FDI Promote Economic Growth

8/3/2019 FDI Promote Economic Growth

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NBA SCHOOL OF BUSINESS

Does Foreign Direct Investment (FDI)

promote economic growth?Paper Presentation

Syed Ahmed Bari (MBA Semester I, MDU Section A)11/25/2011

The Concept of Foreign Direct Investment is now a part of Indias economic future but the termremains vague to many, despite the profound effects on the economy. Despite the extensivestudies on FDI, there has been little illumination forthcoming and it remains a contentious topic.The paper explores the uneven beginnings of FDI, in India and examines the developments

(economic and political) relating to the trends in key sectors. This paper examines whether theeffect of foreign direct investment (FDI) on economic growth is dependent upon differentabsorptive capacities.


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Does Foreign Direct Investment (FDI) promote economic growth?

Abstract

The Concept of Foreign Direct Investment is now a part of Indias economic future but the term

remains vague to many, despite the profound effects on the economy. Despite the extensivestudies on FDI, there has been little illumination forthcoming and it remains a contentious topic.

The paper explores the uneven beginnings of FDI, in India and examines the developments

(economic and political) relating to the trends in key sectors. This paper examines whether the

effect of foreign direct investment (FDI) on economic growth is dependent upon different

absorptive capacities. The empirical analysis shows that FDI alone plays an ambiguous role in

contributing to economic growth based on a sample of 62 countries covering the period from

1975 through 2000. Under the threshold regression, we find that initial GDP and human capital

are important factors in explaining FDI. FDI is found to have a positive and significant impact on

growth when host countries have better levels of initial GDP and human capital. Foreign direct

investment (FDI) is known as an important catalyst for economic growth in the developingcountries. It affects host countries economic growth by transferring technology, increasing

human capital formulation and by stimulating domestic investment, and access to global

markets. This paper is about characteristics of FDI in India and its role in rise of economy. The

main purpose of the paper is to investigate the impact of FDI on Indian economic growth since

1947.

By

Syed Ahmed Bari

MBA (MDU; Section A)


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1 Introduction

Foreign direct investment (FDI) is usually viewed as a channel through which for technology is

able to spread from developed countries to developing countries. This frequently leads to the

following question: Does foreign direct investment (FDI) contribute to economic growth? The

answer to this is uncertain. In the theoretical literature, the role of FDI is that of a carrier offoreign technology that can boost economic growth (Findlay (1978) and Romer (1993)). In the

empirical studies on FDI, however, the evidence is still divided. Aitken and Harrison (1999), for

instance, find that the net effect of FDI on productivity is quite small. Borensztein(1998) and

Carkovic and Levine (2005) also arrive at similar results by finding FDI does not have an

unmitigated and positive effect on economic growth. On the other hand, Haddad and Harrsion

(1993), Kokko(1996), and Alfaro (2004) point out that FDI can increase the rate of growth in

the host economy through technology transfer.

Although the evidence on the relationship between FDI and economic growth is ambiguous,

several studies argue that the host countrys absorptive capacity plays an important role inexplaining FDI. For instance, Blomstrom (1994) state that FDI is positive and significant only for

higher income countries and that is has no impact in lower income countries. Borensztein

(1998) point out that the contribution of FDI to economic growth is enhanced by its interaction

with the level of human capital in the host country. Balasubramanyam et al. (1996) argue that

FDI plays different role in the growth process due to the differing trade policy regimes. For

these reasons, in this paper we choose three threshold variables which are the initial GDP,

human capital and the volume of trade.

The main contribution of this paper is that it revisits the relationship between FDI and

economic growth using threshold variables. We apply an instrumental variable estimation of an

endogenous threshold model which as proposed by Caner and Hansen (2004). In their

approach, the estimator for the threshold value involves a two-stage least squared (2SLS) and

the estimates of the slope parameters are obtained using the generalized method of moment

(GMM). Im trying to resorts to endogenous threshold regression techniques rather than

arbitrarily assuming cut-off values. Using a cross-sectional survey of 62 countries over the

19752000 period, we find that FDI does not accelerate growth based on the least squares (LS)

approach. Furthermore, in using the GMM method that takes endogenity into consideration, FDI

is not found to have a positive effect on growth. In threshold models, the results show that FDI

can influence growth to different degrees based on different threshold variables. In addition,

FDI is found to have a positive and significant effect on economic growth when the host

countries have higher level of initial GDP and human capital. Another important result is the

convergence club. When the threshold variable is initial GDP, we find that the rich countries are

becoming richer and the poor ones are becoming poorer.

The remainder of this paper is organized as follows. Section 2 lays out the IV regression model

with the threshold that is proposed by Caner and Hansen (2004). Section 3 reports the data and

the empirical findings. The conclusions are presented in Section 4.

