Foreign Direct Investment, Governance and Economic Development in Developing Countries

223 Foreign Direct Investment, Governance and Economic Development in Developing Countries Berhanu Mengistu Samuel Adams* Old Dominion University, Vi...
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Foreign Direct Investment, Governance and Economic Development in Developing Countries Berhanu Mengistu Samuel Adams* Old Dominion University, Virginia How does foreign direct investment (FDI) affect domestic investment and economic growth? What is the importance of institutional infrastructure or governance in promoting growth in developing counties? This study empirically examines these issues for a cross section of 88 developing countries. Using ordinary least squares (OLS) and fixed effects (FE) estimation techniques, the study finds that FDI is positively and significantly correlated with economic growth. The study also finds that FDI has had a greater impact in Asia than in other developing countries. However, FDI has had a net crowding-out effect on domestic investment, which suggests that FDI promotes growth through its efficiency-inducing effects rather than its augmentation of domestic investment. Finally, the study found that a country’s institutional infrastructure is positively and significantly correlated with economic growth. Key Words: Foreign Direct Investment; Domestic Investment; Governance; Economic growth and developing countries

1. Introduction The inflow of foreign direct investment (FDI) around the world has increased dramatically in the past two decades. In the developing world, FDI has become the most stable and largest component of capital flows. As a result, FDI has become an important alternative in the development finance process (Global Development Finance, 2005). There are many reasons why FDI should promote economic performance, including: the injection of capital; transfer of production technology; employment creation; improved managerial and marketing competence; and enhanced competitiveness of domestic firms (Ngowi, 2001: Kobrin, 2005; Kumar and Pradhan, 2002). FDI can therefore be

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Corresponding author: Samuel Adams College of Business and Public Administration 2096 Constant Hall Old Dominion University, Norfolk, VA 23529-0218 TEL: 757-683-5629 Email: [email protected]

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expected to contribute relatively more to growth compared to domestic investment in a host country (Kumar and Pradhan, 2002). The empirical evidence to date of the effect of FDI on economic performance, however, is not conclusive. While some studies have indicated a positive impact of FDI on economic growth, other studies report otherwise. On the other hand, a third group of studies suggest that the effect of FDI on a host country’s economy is dependent on the country’s absorptive capacity in terms of its human capacity, the level of development, and financial development (Borenstein et al. 1998; Hermes and Lensink, 2004; Makki and Somwaru, 2004). This paper contributes to the literature on FDI in three main ways. First, the focus on developing helps to reduce any bias that might result when developing and developed countries are included in the same regression (Al-Obaidan, 2002; Schneider, 2005). Second, the paper analyzes the mechanisms (efficiency and/or augmentation of domestic investment) by which FDI impacts economic growth in a large number (88) of developing countries. The study will therefore examine whether FDI crowded out domestic investment over the period of study. Finally, most of the literature that has examined the FDI-growth relationship does not control for the institutional or governance infrastructure and virtually none of the studies have considered the role of geographical location, which recent growth studies have shown are important determinants of growth. Accordingly, the inclusion of these variables may help to reduce the bias in the regression estimates that are caused by omitted variables. The rest of the paper is organized as follows: Section two discusses the theoretical and empirical arguments for and against the impact of FDI on economic growth. Section three describes the data and measures used. Section four presents the empirical results and discusses the findings. Section five discusses the managerial and policy implications, makes suggestions for future research and offers concluding remarks. Literature Review There are many reasons why FDI could have either a positive or negative effect on a host county’s development. These reasons are usually discussed under two main theoretical perspectives: The Journal of Social, Political and Economic Studies

