The foreign direct investment–economic growth nexus

The foreign direct investment–economic growth nexus

International Review of Economics and Finance 42 (2016) 116–133 Contents lists available at ScienceDirect International Review of Economics and Fina...

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International Review of Economics and Finance 42 (2016) 116–133

Contents lists available at ScienceDirect

International Review of Economics and Finance journal homepage: www.elsevier.com/locate/iref

The foreign direct investment–economic growth nexus Sasi Iamsiraroj ⁎ Alfred Deakin Institute for Citizenship and Globalisation, Deakin University, Geelong, Victoria 3220, Australia

a r t i c l e

i n f o

Article history: Received 31 May 2014 Received in revised form 21 October 2015 Accepted 21 October 2015 Available online 11 November 2015 JEL classification: F21 O11

a b s t r a c t The nexus between foreign direct investment (FDI) and economic growth has been a longstanding debate from mixed empirical findings. There is also a possibility of a bi-directional relationship between FDI and economic growth. This paper investigates FDI–growth associations using a simultaneous system of equations approach of 124 cross-country data for the period 1971–2010. Results from the estimation indicate that overall effects of FDI are positively associated with growth and vice versa; whereas labor force, trade openness and economic freedom are other key determinants of FDI, which in turn stimulate income growth further. © 2015 Elsevier Inc. All rights reserved.

Keywords: Foreign direct investment Economic growth Panel data

1. Introduction International transfers are significant features of the global economy. Foreign direct investment (FDI) is one of the most important components of such transfers. Being critical to the formation of capital in both developed as well as developing countries and much research into its impact has grown substantially over the years. Most countries, especially developing nations, target to attract FDI into their economies as they expect long-term economic growth from additional stable resources in host countries. There are some more fundamental reasons that support the attractiveness of FDI, such as advanced technology, skills, research and development (R&D) and know-how to host countries. These intangible assets would be useful for host countries to stimulate productivity and economic growth. FDI may also help to access foreign markets when host countries are used as an export platform to distribute products in the region. Hence, FDI appears to offer good characteristics ranging from a high degree of stability, financial resource augmentation, positive productivity effects and access to foreign market. The growing importance of FDI can be observed in Fig. 1, which illustrates the flow of global FDI and by group of economies. The significant increase in growth of FDI after the 1990s associated with a substantial number of theoretical and empirical works have emerged; exploring the effects of FDI on host country growth, together with economic growth as a locational determinant of FDI. Due to the possibility that FDI has an effect on economic growth and in turn that economic growth could influence FDI inflows, the associations between FDI and economic growth are most likely dynamic. These dynamic mechanisms may suggest the existence of both endogeneity and simultaneity, which the results of existing studies might miss depicting accurately.1 The core objective of this paper is to present a holistic picture by incorporating the links between FDI and growth using a comprehensive econometric framework.

⁎ Tel.: +61 3 924 43758; fax: +61 3 9918 9001. E-mail address: [email protected] 1 At this stage, the vast majority of the empirical studies have adopted a single equation approach to analyze both associations.

http://dx.doi.org/10.1016/j.iref.2015.10.044 1059-0560/© 2015 Elsevier Inc. All rights reserved.

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117

2000 1800

Billions of Dollars

1600 1400 1200 1000 800 600 400 200 0

World

Developed economies

Developing economies

Fig. 1. FDI inflows, global and by group of economies, 1970–2010. Source: Constructed using data from UNCTAD, based on its FDI/TNC database (UNCTAD, 2012).

This paper employs panel data for 124 countries spanning the period 1971 to 2010 in a simultaneous system of equations. The benefits of the systemic nature of the framework applied in this paper are (1) to provide more consistent estimates since it takes the endogeneity and simultaneity issues into consideration and (2) to identify channels generating potential effects on growth through FDI. The primary data analysis also benefits by identifying other drivers of economic growth and FDI determinants. This paper finds that, on average, FDI is associated with higher rates of economic growth and vice versa. The paper is organized as follows: Section 2 provides a brief review of theoretical and empirical literature of FDI and growth. Section 3 outlines econometric models of FDI and growth. Section 4 discusses the data and estimation method used in this empirical study. The estimation results are reported and discussed in Section 5. Finally, conclusions are drawn in Section 6.

2. A brief review of theoretical and empirical literature of FDI and growth The theoretical literature on the effects of FDI and economic growth identifies contrasting views from the neoclassical and the endogenous growth models. In the context of the neoclassical model of economic growth, the long-run growth could only result from technological progress and/or labor force growth, which are considered as exogenous. Some empirical studies, such as de Mello (1997) and Solow (1957) model the effects of FDI within this framework since it could stimulate economic growth if it influences technological progress positively and permanently. Under the assumption of diminishing returns to capital inputs, economies are converging to the same steady-state growth rate in neoclassical growth theory. FDI only affects growth in the short-run and leaves long-run growth unchanged. This lack of realism in the neoclassical models stimulated the development of the endogenous growth model, which many regard as a more appropriate model emphasizing the role of technological change. The endogenous growth model has been developed by Lucas (1988), Rebelo (1991) and Romer (1986). This growth model introduces capital in the form of human capital accumulation and R&D and highlights the externalities that arise from these types of capital. FDI encourages the incorporation of new inputs and technologies in the production systems of host countries. FDI could also stimulate economic growth endogenously if it generates productivity, positive externalities and spillover effects. Since FDI is considered as an important source of know-how, human capital and technological diffusion, these factors can be initiated to promote economic growth through FDI inflows. Both direct and through channels from endogenous growth models can explain the effects of FDI inflows on growth more clearly, compared to the neoclassical growth model. As such, it may be more appropriate to use endogenous growth models to explain the FDI–growth association. An alternative approach is based on neoclassical trade theory, which has mainly focused on the direct effects of FDI on factor rewards, employment and capital flows, while those following the industrial organization approach have put more emphasis on potential effects or externalities from FDI inflows. In the industrial organization approach,2 FDI can be a channel to stimulate host country growth as it can supplement the domestic capital formation which may be insufficient in the recipient economy. FDI can also accelerate domestic human capital accumulation through know-how and spillovers, and thereby act as a positive force for growth. On the other hand, several authors argue that FDI might have no effect on growth on its own. These authors criticize that the effects of FDI on growth are conditional upon the existence of some other factors. For example, the models proposed by Benhabib and Spiegel (1994) and Nelson and Phelps (1966) highlight the need for an adequate stock of human capital as an

2

From Buckley and Casson (1976), Dunning (1973), Hymer (1976), Kindleberger (1969) and Vernon (1966).