2 Methodology

The pure cross-sectional analysis uses data averaged over 19752000. There is one observation

per country. The basic regression takes the form:


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yi = Fi + Xi + ui . (1)

Where yi is the rate of growth, Fi equals FDI, and Xi presents a vector of conditional information

set.

As is widely known that the effect of FDI on growth give rise to the possibility of bothendogeneity and reverse causality of FDI, as a result of which both FDI and growth are

simultaneously determined and FDI is correlated with the error term. We then apply the

instrumental threshold regression proposed by Caner and Hansen (2004) to avoid the

endogeneity problem and investigate the threshold effect of FDI on economic growth. Hence,

equation (1) can take the following from:

yi = (1Fi + 1Xi)1(Ti )+ (2Fi + 2Xi)1(Ti > ) + ui. (2)

Fi = (1Wi + 1Xi)1(Ti )+ (2Wi + 2Xi)1(Ti > ) + vi..(3)

where 1() is the indicator function, Ti is the threshold variable and an element of the vector Xi, is the threshold parameter, Wi is a vector of instrumental variables and the order condition is

satisfied. We estimate the parameters sequentially. First, we estimate (3) using LS, by

substituting the predicted values of the endogenous variable Fi into (2). Second, we estimate the

threshold parameter, , using LS. Finally, we estimate the slopes using GMM on the split

samples.

3 Empirical results

3.1 Data and Variables

This paper uses cross-sectional data for 62 countries over the period 19752000 to analyse the

relationship between foreign direct investment (FDI) and economic growth. FDI (Fi) equals net

FDI inflows as a share of GDP. The economic growth rate (yi) equals the rate of real per capita

GDP growth. We also control other determinants (Xi), namely, initial GDP, human capital,

government consumption, black market premium, inflation, and the volume of trade. In order todeal with the endogenous problem, corruption, bureaucracy, the log of population, and


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institutional quality are used as instrumental variables (Wi) for FDI. A detailed description of all

the variables is included in the Appendix.

Table 1 provides summary statistics for our sample. The mean of the per capita growth rate for

the sample is 1.4 % and ranges from 2.2% for Sierra Leone to 5.7% for Korea. The mean of the

FDI is 1.8% and ranges from 4.4% for Sierra Leone to 8.3% for Belgium.

3.2 Findings

Table 2 presents the results based on the LS and GMM methods. Each column of this table shows

the results for a selection of the conditioning information, Xi , and adds the interaction terms

into it. The interaction terms are FDI(initial GDP), FDI(human capital) and FDI(trade

volume). Columns 2 to 4 show that the coefficients of FDI in these specifications are not

statistically significant. If we ignore the problem of endogeneity in terms of the relationship

between economic growth and FDI, FDI does not have a reliable impact on economic growth.

We can find that the initial value of GDP is negative and

statistically significant in this table. This finding points to conditional convergence, for it

predicts a higher growth in response to a lower starting per capita GDP, and has an important

influence on the growth rate (Barro and Sala-i-Martin (2003)). Human capital also has asignificant impact with the expected sign, as explained in Borensztein et al. (1998). The black


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market premium is found to be significantly negative and hurts economic growth in all of the

regressions.

Columns 6 to 9 of Table 2 report the results based on the GMM method that can avoid the

endogenity problem. We use corruption, bureaucracy, the log of population, and institutional

quality as instruments. It is clear that FDI is not significantly linked with economic growth at all.

To further examine the contribution of FDI to economic growth, we analyse its relationship with

different threshold variables and different regimes. Table 3 summarizes the results of the

threshold regressions using Caner and Hansen (2004). Threshold values are estimated

using the 2SLS method and the coefficients are estimated using GMM. The instrumental

variables are the same as for the GMM regression. The threshold value ( ) for initial GDP is

8.011, and there are 34 countries with values smaller and 28 countries with values larger than

. For human capital, is 2.108 with 42 countries smaller than it and 20 countries larger than it.

As for trade volume, is -0.813 with 17 countries smaller than it and other countries larger than

it. Column 2 indicates that the direct effect of FDI for higher income countries is significantly

positive and the same as the results of Blomstrom (1994).Although the interaction term for

higher income countries is both negative and significant, the direct effect of FDI is lager than the

indirect effect. Therefore, local firms are advanced enough to learn from foreigners when the

host country is a high income country. Another important finding concerns the initial GDP

which has significantly different signs in different regimes. This means that there exist


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convergence clubs (for example, Quah (1997)).This points to a group of convergent economies

and another group of divergent economies.