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modernization and dependency theories. Modernization theories are based on the neoclassical and endogenous growth theories, which suggest that FDI could promote economic growth in developing countries. The neoclassical perspective assumes that economic growth requires capital investment (Firebaugh, 1992), and therefore if FDI can augment domestic capital accumulation it can enhance the potential for economic growth. As noted by Sylwester (2005), in the presence of complementarities, FDI might even spark domestic investment and so have an indirect positive effect on the total level of investment. Another perspective of the modernization theory does not differentiate between domestic and foreign investment; suggesting that “capital is capital” and hence the investment of capital (foreign or domestic) should lead to increased production as well as growth in the enterprises into which it is channeled (Crenshaw, 1992). The new growth theories or endogenous growth models indicate that knowledge or technology are factors of production (Romer, 1993; Romer, 1994) and, consequently, FDI associated with transfer of production and managerial knowledge can lead to appreciable growth in the host economy (Kumar and Pradhan, 2002). Obviously, by bringing new knowledge and investment in physical infrastructure like roads and factories, multinational enterprises (MNE) that bring in FDI may help to reduce what Romer (1993) referred to as “idea gaps” and “object gaps” between developed and developing countries. This would thereby increase the absorptive capacity of developing countries. Hence, the externalities generated by FDI in promoting growth could be more valuable (efficiency effect) than its direct generation of output by complementing domestic investment (Kumar and Pradhan, 2002). Dependency theorists, on the other hand, argue that dependence on foreign aid and investment may be expected to have a negative effect on growth and a positive impact on income inequality (Chase – Dunn, 1975; Bornschier et al. 1978; Nolan, 1983). Bornschier and Chase – Dunn (1985) claimed that foreign investment creates an industrial structure in which monopoly is predominant, leading to what they described as “underutilization of productive forces.” Chase-Dunn (1975) asserted that FDI could crowd out domestic investment and thereby create distortions that might be detrimental to the development of the host Volume 32, Number 2, Summer 2007

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economy. A similar critique was made by ActionAid (2003) in their assertion that foreign investors crowd out local firms because the local firms cannot compete due to limitations in size, financing, and marketing power. This argument is related to Amin’s (1974) assertion that an economy controlled by foreigners would not develop organically, but would rather grow in a disarticulated manner. This is because the multiplier effect by which demand in one sector of a country creates demand in another is weak, thereby leading to stagnant growth in the developing countries (Beer 1999; Kentor, 1998). The slow or stagnant growth is also enhanced by the expatriation of profits by foreign investors and the transfer of demand to the international rather than to the local economy (Kentor, 1998; Reis, 2001). Thus, while the host country may have a broad range of economic and social objectives, foreign investors are generally interested in a limited number of private goals (Chudnovsky and Lopez, 2003). In the light of the conflicting views, many empirical studies have examined the relationship between FDI and economic growth in developing countries, but the findings to date are inconclusive. For example, while Makkii and Somwaru (2004), Sylwester (2005) and Hsiao (2003) found a significant positive effect of FDI on economic growth, Chase-Dunn (1975), Dutt (1997), and Hermes and Lensink (2003) reported a negative effect of FDI on economic growth. Makkii and Somwaru (2004) employed the seemingly unrelated regression (SUR) estimation technique to study the impact of FDI on economic growth in 66 developing countries over three time periods (1971 - 2000) and found a significant positive effect of FDI on economic growth. Similarly, Sylwester (2005) used different estimation techniques (OLS, SUR, and 3-stage least squares) to study the effect of FDI on economic growth in 29 less-developed countries and found that FDI positively affects the economic growth rate. Carkovic and Levine (2002), however, showed that the macro-level positive findings of FDI on growth must be viewed with skepticism. This is because most of the studies did not control for simultaneity bias and country-specific effects. Employing the General Method of Moments (GMM) technique to control for the aforementioned problems in a 72 country study from 1960 to 1995, the authors reported that the exogenous component of The Journal of Social, Political and Economic Studies

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FDI does not exert a robust positive influence on economic growth. Carkovic and Levine (2020) therefore argue that there is no reliable cross country study supporting the claim that FDI per se accelerates economic growth. On the other hand, Dutt (1997) in a study of 58 developing countries from 1985 to 1994, reported that total investment had a positive impact on economic growth, but FDI stock had a significant negative impact on economic growth. This finding supports the earlier studies of Chase-Dunn (1975), Bornschier et al. (1978), and Dixon and Boxwell (1996) that reported that foreign capital penetration has a negative effect on economic growth. A third group of studies suggest that FDI does not have an independent positive effect on economic growth; and that the impact of FDI is dependent on host country conditions or absorptive capacity in terms human capacity, level of technology, degree of openness, and financial development (Balasubranyam et al. 1996; 1999; Borensztein et al., 1998; Zhang, 2001). Zhang (2001) studied 11 Latin American and Asian countries between 1970 and 1997 by using co-integration test to establish the direction of causality and reported that FDI tended to promote economic growth when the host country adopted liberalized trade polices, improved education, and maintained macroeconomic stability. Also, Balasubranyam et al. (1996), in a study of 46 countries, reported that the growth-enhancing effects of FDI were stronger in countries with a highly educated workforce and pursued a policy of export promotion rather than import substitution. The differences in the results of the studies reviewed show the importance of controlling for country-specific effects in cross-national studies. This study therefore complements the work of Nath (2005) and Kumar and Pradhan (2002) in employing dynamic fixed effects estimation approach to examine the effect of FDI dependence on economic growth in developing countries. Methodology The growth equation we estimate is that used by many authors in FDI-growth studies (Zhang, 2001; Hermes and Lensink, 2003; Kumar and Pradhan, 2002; Nath, 2005). The empirical analyses are based on a Volume 32, Number 2, Summer 2007