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absorptive capability. According to Akinlo (2004), FDI contributes to economic growth only when a sufficient absorptive capability is available in the host economy to absorb the advanced technologies. Furthermore, the beneficial impact of FDI is enriched in an environment characterized by an open trade and investment regime and macroeconomic stability (Balasubramanyam et al., 1996). Thus, the pure effect of FDI on growth can be zero, while the effects of FDI interacted with some factors such as human capital, financial market development and trade, might be positively correlated with income growth (Borensztein et al., 1998). Other scholars discuss that FDI might have an adverse effect on growth due to the intervening mechanisms of dependence and decapitalization. According to the dependency theory developed by Amin (1974) and Frank (1979), foreign capital flows would not influence long-term economic growth in developing countries. The empirical studies by Alschuler (1976) and Bornschier et al. (1978) find that FDI, foreign aid and trade have the long-term effect of decreasing the rate of economic growth and of increasing inequality. An adverse effect of FDI on growth can also be explained by decapitalization if FDI displaces savings in the country or diverts domestic capital toward areas of FDI activity from other more productive areas. Decapitalization is defined by Bornschier (1980) as the reduction in funds available for investment in the host country. Bornschier provides examples of decapitalization in the recipient country, especially least developed countries (LDCs). For example, LDCs strive to attract foreign investment in order to transfer advanced technology into their economies. These flows are mainly concentrated in industrial sectors, which are likely to employ much of the available capital for investment. Therefore, the capital formation available for use in other sectors of the host economy may be reduced. Consequently, FDI could influence higher investment and consumption in the short-term and reflect negatively on long-term growth (Bornschier, 1980, O'Hearn, 1990, Stoneman, 1975). This serves as another example of crowding out effect. 3. Econometric models of FDI and growth From the theoretical and literature review, it is critically important to model the underlying data-generating process, as well as to derive reliable estimates of it. Fig. 2 illustrates one conception of the data generating process. Economic growth is a function of capital inputs—domestic capital, human capital, foreign capital including other factors, such as labor, institutions and government policies. This figure suggests that FDI can have a direct effect on growth which is represented by C1. The effects of other growth drivers are denoted by C2. In addition to the direct effect, FDI could influence economic growth through three channels: C3 represents an interaction effect of FDI associated with other inputs on the marginal product; C4 and C5 represent potential effects from the domestic endowments, such as economic growth, human capital, domestic capital and institutions, which can be considered as determinants of FDI inflows; and C6 represents an indirect effect of FDI through other channels. The focus of this paper is on channels C1, C2, C3, C4 and C5. 3.1. Growth model In general, the growth models are constructed by considering the effects of domestic capital, human capital, foreign capital, as well as institutional factors, policy-related factors and conditional convergence. The approach adopted in this study is to estimate the effects of FDI on growth that draws upon two sets of information: the theoretical literature and prior empirical studies.3 Fig. 2 involved modeling the direct effects of FDI on growth (C1), the effects of other drivers of economic growth (C2) and the interaction effects between FDI and other types of capital (C3). Eq. 1 follows the extant literature and abstracts from the direct effects of FDI on economic growth, controlling for the effects of other explanatory variables, and interaction effects of FDI on the accumulation of other capital. The most widely explored interaction effects involve FDI and human capital.4 Eq. 1 presents the growth model estimated in this paper. Growthit ¼ α þ β1 FDIit þ β2 FDIit x Hit þ β’3 Z it þ εit

ð1Þ

where Growthit is a real growth GDP per capita, FDIit is the percentage of FDI relative to GDP, FDIit × Hit is the multiplicative interaction term between FDI and three different human capital indicators defined above and Zit is a vector of control variables. εit is a residual. Subscript i represents recipient country and t represents time. The selection of elements of the control vector of variables is guided by theoretical and existing empirical literature. The vector of control variables (Zij) contains four variables relating to domestic endowments, three measures relating to government policies and two variables of institutions. 3.1.1. Measure of FDI The existing empirical studies use different measures of FDI. While ‘flow’ measures are based on current account inflows or outflows of foreign capital for certain period of time, ‘stock’ measures estimate the total cumulated value of foreign-owned capital in a country (Bornschier et al., 1978). The difference between FDI inflows and FDI outflows is generally known as net FDI. The analysis in this paper focuses on the FDI inflows to the host economy rather than net FDI or stock of FDI.5 FDI inflows are based on current accounts in the balance of payments. Alfaro et al. (2004) and Bornschier et al. (1978) state that FDI inflows measure the value of new foreign capital flows into the host country in a particular year. Hence, this provides a measure of additional capital available to the production process of host economies for certain period of time. The analysis intends to examine 3

See Iamsiraroj and Ulubasoglu (2015). Of the 109 empirical cross-country studies, seven consider the effects of FDI interacted with human capital: Borensztein et al. (1998), Durham (2004), Hermes and Lensink (2003), Kosack and Tobin (2006), Li and Liu (2005), Olofsdotter (1998). Only a handful of studies consider the interactions between FDI and trade, FDI and capital, and FDI and financial market development. 5 The depreciation rate of capital normally addresses the decline in the economic value of capital stock in an economy. Both foreign and domestic capital variables in this paper are measured as flows to GDP. If stocks were used, depreciation would be an issue. 4

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Human capital

C6

119

C2 C3

C5

Economic Growth

C1

Foreign capital

C4 C6

C5 C2 Domestic capital

C5

C2

Other factors

Fig. 2. Hypothesized relationships between FDI and economic growth.

whether new foreign capital would influence host country growth rather than existing foreign capital in the economy. The above considerations may lead to the hypothesis below. H1: As FDI inflows could provide additional capital to the host country’s production process, its growth rate is expected to increase. 3.1.2. Measure of host country endowments The first control variable captures existing economic conditions. This variable is the natural logarithm of the level of initial GDP per capita, measured in constant US dollars. Convergence theory implies that growth rates of per capita income will eventually equalize (Barro, 1991, Mankiw et al., 1992). This leads to the following hypothesis. H2: If convergence holds, then the expected coefficient of initial GDP per capita will be negatively related with economic growth. The second, third and fourth host country endowments control variables are, respectively, labor growth, human capital and domestic investment. Labor growth measures the contributions of labor to income growth rate, holding other factors constant. Gao (2002) and Levine and Renelt (1992) suggest that labor growth is an important factor in explaining economic growth. The Solow growth model predicts that high population growth results in lower steady-state income as each worker has less capital to work with. The above considerations may be outlined in the following hypothesis. H3: Labor force growth is expected to have a negative correlation on economic growth as it is part of the investment requirement. The stock of human capital might be a minimum requirement of absorptive capability in the host country. They are expected to be positively related with economic growth, though human capital could possibly have no effect on short-run growth, exerting its effect only on income levels (or in the long run). Barro et al. (1995) and Mankiw et al. (1992) highlight the importance of human capital in economic growth model. On the other hand, Islam (1995) argues that human capital variables do not appear to be significant in panel data regressions, possibly because they are not specified well in empirical models. This paper takes this issue seriously. In this particular context, educational attainment would capture the absorptive capacity of the economy, which is relevant to process and utilize through FDI. In Eq. 1, the coefficients attached to human capital variables reflect the direct effects of human capital, while the coefficients attached to the interacted variables reflect the effects of human capital interacted with FDI, and the two together measure the total effects related to human capital on economic growth. The effects of human capital on growth might be hypothesized as below. H4: The stock of human capital level could positively stimulate growth. Domestic investment is a robust determinant of economic growth in many empirical studies, such as Barro (1999), Dixon and Boswell (1996) and Levine and Renelt (1992). According to the World Development Indicators (WDI), the domestic investment to GDP ratio is defined as the additional fixed capital formation available in a local economy for a given time period. This argument leads to the following hypothesis. H5: Where domestic investment makes up a larger proportion of domestic capital, this will be positively associated with economic growth.

