Rapid population growth has long been recognized as one of most binding constraints to alleviating poverty in Bangladesh. It took six decades for the population to almost double from 29 million in 1901 to 53 million in 1961. But it required only 26 years to double again to 106 million by 1987, as a result of high fertility and falling mortality rates.
Foreign Direct Investment and Economic Growth in Asia Dharmendra Dhakal Department of Economics and Finance Tennessee State University Nashville, TN 37203, U.S.A Telephone: (615) 963-7345 E-mail: firstname.lastname@example.org Saif Rahman Department of Economics Ohio Wesleyan University Delaware, OH 43015. U.S.A Telephone: (740) 368-3549 E-mail: email@example.com and Kamal P. Upadhyaya * Department of Economics and Finance University of New Haven 300 Boston Post Road West Haven, CT 06516, U.S.A Telephone: (203) 932-7487 E-mail: Kupadhyaya@newhaven.edu * Corresponding authors 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 2 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. 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 1 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 2 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 3 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 4 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 with respect to resource flows and commodity trade in the sample countries vis-à-vis the world economy. Table 2 presents some data on cumulative growth rates of these flows. 5 TABLE 1. RESOURCE FLOWS AND COMMODITY TRADE: 1980–2001 AVERAGE Country / Group FDI FPI Aid Trade (% of GDP) (% of GDP) (% of GDP) (% 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 portfolio investment. Aid measures the sum of official development assistance (ODA) and net official aid flows. 6 TABLE 2. CUMULATIVE GROWTH RATES: 1980–2001 Country / Group GDP FDI FDI Aid Aid Exports Imports Trade (%GDP) (%GDP) (%GDP) Bangladesh 155 2472 898 -8 -64 482 164 34 India 144 3143 1218 -19 -67 419 302 83 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. 7 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): k k GDPt i GDPt i i FDIt i t (1) i 1 i 1 k k FDI t i GDPt i i FDIt i t (2) i 1 i 1 where GDPt and FDI t are stationary time series sequences, and are the respective intercepts, t and t are white noise error terms, and k is the maximum lag length used 8 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) k minimum final prediction error criterion. If in equation (1) i is significantly different i 1 k from zero, then we conclude that FDI Granger causes GDP. Separately, if i in i 1 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): n X t t i X t i i X t i t (3) i 1 where X is the variable under consideration, is the first difference operator, t captures 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 9 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. 10 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 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 11 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 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 12 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 Korea, Countries in Group Bangladesh, Singapore, Pakistan India, Malaysia Sri Lanka, Philippines Thailand 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. 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 exchange rates. 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 13 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. 14 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*** (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*** (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 15 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 (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 16 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 17 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. 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