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panel data set of 88 developing countries over a period of 19 years (1985 -2003). Growth Regression We estimate a pooled time-series cross-section regression of the form; Y = β0 + β1Xit + β2 Zit + µi + εit

1

where Y is the Real GDP per capita growth rate for country I in year t; µI is the country-specific fixed effect, β iS are the coefficients to be estimated. Xit is a vector of variables including: the stock of human capital (SEC), degree of openness of the economy (OPEN), domestic investment (DI) and foreign direct investment (FDI). Z is a set of additional variables that are included as determinants of growth in cross-country growth studies (Barro, 1991; Rodrik et al., 2004). These variables include government consumption, inflation rate, and a proxy for institutional or governance infrastructure. µi represents the countryspecific effect, which is assumed to be time invariant, and εit is the classical disturbance error component. The fixed effects specification allows us to control for unobserved country heterogeneity and the associated omitted variable bias, a problem that seriously afflicts cross – country regressions (Basu and Guariglia, 2005; Prasad, Rajan, and Subranian, 2006). Domestic Investment Regressions An important question in the FDI-growth literature is whether FDI augments or crowds out domestic investment. We therefore regress domestic investment on FDI after controlling for other variables as used in the growth equation. The equation we estimate is specified as follows: DI = β0 + β1Xit + β2 Zit + Y + Y t-1 + FDIt-1 + DIt-1 + µi + εit (2) The Y, β 0, β is , Xit, and Zit notations are as explained in the growth equation above. Y t-1, ( FDIt-1), and (DIt-1) are the lagged values of the growth rate, FDI and DI respectively. The inclusion of the lagged values is to capture the dynamic relationship between the three variables (Agosin and Mayer, 2000; Kumar and Pradhan, 2002). The Journal of Social, Political and Economic Studies

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Data We use a panel dataset of developing countries for the period 1985 to 2003 to empirically examine the impact of FDI on economic growth. Since the focus of the study is developing countries, we restrict our sample to only developing countries to avoid the complications of mixing developed and developing countries in the regression analyses (Blonigen and Wang, 2005; Folster and Henrekson, 1999). The countries used in the study are listed in Table 1 and the variables, symbols, and sources of data collection are summarized in Table 2 in the appendix. Dependent Variables Real GDP per capita growth rate rather than the GDP per capita is used as the dependent variable in the growth equation because it is inflation-adjusted and consequently reflects the real value of goods and services in the economy (Nunnenkamp and Spatz, 2004; Sylwester, 2005). Domestic investment is used as the dependent variable in the second set of regressions. Independent Variables Our choice of the explanatory variables was informed by prior literature (Borensztein et al. 1998; Schneider, 2005; Makki and Somwaru, 2004). The variables used include: FDI share of GDP; Domestic investment share in GDP; trade share in GDP, political risk, geographical location, and secondary school enrollment. The main independent variable of interest is FDI. The data on FDI inflows comes from the World Development Indicators (2006), and is measured as the net FDI inflows. The net FDI consists of the net inflows of investment to acquire a lasting management interest other than that of the investor. This is the sum of equity capital, reinvestment of earnings, other longterm capital, and short-term capital as shown in the balance of payments. FDI inflows are subtracted from gross fixed investment to calculate domestic investment to prevent double counting (Kumar and Pradhan, 2002; Nath, 2005). The trade (exports plus imports) share as a percentage of GDP is a proxy for the degree of integration of a country in the world economy, which both the dependency and modernization theorists claim has an Volume 32, Number 2, Summer 2007