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3.1.3. Measure of host country policies The control variables capture host country policies included in the growth model are trade to GDP, government expenditure to GDP and the inflation rate. In effect, these variables are the outcomes of government policies. The trade to GDP is a proxy for the degree of openness to trade in the host country. Openness is generally known as an important determinant of economic growth (Frankel and Romer, 1999). Trade enables a more efficient production of goods and services by shifting production to countries that have a comparative advantage. This leads to the hypothesis below. H6: The degree of openness is expected to be positively correlated with income growth. While government consumption is an important variable in growth regressions, several empirical studies on the determinants of growth, however, have found that government consumption has a negative effect on economic growth (Barro, 1990, King and Rebelo, 1990). An increase in government consumption may affect growth negatively by inducing the amount of distortion taxation and a crowding out of private sector investment (Akinlo, 2004). The relationship between government consumption and economic growth should be hypothesized as follows. H7: An increase in government expenditure should stimulate aggregate expenditure or income growth. The inflation rate is used as an indicator for macroeconomic stability such as the ability of government and the central bank to control the budget and money supply. Since the inflation rate is measured as the percentage change in the GDP deflator, it is a proxy for the lack of commitment and monetary discipline of the host country. H8: The inflation rate could cause a slowing down of economic growth. 3.1.4. Measure of host country institutions and market development It is common in the literature on FDI and growth to use one or more indicators of financial market development as control variables. Indicators differ among studies. The empirical analysis in this paper proxies the financial market development and the market-friendly locations in the economies by using credit in the private sector and economic freedom, respectively. Various financial market development indicators differ among studies, such as Akinlo (2004) and Borensztein et al. (1998) use M2/GDP as a proxy of financial market development. Alfaro et al. (2004) consider various indicators to capture financial market development: bank credit, commercial bank assets as a ratio of total bank assets, private sector credit and liquid liabilities. The analysis in this paper considers credit in the private sector as a proxy of financial market development, which is expected as outlined in the hypothesis below. H9: Financial market development has a positive correlation to economic growth. Economic freedom index is constructed by the Fraser Institute and is a measure of the degree of economic freedom in terms of five major areas: (1) government size, taxes, and enterprises; (2) legal structure and the security of property rights; (3) access to sound money; (4) freedom to trade internationally and (5) the regulation of credit, labor and business. A larger value of the index means that the country is more outward-oriented, less regulated and thus can be expected to be more receptive to the entrance of FDI. Since the effects of trade, government consumption, inflation and credit in the private sector are captured by these variables in Eq. 1, the economic freedom index in this analysis captures the remaining effects, which comprise the regulation of business and labor, and the security of property rights. In their meta-analysis of the literature, Doucouliagos and Ulubasoglu (2006) find a positive correlation between economic freedom and growth. This leads to the following hypothesis. H10: A higher degree of economic freedom is positively associated with income growth.

3.2. FDI model The estimation frameworks on the determinants and destination of FDI can be explained by industrial organization theory (Dunning, 1973, Hymer, 1976), by product cycle theory (Vernon, 1966) and by the eclectic paradigm of ownership–location–internalization (OLI) (Dunning, 1981). These include the availability of resources (such as natural, labor and capital), factor costs, the exchange rate, as well as the size of the market and economic growth. Fig. 2 involves modeling the potential effects from host country growth (C4) and the domestic endowments (C5), which can influence FDI inflows. The variables in Eq. 2 measure the effects of the potential explanatory variables on FDI. They are all derived from the extant theoretical and empirical literature. Eq. 2 presents the FDI model estimated in this analysis. FDIit ¼ λ þ γ1 Growthit þ γ’2 Q it þ μ it

ð2Þ

The vector of control variables (Q it) contains four variables relating to domestic endowments, three variables relating to government policies and two institutional variables. μit is a residual.

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In the theoretical literature, economic growth is recognized as one of the main FDI determinants. Many empirical studies find that economic growth is an incentive for multinational firms (Al Nasser, 2010, Jiménez, 2011, Kandil, 2011, Mohamed and Sidiropoulos, 2010). Other things being equal, a growing market can be attractive to multinational firms because it leads to a higher level of aggregate demand and greater opportunities for making profits from the realization of economies of scale (Lim, 1983, Zhang, 2001). The prospects for market growth would need to be favorable to ensure a long-term commitment by the foreign investor. These incentives attract FDI to growing economies. The above considerations may lead to the formulation of the hypothesis below. H11: Host country growth is expected to be positively associated with FDI inflows. 3.2.1. Measure of host country endowments The first control variable of host country endowments is labor force. It measures the availability of labor in the economy. Availability in this sense implies not only abundance but also low cost relative to productivity under the assumption that a natural consequence of the abundance of labor will be its relatively lower price, ceteris paribus. H12: The host country with higher level of labor force could influence FDI inflows. The second, third and fourth host country endowments control variables are, respectively, human capital, domestic investment and infrastructure. Human capital can enhance the productivity of physical capital and labor. Lucas (1988) argues that the accumulation of human capital has both internal effects (the effects of an individual's human capital on the persons own productivity) and external effects (the contribution to the productivity of all factors of production by the average level of skill or human capital). The primary, secondary and tertiary school attainment rates are adopted to approximate the accumulation of human capital in a country. The hypothesis of human capital is outlined below. H13: Greater level of human capital will contribute to host country productivity, which could enhance more FDI. Domestic investment as a ratio to GDP is used to proxy for domestic capital. It represents physical capital intensity in the form of fixed capital formation and the availability of domestic funds in the host country. There is some disagreement in the literature on the expected relationship between foreign and domestic forms of capital. On the one hand, FDI and domestic capital might be complements in the production process (see Clegg and Scott-Green, 1999, Naudé and Krugell, 2007, Obwona, 2001). On the other hand, these two types of capital might be substitutes. Cohen (1993), Papanek (1973) and Reinhart and Talvi (1998) all argue that FDI may displace domestic savings. A reduction in domestic savings could lead to further increase on the dependency on foreign capital. From the argument, this study formulates the following hypothesis. H14: The host country with higher domestic capital intensity will draw more attention from multinational firms. The availability of infrastructure in the host country is considered by many scholars as a necessary facility to attract FDI inflows. Well-developed infrastructure facilitates the production process and the distribution of the produced goods. It increases the productivity of investments, and reduces operating costs (Asiedu and Lien, 2004, Vogiatzoglou, 2007, Wheeler and Mody, 1992). This paper uses the number of telephone mainlines per 100 people as a proxy to measure infrastructure development. This leads to the following hypothesis. H15: The availability of infrastructure in the production process enhances a country's ability to draw more FDI inflows. 3.2.2. Measure of host country policies Three variables relating to government policies are included in the FDI model: real exchange rate, trade to GDP and interest rate. The real exchange rate may play an important role in the attractiveness to FDI inflows through economic policy and international competitiveness. The impact of real exchange rate on FDI inflows may depend on the type of FDI. Ramirez (2006) argues that if foreign affiliates have a strong export orientation in any particular sector, ceteris paribus, a real depreciation of the domestic currency should increase the profitability of foreign firms and attract more FDI flows. In contrast, a real depreciation of the domestic currency reduces the value of profits and dividends back to the parent company. Hence, the rate of return on the initial investment is decreasing. The above argument leads to the following hypothesis. H16: A depreciation of the domestic currency could be an incentive for foreign firms. The ratio of trade to GDP is often used as a measure of the degree of openness of an economy. Asiedu (2002) argues that the impact of openness on FDI depends on the type of FDI. If the foreign firm is a market-seeking FDI, trade restrictions can bring more FDI inflows. On the other hand, foreign firms in export-oriented investment may prefer to locate in a more open economy since increased imperfections that accompany trade protection generally imply higher transaction costs associated with exporting. This consideration may lead to the formulation of the following hypothesis. H17: If the foreign firm has a strong export orientation, trade openness can influence foreign firms to set up subsidiaries in the host country.

