreciates,

the foreign cost of capital will decreases and hence increasing the flow of FDI. Xing and

Zhao (2008) had used reverse imports as a means to shown that exchange rates can

significant affect FDI. They investigate relation between reverse imports, exchange rate and

FDI by using a two countries model (Japan and China) with oligopolistic markets. If the

exchange rate changes, the wage and cost of capital shift, then barriers due to the brand

recognition will encourage the Japanese FDI in China. Yen appreciation result in a relatively

cheap input cost in China, Japanese will then search those input through the FDI. This

appreciation will decrease thee exports from local Chinese company since the reverse imports

of Japanese will rises due to the barriers in brand name recognition in Japan. Therefore, they

show that if the exchange rate of FDIs recipient appreciates more than the rival country, this

will lead to the shifting of the relative FDI to the rival country.

Most empirical studies in the foreign direct investment (FDI) literature have found

conflicting results regarding labour cost on the direction of influence of the determinants of

FDI. In the cost reduction case, which means the foreign investors try to utilize certain host

countrys production factors, there may be a significant important determinant of foreigninvestors in choosing the investment location if the host country have a low labour standards.

The wage related labour standards including regular, overtime and minimum wages in a host

country. Logically, foreign investors making their investment in developing countries are

able to take advantage of low labour cost. According to Coughlin, et al. (1991), the FDI

inflows are affected by the condition of local labour market. By using high state specific real

wages in manufacturing sector as a proxy for local labour cost are was found significantly

affect the FDI inflows. On the other hand, the rate of unemployment in host country indicates

the availability of labour also suggests to attracting the flow of FDI. The Hecksher-Ohlin

model in comparative advantage framework suggests that the location decisions are pre-

determined by natural endowments such as the relative prices for raw materials and labour.

Hence, the costs in the host country relative to those elsewhere are play as vital a role in the

investment location decision for the labour intensive foreign firms. The other studies, Swain

and Wang (1995), found that relative cheap labour costs in China are significantly attracting

inward FDI. On the other side, Zhang (2000) argued that the factor of labour cost hardly to


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CHAPTER 3: METHODOLOGY

In the vast majority of empirical studies, there is a distinct lack of consensus conclusion

as to which determinant has the most significant and positive impact on foreign investment

flows. The above literature review shows that there are a variety of determinants both

economic and non-economic or qualitative and quantitative play as vital a role in the foreign

investment decision. Thus, it could be conclude in this discussion of theories and empirical

work on the variables that determine foreign direct investment (FDI) by choosing base on the

basis of the literature reviewed. The five variables chosen as the determinants of the FDI

flows to Malaysia includes real exchange rate, corporation tax rate, degree of openness in

Malaysia, labour cost and also the market size. This chapter presents the methods used

throughout the analysis of the determinants of FDI in Malaysia. The data sources are obtained

to present in this section and this chapter is categorized to three parts, first part explains the

data sources that are collected in this analysis. The second part shows the empirical model ofthis study while the expected result of the study will be discusses in the third part of this

chapter.

3.1 DATA SOURCES


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All the data sources in this part of analysis are collected from the financial statistical

database, Thomson Reuters Datastream and the World Development Indicators database from

the World Bank. This study cover with quarterly data so that it will allows the analysis to

restricted to the more recent years and able to be more compact with an enough number of

the observations for the analysis. However, the sample period and the data frequency for the

study are largely determined by the availability of the data. Since this is a country specific

study and thus it is not using a panel model in this study.

The data of the net inflows for foreign direct investment (FDI) in Malaysia cover from

the year 1960 through 2009 but in this study it is restricted to only year 1997 through 2007.

The exchange rate was measured by the trade-weighted index (TWI). This is representing the

broad range of exchange rate associate to the trading partners weighted by the share in term

of the trade. The trade openness is defined as the sum of exports and imports over GDP. A

tax variable is measured by the quarterly corporate tax revenue in Malaysia. Since some of

the available data are not always in satisfactory stage and the proxy had to be used in the

analysis. For the market demand and market size, the variable used here is the real GDP in

Malaysia. While the average quarterly earnings are used to measure the level of wages, this is

the approximation of the labour cost in Malaysia. In this study, as all trade in Malaysia are in

terms of U.S. dollars and hence all the variables are in terms of U.S. dollars as well. Table 1below shows details of the sources of the data and the units of measurement used in the

analysis.