Columns 3 and 4 of Table 3 assess whether the level of human capital in the recipient country

influences the relationship between FDI and economic growth. FDI is found to significantly and

positively enter countries with higher human capital countries. This result is the same as inBorensztein et al. (1998). They state that FDI has a positive growth effect once h uman capital is

greater than average human capital. Besides, we can only find conditional convergence in this

case and human capital can boost economic growth.

Columns 5 and 6 assess whether the relationship between FDI and growth varies with the

degree of the volume of trade. The coefficients for FDI and their interaction terms are not

significant. We therefore cannot confirm the findings of Balasubramanyam (1996) and

Balasubramanyam et al. (1999) that FDI can promote economic growth in the presence of a

liberal trade regime.

To sum up, we find that FDI alone plays an ambiguous role in contributing to economic growth

when we use the LS and GMM regressions. Furthermore, we apply the threshold model

proposed by Caner and Hansen (2004) to discuss the role of FDI for the different levels of

threshold variables. The main result of this paper is that the effect of FDI on growth is

dependent upon the extent of the host countrys absorptive capacity. In particular, initial GDP

and human capital are the most important factors for FDI. Apart from this, we find the

convergence club using initial GDP as the threshold variable.

4 Conclusions This paper examines the influence of FDI on economic growth using threshold

variables that include the initial GDP, human capital, and volume of trade based a cross-

sectional study of 62 countries covering the period 19752000. We adopt the instrumentalvariable estimation of a threshold regression approach developed by Caner and Hansen (2004).

The empirical evidence suggests that there are conflicting effects of FDI. The results of the

threshold regression show that FDI can promote economic growth when the host country has

achieved a certain threshold of development, initial GDP and human capital. This is perhaps

indicative of the recipient countries learning and/or benefiting from foreign investors. Thus,

initial GDP and human capital are important factors for FDI that are consistent with Blomstrom

(1994), and Borensztein (1998).

Other example is Foreign Direct Investment and Economic Growth in Asia

I. INTRODUCTION

Over the past two decades, many countries around the world have experienced substantial

growth in their economies, with even faster growth in international transactions, especially in

the form of foreign direct investment (FDI). The share of net FDI in world GDP has grown five-

fold through the eighties and the nineties, making the causes and consequences of FDI and

economic growth a subject of ever-growing interest. This paper attempts to make a

contribution in this context, by analyzing the existence and nature of causalities, if any, between

FDI and economic growth. It uses as its focal point the South and Southeast Asian region, where

growth of economic activities and FDI has been one of the most pronounced.


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The literature on FDI and economic growth generally points to a positive relationship

between the two variables, and offers several, standard explanations for it. In principle,

economic growth may induce FDI inflow when FDI is seeking consumer markets, or when

growth leads to greater economies of scale and, hence, increased cost efficiency. On the other

hand, FDI may affect economic growth, through its impact on capital stock, technology transfer,

skill acquisition, or market competition. FDI and growth may also exhibit a negative

relationship, particularly if the inflow of FDI leads to increased monopolization of local

industries, thus compromising efficiency and growth dynamics. Empirically, the positive effect

of economic growth on FDI and also the positive and negative effects of FDI on economic growth

have been identified in the literature. However, very few studies attempt to directly test for

causality between FDI and growth. Two studies that do so include Basu, Chakraborty and

Reagle (2003), and Trevino and Upadhyaya (2003). Both find that FDI-to-growth causality is

more likely to exist in more open economies. In addition, an earlier study by Ericsson and

Irandoust (2000) explores the causal relationship between FDI and total factor productivity

growth in Norway and Sweden, and finds the two to be causally related in the long run.

This paper extends the line of work mentioned above, and provides a direct test of causality

between FDI and economic growth in one of the most dynamic regions of the world: South and

Southeast Asia. Using Granger causality tests, the analysis reveals substantial variation in the

FDI-growth causal relationship across countries, implying that generalization of any causality

between the two variables can be problematic. To better understand the cross-country

variation, the paper extends the analysis using regression techniques, and identifies

institutional variables that affect the FDI-growth relationship. The importance of institutions to

economic dynamics is now well recognized, and given the widespread but varying institutional

reforms across countries through the eighties and the nineties, the inclusion of institutional

factors is indispensable for the analysis at hand. To identify their relevance to the FDI-growthrelationship, separate from their direct effects on FDI or growth alone, the analysis focuses on

interaction effects involving the explanatory variables. The results show that FDI-to-growth

causality is reinforced by greater trade openness, more limited rule of law, lower receipts of

bilateral aid, and lower income level in the host country. Growth-to-FDI causality, on the other

hand, is reinforced by greater political rights and more limited rule of law.