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In general, the real interest rate represents the rate of return on investment. Other things being equal, FDI may move toward areas where average profit rates are higher. Therefore, the different expected rate of return on investment between host and home countries should impact the amount of FDI inflows. The interest rate could also represent the cost of borrowing in the home and host countries, which may affect FDI inflows (Aliber, 1970). H18: The flow of foreign investment is influenced by a higher interest rate and higher marginal productivity of capital. 3.2.3. Measure of host country institutions Two institutional variables are included in the regressions: the average of political rights and civil liberties and economic freedom. These institutional indicators are likely to be determinants of FDI inflows. They can be considered as indicators that reflect the investment atmosphere in the host country. Coase (1937) and Estrin et al. (1997) find that inefficiencies in developing economies led to substantial extra costs and delays of conducting business. Political rights and civil liberties capture a vector of institutional and political factors in the host country. Several studies of FDI stress the importance of institutions. Bevan and Estrin (2004) and Lensink and Morrissey (2006) find that higher levels of democracy increase foreign and domestic investment because democracy provides checks and balances on the executive and strengthens the rule of law, thus reducing the potential for arbitrary government intervention in the affairs of investing firms (Henisz, 2000, Jakobsen and de Soysa, 2006, Olson, 1993). Many measures of democracy are proxies of political rights. Easterly (1999) includes government reputation, expropriation, corruption, rule of law and bureaucratic quality, which represent different measures of democracy. The above arguments may lead to the following hypothesis. H19: The political rights and civil liberties have a positive relationship with a country's ability to attract FDI inflows. The degree of economic freedom might be an important aspect of locational advantages to influence FDI inflows. Balasubramanyam et al. (2002) take the economic freedom index into account in order to investigate market-friendly locations. This leads to the following hypothesis. H20: The degree of economic freedom could exert a significant positive influence on the magnitude of FDI inflows.

4. Data and estimation method The empirical estimation uses panel data for 124 countries spanning the period 1971 to 2010. The selection of countries, variables and time periods in the econometric models is based purely on data availability. All variables are averaged over five-year periods, as is standard practice. The descriptive statistics of the variables and sources of data used in the analysis are presented in Appendix I. In testing the relationship among economic growth, FDI and other explanatory variables, Eqs. 1 and 2 are initially estimated using ordinary least squares (OLS) of pooled cross-country data with country and time period fixed-effects. Results from these estimations are reported in Appendices II and III. They can be validly questioned due to concerns over the potential endogeneity and simultaneity of the FDI and growth variables in the extant theoretical and empirical discussions. The Durbin–Wu–Hausman (DWH) endogeneity test indicates that the OLS estimator is inconsistent with the presence of endogeneity. This means that using a single equation in cross-country regression models may produce inconsistent results. In response to these concerns, the simultaneous system of equations approach was adopted and associated with instrumental variables estimation. The specification of the econometric model is that the two sets of equations (FDI and growth models) are estimated jointly through the system of equations technique. In the literature, four system estimators have been employed in the relevant empirical literature: seemingly unrelated regression (SUR), two-stage least squares (2SLS), three-stage least squares (3SLS) and generalized methods of moments (GMM). The 3SLS method is preferred over other estimators as it takes into account the cross-correlation equations and thus improves the large sample efficiency. As a result, the estimates have smaller asymptotic variance-covariance matrix than single-equation estimators. That means 3SLS addresses not only any endogeneity and simultaneity problems but also any correlation between the error terms of the system of equations. If heteroskedasticity is not an issue, results from both 3SLS and GMM estimations are qualitatively similar.6 The instrumental variable technique is a general estimation procedure applicable to situations in which the independent variable is not independent of the disturbances. If appropriate instrumental variables can be found for the endogenous variables that appear as regressors in the simultaneous equation, the instrumental variable technique provides consistent estimates. Usually, exogenous variables and lagged exogenous variables in the system of simultaneous equations are considered best candidates since they are correlated with the endogenous variables through the interaction of the simultaneous system and are uncorrelated with the disturbances. The most common test of the validity of instruments is the Sargan test for overidentifying restrictions (Sargan, 1958), which assesses the contemporaneous correlation between the set of instruments and the residuals. The Sargan test shows the appropriateness of the instruments used, and is employed in this paper in order to test the validity of instruments.

6

The GMM estimation results are available upon request.

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In the simultaneous system of equations approach, FDI, income growth and openness to trade are considered as endogenous variables. There are a number of instrumental variable combinations applied in the estimation.7 The set of instrumental variables that is validated by the overidentifying restrictions test included a one-period lag of the endogenous variables and some explanatory variables: initial level of income, domestic investment to GDP ratio, inflation rate, financial market, economic freedom, secondary schooling, tertiary schooling, telephone lines, interest rate and political rights and civil liberties. All other explanatory variables were used as instruments, but they were not lagged, assuming that they are exogenous.8 Since there is a strong possibility that independent variables in both growth and FDI models are highly correlated, the issue of multicollinearity among independent variables is investigated by estimating a benchmark model consisting only of core explanatory variables. Then, educational variables, interactive terms, trade and government expenditure are added into the benchmark model one at a time. The results hold when the multicollinearity issue is tested. The empirical results associated with the correlation matrix in Appendices V and VI indicate that FDI coefficients remain statistically significant. Thus, there is no multicollinearity issue among these variables. However, a high correlation between FDI and interacted variables is unavoidable. In addition, the sensitivity of FDI to economic growth is explored across country groups. This model is estimated for the full sample of countries, as well as in five sub-samples: Africa and the Middle East, North America and Western Europe, Asia and Australasia, Latin America and the Caribbean and developing countries.9 From the perspective of efficiency, country group effects can be investigated alternatively by using dummy variables together with corresponding interaction dummy variables. The aim of this analysis is simply to check the robustness of the results, rather than to identify structural differences across geographical areas. The paper only presents results from general-to-specific models, which include only those variables that remain statistically significant after a general-to-specific modeling strategy was implemented. The most insignificant variable is dropped out at a time.10 The models with only significant variables11 remaining are called specific models. In order to justify the removal of an explanatory variable from the general model, the Wald test was conducted. The general-to-specific modeling strategy results in a parsimonious model, and it also economizes on degrees of freedom. As they are the main variables of interest, these variables were retained in the equations even when they were not statistically significant. 5. Empirical results Results from the system of equations estimation are shown in Table 1. The key results in column (1) of Table 1 indicate that, on average, FDI is positively correlated with economic growth and vice versa. These findings suggest a bi-directional relationship between FDI and growth. Hence, host country growth can determine and be determined by FDI as expected. The direct effects of FDI (C1), other growth drivers (C2), and the interaction effects between FDI and human capital variables (C3) are the estimates of growth equation. The estimates of FDI equation are shown in the potential effects, which capture the joint impact of growth (C4) and other domestic endowments (C5) on FDI inflows. These effects eventually influence economic growth. The potential effects are estimated from integration between the coefficients of FDI determinants and the direct effects of FDI on growth.12 According to the simultaneous system of equations framework, it enables the teasing out of the potential effects, as well as total effects of variables on growth. The total effects of variables on growth are the sum of the direct and the potential effects.13 Table 2 summarizes the direct effects, potential effects and total effects on growth in columns (1), (2) and (3), respectively. The direct effects of FDI (C1) indicate that FDI has a positive and strong statistically significant effect on economic growth as expected. This finding lends additional empirical support to the endogenous growth theory. These effects are of significance to be compared with the results from OLS estimation in column (4). While results from both OLS and 3SLS estimations support the hypothesis, the magnitude of the growth effect of FDI from OLS estimation is approximately three percent of the effect from 3SLS estimation (+ 3.13). This result strongly suggests that the single equation framework may significantly understate the magnitude of the impacts of FDI on host country growth. The other economic growth determinants are also estimated in the empirical investigation of FDI–growth association. While some factors could motivate growth directly (C2), some could potentially affect growth through FDI (C5). In column (3) of Table 2, per capita