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impact on growth (Balasubramanyam et al. 1996, 1999; Borensztein et al. 1998). Human capital is proxied by the secondary school enrollment, which captures the degree of human capital improvement beyond the basic level of education (Ahluwalia, 1976). The inflation rate over the study period is included to capture the consistency of monetary and fiscal policies, as large structural fiscal imbalances may lead to debt monetization and higher inflation rates and a subsequent negative effect on economic growth.Political risk, which is an indication of the political and institutional or governance infrastructure, is included in the analysis as this might directly impact the growth rate or indirectly influence how FDI impacts the host country’s economy. The political risk measure is rated on a scale of zero (0) to 100, with high scores indicating high levels of political stability and low scores indicating low levels of political stability. The political risk is a composite measure of 12 factors and it includes factors like law and order, government stability, bureaucratic quality, corruption, and democratic accountability. Finally, a geographical location variable is included in the regression because recent growth literature suggests that the direct effects of geographical location explain a large portion of the variance in the income per capita across countries (Acemoglu et al., 2003; Redding and Venables, 2004). Redding and Venables (2004), for example, claimed that remoteness of markets and sources of supply explain why many developing countries have not benefited from the globalization process. In this study, a landlocked measure is employed, which is a dummy variable showing whether or not a country has a coastline or has access to the sea or ocean. Obviously, lack of territorial access to the sea, remoteness and isolation from world markets will lead to high transit costs and impose constraints on the overall socio-economic development of the landlocked country (See Table 3 for landlocked countries in the study sample). Empirical Results The results of FDI and growth regressions are reported in Table 4. The results show that FDI is positively and significantly correlated with economic growth (mostly at the 1% level) in both the OLS and fixedeffects estimations. To capture the dynamic relationship between FDI The Journal of Social, Political and Economic Studies

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and the growth rate, their lagged values were included in the regression (Columns 3 and 4 in the OLS and 7 and 8 in the Fixed effects), and the results confirm the positive effect of FDI on economic growth. The past period’s FDI, however, is not significantly related to economic growth in any of the estimations. (Columns 4, 7, and 8). Thus, FDI has a contemporaneous rather than a lag effect on economic growth. Domestic investment is significantly correlated with economic growth in the OLS but not in all the fixed-effect estimations (Columns 6 and 7). Thus, the relationship between domestic investment and economic growth is not robust. The reason for this is explained in our discussion of the FDI-DI regressions later here. The human capital variable is negatively correlated with growth (Columns 4, 6, and 7), contradicting theoretical and some empirical findings (Borenzstein et al., 1998; Makki and Somwaru, 2004). It is possible the SEC variable is not capturing the real level of human capital development. However, it is important to note that Bashir (1999), in a study of Middle Eastern and North African countries, also reported a negative correlation between human capital and economic growth. Similarly, Sylwester (2005) found a positive but insignificant effect of the human capital variable. Further, Nyatepe-Coo (1998), in a study of selected developing countries, reported a negative significant relationship between human capital and economic growth. The difference in results could be due to the proxy used for human capital, as there is no consensus as to which is the best proxy for that purpose. For example, Nyatepe-Coo (1998) used the percentage of working-age population enrolled in secondary education, while Sylwester (2005) used the average number of years of schooling obtained by the adult population. This study has employed the gross secondary school enrollment. Inflation is negatively and significantly correlated with economic growth in both the OLS and fixed effects estimations, which is consistent with the idea that inflation has a deleterious effect on economic growth (Romer and Romer, 1998). Government consumption is generally positively related to economic growth but significant only in the OLS estimations (Columns 1 through 4). Thus, we do not find evidence in support of Barro’s (1991) assertion that an increase in government consumption is associated with a decline in the rate of economic growth. Volume 32, Number 2, Summer 2007

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The effect of openness is subject to which estimation method and variables are included in the regression (Columns 1, 2, 4, and 6) and therefore the effect of openness on economic growth is not certain in developing countries. This supports the view of Rodrik (2006), who argued that the evidence that trade openness has predictable, robust, and systematic effects on national growth rates is quite weak. Rodrik (2006) noted that though autarkic trade policies can stifle economic growth, moderate amounts of trade may be associated with widely varying economic outcomes. Equally, Zagha et al. (2006) claimed that the effect of trade reform is dependent on country-specific conditions and how the process of liberalization is implemented. Consequently, they suggested that trade is an opportunity, not a guarantee, and that it is overly naive to expect that simply opening one’s economy or reducing tariffs would automatically increase growth. The political risk measure is significant and positively correlated with economic growth in all the model specifications, which suggests that a country’s institutional or governance infrastructure is robustly correlated with the rate of economic growth. Many other studies have shown that a country’s economic growth rate is affected by the quality of its institutions (Ndulu and O’Connell, 1999; Rodrik, 2006). This is because good institutions ensure the formalization of property rights and the efficient allocation of resources (North, 1996; De Soto, 1996). While De Soto (1996) described institutions as the missing ingredient needed to spur growth in developing countries, North (1996) argued that institutions are not only important in establishing efficient markets, but may indeed be the single most important determinant of economic performance. The landlocked variable is negatively and significantly correlated with economic growth (Columns, 2, 3, and 4). This result provides empirical support to Bosker and Garretsen’s (2006) study that showed that being landlocked plays a significant role in explaining world income differences. Other studies have shown that landlocked developing countries spend almost two times more of their export earnings for the payment of transport and insurance services than the average of developed economies. The United Nations Report (2005) and United Nations Conference on Trade and Development [UNCTAD], 2006) The Journal of Social, Political and Economic Studies