Table 1: Data source and units of measurement

Variable Units of Measurement Source

Foreign Direct Investment (FDI) U.S. dollar World Development Indicators &Global Devolopment Finance, World

dataBank

Real Effective Exchange Rate

(REER)

Percentage, Year Over

Year

Global Economic Monitor (GEM),

World dataBank

Market Size Percentage, Year Over

Year

Global Economic Monitor (GEM),

World dataBank

Corporation Tax U.S. dollar Thomson Reuters Datastream, Cass

Business School

Degree of Openness Ratio Thomson Reuters Datastream, Cass

Business SchoolLabour Cost U.S. dollar Thomson Reuters Datastream, Cass


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Business School

3.2 EMPIRICAL MODEL

Past literature studies showed no consensus among the identification of the

determinants of foreign direct investment (FDI) as to which variable have the most important

effect on FDI flows. But in this empirical analysis, five variables have been chosen in thisstudy to examine the most significant factors that attract FDI flows into Malaysia. A

theoretical model suggests the relationship between FDI and its determinants had been

developed in earlier studies as below:

FDI = f (OPN, RER, GDP, TAX, WGE)

Where FDI is foreign direct investment, OPN is openness of the economy, RER is exchange

rate, GDP used as a proxy for the domestic market size, TAX are level of corporation tax in

Malaysia and WGE represents the cost of labour. Above model can be further expressed

become:

(1)

In the equation 1, the error term capture all of the variable that are not included in

the independent variables list mention above but they have the influence on the flow of FDI

in Malaysia. The empirical models that are related to the determinants of foreign investment

always consist of a generalized version of the above theoretical model. This is according to


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the new growth theory derived from the international trade and economic development where

normally involves using a multiple regression model, which can be estimates in log-linear

form. Therefore, equation 1 can be written as follows:

(2)

The variables expressed in term of logarithm form in order to achieve mean-reverting

relationship and enable all the econometric tests become valid through all the procedure. Note

that the FDI inflow, tax rates and wages are expressed in logarithmic form while the rest of

the variables are expressed as ratios or percentages. The variables in the model remained as

defined above while in the equation represents K1 vector of unknown parameters and is

a random error.

3.3 EXPECTED RESULT

A distinct lack of consensus regarding to the relative importance and the direction of

the impact of the potential determinants of foreign direct investment (FDI) suggests that it is

fundamentally empirical among the exact relationship between the FDI and the factors affects

the flows of FDI. According to the majority of empirical studies, the effect of exchange rate

on FDI was less clear. There was many mixed result in explaining the link between the

exchange rate and FDI since its coefficient could be positive if foreign investors regarding it

as lower cost of capital but if they looking for a higher return on the investment project then

the coefficient will be negative. In short, there have no consensus concerning the nature of

the relationship between both variable. Likewise, there have variety of results regarding the

empirical investigation in area of the openness of the host countrys economy affected the

flows of FDI. However, most of the researchers tend to support the view that more openness

to trade and less barrier is likely encouraging the foreign investment. Hence, it is to be

expected that a significantly positive correlation between openness and FDI.

Empirical findings implicate that market size and market demand has positive effect

on the flow of FDI and its mostly flows towards the host country with higher GDP growth

rate because foreign investors prefer a big market as their investment location. It is expected

that the market size will be a significant determinant of FDI with a positive coefficient.


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Corporate tax rate as an important determinant of FDI always found to give a significant

negative impact on flow of FDI in past literatures. On the other hand, most empirical studies

found conflicting results among the relationship between labour cost and FDI and there have

no consistently significant effects have been founded from the labour costs variable.

Therefore, the expected signs for the coefficient in the equation 2 based to the discussion

above should be: > 0 that is OPN have positive impact on FDI; and cannot be

determined a priori since both of these variables might have positive or negative effect on

FDI. The expected sign for > 0, represents GDP have positive relationship with FDI

inflow. < 0, that is, TAX negatively correlated to the FDI.