7 This paper explores the sensitivity of the results to the use of two different sets of instruments in 3SLS estimations to ensure that the results are robust with respect to the choice of method. 8 Note that where FDI is interacted with one of the human capital variables, the interaction variable is also treated as an endogenous variable and is also instrumented by its lagged value. 9 The empirical results from the single equation regression analysis only present in the full sample of countries in order to illustrate the endogeneity and simultaneity issues. 10 The most insignificant variable is the variable that contains largest p-value. 11 Significant variables are variables that have p-value smaller than 0.10. 12 For example, the coefficient of FDI on growth in the full sample of countries is positive (+3.13), domestic investment to GDP has a negative correlation to FDI inflows (−0.18). The potential effect of domestic investment on growth (−0.56) is calculated from the coefficient of FDI multiplied by the coefficient of domestic investment. 13 In general, the total effect is calculated from the sum of the direct and the indirect effects. However, the total effects in this paper are slightly different. They are the sum of the direct and the potential effects.

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Table 1 System of simultaneous equations using three-stage least squares (3SLS), 1971–2010. Dependent Variable Equation: Growth of GDP per capita Constant FDI inflows/GDP

All Countries (1)

Africa and the Middle East (2)

Asia and Australasia (3)

Latin America and the Caribbean (4)

North America and Western Europe (5)

Developing countries

0.63 (0.40) 3.13* (2.78)

−6.26* (−2.94) −0.10 (−0.82)

8.67 (1.10) −0.18 (−1.10) −2.78* (−3.29)

36.51* (2.37) −2.45* (−3.62) −4.84* (−2.86) −0.44* (−3.46) 0.17* (3.68)

31.87* (3.62) 0.49* (3.93) −3.67* (−3.90)

1.86 (0.67) 4.11* (2.95)

0.02* (1.94)

−0.05* (−1.86)

0.08* (2.19)

−0.17* (−2.38) −0.05* (−2.67) −0.04* (−2.72) −0.03* (−2.92) 0.17* (10.40)

Log (initial GDP/cap) Labor growth Primary attainment −0.13* (−4.21)

Secondary attainment

0.10* (2.72)

Tertiary attainment FDI/GDP × primary FDI/GDP × secondary FDI/GDP × tertiary Domestic investment/GDP

−0.03* (−2.28) −0.03* (−2.44) −0.03* (−2.87) 0.19* (14.43)

0.15* (8.15)

0.17* (5.33)

Trade/GDP Government expenditure/GDP Credit in private sector Economic freedom Sargan test

Equation: Ratio of FDI inflows to GDP Constant Growth GDP per capita Log (labor force) Primary attainment

−0.01* (−3.10) 0.61* (3.13) 9.08 (0.17)

−42.92* (−2.88) 0.79* (6.85) 2.59* (2.39) −0.03* (−1.95)

Log (telephone lines)

−56.55* (−2.43) −0.35* (−3.81) 4.14* (2.57)

−0.09* (−2.72)

Secondary attainment Domestic investment/GDP

7.52 (0.18)

−0.18* (−6.93) −1.24* (−4.64)

−2.40* (−5.35)

0.05* (4.07) 0.05* (2.46) 0.09* (4.10) 0.09* (2.77) −0.28* (−3.22)

1.79* (4.30) 14.30 (0.27)

6.30 (0.18)

1.43 (0.92)

−0.03* (−3.88) 1.04* (3.75) 10.31 (0.67)

−10.13* (−2.77) −0.33* (−2.38)

3.97 (0.99) 0.21* (2.14)

−25.23* (−2.13) 0.87* (2.49)

−7.25* (−2.74) 0.08 (1.26)

−0.13* (−2.92) −0.13* (−2.26)

−0.16* (−2.76) −0.13* (−2.48) −0.40* (−4.35)

−0.03* (−1.81)

0.08* (2.03) 0.11* (2.88) −0.53* (−1.72)

−1.56* (−5.48)

Log (exchange rate) Trade/GDP Economic freedom No. of observations Wald test Sargan test

0.10* (7.15) 0.42* (1.80) 489 0.93 2.21 (0.82)

155 0.22 12.12 (0.65)

−0.01* (−2.60) 0.24* (11.73) 0.03* (1.91)

0.04* (3.05) 0.96* (2.23) 82 0.83 8.17 (0.23)

1.44* (4.28) 100 0.23 3.00 (0.81)

4.89* (1.97) 0.16* (5.09) 1.07* (1.75) 113 0.25 8.08 (0.23)

0.07* (4.88) 0.69* (3.20) 349 0.66 5.73 (0.45)

* denotes statistically significant difference from zero at 90% or greater confidence level; t-statistics in parentheses. Using heteroskedasticity robust standard errors. Sargan test (chi-square test statistic in parentheses χ2z−k where z is the number of instruments. and k is the number of right-hand side variables). Instrumental variables: FDI to GDP ratio, growth GDP per capita, trade to GDP ratio, initial. GDP per capita, domestic investment to GDP ratio, inflation rate, credit in private sector, economic freedom, secondary attainment, tertiary. attainment, telephone lines, interest rate, political rights and civil liberties are instrumented using the corresponding one-period lagged value.

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Table 2 Direct, potential, and total effects on growth, full sample of countries, 1971–2010. Variables FDI inflows/GDP Growth Log (initial GDP/cap) Labor growth Log (labor force) Primary attainment Secondary attainment Tertiary attainment FDI/GDP × primary attainment FDI/GDP × secondary attainment FDI/GDP × tertiary attainment Domestic investment/GDP Trade/GDP Government expenditure/GDP Inflation rate Real interest rate Credit in private sector Political rights and civil liberties Economic freedom Log (telephone lines) Log (exchange rate)

Direct effects (1)

Potential effects† (2)

Total effects (3)

Single growth equation from Appendix II (4)

+3.13* n/a 0 0 n/a 0 0 0 −0.03* −0.03* −0.03* +0.19* 0 0 0 n/a −0.01* n/a +0.61* n/a n/a

n/a +2.47* n/a n/a +8.11* −0.09* 0 0 n/a n/a n/a −0.56* +0.31* n/a n/a 0 n/a 0 +1.31* −3.88* 0