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noted that high transport cost is a far more restrictive barrier to trade than tariffs in promoting growth in landlocked countries Foreign Direct Investment and Domestic Investment The results of the FDI-DI regressions are reported in Table 5. As shown in Column 9, there is a problem of positive serial correlation as indicated by the very low Durbin Watson (DW) statistic (Columns 9 and 10 in the OLS and Column 13 in the FE). The inclusion of the lagged dependent variable (D It-1) helps to correct the serial correlation problem as seen in the improvement of the DW (Columns 11 and 12 in the OLS and Columns 15 and 16 in the FE estimations).The results of the study show contrasting effects of the current and lagged values of FDI on domestic investment in both the OLS and FE specifications (Columns 12 and 15). The contemporaneous FDI is negatively and significantly correlated with domestic investment (at the % level), while the lagged values are positively and significantly correlated with DI. A one percent increase in FDI is associated with a decrease in of about 0.80% to 0.86% in DI in the current period and a one percent increase in FDI from the past year is expected to lead to an increase of about 0.56% to 0.75% in the current year. Taking account of the magnitude and sign of the FDI coefficient for the current and lagged periods, the result suggests a net crowding-out effect of FDI on DI. This means that FDI has a negative effect on the current period’s domestic investment because it erodes market share of domestic investors, but exerts a positive effect on domestic investment in later periods because of the generation of backward linkages (Kumar and Pradhan (2002). Further, the net crowding-out effect of FDI on DI, but positive effect of FDI on economic growth, indicate that FDI promotes growth through its efficiency effects or the externalities it generates in the economy rather than its augmentation of domestic investment. The crowding-out effect of FDI on DI might explain the not-so-robust relationship between domestic investment and economic growth. Finally, to assess whether the effect of FDI might have some regional variations, we employed the least square dummy approach to control the regional groups, The results are reported in Table 6. The growth regressions show that the inclusion of the regional dummies Volume 32, Number 2, Summer 2007

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(Column 17) does not change the coefficient of the FDI, suggesting a robust effect of FDI on economic growth. Further, only the Asian dummy AS) is positively and significantly correlated with economic growth, which implies that compared to the reference group (Middle Eastern and North African countries-MENA), the Asian grew the most over the study period. Second, the interaction of FDI with regional dummies indicates that only the Asia-FDI (FDIAS) interaction variable is significant (Column 18), but not the Sub-Saharan Africa (SSA)-FDI and Latin America (LA)-FDI interactions. This finding demonstrates that while there was no significant difference between SSA and LA compared to the reference group, there was a significant difference between Asia and the reference group. The implication is that FDI had a greater effect on economic growth in Asia than in all the other regions. The domestic investment regressions show similar effects of the contemporaneous and lagged FDI as reported earlier (Column 19). Further, the results also show that only FDIAS is significantly and positively correlated with domestic investment (Column 20). Thus, FDI had a substantial effect on domestic investment in Asia compared to MENA, whereas the effects of FDI in LA and SSA were not different from that of MENA. The study’s findings are supported by Agosin and Mayer (2000) and Fry (1993), who found that FDI has been more productive in Asia than in other regions of the world. This is because Asian governments actively implemented policies that discriminated in favor of foreign investment that have positive effects on total investment. The implications of the study’s findings are discussed next. Implications The results of the study illustrate that not only were developing nations successful in attracting FDI, but also that FDI had substantial effects on their economies. The study also found that the institutional environment is an important determinant of economic growth. However, the study’s results show a net crowding-out effect of FDI on domestic investment, which suggests that FDI’s impact on economic growth is through its efficiency-inducing effect rather than its augmentation of domestic capital. This finding has important implications for developing countries. The Journal of Social, Political and Economic Studies