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CHAPTER 4: EMPIRICAL RESULTS

This chapter presents the empirical results of the determinants of foreign direct

investment (FDI) in Malaysia. Batteries of diagnostic tests are divided into seven sections andexplain the results for each of the test.

The purpose of the empirical investigation is to analyse the determinants of foreign

direct investment (FDI) in country of Malaysia. The study employs quarterly data on inflows

of FDI, gross domestic product (GDP), degree of openness (OPN), defined as the ration of

the sum of exports and imports over GDP, real exchange rate (RER), corporation tax (TAX)

and average wage (WGE). All the analysis will be conduct by using EViews 6 statistical

software.


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4.1 Augmented Dickey Fuller Unit Root Test

Prior proceedings to the estimation of the FDI equation, all the variables in the seriesare subject to the augmented Dickey and Fuller (ADF) unit root test. If there have the

presence of unit root, ADF test have to proceed in the first difference. This is to avoids to

employ the non-stationary data where could result in the results obtain from the regression of

this kind are totally spurious. The ADF unit root test results are in Table 2.

Table 2: ADF Unit Root Test Results

Variables Constant Constant and trend

LEVEL t-statistic Prob. t-statistic Prob.

Log FDI -0.9651 0.7561 -1.7541 0.7074

OPN -9.6017 0 -9.62274 0

RER -1.9164 0.3219 -2.5247 0.3153

GDP -4.1189 0.0025 -5.55672 0.0002

Log TAX -1.5454 0.5007 -2.7143 0.2366

Log WGE 1.0167 0.9958 -4.9179 0.0016

FIRST

DIFFERENCE

t-statistic Prob. t-statistic Prob.

Log FDI -6.2084 0 -6.1887 0

OPN -7.1856 0 -7.0859 0

RER -3.8924 0.0045 -3.8618 0.0228

GDP -3.6830 0.008 -3.661 0.0360

Log TAX -11.4401 0 -11.5045 0

Log WGE -3.7189 0.0072 -5.5834 0.0003

Note:Denotes significance at the 5% significant level and the rejection of the null hypothesis of non-stationarity. The critical values obtained from the ADF test are -2.9389 for the constant equation, -3.5331 for the constant and trend equation respectively.

By taking into account the intercept and trend in the ADF test, the null hypothesis is

that contain unit root in the process for all cases. The unit root test shown each of the series is


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non-stationary when the variable defined in levels. But the first differencing the series

removes the non-stationary components in all cases and the test reject the null hypothesis

suggesting that the series are stationary at first difference. The result indicate all the variables

are all at most I(1) as only first difference able to induce stationary except for the OPN and

GDP variable, where the test indicate that they areI(0). However, the robustness of the model

allows us to treat the variable asI(1) and proceed with the further analysis work.

4.2 Correlation Matrix

Table 3 shows the correlation among the dependent variable and the explanatory

variable. If there have the problem of multicollinearity, which is the linear relationship

among the sample values of the independent variable will leads to incorrect results on OLS

estimators.

Table 3: Correlation Matrix

LFDI OPN RER GDP LTAX LWGE

LFDI 1.000000 -0.179789 -0.368280 0.055110 -0.026221 -0.464064

OPN -0.179789 1.000000 0.162103 -0.002928 0.186713 0.156783

RER -0.368280 0.162103 1.000000 0.399538 -0.010639 0.353973

GDP 0.055110 -0.002928 0.399538 1.000000 0.084804 0.568450

LTAX -0.026221 0.186713 -0.010639 0.084804 1.000000 0.362557

LWGE -0.464064 0.156783 0.353973 0.568450 0.362557 1.000000

Coefficient of determination, > 0.9 are considered to be highly correlated among

independent and dependent variable. It is generally viewed as evidence of the existence of

problematic multicollinearity. If the correlation between two of the variables is negative, it

means that there have a negative relationship among two variables. Contrarily, there is a

positive relationship between two variables if the correlation among them is positive. From

the result output of the correlation matrix above, the dependent variable (FDI) and the

independent variables where are positively correlated will be only the variable of GDP, with

a positive value of 0.0551. The rest of the explanatory variables, (TAX, OPN, RER, WGE)

have a negative effect on FDI variable with negative value -0.0262, -0.1798, -0.3683 and -

0.4641 respectively. Overall, the dependent variable has weak correlation with most of the

independent variables except for the average wage (WGE = -0.4641). In general, the linear

relationship between the independent variables is considered low. However, it could be see


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that only variable of wages (WGE) and market size (GDP) have relative high correlation

(0.5685) if compare with others.

