Foreign direct investment and economic growth in Asia.

Dhakal, Dharmendra ; Rahman, Saif ; Upadhyaya, Kamal P. 等

Abstract

The literature on foreign direct investment (FDI) and economic growth generally points to a positive FDI-growth relationship. However, very few studies offer direct tests of causality between the two variables. In theory, economic growth may induce FDI inflow, and FDI may also stimulate economic growth. This paper adds to the literature by analyzing the existence and nature of these causal relationships. The present analysis focuses on South and Southeast Asia, where growth of FDI has been the most pronounced. Using Granger causality tests, the paper finds substantial variation in the FDI-growth relationship across countries. Further analyses, based on regression techniques, reveal that FDI-to-growth causality is strengthened by the presence of greater trade openness, more limited rule of law, lower receipts of aid, and lower income level of the host country. Growth-to-FDI causality, on the other hand, is reinforced by greater political rights and more limited rule of law.

Keywords: Foreign direct investment; economic growth; Granger causality

JEL Classification: F21, O17, O19

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.

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-growth relationship, 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 that help 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 GROWTH

Standard 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 country's capital stock, introducing complementary inputs, inducing technology transfer and skill acquisition, or increasing 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 direction-from GDP growth to FDI--in 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 test of the world. Table 1 presents some of the key statistics with respect to resource flows and commodity trade in the sample countries vis-a-vis the world economy. Table 2 presents some data on cumulative growth rates of these flows.

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 CAUSALITY

In order to test for direct causality between FDI and economic growth, we perform a Granger causality test using equations (1) and (2):

GD[P.sub.t] = [gamma] + [k.summation over (i=1)] [[alpha].sub.i] x [GDP.sub.t=i] + [k.summation over (i=1)] [[beta].sub.i] x [FDI.sub.t-i] + [[micro].sub.t] (1)

[FDI.sub.t] = [phi] + [k.summation over (i=1)] [[delta].sub.i] x [GDP.sub.t=i] + [k.summation over (i=1)] [[lambda].sub.i] x [FDI.sub.t-i] + [[eta].sub.t] (2)

where [GDP.sub.t] and [FDI.sub.t] are stationary time series sequences, [gamma] and [phi] are the respective intercepts, [[micro].sub.t] and [[eta].sub.t] are white noise error terms, and k is the maximum lag length used in each time series. The optimum lag length is identified using Hsiao's (1981) sequential procedure, which is based on Granger's definition of causality and Akaike's (1969, 1970) minimum final prediction error criterion. If in equation (1) [k.summation over (i=1)] [[beta].sub.i] is significantly different from zero, then we conclude that FDI Granger causes GDP. Separately, if [k.summation over (i=1)] [[delta].sub.i] 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):

[DELTA][X.sub.t] = [kappa] + [rho] x t + [[theta].sub.i] x [X.sub.t-i] + [n.summation (i=1)] [[PHI].sub.i] x [DELTA][X.sub.t-i] + [[epsilon].sub.t] (3)

where X is the variable under consideration, A is the first difference operator, t eaptures any time trend, [[epsilon].sub.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 [theta] = 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 nonparametric 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 the respective 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.

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.

IV. INSTITUTIONAL FACTORS AFFECTING THE FDI-GROWTH RELATIONSHIP

Most 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, is similar to existing studies. The key finding from the causality tests here that is of particular 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 investor's motivation behind FDI, such as access to host country consumer markets versua 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.

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. The results 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 by greater trade openness, more limited rule of law, lower receipts of bilateral aid, and lower income level. The positive effect of openness 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.

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. Weak institutions and economic growth thus exhibit some substitutability in inducing FDI, and it may 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. CONCLUSION

We 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 of law.

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 ate region-specific, and further work is needed to establish whether we may generalize the results for the global economy.

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DHARMENDRA DHAKAL

Tennessee State University, U.S.A

SAIF RAHMAN

Ohio Wesleyan University, U.S.A

KAMAL P. UPADHYAYA

Universlty of New Haven, U.S.A

Table 1
Resource Flows and Commodity Trade: 1980-2001 Average

 FDI FDI
Country / Group (% of GDP) (% of GDP)

Bangladesh 0.105 0.001
India 0.255 0.380
Korea, Rep. 0.552 0.998
Malaysia 4.316 1.378
Pakistan 0.606 0.362
Philippines 1.230 0.928
Singapore 10.038 n.a.
Sri Lanka 0.991 0.383
Thailand 1.898 0.734
Sample Countries 2.232 0.688
Low & Middle Income Countries 1.437 0.230
High Income Countries 1.118 n.a.
World 1.180 n.a.

 Aid Trade
Country / Group (% of GDP) (% of GDP)

Bangladesh 5.100 26.366
India 0.669 20.081
Korea, Rep. 0.026 68.461
Malaysia 0.387 152.059
Pakistan 2.490 35.495
Philippines 1.623 69.850
Singapore 0.077 329.231
Sri Lanka 6.380 73.264
Thailand 0.801 75.885
Sample Countries 1.950 82.037
Low & Middle Income Countries 1.121 42.199
High Income Countries 0.015 40.478
World 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 portfolio investment. Aid measures the sum of
official development assistance (ODA) and net official aid flows.