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First, to obtain the full benefits of FDI, developing countries need to promote policies that enhance domestic capacity to increase domestic investment and focus on FDI that leads to increasing returns to domestic production. For example, Agosin and Mayer (2000) observed that compared to Latin American countries that implemented farreaching liberalizations of their FDI regimes in the 1990s, the Asian countries screened investment applications and granted differential incentives to different firms and even prohibited some types of investment. Interestingly, the authors found that it is in the Latin American countries that there is strongest evidence of a crowding out of domestic investment. Accordingly, in the developing world, FDI may be more useful when the host country is able to control, regulate and direct FDI into sectors that generate externalities to the overall economy (Rhagavan, 2000) Second, the net crowding-out effect of FDI on domestic investment may be related to the skepticism most developing countries have about multinational enterprises (MNEs) as agents of development. Consequently, from a political economy perspective, it is important that MNEs become proactive and implement strategies that are not limited to their private goals of profit maximization but also to overall development of the countries in which they invest. The managerial implication for MNEs is an orientation toward long-term policies that support the development of educational and technological infrastructure to increase the absorptive capacity of the local citizens and enhance the positive externalities that the MNEs bring to the local economy. The assumption is that in the long run the growth of the economies will lead to a higher level of income and subsequently market expansion for the MNEs. As argued by Murphy et al. (1989), the benefits of the increased demand due to higher purchasing power are possible only when potential customers of the domestic industries share in the profits generated by the MNEs. Accordingly, the large market and concentrated population of most developing countries should be an incentive for MNEs to consider the region as a potential location for its products even as it seeks to empower the citizens of the region. Further, the similar social, cultural and economic conditions should offer opportunities for standardization of MNEs’ products – the scale Volume 32, Number 2, Summer 2007

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economies and the resultant reduction in cost of production would invariably lead to increased profitability of the MNE. No research is without limitations and so is this research. The study examined the overall effect of FDI, and hence did not examine the sectoral components of FDI. Data constraints made this impossible. Consequently, future research should seek to examine the differential effects, if any, of the various components of FDI. Second, as the pace of globalization intensifies and FDI becomes the most stable and largest component of capital flows, it is important that the effect of FDI on both economic and social development, especially its impact on income inequality, is examined. The focus on income distribution is important because the well-being of the poor has a special role in the objective function of policymakers. Further, there is a consensus in the economic development literature that high inequality slows growth and promotes political instability (Baliamourne-Lutz, 2004; Cling et al., 2006). Conclusion In this paper, we have examined the dynamic relationship between FDI, domestic investment, institutional environment, and economic growth in developing countries. The results indicate that the two most important determinants of economic growth over the study period were FDI and institutional infrastructure. The study also found that FDI’s effect on economic growth was more through its efficiency effects than through its augmentation of domestic investment. Accordingly, developing countries need to focus on policies that promote institutional development and become attractive destinations for FDI, but even more important to be able to direct the inflow of FDI to sectors that lead to increasing returns to domestic investment and production. The central message of this paper is that governments in the region must focus on FDI that enhances the entrepreneurial capacity and innovation of the citizenry and stimulates domestic investment to promote economic growth. In light of the study’s findings, we argue that MNEs should not see the region only as a source of cheap labor or as an export production center, but even more importantly to see the people there as consumers of their products – and thus seek to enhance the development of the region for their own long-term survival and growth. The Journal of Social, Political and Economic Studies

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The paper concludes by stating that the challenge for developing countries is not of how much FDI but of how well it is utilized to promote growth and reduce income inequality and poverty in developing countries. Appendix