4.3 Ordinary Least Squares (OLS) Estimation

Table 4 are the output of using the OLS estimation to examine the equation (2) as

stated above.

Table 4: OLS Estimation Results

Dependent Variable: LFDI

Method: Least Squares

Date: 09/11/10 Time: 00:50

Sample (adjusted): 1997Q1 2006Q4

Included observations: 40 after adjustments

Coefficient Std. Error t-Statistic Prob.

C 75.27765 12.20297 6.168799 0.0000

OPN -8.95E-06 2.57E-05 -0.348312 0.7298

RER -0.006500 0.002670 -2.434493 0.0203

GDP 0.018917 0.004868 3.885837 0.0004

LTAX 0.451387 0.300103 1.504108 0.1418

LWGE -4.645902 1.003832 -4.628166 0.0001

R-squared 0.507004 Mean dependent var 19.43614

Adjusted R-squared 0.434505 S.D. dependent var 1.258796

S.E. of regression 0.946607 Akaike info criterion 2.865616

Sum squared resid 30.46621 Schwarz criterion 3.118948

Log likelihood -51.31232 Hannan-Quinn criter. 2.957213

F-statistic 6.993219 Durbin-Watson stat 0.505858

Prob(F-statistic) 0.000138

The result obtained above could interpret the equation (2) as below:


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This equation explains the relationship between the dependent variable (FDI) and

various explanatory variables (OPN, RER, GDP, TAX, and WGE). With exception of

economys openness and corporate tax rate, the estimated coefficients of all the specified

independent variables are statistically significant at least at the 5 % significant level.

According to the EViews output table above, the results of the FDI equation can be

summarised as follows: the intercept of the equation is equal to 75.2777. This value indicates

that the inflow of foreign direct investment in Malaysia will be 75.28 when all of the

independent variables are equal to zero. On the other hand, when the degree of openness in

the host country rise by 1%, the flow of the foreign investment into Malaysia will be decrease

by 0.000009%. If the real exchange rate appreciates by 1%, the value of FDI in Malaysia will

then fall by 0.0065%. A one percent increasing of the size and demand in host countrys

market, the inflow of FDI will be goes up by 0.0189%. Also, when the corporate tax rate

raise for 1% will lead to the flow of FDI decrease by 0.4514% while for a one percent

increase of average wage will result in the value of FDI in Malaysia falls by 4.6459%.

Furthermore, the variable of market size (GDP) gain a positive and significant result

at 5% level as expected. Since the past literature shown a mixed result for the real exchange

rate and wages in determined the flow of FDI. Each of the coefficients for the real exchange

rate (RER) and labour cost (WGE) both showing a negative sign but statistically significant

in 5% significant level. This is supported by the views of Moore (1993), Love and Lage-

Hidalgo (2000) where lower wages in the host country encourages FDI. The negative sign of

RER also consistent with Froot and Stein (1991) claimed that a depreciation of host countrys

currency should increase FDI and conversely. The coefficient of corporation tax (TAX) are

negative signed while the degree of openness (OPN) shows a negative sign which is

contradict with the expected result in this study and both of them are statistically insignificant

at 10% significant level.

The regression has the p-value of the F-statistic equal to 0.0001. The almost zero

value indicates that the model is valid in examining the determinant of FDI in Malaysia and it

is substantial enough to conclude there is joint significance of the chosen explanatory

variables. In addition, the value of R-squared equal to 0.507 imply that 50.7% of the variation

in foreign direct investment (FDI) is explained by real exchange rate (RER), corporation tax

rate (TAX), degree of openness (OPN), labour cost (WGE) and market size (GDP). The

remaining of 49.3% is unexplained and it may be due to the other qualitative factors which

are not accounted within this model.


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4.4 Breusch-Godfrey LM Test for Serial Correlation

After estimating the FDI regression equation above, we proceed by testing the fourth-order serial correlation due to the fact that we have quarterly data by using the Breusch-

Godfrey LM test.