+3.13* +2.47* 0 0 +8.11* −0.09* 0 0 −0.03* −0.03* −0.03* −0.37* +0.31* 0 0 0 −0.01* 0 +1.92* −3.88* 0

+0.10* 0 −2.09* 0 n/a 0 −0.03* 0 0 0 0 +0.14* +0.03* −0.12* −0.002* n/a −0.01* n/a +0.92* n/a n/a

† standard errors for potential effects calculated using the Delta method. ⁎ denotes statistically significant difference from zero at 90% or greater confidence level.

economic growth, on average, appears to have been driven by openness to trade, labor force and economic freedom. These factors all exert a positive effect on growth. Trade openness is included as an explanatory variable in both growth and FDI equations. In general, even though the results from 3SLS estimation suggest that economic growth is not generated directly by trade to GDP, trade does nevertheless enhance growth through FDI inflows (+0.31). This means a higher degree of openness to trade leads to a larger FDI inflows and, consequently, it has a positive effect on economic growth. This result implies that most foreign firms are export-oriented investment as they prefer to locate in an open economy and distribute their products across region. Similar results are found in the labor force. It could potentially stimulate income growth through FDI. Interesting results also found that economic freedom has positive direct and potential effects on growth. This means that they reinforce each other. From the empirical findings, economic freedom emerges as one of the main growth and FDI determinants. These results are consistent with the hypotheses, which imply that the quality of institutions plays a crucial role in enhancing economic growth directly and through FDI inflows. A surprising finding is a negative effect of domestic investment on growth. While domestic investment could influence economic growth directly as expected (+0.19), the total effect of domestic investment is negatively correlated with economic growth (−0.37). This is due to the negative correlation between domestic investment and FDI inflows. Hence, on average, these two types of capital are substitutes. This is different from the hypothesis and some empirical findings. However, it is consistent with Bornschier's notion that FDI might compete against domestic investment. Cohen (1993), Papanek (1973) and Reinhart and Talvi (1998) all argue that FDI may displace domestic savings. A reduction in domestic savings could lead to further increase on the dependency on foreign capital. In addition, the effect of FDI on growth is larger than domestic investment. These results suggest that there is relatively more incentive to attract FDI, on average, than there is to expand domestic investment.14 Turning to the interactive variables between FDI and human capital indicators (C3), they are all negatively correlated with economic growth. These findings contradict some theories and the arguments advanced by Balasubramanyam et al. (1999), Borensztein et al. (1998), Jalilian and Weiss (2002) and Li and Liu (2005) that human capital is an important precondition for positive effects of FDI. Their findings are not supported when simultaneity is modeled in lieu of a comprehensive literature survey, country and time fixed-effects associated with a longer time period and a larger sample of countries. This suggests that all educations are substitutes with FDI inflows in the production process. The estimate of the potential effects of growth on FDI (C4) is positive and statistically significant as expected. It indicates that economic growth is a determinant of FDI inflows as it reflects the possibility of making profits through the realization of economies of scale from a larger size of economy. The other key determinants of FDI (C5) are consistent from both OLS and 3SLS estimations. As discussed above, FDI is attracted to host countries that have higher levels of labor force, openness to trade and economic freedom. However, there is also a pattern of substitution effect of human capital, physical investment and infrastructure on foreign investment. The negative correlation

14

If there are diminishing returns from capital, then this finding is consistent with the fact that domestic investment is a greater share of GDP than is FDI.

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between primary schooling and FDI inflows suggest that a basic level of human capital in the host country is not a prerequisite to attract foreign investment. Indeed, it rather tends to reduce foreign investment. This result adds support to the findings from the growth equation where interactions between FDI and human capital indicators have negative associations with growth. Two conclusions can be drawn: (1) human capital does not stimulate FDI inflows and (2) it is not an important channel from which host countries can absorb any positive externalities that might arise from foreign investment to stimulate economic growth. The coefficient attached to the level of infrastructure is negatively correlated with FDI inflows. It implies that the higher the level of infrastructure, the less FDI inflows is attracted. This finding may result from the country-specific effects since a negative coefficient is indicated in models with country fixed-effects. The level of infrastructure has no effect on FDI inflows when country fixed-effects are excluded from the model. The effect of infrastructure in a host country on FDI inflows might also be captured by domestic investment variables. The results presented in this analysis have some clear and important policy implications. They are consistently in favor of significant gains to a host country from attracting FDI. The existence of a virtuous cycle suggests that FDI contributes to economic growth and growth attracts FDI inflows, which in turn stimulates growth further. The host country's policymakers should focus their efforts on achieving growth which will result in higher FDI inflows. In addition, their efforts on openness to trade and economic freedom would be very crucial. In other words, the results suggest that it is not only the direct growth experience per se that matters for foreign investors, but also an abundant supply of labor, high level of trade openness and friendly investment climate.

5.1. A comparison among groups of countries It is of significant interest to examine the associations between FDI and growth across regions. Countries are categorized into the following regions: Africa and the Middle East, Asia and Australasia, Latin America and the Caribbean, North America and Western Europe, and developing countries. The results of North American and Western European countries can be taken to represent the effects of FDI in developed countries. Even though both developed and developing countries receive a positive impact on growth from FDI, the coefficient attached to FDI inflows is larger in developing countries (+ 4.11) compared to developed countries (+0.49). Government policy is a main factor that leads to a larger magnitude of FDI. Foreign investment in most developing countries aims not only to produce for the local market. Balasubramanyam et al. (1996) and Bhagwati (1978) argue that FDI is more likely to stimulate economic growth in those countries pursuing export-promoting policies. Hence, foreign firms may well contribute to appropriate specialization and utilization of abundant resources in the host country. The effect disappears when the relationship is investigated in the African and the Middle East and in the Asian and Australasian samples. FDI could have no effect on growth due to inadequate absorptive capability and host country characteristics. Some empirical studies by Akinlo (2004), Balasubramanyam et al. (1996), Benhabib and Spiegel (1994), and Nelson and Phelps (1966) highlight that FDI contributes to economic growth in countries with sufficient absorptive capability as well as an open trade and investment regime and macroeconomic stability. Furthermore, FDI is mainly directed into the primary sectors in some countries. Thus, the benefits of advanced technology would be in the form of lower prices of output rather than positive technology spillovers, which is the main channel of long-run economic growth.15 A negative correlation between FDI and economic growth is found in Latin America and the Caribbean. As mentioned in Section 2, an adverse effect of FDI on growth can be explained by the intervening mechanisms of dependence and decapitalization. A case study from Bornschier (1980) suggests that more than half of the largest industrial enterprises are foreign-controlled and foreign subsidiaries, which tend to predominate in the high extractive industries. High industrial concentration is likely to result in monopolization and extra profits. However, the profits from foreign investment may also have been repatriated overseas rather than re-invested in the host country. Bornschier (1980) and Firebaugh (1992) conclude that the combination of diminishing investment opportunities, possibly growing social and political tension, and possible respective government interventions could lead to capital flight thus adding to decapitalization. The main driver of economic growth in all sub-samples is domestic capital. The size of the coefficient is fairly similar, except a relatively lower effect of domestic capital on growth in Latin America and the Caribbean. Results in Table 1 also suggest that economic freedom is a growth determinant in Asia and Australasia and developing countries. While economic freedom has both direct and potential effects on growth in developing countries, it has no direct effect on growth in the case of North America and Western Europe, economic freedom potentially influences growth through FDI inflows. Given the contributions of FDI to growth, it is important to identify the factors that attract FDI. The results from 3SLS estimation suggest that economic growth is an important determinant of FDI inflows to Latin America and the Caribbean and North America and Western Europe. The positive effect of growth on FDI suggests that higher economic growth in a host country could attract more FDI inflows in these regions. A negative correlation on growth–FDI association is found in Africa and the Middle East and Asia and Australasia. There are a few explanations from empirical studies. Jensen (2003) and Tsai (1994) explain these results as a scaling effect; economies that grow at a faster rate than the growth in FDI experience a decrease in FDI as a percentage of GDP. In addition, domestic growth might not be the main determinants of export-oriented and extractive FDI. Torrisi (1985) and Zhang (2001) argue that export-oriented FDI is motivated by factor–price differentials, such as labor cost and transportation cost from host countries to other countries in the region.