Table 1: List of countries in study Sub-Saharan Africa

Latin

Middle East

America

and North

Asia

Africa _Angola

_Mauritania

_Argentina

_Algeria

_Bangladesh

_Benin

_Mauritius

_Barbados

_Egypt

_India

_Botswana

_Mozambique

_Belize

_Burkina

_Nigeria

_Bolivia

_Iran

_Pakistan

_Burundi

_Rwanda

_Brazil

_Jordan

_Sri Lanka

_Cameroon

_Senegal

_Chile

_Kuwait

_China

_Cape Verde

_Seycheles

_Colombia

_Morocco

_Fiji

African Rep

_Sierra Leone

_Costa R

_Syria

_Indonesia

_Chad

_South Africa

_Dominica

_Tunisia

_Laos

_Comoros

_Sudan

_Dom Rep

_Yemen

_Malaysia

_Congo

_Swaziland

_Ecuador

Guinea

_Cote d'voire

_Tanzania

_El Salvador

_Philippines

_Togo

_Grenada

_Thailand

_Uganda

_Guatemala

_Vietnam

_Ethiopia

_Zambia

_Guyana

_Gabon

_Zimbabwe

_Haiti

_Nepal

_Central

_Papua New

_Equatorial Guinea

_Gambia

_Honduras

_Ghana

_Jamaica

_Guinea

_Mexico

_Guinea Bissau

_Nicaragua

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Sub-Saharan Africa

Latin

Middle East

America

and North

Asia

Africa _Kenya

_Panama

_Lesotho

_Paraguay

_Madagascar

_Peru

_Malawi

_Uruguay

_Mali

_Venezuela

Table 2: Variables, Symbols, and Sources of Data Collection Variable

Symbol

Source of Data

FDI share in GDP

FDI

World Development Indicators (2006): CD ROM

DI share in GDP

DI

World Development Indicators (2006): CD ROM

Real GDP growth rate

Y

World Economic Outlook (2004) and Global Development Network Growth Database

Rate of inflation

INF

World Development Indicators (2006):CD ROM

Government consumption

CONS

World Development Indicators (2006): CD ROM

Trade share in GDP

OPEN

Global Development Network Growth Database

Political risk

POLRISK

International Country Risk Guide (Political Risk Services Group).

Composite risk

COMRISK

International Country Risk Guide (Political Risk Services Group).

Secondary school enrollment

SEC

Global Development Network Growth Database

Landlocked

LLOCK

http://www.un.org/special-rep/ohrlls/lldc/list.htm

The Journal of Social, Political and Economic Studies

Volume 32, Number 2, Summer 2007 -0.060*** (0.041) -0.002 (0.031)

0.232 (0.085) 0.214*** (0.064)

0.035 (0.045) 0.127*** (0.031)

1.349*** (0.391) -0.867*** (0.281)

0.003

(0.007)

-0.002

(0.006)

-0.010

-0.004

(0.009)

(0.362)

(0.014)

0.236*** (0.079)

0.038 (0.042)

-1.083***

(0.262)

(0.009)

0.002

0.198*** (0.059)

0.123*** (0.030)

-0.748***

0.002

(0.005)

-0.004

(0.006)

(0.037)

(0.076)

(0.027)

(0.225)

(0.001)

(0.005)

0.009

0.107***

0.288***

0.111***

-0.86***

0.014***

-0.009

(0.024)

0.105***(

0.266*** (0.068)

0.110*** (0.027)

0.864***

-

0.013***

(0.020)

(0.175)

(0.000)

(0.004)

-0.009*

0.242*** (0.0516)

0.138***

-0.483***

0.016***

-0.016***

Y t-1

(0.011)

0.24***(0

0.145*** (0.020)

0.624***

0.016***

(0.000)

FDI

-

DI

LGINF

CONS

0.017***

OPEN

FDI, Governance and Economic Development in Developing Countries 239

Table 3: List of landlocked countries

Bolivia Chad Lesotho Nepal Uganda

Burkina Faso Ethiopia Malawi Niger Zambia

Burundi Laos Rep Mali Paraguay Zimbabwe

Table 4: Regression Coefficients for the Impact of FDI on Growth OLS OLS OLS OLS FE FE FE FE

1 2 3 4 5 6 7 8

.53

.635

.572

.61

.200

.485

.483

adjust

R2

1110

692

744

1171

692

692

1171

1171

N

1.91

1.88

1.959

1.91

1.80

1.80

1.66

1.65

DW K

ed

0.104*** (0.020)

0.053

-5.663*** (1.446)

0.102*** (0.026)

0.066***

0.003 (0.075

-1.06

(0.024)

(2.070)

(2.22)

0.098*** (0.024)

-0.057**

-1.753

0.105 (0.019)

(1.340)

(0.016) (0.391)

(0.007)

(0.068

-5.929***

0.059*** -1.41***

-0.01***

-0.04

(1.00)

(0.391)

(0.007)

-2.29**

0.058*** (0.016)

-1.412

-0.011

-

(0.012)

(0.295)

(0.778)

2.22**(0.

0.081***

-0.768***

-4.909***

0.085***

POLRIS

Landlock

(0.012)

SEC

(0.770)

FDIt-1

-5.23***

Constant

240 Berhanu Mengistu and Samuel Adams

OLS OLS OLS OLS FE FE FE FE

1 2 3 4 5 6 7 8

Note. t statistics in parentheses: *Significant at the 10% level. **significant at the 5% level.