Table 5: Breusch-Godfrey LM Test Results

Breusch-Godfrey Serial Correlation LM Test:

F-statistic 0.357469 Prob. F(4,29) 0.8367Obs*R-squared 1.832579 Prob. Chi-Square(4) 0.7665

From the results above, the values of both LM statistic and the F statistic are quite low.

If the probability of the Breusch-Godfrey LM Test is higher than 0.05 means that the model

is not able to reject the null of no serial correlation. Since the probability of the LM Test in

this result is 0.7665, higher than 0.05. This suggesting there is no autocorrelation in the

model and it could say that the model is fit to examine the determinants of foreign direct

investment in Malaysia.

4.5 Ramsey RESET Test for General Misspecification

Table 6: Ramsey RESET Test Results

Ramsey RESET Test:

F-statistic 7.393177 Prob. F(1,32) 0.0105

Log likelihood ratio 8.106412 Prob. Chi-Square(1) 0.0044

From the result above we can see that because thep-value for the F-stat is bigger than

the one percent significance level (0.01) but less than required level of significance (0.05).

Therefore, we cannot reject the null hypothesis of correct specification at 1% significant level


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but able to reject the null hypothesis at 5% of the significant level and conclude that the

model is misspecified.

4.6 The Whites Test for Heteroskedasticity

Heteroskedasticity deals with unequal variances and we run the Whites Test to

detecting the presence of heteroskedasticity in the model. Below is the result of the test:

Table 7: Whites Test Results

Heteroskedasticity Test: White

F-statistic 2.434648 Prob. F(5,33) 0.0552

Obs*R-squared 10.50968 Prob. Chi-Square(5) 0.0620

Scaled explained SS 27.48483 Prob. Chi-Square(5) 0.0000

The result from Table 7 shown that the LM-stat is 10.5097 and thep-value, 0.062 is

also bigger than the level of significance where usually is 0.05. Both suggest that the model

have no evidence of the heteroskedasticitys problem because we cannot reject the null

hypothesis of homoskedasticity. Therefore, the results obtained from different diagnostic tests

above indicate no serious problem with the model estimated in the study.


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4.7 Descriptive Test

Table 8: Descriptive Test Results

LFDI OPN RER GDP LTAX LWGE

Mean 19.43614 1423.134 -20.56079 35.87568 7.095720 12.88103

Median 19.75075 909.4621 -5.504480 47.04036 7.177896 12.92128

Maximum 20.97335 34759.09 57.41440 94.96056 8.282205 13.21533

Minimum 16.40214 -15121.75 -222.2356 -89.45480 6.000424 12.28461

Std. Dev. 1.258796 6147.205 64.24002 39.81416 0.559253 0.203923

Skewness -1.312837 3.626835 -1.614804 -1.574403 0.126096 -1.106267

Kurtosis 3.971301 24.15039 5.391693 5.530385 2.660758 3.990141

Jarque-Bera 13.06266 833.2576 26.91760 27.19638 0.297810 9.792804

Probability 0.001457 0.000000 0.000001 0.000001 0.861651 0.007473

Sum 777.4457 56925.35 -822.4315 1435.027 283.8288 515.2413

Sum Sq. Dev. 61.79810 1.47E+09 160944.4 61821.52 12.19781 1.621792

Observations 40 40 40 40 40 40

Table above present the descriptive analysis for the entire specified variable in the

model. All of these variables cannot be comparing to each other since they are all

independent among others. According to the result of the descriptive analysis table, variable

of economys openness (OPN) has a very large mean value which is 1423.134 while the real

exchange rate (RER) has the lowest mean with the value of -20.561. On the other hand, the

variable has the lowest median is also from variable of RER with a negative value, -5.504.

While the variable with highest median is still remain the same, which is OPN. Regarding to

the standard deviation, again OPN has a highest value with 6147.205 and the lowest is wages

(WGE) with a value of 0.204. All the variables within this model exhibit the variability and

the average distance of a set of score from the mean of each variable from the standard

deviation.