15

Lower prices obviously benefit host country consumers and increase their real incomes. However, Singer (1950, 1975) suggests that this will not stimulate growth.

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In summary, the results indicate that higher levels of FDI are associated with higher growth rates. These empirical results suggest a bi-directional relationship between FDI and growth. Per capita economic growth in the full sample of countries appears to have been enhanced by FDI, labor force, openness to trade and economic freedom.

6. Summary and conclusions This paper investigates the linkage between FDI inflows and per capita income growth by using simultaneous system of equations approach of 124 cross-country data for the period 1971–2010. In so doing, it sought to offset a significant gap in the literature on the associations between FDI and economic growth, which may significantly miss depicting these dynamic relationships accurately. The results indicate that FDI is associated with higher rates of economic growth and vice versa. They are consistently in favor of significant gains to a host country from attracting FDI. The existence of a virtuous cycle suggests that FDI contributes to economic growth and growth attracts FDI inflows, which in turn stimulates growth further. This is a useful finding to the extent that it justifies the importance of foreign investment flows and the efforts that ought to be taken to achieve higher levels of FDI. The results presented in this analysis have some clear and important policy implications. The host country's policymakers should endeavor to accelerate the country's economic growth which will result in higher FDI inflows. The investment authority should also ensure that the flow of FDI is stimulated into the country stability as it could influence economic growth and stabilize economic growth from the impact of significant swings. The policy on attracting FDI aims to enhance host country growth as well as to minimize the volatility of economic growth. In addition, the number of labor force, openness to trade and economic freedom are other key determinants of FDI. In other words, the results suggest that it is not only the direct growth experience per se that matters for foreign investors, but also domestic endowments, trade restrictions and friendly investment climate. Due to the dynamic relationships between FDI and economic growth, these elements will influence FDI into the country and potentially stimulate economic growth through FDI inflows. Hence, the government must generate and maintain the availability of labor force, good macroeconomic environment and diminish trade barriers. These are essential elements for a country to be competitive in attracting and maintaining FDI inflows for future development. These policies appear to make important contributions to FDI inflows and per capita income growth.

Appendix I. Descriptions, data sources, and descriptive statistics of variables Variable

Description

Data Source

Growth GDP/cap FDI inflows/GDP Log Initial GDP/cap Labor force growth Primary attainment Secondary attainment Tertiary attainment FDI × primary attainment

WDI (2013) WDI (2013) WDI (2013) WDI (2013) Barro and Lee (2010) Barro and Lee (2010) Barro and Lee (2010) WDI (2013) and Barro and Lee (2010) WDI (2013) and Barro and Lee (2010) WDI (2013) and Barro and Lee (2010) WDI (2013) WDI (2013)

Political rights and civil liberties

Growth of GDP per capita (%) FDI inflows as a percentage of host country GDP Log level of GDP per capita (constant US$) Growth of labor force (%) Primary school attainment Secondary school attainment Tertiary school attainment The interaction between FDI inflows to GDP and primary school attainment The interaction between FDI inflows to GDP and secondary school attainment The interaction between FDI inflows to GDP and tertiary school attainment Gross domestic investment as a percentage of GDP Trade is the sum of exports and imports of goods and services measured as a percentage of GDP General government final consumption expenditure on goods and services as a percentage of GDP Inflation rate in the GDP deflator (%) Domestic credit to the private sector as a percentage of GDP Log number of labor force Log telephone mainlines per 100 capita Log average of the exchange rate between the local currency and one US dollar. Real effective exchange rate is the nominal effective exchange rate (a measure of the value of a currency against a weighted average of several foreign currencies) divided by a price deflator or index of costs Real interest rate (%) is the lending interest rate adjusted for inflation as measured by the GDP deflator The average index of political rights and civil liberties

Economic freedom

Economic freedom index

FDI × secondary attainment FDI × tertiary attainment Domestic investment/GDP Trade/GDP Government expenditure/GDP Inflation rate Credit in the private sector Log labor force Log telephone lines Log exchange rate

Real interest rate

Mean

S.D.

1.93 3.15 7.71 2.21 32.83 35.22 8.63 73.47

4.04 6.12 1.60 2.00 17.14 19.85 8.56 117.76

106.99

179.82

27.55

56.72

7.81 81.29

10.48 48.49

WDI (2013)

16.66

6.91

WDI (2013) WDI (2013) WDI (2013) WDI (2013) WDI (2013)

31.99 39.42 14.78 1.55 3.63

191.92 36.84 1.82 1.86 3.25

WDI (2013)

6.51

20.45

Freedom House (2013) (available yearly from 1972 to 2010) The Fraser Institute (2013) (available in five-yearly intervals between 1970 and 2000, and annually afterwards)

3.80

2.02

6.07

1.29

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Appendix II. Regression analysis of determinants of economic growth using OLS with two-way fixed-effects, full sample of countries between 1971 and 2010 (five-year averages)

Dependent Variable

General

Specific

13.78 (4.03) 0.04 (0.17) −2.03* (−4.34) 0.04 (0.50) −0.02 (−1.55) −0.04* (−2.87) −0.02 (−0.61) 0.0004 (0.12) 0.001 (0.40) −0.005 (−1.20) 0.14 (12.74) 0.03* (4.66) −0.13* (−4.13) −0.002* (−4.24) −0.01* (−2.45) 0.97* (7.40) 724 124 0.49

13.05* (4.13) 0.10* (1.86) −2.09* (−4.68)

Equation: Growth of GDP per capita Constant FDI inflows/GDP Log (Initial GDP/cap) Labor growth Primary attainment Secondary attainment Tertiary attainment FDI/GDP × primary FDI/GDP × secondary FDI/GDP × tertiary Domestic investment/GDP Trade/GDP Government expenditure/GDP Inflation rate Credit in the private sector Economic freedom No. of observations No. of country Adj R-squared

* denotes statistically significant difference from zero at 90% or greater confidence level. t-statistics in parentheses. Shaded cells highlight robust relationships.