***Significant at the 1% level.

Table 5: Regression Coefficients for the Impact of FDI on Domestic Investment

OLS

OLS

OLS

OLS

FE

FE

FE

FE

9

10

11

12

13

14

15

16

The Journal of Social, Political and Economic Studies

Volume 32, Number 2, Summer 2007 0.654*** (0.043 0.654*** (0.043

-0.825*** (0.043) -0.825*** (0.043)

0.327 (0.204) 0.438** (0.207)

0.002 (0.004) 0.002 (0.004)

0.022*** (0.007) 0.023*** (0.006)

0.019 (0.014) 0.045** (0.017)

0.172***

(0.022)

0.167***

(0.023)

0.598***

(0.046)

0.595***

(0.046)

0.099***

0.092***

(0.023)

(0.044) (0.005)

(0.022)

0.562*** (0.022)

-0.633*** 0.227 (0.222)

-.001

0.028*** (0.007)

0.052***

(0.055)

(0.005)

(0.030)

(0.015)

-0.722*** 0.335 (0.264)

-0.002

0.039*** (0.009)

0.113*** (0.019)

0.124***

0.162

(0.041)

(0.000)

(0.009)

(0.024)

0.828*** (0.014)

-0.845***

0.7198 (0.124)

-0.005***

0.007** (0.003)

-0.012

0.183***

(0.021)

0.714***

(0.043)

(0.040)

(0.000)

0.077***

0.777*** (0.015)

-0.495***

0.102** (0.140)

-.003***.

0.015*** (0.003)

0.014*** (0.010)

(0.055)

(0.241)

(0.001)

(0.041)

0.204

-0.796***

-0.134

-0.014***

0.035*** (0.005)

0.069*** (0.041)

0.298***

DIt-1

(0.023)

-.749*** (.072)

0.301 (.245)

FDI

(0.000)

LGINF

-0.009***

CONS

0.031***

OPEN

(0.005)

K

SK 0.096***

POLRIS

COMPRI

(0.017)

Y

(0.021)

FDI t-1

Y t-1

FDI, Governance and Economic Development in Developing Countries 241

OLS OLS OLS OLS FE FE FE FE

9 10 11 12 13 14 15 16

Berhanu Mengistu and Samuel Adams

10

11

12

13

14

15

16

2.001 1097 .847

2.01. 1107 .845

3.71*** 1.76

0.68 1171 .702

1110

2.12 1107 .834

.815

1.98 1100 .789

(0.591)

0.337 1171

.1177 .294

.327

12.55***( 0.293

Constant DW N adjusted

R2

1.49

9

3.12***

FE

(1.057).

FE

(1.13)

FE

9.46***(1

FE

3.207***

OLS

2.779***

OLS

(0.657)

OLS

13.46***(

OLS

(1.23).

242

Note. t statistics in parentheses) *Significant at the 10% level. **significant at the 5% level. ***Significant at the 1% level.

Table 6: Effect of FDI on Growth and Domestic Investment Growth Regressions

Domestic Investment Regressions

17

19 0.193***

(0.024)

0.193***

(0.024)

(0.016)

0.836***

(0.014)

(0.030)

0.127***

20

0.766***

DIt-1

Y t-1

Y

18

The Journal of Social, Political and Economic Studies

-0.503*** (0.040)

-0.954*** (0.100)

0.287* (0.167)

0.223* (0.135)

-0.003*** (0.000)

-0.005*** (0.000)

0.016*** (0.003)

0.005*** (0.003)

0.014 (0.010)

0.008 (0.009)

-0.012 (0.307)

-0.195 (0.225)

0.724***

(0.043)

0.863**

(0.416)

(0.438)

(0.188)

(0.004)

-0.102

0.063 (0.139)

0.106*** (0.021)

-0.432**

0.012*** (0.001)

-0.014***

0.069*** (0.012)

(0.312)

(0.205)

(0.004)

-0.691**

0.179*** (0.052)

0.092*** (0.021)

-0.405**

0.013*** (0.000)

-0.014***

FDI

0.079***

DI

(0.012)

LGINF

(0.375)

CONS

-0.920

OPEN

2.119***

K

CK

(0.510)

POLRIS

LANDLO

(0.536)

FDI t-1

0.786

AS

SSA

FDI, Governance and Economic Development in Developing Countries Growth Regressions Domestic Investment Regressions

17 19

18

Volume 32, Number 2, Summer 2007

243

20

Berhanu Mengistu and Samuel Adams Growth Regressions

Domestic Investment Regressions

17

19

0.098

(0.108)

0.146

(0.106)

0.209*

(0.1250

2.13 1110 .83

2.962***

1.96 1110 .79

(0.590)

0.305

(0.362)

2.508***

0.112

(0.148) (0.83)

065 0. 0.419**

(0.174)

-3.78*** 1.95 1111 .50

1.94 1111 .51

(0.715)

(0.442) (0.88)

FDILA FDIAS Constant DW N adjusted

R2

20

(0.152)

-0.022 -4.628***

18

FDISSA

LA

244

Note. t statistics in parentheses) *Significant at the 10% level. **significant at the 5% level. ***Significant at the 1% level.

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FDI, Governance and Economic Development in Developing Countries

245

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