The remainder of the paper is structured as follows. Section II discusses the background

literature on the determinants of and relationship between FDI and economic growth. It also

describes the sample used in the present analysis. Section III carries out the Granger causality

tests and establishes the cross-country variation in FDI-growth causality. Section IV extends the

analysis using regression techniques and identifies the economic and institutional factors thathelp to explain the cross-country variation in the FDI-growth causal relationship. Finally,

Section V concludes. Relevant tables, with descriptive statistics and results of the analyses, are

presented in the appendix.

II. FOREIGN DIRECT INVESTMENT AND ECONOMIC GROWTHStandard economic theory points to a direct, causal relationship between economic growth

and FDI that can run in either direction. On the one hand, FDI flows can be induced by host

country economic growth if the host country offers a sizeable consumer market, in which case

FDI serves as a substitute for commodity trade, or if growth leads to greater economies of scale

and cost efficiency in the host country. On the other hand, FDI itself may contribute to host

country economic growth, by augmenting the countrys capital stock, introducingcomplementary inputs, inducing technology transfer and skill acquisition, or increasing


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competition in the local industry. Of course, FDI may also inhibit competition and thus hamper

growth, especially if the host country government affords extra protection to foreign investors

in the process of attracting their capital.

Empirically, the positive effect of host country economic growth on FDI inflow has been

confirmed by various studies (see Veugelers, 1991; Barrell and Pain, 1996; Grosse and Trevino,1996; Taylor and Sarno, 1999; Trevino et al., 2002). The effects of FDI on subsequent economic

growth has been shown to be both positive (Dunning, 1993; Borensztein et al., 1998; De Mello,

1999; Ericsson and Irandoust, 2000; Trevino and Upadhyaya, 2003) and negative (Moran,

1998). Generally, the positive growth effects of FDI have been more likely when FDI is drawn

into competitive markets, whereas negative effects on growth have been more likely when FDI

is drawn into heavily protected industries (Encarnation and Wells, 1986). Overall, though, FDI

turns out to be associated with greater domestic investment, not smaller. Moreover, this

positive association between FDI and domestic investment tends to be greater than that

between foreign portfolio investment and domestic investment (Bosworth and Collins, 1999).

Basu, Chakraborty and Reagle (2003) study a panel of 23 developing countries from Asia,

Africa, Europe and Latin America, and find the causal relationship between GDP growth and FDI

to run both ways in more open economies, and in only one directionfrom GDP growth to

FDIin more closed economies. Trevino and Upadhyaya (2003) find a comparable result,

based on their study of five developing countries in Asia, that the positive impact of FDI on

economic growth is greater in more open economies. Whether other factors, especially

institutional ones that directly affect FDI or economic growth, also influence FDI-growth

relationship remains an open question.

Generally speaking, FDI decisions depend on a variety of characteristics of the host

economy, in addition to its market size. These include the general wage level, level of education,

institutional environment, tax laws, and overall macroeconomic and political environment. The

impact of host country wage level or education level on FDI depends on the skill intensity of the

particular production process in question and, hence, may vary from case to case. The impact of

institutional quality, physical infrastructure, import tariffs, macroeconomic stability, and

political stability on FDI inflow is usually positive (see Wei, 1997; Mallampally and Sauvant,

1999; Trevino et al., 2002; Biswas, 2002), whereas that of corporate taxes tends to be negative

(see Wei, 1997; Gastanaga et al., 1998; Hsiao, 2001). Turning to economic growth, the standard

determinants include the rate of capital accumulation and variables that raise total factor

productivity, such as education level, institutional quality, macroeconomic stability, political

environment, and, potentially, trade openness. In studying the direct, causal relationship

between FDI and economic growth in this paper, we explore the relevance of some of these

economic and political economy variables just mentioned.

Our study covers the FDI-growth relationship in nine countries: Bangladesh, India, Korea,

Malaysia, Pakistan, the Philippines, Singapore, Sri Lanka and Thailand. The choice of this

sample was driven by our attempt to include an economically diverse set of countries in a

region that has been characterized by relatively high rates of economic growth and FDI over the

past two decades. Collectively, the sample countries have featured higher rates of foreign

investments, foreign aid, and commodity trade relative to their GDP than has the rest of world.

They also experienced significantly greater growth rates in GDP, foreign investments, and

commodity trade, compared to the rest of the world. Table 1 presents some of the key statistics


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with respect to resource flows and commodity trade in the sample countries vis--vis the world

economy. Table 2 presents some data on cumulative growth rates of these flows.