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CHAPTER 5: CONCLUSION

5.1 SUMMARY

The main purpose of this study is to examine the determinants of foreign direct

investment (FDI) in Malaysia over the period 1997 to 2007. The main interest is to study how

different variables in attracting FDI in Malaysia. The analysis uses the Ordinary Least Square

(OLS) method for the model estimation to identify the variable in explaining the FDI in

Malaysia. The study considers the market size, exchange rate, wages, corporate tax and the

host countrys openness variables if they explain the inflow of FDI where the FDI in

Malaysia denoted as the dependent variable in the model. All the variables are statistically

significant except for the degree of openness in economy and the corporation tax rate. The

variables indicated a correct sign includes real exchange rate, market size, and labour cost.

The rest of the variables, degree of openness and corporate tax have a contradict result as

expected. The study clearly emphasizes the role of these policy variables in determining the

FDI inflow in Malaysia.

5.2 MAJOR FINDINGS

Past literatures and studies argued that the impact of the openness in host countrys

economy is expected to be mixed but generally this variable in the conventional findings

tends to be positively associated with the FDI inflows. According to the empirical results

above, the regression analysis shown that the ratio of exports and imports to gross domesticproduct (GDP) as the indicator to measured the degree of openness (OPN) has negative effect

on the flow of foreign direct investment (FDI) in Malaysia. However, the variable is not

statistically significant in the analysis and implying it has no impact on FDI. It becomes the

weakest variable in determining the FDI inflows in Malaysia among the other explanatory

variables which have been tested in the model. There are some possible explanations for this

negative sign. The negative coefficient for degree of openness in Malaysia might be due to

the fact where FDI inflows are one of the substitutes for trade and therefore decreasing in

trade flows as an evidenced by a fall in the openness in the economy of host country. The


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substitution for trading is the result of the trade barriers imposed by host countrys

government, which is Malaysia in this case. This includes the reservation certain percentage

of the share and employment for Bumiputras (Malays) in the corporate sector. Another

explanation for the negative sign could be based on the argument of Markusen and Maskus

(2002), the trade restrictions might be less important as an incentive for the horizontal FDI

which mostly catering to the host market. This means the effect on market seeking foreign

investment will be lesser when the degree of openness in host country becomes greater.

Previous theoretical findings suggest that higher tax levels of host country will deter

potential FDI. Hence, it is predicted that the corporate tax rate will have a negative

coefficient in the regression model. However, the empirical result for the TAX variable is

found to be insignificant at conventional significance level. The positive coefficient on the

TAX variable will only be statistically significant in 15% level, observed that tax rate has

little role to play in influence the FDI inflows in Malaysia. Nevertheless, this insignificant

determinant is consistent with the study of Wheeler and Modys (1992). The positive sign in

the FDI equation where contrary to the expected result in Chapter 3 might be have used an

inappropriate TAX variable. One of the possibilities is the corporation tax measure in this

study captures taxes as income rather than taxes as cost. Or the statutory tax rate does not

consider tax base effects then may be unsuitable measures of the true tax burden. Therefore,

it can be explain why the two variables, TAX and FDI would be positively correlated in the

regression model.

The importance of the market size has been confirmed in many past literatures as the

host market size represents the host countrys economic condition and the potential demand

for their output. The empirical findings in our analysis reveal that the market demand and

market size, indicated by the variable of GDP in the regression model are positively related to

the flow of foreign investment in Malaysia, as expected. The coefficient of this variable is

positive and statistically significant in 1% level, implying that increased size of the domestic

market results in more FDI inflows due to the economies of scale and efficient utilization of

economic resources once the market size reaches a threshold level. Similar evidence of a

positive correlation between GDP and flow of FDI corroborates the studies on determinants

of FDI in Malaysia (Hassan 2007; Ang 2008; Ngie and Yol 2009) that reported a positive

relationship between the two variables.