−0.03* (−2.31)

0.14* (13.04) 0.03* (4.80) −0.12* (−3.94) −0.002* (−4.27) −0.01* (−2.80) 0.92* (7.48) 728 124 0.49

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129

Appendix III. Regression analysis of determinants of foreign direct investment using OLS with two-way fixed-effects, full sample of countries between 1971 and 2010 (five-year averages)

Dependent Variable

General

Specific

−42.41 (−4.03) 0.02 (0.38) 2.54* (3.34) −0.05* (−2.27) −0.03 (−1.31) 0.01 (0.12) −0.005 (−0.36) −0.75* (−2.84) −0.03 (−0.18) 0.06* (8.44) −0.01 (−1.10) −0.14 (−1.09) 1.02* (6.27) 550 116 0.43

−45.39* (−6.20) 0.05 (1.56) 2.79* (5.47) −0.04* (−3.85)

Equation: ratio of FDI inflows to GDP Constant Growth GDP/cap Log (labor force) Primary attainment Secondary attainment Tertiary attainment Domestic investment/GDP Log (telephone lines) Log (exchange rate) Trade/GDP Real interest rate Political rights and civil liberties Economic freedom No. of observations No. of country Adj R-squared

* denotes statistically significant difference from zero at 90% or greater confidence level. t-statistics in parentheses. Shaded cells highlight robust relationships.

−0.83* (−4.18)

0.04* (7.38)

0.77* (5.79) 774 125 0.34

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Appendix IV. Regional grouping of countries

Latin America and the Caribbean

Asia and Australasia

Africa and the Middle East

North America and Western Europe

Argentina Belize Bolivia Brazil Chile Colombia Costa Rica Dominica Dominican Rep. Ecuador El Salvador Grenada Guatemala Guyana Haiti Honduras Jamaica Mexico Panama Paraguay Peru Trinidad and Tobago Uruguay Venezuela

Australia Bangladesh China Fiji India Indonesia Japan Korea Rep. Malaysia Nepal New Zealand Pakistan Papua New Guinea The Philippines Singapore Sri Lanka Thailand Vietnam

Algeria Benin Botswana Burundi Cameroon Central African Rep. Congo Rep. Cyprus Egypt Ghana Iran Israel Jordan Kenya Lesotho Malawi Mali Mauritius Morocco Namibia Niger Rwanda Senegal Sierra Leone South Africa Syrian Arab Rep. Tanzania Togo Tunisia Uganda Zambia Zimbabwe

Belgium Canada Denmark Finland France Germany Greece Iceland Ireland Italy The Netherlands Norway Portugal Spain Sweden Switzerland United Kingdom United States

Appendix V. Regression analysis on the sensitivity of human capital, FDI and human capital interactions, trade and government expenditure as economic growth determinants

Dependent variable

Primary

Secondary

Tertiary

FDI* Primary

FDI* Secondary

FDI* Tertiary

Trade

Gov

Equation: Growth of GDP per capita (OLS) Constant 13.78 11.74* (4.03) (3.80) FDI inflows/GDP 0.04 0.12* (0.17) (3.31)

Full model

Benchmark

11.60* (3.47) 0.12* (3.24)

10.60* (3.34) 0.12* (3.28)

12.11* (3.72) 0.12* (3.21)

12.13* (3.95) 0.09 (1.43)

12.33* (3.98) 0.13 (1.28)

11.86* (3.87) 0.16* (2.89)

13.89* (4.53) 0.07* (1.80)

13.03* (4.24) 0.10* (2.72)

Equation: Growth of GDP per capita (3SLS) Constant 2.80 14.59* (0.34) (4.01) FDI inflows/GDP 6.35* 0.47* (3.19) (4.19)

14.42* (3.73) 0.47* (4.05)

14.93* (4.02) 0.46* (4.15)

13.40* (3.47) 0.47* (4.25)

15.42* (3.92) 0.45* (2.77)

13.93* (3.85) 0.29* (2.16)

9.69* (2.40) 0.58* (3.90)

15.29* (4.35) 0.28* (2.29)

15.37* (4.25) 0.46* (4.14)

Notes: * denotes statistically significant difference from zero at 90% or greater confidence level; t-statistics in parentheses. Only the estimates of FDI variable are reported. All regressions include core explanatory variables from a benchmark model: initial income per capita, labor growth, domestic investment to GDP ratio, inflation rate, credit in the private sector and economic freedom. The estimates of full model using OLS and 3SLS are obtained from Appendix II and column (1) of Table 1, respectively.

Appendix VI. Correlation matrix Growth

Initial GDP/ cap

Labor Growth

Primary

Secondary

Tertiary

FDI* Primary

FDI* Secondary

FDI* Tertiary

Investment

Trade

Government

1.00 0.07 −0.10 −0.05 −0.24

1.00 0.11 −0.04 0.15

1.00 −0.04 0.27

1.00 0.25 0.14

1.00 0.23

1.00

−0.14

−0.09

−0.31

−0.09 0.32 0.15 0.21 0.25

−0.12 −0.22 0.24 0.32 0.59 −0.41 0.16 0.63 −0.25 0.81 0.09 0.03 0.94 0.27 −0.19

1.00 −0.57 −0.47 0.29 −0.29

1.00 0.43 0.01 0.50

1.00 −0.05 0.21

1.00 0.60

1.00

0.16 0.42 0.20 −0.06 −0.12 0.08

0.82 0.37 −0.13 0.06 −0.25 0.11 0.62 0.20 −0.01 0.10 0.40 −0.19 −0.04 −0.05 0.02 0.24 0.68 −0.23

−0.30 0.09 −0.02 −0.18 0.02 −0.28

0.33 −0.03 0.25 0.32 −0.03 0.38

0.51 −0.16 −0.01 0.24 −0.02 0.55

0.50 0.13 0.58 −0.03 −0.03 0.10

0.80 0.03 0.56 0.16 −0.04 0.25

−0.25

−0.21

0.51

0.55

0.30

0.40

0.15 0.28 −0.15

−0.20 −0.04 −0.14 0.31 0.91 −0.38 0.01 0.02 −0.03

−0.17 −0.23 0.01

0.01 0.69 −0.10

0.25 0.64 0.09

−0.24 0.16 0.05

−0.17 0.37 −0.01

−0.06 0.42 0.03

−0.11 −0.18 −0.09

−0.42 0.25 −0.02

−0.19 0.39 −0.05

−0.12 −0.18

−0.03 −0.21

0.13 0.16

−0.02 −0.54

−0.10 −0.48

0.03 −0.11

−0.06 −0.27

−0.09 −0.30

0.11 0.14

−0.05 −0.09

−0.04 −0.39

0.32

0.40

0.69

−0.13 −0.74

Inflation Financial market

Economic Freedom

Labor force

Telephone Exchange Interest rate rate

Political rights

1.00

0.10 0.32

1.00 −0.07 0.41 0.16 −0.04 0.40 0.45

−0.08

0.26

0.14

1.00 −0.07 −0.17

1.00 0.60

1.00

−0.03 −0.04 0.05

0.20 0.61 0.09

0.06 0.69 −0.06

−0.29 0.02

−0.13 −0.47

−0.02 −0.63

1.00 0.001 0.13 −0.07 0.13

1.00 −0.03

1.00

−0.09 −0.73

−0.02 0.03

1.00 0.06

1.00

S. Iamsiraroj / International Review of Economics and Finance 42 (2016) 116–133

Growth FDI Initial GDP/ cap Labor Growth Primary Secondary Tertiary FDI* Primary FDI* Secondary FDI* Tertiary Investment Trade Government Inflation Financial market Economic Freedom Labor force Telephone Exchange rate Interest rate Political rights

FDI

131

132

S. Iamsiraroj / International Review of Economics and Finance 42 (2016) 116–133

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