TABLE 1. RESOURCE FLOWS AND COMMODITY TRADE: 19802001 AVERAGE

Country / Group FDI

(% of GDP)

FPI

(% of GDP)

Aid

(% of GDP)

Trade

(% of GDP)

Bangladesh 0.105 0.001 5.100 26.366

India 0.255 0.380 0.669 20.081

Korea, Rep. 0.552 0.998 0.026 68.461

Malaysia 4.316 1.378 0.387 152.059

Pakistan 0.606 0.362 2.490 35.495

Philippines 1.230 0.928 1.623 69.850

Singapore 10.038 n.a. 0.077 329.231

Sri Lanka 0.991 0.383 6.380 73.264

Thailand 1.898 0.734 0.801 75.885

Sample Countries 2.232 0.688 1.950 82.037

Low & Middle Income Countries 1.437 0.230 1.121 42.199

High Income Countries 1.118 n.a. 0.015 40.478

World 1.180 n.a. 0.244 41.514

Sources: World Development Indicators, Global Development Finance, and authors

calculations.

Notes: FDI refers to net inflows of foreign direct investment; FPI refers to foreign portfolioinvestment. Aid measures the sum of official development assistance (ODA) and net official aid

flows.

TABLE 2. CUMULATIVE GROWTH RATES: 19802001

Country / Group GDP FDI FDI

(%GDP)

Aid Aid

(%GDP)

Exports Imports Trade

(%GDP)

Bangladesh 155 2472 898 -8 -64 482 164 34

India 144 3143 1218 -19 -67 419 302 83


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Korea, Rep. 525 12225 1936 -172 -111 699 530 13

Malaysia 231 129 -29 -48 -84 659 480 101

Pakistan 116 419 140 15 -48 211 71 0

Philippines 111 4298 2370 84 -13 391 285 105

Singapore 539 474 -9 -98 -100 n.a. n.a. n.a.

Sri Lanka 262 234 -7 -26 -80 354 240 5

Thailand 245 1896 477 59 -55 832 566 128

Sample Mean 259 2810 777 -24 -69 506 330 59

Low & Middle Income 99 972 297 90 -4 156 150 64

High Income 201 2087 500 -15 -72 242 241 16

World 180 1783 442 85 -34 227 224 32

Source: Authors calculations.

Notes: Growth rates reflect cumulative growth from 1980-82 average (in current dollars) to

1999-2001 average.

Evidently, not all countries in the sample have been highly open to foreign investments or trade,

and not all countries have experienced similar growth in GDP or in international transactions.

In terms of GDP growth, Bangladesh, India, Pakistan, and the Philippines outperformed other

low and middle-income countries collectively, but they lagged behind the world average. As for

FDI, Bangladesh, India, Pakistan, Sri Lanka, and Korea tended to attract less investments

compared with other countries. However, over the years Bangladesh, India and Korea outpaced

most other countries in terms of FDI growth. As for trade, one finds lower-than-average

openness (defined as the ratio of total trade to GDP) in Bangladesh, India and Pakistan, with

Pakistan also lagging behind the rest of the world in terms of growth in trade.

A casual look at the data does not reveal any clearly discernible pattern involving GDP

growth and FDI. However, it seems consistent with a positive correlation between the two

variables. As already discussed, causality, if any, can run in either direction, and other variables

may also complicate these direct, causal relationships. We now turn to the empirical

examination of these relationships for our sample countries.

III.GRANGER CAUSALITYIn order to test for direct causality between FDI and economic growth, we perform a

Granger causality test using equations (1) and (2):

tGDP

t

k

iiti

k

iiti

FDIGDP

11 (1)


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tFDI

t

k

iiti

k

iiti

FDIGDP 11

(2)

wheret

GDP andt

FDI are stationary time series sequences, and are the respective

intercepts, t and t are white noise error terms, and kis the maximum lag length used in eachtime series. The optimum lag length is identified using Hsiaos (1981) sequential procedure,

which is based on Grangers definition of causality and Akaikes (1969, 1970) minimum final

prediction error criterion. If in equation (1)

k

ii

1

is significantly different from zero, then we

conclude that FDI Granger causes GDP. Separately, if

k

ii

1

in equation (2) is significantly

different from zero, then we conclude that GDP Granger causes FDI. Granger causality in both

directions is, of course, a possibility.

Since macroeconomic time-series data are usually non-stationary (Nelson and Plosser,1982) and thus conducive to spurious regression, we test for stationarity of the data series

before proceeding with the Granger causality test. We employ two separate methods for the

stationarity test. First, we conduct an augmented Dickey-Fuller test (Nelson and Plosser, 1982)

by carrying out a unit root test based on the structure in (3):

tX

t

n

iitiiti

XXt 1

(3)

whereXis the variable under consideration, is the first difference operator, tcaptures any

time trend, t is a random error, and n is the maximum lag length. The optimal lag length is

identified so as to ensure that the error term is white noise. If we cannot reject the null

hypothesis 0 , then we conclude that the series under consideration has a unit root and is

therefore non-stationary. Second, in addition to the Dickey-Fuller test, we perform the Phillips-

Perron test (Phillips, 1987; Phillips-Perron, 1988), using a non-parametric correction to deal

with any correlation in error terms.