Table 2
Cumulative Growth Rates: 1980-2001

 FDI
Country / Group GDP FDI (% GDP) Aid

Bangladesh 155 2472 898 -8
India 144 3143 1218 -19
Korea, Rep. 525 12225 1936 -172
Malaysia 231 129 -29 -48
Pakistan 116 419 140 15
Philippines 111 4298 2370 84
Singapore 539 474 -9 -98
Sri Lanka 262 234 -7 -26
Thailand 245 1896 477 59
Sample Mean 259 2810 777 -24
Low & Middle Income 99 972 297 90
High Income 201 2087 500 -15
World 180 1783 442 85

 Aid Trade
Country / Group (% GDP) Exports Imports (% GDP)

Bangladesh -64 482 164 34
India -67 419 302 83
Korea, Rep. -111 699 530 13
Malaysia -84 659 480 101
Pakistan -48 211 71 0
Philippines -13 391 285 105
Singapore -100 n.a. n.a. n.a.
Sri Lanka -80 354 240 5
Thailand -55 832 566 128
Sample Mean -69 506 330 59
Low & Middle Income -4 156 150 64
High Income -72 242 241 16
World -34 227 224 32

Source: Authors' calculations.

Notes: Growth rates reflect cumulative growth from 1980-82 average
(in current dollars) to 1999-2001 average.

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 **

Table 4 Granger Causality test Result

 FDI GDP
 [right arrow] [right arrow]
 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

Table 5
FDI, GDP, and Institutional Variables: Group Averages

FDI [right arrow] GDP 0 0
GDP [right arrow] FDI 0 1

 Korea,
 Singapore,
 Bangladesh, Sri Lanka,
Countries in Group Malaysia Thailand

FDI (% of GDP) 2.33 3.24
Growth in GDP-PC (%) 6.32 8.64
Open (% of Years) 0.50 0.87
Corruption 2.52 3.58
Rule of Law 2.61 3.20
Political Rights Index 3.77 3.48
Bilateral Aid (% of GDP) 0.42 0.35
ODA-USA (mil 1985$) 66 13
GDP-PC (PPP$) 2391 5073

FDI [right arrow] GDP 1 1
GDP [right arrow] FDI 0 1

 India,
Countries in Group Pakistan Philippines

FDI (% of GDP) 0.44 0.45
Growth in GDP-PC (%) 5.76 4.54
Open (% of Years) 0.00 0.20
Corruption 1.67 2.10
Rule of Law 1.70 1.93
Political Rights Index 4.93 2.99
Bilateral Aid (% of GDP) 0.35 0.37
ODA-USA (mil 1985$) 102 95
GDP-PC (PPP$) 1133 2064

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

Notes: '0' for FDI [right arrow] GDP or GDP [right arrow] FDI
denotes the absence of the corresponding granger causality.
1' for FDI [right arrow] GDP or GDP [right arrow] FDI denotes
the presence of the corresponding granger causality. GDP-PC
refers to per capita GDP, measured at purchasing power parity
exchange rates. Political rights index is based on Freedom
House reports, with lower values reflecting more freedom.

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.sub.t-1] -0.1167
 (0.1205)
Rule of [Law.sub.t-1] 4.654 ***
 (1.749)
Political Rights (PR) [Index.sub.t-1] 1.2038
 (0.8593)
Bilateral [Aid.sub.t-1] 13.197 **
 (6.503)
U.S. [Aid.sub.t-1] -0.03565 *
 (0.02158)
[GDP-PC.sub.t-1] 0.004333
 (0.002920)
[([GDP-PC.sub.t-1]).sup.2] -0.44 E-06 *
 (0.25 E-06)
[FDI.sub.t-1] 9.738
 (9.353)
[([FDI.sub.t-1]).sup.2] -0.7423
 (0.6978)
Trade [Openness.sub.t-1] x [FDI.sub.t-1] 0.14579 ***
 (0.06380)
Rule of [Law.sub.t-1] x [FDI.sub.t-1] -3.151 **
 (1.684)
PR [Index.sub.t-1] x [FDI.sub.t-1] -0.886
 (1.348)
Bilateral [Aid.sub.t-1] x [FDI.sub.t-1] -13.505 **
 (6.147)
U.S. [Aid.sub.t-1] x [FDI.sub.t-1] 0.01807
 (0.02994)
[GDP-PC.sub.t-1] x [FDI.sub.t-1] -0.0018319 ***
 (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.sub.t-1] 0.04079
 (0.05447)
Rule of [Law.sub.t-1] 2.863 **
 (1.472)
Political Rights (PR) [Index.sub.t-1] 1.960 *
 (1.162)
Bilateral [Aid.sub.t-1] -8.596
 (8.850)
U.S. [Aid.sub.t-1] 0.04373
 (0.03266)
[GDP-PC.sub.t-1] 1.5981 **
 (0.8786)
Trade [Openness.sub.t-1] x GDP-PC [Growth.sub.t-1] -0.000246
 (0.006869)
Rule of [Law.sub.t-1] x GDP-PC [Growth.sub.t-1] -0.3041 *
 (0.1898)
PR [Index.sub.t-1] x GDP-PC [Growth.sub.t-1] 0.2712 *
 (0.1671)
Bilateral [Aid.sub.t-1] x GDP-PC [Growth.sub.t-1] 1.336
 (1.271)
U.S. [Aid.sub.t-1] x GDP-PC [Growth.sub.t-1] -0.005635
 (0.004698)
[GDP-PC.sub.t-1] x GDP-PC [Growth.sub.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.