In regard to the real exchange rate (RER), the coefficient for exchange rate is

ambiguous in many studies. It is worthwhile to note that the Ringgit Malaysia was pegged


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from September 1998 to July 2005 at MYR 3.80 to the U.S. dollar as a part of series capital

controls due to the Asian Financial Crisis in year 1997. The estimated coefficient of RER in

the regression equation is negatively signed and statistically significant at the 5% level,

implying that a depreciation of the Ringgit Malaysia against the U.S. dollar encourages FDI

inflows into Malaysia. This negative sign suggests that the foreign investors expecting a

higher return on their investment since their wealth position will become larger due to the

depreciated currency value able to bring in a cheaper cost of capital. The finding is consistent

with Ang (2008) but contrarily to Hasan (2007), Ngie and Yol (2009), they argued that weak

currency is likely to encourage the FDI over time in their recent study on Malaysia. The

conflicting results on the coefficient of RER reflect that the influence of real exchange rate on

FDI is quite elusive.

Average wages (WGE) as a proxy for labour cost in the analysis react negatively to

the flow of FDI in Malaysia. The estimated coefficient of WGE is negative and found to be

statistically significant could be explain as there is low level of skilled labour force in

Malaysia and only the labour intensive foreign investment would be attracted as wages are

low enough. Similar result are also obtained by Little (1978), Swain and Wang (1995).

5.3 POLICY IMPLICATIONS

The important lesson to learn from this study is the government of Malaysia should

keep an eye on the factors that have negatively influence the flows of FDI in the country

since this finding has important policy implications. Trade openness in the study react

negatively to the FDI suggested Malaysias economic system does not create globally

competitive atmosphere for the growth of foreign direct investment (FDI). Certain level of

protectionism extends in some of the industries such as the foreign ownership restriction

result in Malaysia becomes the most restrictive country in terms of financial sector openness.

Decision made by the Malaysia government to implement the relaxation of the FDI

restriction by liberalise 27 services sub-sectors in the financial sector on November, 2009 in

fact a wise decision in opening up previously protected industries. For instance, relaxation

ownership rules in Thailand and South Korea allowing foreign investors to acquire local

banks and other financial institutions motivated greater FDI inflows.


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Empirical result shown cheap labour as determinant to attract FDI but the labour

intensity of FDI project in Malaysia has been decreasing in recent year indicating rapid wage

increase and depletion of surplus labour reserves in the country. Malaysia no longer has the

advantage of cheap labour cost and local people become more selective about jobs.

Furthermore, Malaysia face the competition from China where has a huge comparative

advantage in terms of cheap labour and attract large volumes of FDI from the labour-

intensive industries. Thus, Malaysia needs to make further efforts to attract FDI with

strengthen interest in human resource development and skill formation in FDI policy. For

instance, Singapore and Korea able to maintain high inflows of FDI despite the expensive

labour cost if compare with Malaysia. Hence, making appropriate investment in human

capital by provides professional training and education to improve the ability in develop the

skilled human resources base in Malaysia. The similar move had been taken by Malaysia

government in setting up the skills development centres to promote technical and vocational

training and this enhanced human resource capabilities able to attract more foreign

investment such as relocation of world class high-tech plant in Malaysia.

In view of the result from Malaysia to develop infrastructure to promote linkages with

foreign enterprises and established the Small and Medium Industries Corporation to offer

advice, and guidance to increase the competitiveness of small and medium-sized enterprises

to help deter the decline in FDI. This evident that economic policy in Malaysia orientated

towards attracting FDI and it is necessary to reform by creating an investment-oriented

climate in Malaysia to meet the demands of foreign investors and boosting all of the variables

that encourage the growth of foreign investment such as creating a larger market through

regional and bilateral cooperation.

5.4 LIMITATION OF THE STUDY

There are 44 observations in the study and it is fulfil the requirement of time series

where need at least 25 observations to ensure the result of the analysis is stable and precise.

However, some of the data from Malaysia is not up-to-date or cannot be found. Lack of

availability data in Malaysia might result in the insignificant result from the analysis of

determinant of foreign direct investment in Malaysia.


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5.5 RECOMMENDATION FOR THE FUTURE STUDY

In the future study, it is suggested that association of more broadly type of the

influential factors that determine foreign direct investment (FDI) in Malaysia is needed suchas the political risk, level of corruption, total debt service or domestic gross fixed capital

formation which indicates capital stock in the host country and availability of the

infrastructure. In addition, future research should include large amount of observation by

access the data where spanning the longer time period. Hence, it would probably provide a

more accurate result in the further empirical analysis.


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