The results of the stationarity tests are reported in Table 3. The unit root tests on the levels

of each variable reveal the corresponding series to be non-stationary for all countries.

Analogous tests on the first-difference measures of the variables, however, reveal both series to

be integrated in the first order and, hence, stationary at the first-difference level. We therefore

proceed with the Granger causality tests with equations (1) and (2) using first-differences of therespective series.

According to the test results, reported in Table 4, the existence and direction of causalities

between GDP growth and FDI have varied significantly across the countries in our sample. In

Bangladesh and Malaysia, no direct causal relationship between the two variables seems to have

existed during the given period. In South Korea, Singapore, Sri Lanka, and Thailand, causality

ran from growth to FDI, but not in the reverse direction. In Pakistan, causality ran from FDI to

growth, and not from growth to FDI. In India and the Philippines, causality ran both from

growth to FDI and from FDI to growth.


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It is thus evident that despite the above-average growth rates in both GDP and FDI in the

sample region, we cannot generalize any FDI-growth causal relationship for the region. Growth

seems to induce FDI in several, but not all, cases. Likewise, FDI seems to induce growth in some,

but not all, cases. Overall, the results indicate the presence of some FDI-growth causality in

seven of the nine countries, with the variation in the nature of this relationship pointing to

possible influence of other, institutional factors. We explore these possibilities in the next

section.

TABLE 3. UNIT ROOT TEST

Augmented Dicky Fuller Philip-Perron

Level First Diff. Level First Diff.

Bangladesh FDI -2.608 -3.572*** -2.626 -4.595*

GDP -1.069 -3.479***

-0.544 -5.670*

India FDI -2.512 -3.330*** -2.106 -3.295***

GDP -2.988 -3.759** -2.539 -4.000**

Korea, Rep. FDI -2.892 -3.805** -2.777 -5.393*

GDP -1.408 -3.877** -2.539 -4.648*

Malaysia FDI -1.835 -3.937** -2.768 -5.894*

GDP -1.877 -3.344** -1.800 -4.515*

Pakistan FDI -2.691 -4.506* -3.019 -3.603**

GDP -0.996 -4.261** -0.601 -7.650*

Philippines FDI -1.723 -3.998** -3.046 -6.831*

GDP --2.912 -4.126** -1.871 -3.937**

Singapore FDI -2.434 -3.942** -2.615 -5.764*

GDP -1.979 -3.736** -1.457 -3.920**

Sri Lanka FDI -2.255 -4.618* -2.698 -8.603*

GDP -1.955 -3.051 -2.076 -4.334**

Thailand FDI -1.591 -3.259*** -1.709 -4.051**

GDP -1.707 -3.770** -0.947 -3.753**


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TABLE 4. GRANGER CAUSALITY TEST RESULT

FDI GDP GDP FDI F statistic. P value

Bangladesh No 0.1345 0.967

No 0.619 0.657

India Yes 2.497**** 0.119

Yes 2.593**** 0.117

Korea, Rep. No 0.233 0.915

Yes 2.477*** 0.089

Malaysia No 1.512 0.245

No 1.777 0.187

Pakistan Yes 3.953** 0.039

No 0.624 0.611

Philippines Yes 7.111*** 0.069

Yes 4.437*** 0.085

Singapore No 0.413 0.855

Yes 2.409***

0.098

Sri Lanka No 0.713 0.559

Yes 3.001*** 0.060

Thailand No 0.024 0.976

Yes 2.814*** 0.079

* denotes significance at 99% confidence level; ** denotes significance at 95%

confidence level

*** denotes significance at 90% confidence level; **** denotes significance at 85%

confidence level

IV. INSTITUTIONAL FACTORS AFFECTING THE FDI-GROWTH RELATIONSHIPMost studies investigating the causes of FDI or economic growth concentrate on identifying

factors that directly affect the variable under consideration. In this sense, the analysis in the

preceding section, which tests for a direct, causal relationship between FDI and growth, issimilar to existing studies. The key finding from the causality tests here that is of particular


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significance is the cross-country variation in FDI-growth causality. Some of this variation is

likely due to cross-country differences in the predominant type of FDI inflow, that is, the

investors motivation behind FDI, such as access to host country consumer markets versus

locating low-cost production areas. Additional variation in the FDI-growth causal relationship

likely arises from cross-country differences in economic and institutional structures. Very few

studies have explored these host country influences. Examples include Basu et al. (2003) and

Trevino and Upadhyaya (2003), both of which find that the degree of trade openness of the host

country affects the extent to which growth and FDI affect each other. We extend this line of

work by considering a broader set of economic and institutional factors, and attempt to better

understand the variation in FDI-growth causalities observed within our sample.

In Table 5, we divide our sample countries into four sub-groups, based on the existence of

causal relationships between FDI and growth as established in Section III, and present a set of

economic and institutional data for each sub-group. A glance at these data, though cursory, is

somewhat revealing. A causal link from FDI to economic growth seems more likely to exist in

countries that receive less FDI, are less open, have more limited transparency and rule of law,receive greater amounts of aid from the U.S., and have lower income per capita. On the other

hand, growth-to-FDI causality is more likely in countries that have greater political rights and

receive smaller amounts of bilateral aid overall. Of course, this cursory glance misses valuable

information contained in the time-series variation within the panel data, and is therefore only

suggestive. In order to draw more accurate inferences from the given data, we use basic

regression techniques and look at the interaction effects associated with the FDI-growth

relationship.

TABLE 5. FDI, GDP, AND INSTITUTIONAL VARIABLES: GROUP AVERAGES

FDI GDP 0 0 1 1

GDP FDI 0 1 0 1

Countries in Group Bangladesh,

Malaysia

Korea,

Singapore,

Sri Lanka,

Thailand

Pakistan India,

Philippines

FDI (% of GDP) 2.33 3.24 0.44 0.45

Growth in GDP-PC (%) 6.32 8.64 5.76 4.54

Open (% of Years) 0.50 0.87 0.00 0.20

Corruption 2.52 3.58 1.67 2.10

Rule of Law 2.61 3.20 1.70 1.93

Political Rights Index 3.77 3.48 4.93 2.97

Bilateral Aid (% of GDP) 0.42 0.35 0.35 0.37

ODA-USA (mil 1985$) 66 13 102 95

GDP-PC (PPP$) 2391 5073 1133 2064

Sources: Alesina and Dollar (2000), World Bank (2003), and authors calculations.


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Notes: 0 for FDI GDP or GDP FDI denotes the absence of the corresponding granger

causality.

1 for FDI GDP or GDP FDI denotes the presence of the corresponding

granger causality.

GDP-PC refers to per capita GDP, measured at purchasing power parity exchangerates. Political rights index is based on Freedom House reports, with lower values reflecting

more freedom.

Since FDI typically involves longer-term considerations, we divide the time-series data from

1980 through 1999 into sub-periods of five years each, and regress the dependent variable on

lagged independent variables. The explanatory variables in the growth model include FDI, trade

openness, rule of law, political rights, overall bilateral aid, bilateral aid from the U.S., and per

capital GDP. Additional terms include quadratic terms for FDI and per capita GDP, and

interaction terms involving FDI. The FDI model includes as explanatory variables per capita

GDP growth, trade openness, rule of law, political rights, overall bilateral aid, and bilateral aid

from the U.S. Additional terms include the interaction effects involving economic growth. Theresults from the growth model are presented in Table 6, and those from the FDI model are

presented in Table 7.

For the sample as a whole, the effect of FDI on subsequent economic growth is not

statistically significant (Table 6), whereas the effect of growth on subsequent FDI inflow is

positive and significant (Table 7). It is worth noting, though, that inclusion of country dummies

in the growth model (not reported in the paper) reveals the growth effect of FDI to be positive,

diminishing, and statistically significant. More central to our analysis here are the interaction

effects in the two models. In this context, the growth model reveals that the effect of FDI on

economic growth is more positive in countries characterized bygreatertrade openness, more

limited rule of law, lowerreceipts of bilateral aid, and lower income level. The positive effect ofopenness on FDI-to-growth causality is consistent with the findings by Basu et al. (2003) and

Trevino and Upadhyaya (2003), and likely reflects the importance of an open, competitive

economic environment required for productive investment. The negative interaction effect of

the rule of law, in our interpretation, is suggestive of a beneficial role of FDI within an

institutional environment that otherwise constrains the efficiency of investments.

TABLE 6. ESTIMATING PER CAPITA GDP GROWTH: FDI AND INTERACTION EFFECTS

Dependent variable GDP-PC Growth

R-Squared (%) 93.0

Adjusted R-Squared (%) 78.9

Constant 1131.5****

(292.5)

Trade Openness t-1 0.1167

(0.1205)

Rule of Law t-1 4.654***


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(1.749)

Political Rights (PR) Index t-1 1.2038

(0.8593)

Bilateral Aid t-1 13.197**

(6.503)

U.S. Aid t-1 0.03565*

(0.02158)

GDP-PC t-1 0.004333

(0.002920)

(GDP-PC t-1)2 0.44 E-06*

(0.25 E-06)

FDI t-1 9.738

(9.353)

(FDI t-1)2 0.7423

(0.6978)

Trade Openness t-1 FDI t-1 0.14579***

(0.06380)

Rule of Law t-1 FDI t-1 3.151**

(1.684)

PR Index t-1 FDI t-1 0.886

(1.348)

Bilateral Aid t-1 FDI t-1 13.505**

(6.147)

U.S. Aid t-1 FDI t-1 0.01807

(0.02994)

GDP-PC t-1 FDI t-1 0.0018319***


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(0.0007693)

Year 0.5738****

(0.1469)

Notes: Standard errors are in parentheses below the estimates.

**** denotes significance at 99% confidence level, ***denotes significance at 95%

confidence level, **denotes significance at 90% confidence level, and *denotes

significance at 85% confidence level

TABLE 7. ESTIMATING FDI: PER CAPITA GDP GROWTH AND INTERACTION EFFECTS

Dependent variable FDI

R-Squared (%) 93.5

Adjusted R-Squared (%) 85.8

Constant 354.9***

(135.6)

Trade Openness t-1 0.04079

(0.05447)

Rule of Law t-1 2.863**

(1.472)

Political Rights (PR) Index t-1 1.960*

(1.162)

Bilateral Aid t-1 8.596

(8.850)

U.S. Aid t-1 0.04373

(0.03266)

GDP-PC Growth t-1 1.5981**

(0.8786)

Trade Openness t-1 GDP-PC Growth t-1 0.000246


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(0.006869)

Rule of Law t-1 GDP-PC Growth t-1 0.3041*

(0.1898)

PR Index t-1 GDP-PC Growth t-1 0.2712*

(0.1671)

Bilateral Aid t-1 GDP-PC Growth t-1 1.336

(1.271)

U.S. Aid t-1 GDP-PC Growth t-1 0.005635

(0.004698)

GDP-PC t-1 GDP-PC Growth t-1 0.3003 E-04

(0.2286 E-04)

Year 0.17151***

(0.06619)

Notes: Standard errors are in parentheses below the estimates.

**** denotes significance at 99% confidence level,***denotes significance at 95%

confidence level, **denotes significance at 90% confidence level, and *denotes

significance at 85% confidence level

It is plausible that due to structural reasons foreign investment has a greater degree of

immunity to domestic corruption and institutional weaknesses than does domestic investment,

and consequently the marginal productivity of foreign capital is relatively higher in an

environment with weaker legal infrastructure. In this sense, FDI and domestic rule of law

exhibit some substitutability in generating domestic economic growth. Finally, note that the

negative interaction effects associated with bilateral aid receipts and income level are

consistent with diminishing returns to resources.

Turning to the FDI model, the positive and significant effect of economic growth on

subsequent FDI inflow is found to be greater in the presence of greater political rights (lower PR

index) and more limited rule of law in the host country. Note, however, that the direct effect of

political rights on FDI inflows is negative, and that of domestic rule of law is positive. This

suggests that in the sample region FDI as a whole has been more likely in the presence of more

authoritarian regimes, perhaps reflecting greater stability, whereas market-seeking FDI, which

is induced by growth, prefers political competition in the host country. Similarly, well-

functioning institutions and legal systems attract FDI overall, but in the presence of institutional

weakness, the pull effect of economic growth on FDI inflow tends to be greater. Weakinstitutions and economic growth thus exhibit some substitutability in inducing FDI, and it may


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be that institutional weakness is more harmful to domestic investment than it is to foreign

investment and, consequently, growth induces greater FDI when domestic institutions are

weak.

V. CONCLUSIONWe analyze in this paper the causal relationship between economic growth and increased

FDI in nine Asian countries. Using Granger causality test, we find evidence of FDI-to-growth

causality in three of the nine countries, and growth-to-FDI causality in six countries. Two of the

countries showed causality in both directions, while two showed no causality at all. This

variation in the FDI-growth relationship indicates that causality between the two variables

cannot be generalized and must be considered more carefully.

We extend our investigation of FDI-growth causality using regression techniques, and

identify institutional variables that may help to explain the cross-country variation. The results

show that FDI-to-growth causality is reinforced by greater trade openness, more limited rule of

law, lower receipts of bilateral aid, and lower income level in the host country. Growth-to-FDI

causality, on the other hand, is reinforced by greater political rights and more limited rule oflaw.

Our findings are revealing of the substantial cross-country variation in FDI-growth causality

as well as some of the economic and institutional causes of such variation. Given the rapid

growth of both FDI and GDP around the world, and specifically in South and Southeast Asia,

these findings should be of significant interest to both scholars and policymakers in the arena of

international development. Of course, the present findings are region-specific, and further work

is needed to establish whether we may generalize the results for the global economy.


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FDI Promote Economic Growth

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