Journal of Policy Modeling 31 (2009) 939–949

Available online at www.sciencedirect.com

Foreign Direct investment, domestic investment, andeconomic growth in Sub-Saharan Africa

Samuel Adams ∗Ghana Institute of Management and Public Administration, P.O. Box AH 50, Achimota, Accra, Ghana

Received 1 October 2008; received in revised form 1 February 2009; accepted 1 March 2009Available online 2 April 2009

Abstract

The study analyzes the impact of foreign direct investment (FDI) and domestic investment (DI) on eco-nomic growth in Sub-Saharan Africa for the period 1990–2003. The results show that DI is positive andsignificantly correlated with economic growth in both the OLS and fixed effects estimation, but FDI is posi-tive and significant only in the OLS estimation. The study also found that FDI has an initial negative effect onDI and subsequent positive effect in later periods for the panel of countries studied. The sign and magnitudeof the current and lagged FDI coefficients suggest a net crowding out effect. The review of the literatureand findings of the study indicate that the continent needs a targeted approach to FDI, increase absorptioncapacity of local firms, and cooperation between government and MNE to promote their mutual benefit.© 2009 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.

JEL classification: E22; O16; N77

Keywords: Foreign direct investment; Domestic investment; Institutional infrastructure and economic growth

1. Introduction

Globalization of capital and especially of foreign direct investment (FDI) has increased dra-matically in the past two decades. In the developing world, FDI has become the most stable andlargest component of capital flows. Consequently, FDI has become an important alternative in thedevelopment finance process (Global Development Finance, 2005). Many reasons have been givenfor the importance of FDI inflows, including employment creation, technological know-how, andenhanced competitiveness (Kobrin, 2005).

∗ Tel.: +233 285173307.E-mail address: sadamss2000@yahoo.com.

0161-8938/$ – see front matter © 2009 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.doi:10.1016/j.jpolmod.2009.03.003

940 S. Adams / Journal of Policy Modeling 31 (2009) 939–949

In light of the expected benefits of FDI, many studies have been conducted to examine theimpact of FDI on growth, but only a few studies have considered the impact of FDI in the context ofSub-Saharan Africa (SSA). This paper fills the void in examining the impact of FDI on economicgrowth in SSA. The paper contributes to the literature on FDI in three main ways. First, the focuson SSA with similar social, economic, and political conditions may help to reduce any bias due tosample selection. Second, many authors have noted that FDI has differential effects and that it hasbeen more productive in some regions than others (Agosin & Mayer, 2000; Kumar & Pradhan,2002; Sylwester, 2005). Kumar and Pradhan (2002) and Sylwester (2005), for example, claim thatFDI is less effective in SSA than in Latin America. The results of these studies, however, cannotbe generalized. For example, the Sylwester (2005) study sample is made up of 29 countries withonly two countries (Tanzania and South Africa) from SSA, and Fry (1993) had only one country(Nigeria) from Sub-Saharan Africa. Consequently, the use of a large data set of 42 Sub-SaharanAfrican countries will help to better explain the impact of FDI on economic growth in SSA.Finally, the study examined the effect of FDI on domestic investment to examine whether FDIcrowds in or crowds out domestic investment.

The rest of the paper is organized as follows: Section 2 discusses the theoretical and empiricalliterature on the relationship between FDI and economic growth. Section 3 describes the data andmeasures used. Section 4 presents the empirical results and discusses the findings. Section 5 offersmanagerial and policy implications, suggestions for future research, and concluding remarks.

2. Literature review

Two main theoretical perspectives have been used to explain the impact of FDI on host coun-tries’ economies. These are the modernization and dependency theories. Modernization theoriesare based on the neoclassical and endogenous growth theories, which suggest that FDI couldpromote economic growth in developing countries. The modernization perspective is based on afundamental principle in economics that economic growth requires capital investment.

From the perspective of the new growth theories, the transfer of technology through FDI indeveloping countries is especially important because most developing countries lack the neces-sary infrastructure in terms of an educated population, liberalized markets, economic and socialstability that are needed for innovation to promote growth (Calvo and Sanchez-Robles, 2002).Kumar and Pradhan (2002) note that, apart from technology and capital, FDI usually flows as abundle of resources, including organizational and managerial skills, marketing know-how, andmarket access through the marketing networks of multinational enterprises (MNEs). As a result,FDI plays a twofold function by contributing to capital accumulation and by increasing total factorproductivity (Nath, 2005).

In contrast to the modernization perspective, dependency theorists argue that dependenceon foreign investment is expected to have a negative effect on growth and the distribution ofincome. Bornschier and Chase-Dunn (1985) claimed that foreign investment creates an industrialstructure in which monopoly is predominant, leading to what they describe as “underutilizationof productive forces.” The assumption being that an economy controlled by foreigners wouldnot develop organically, but would rather grow in a disarticulated manner (Amin, 1974). Thisis because the multiplier effect by which demand in one sector of a country creates demand inanother is weak and thereby leading to stagnant growth in the developing countries. This argumentis important as most FDI to Africa is in the natural resources sectors (Pigato, 2000) which havesubstantial barriers to entry.

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Given the conflicting theoretical views, many empirical studies have examined the relationshipbetween FDI and economic growth in developing countries (Alfaro, Areendam, Kalemli-Ozcan,& Sayek, 2004; Borensztein, De Gregorio, & Lee, 1998; Makki & Somwaru, 2004; Zhang, 2001).Zhang (2001) studied 11 Latin American and Asian countries between 1970 and 1997 and reportedthat FDI was more likely to promote growth in Asia than in Latin America. Further, Zhang (2001)finds that FDI tends to promote economic growth when the host country adopts liberalized tradepolices, improve education, and maintain macroeconomic stability. Similarly, Balasubramanyam,Mohammed and David (1996), in a study of 46 countries from 1970 to 1985 reported that thegrowth enhancing effects of FDI are stronger in countries with highly educated workforce andpursued a policy of export promotion rather than import substitution. Carkovic and Levine (2002),however, claim that the macro-level positive findings of FDI on growth must be viewed withskepticism as most of the studies do not control for simultaneity bias and country-specific effects.

In contrast to the studies that find a positive correlation between FDI and growth, othersfind a non-significant or negative effect (Akinlo, 2004; Ayanwale, 2007; Fry, 1993; Hermes &Lensink, 2003). Hermes and Lensink (2003), in a study of 67 developing countries for the period1970–1995, reported that FDI has a significant negative effect on the host country. The differencesin the results reviewed show the importance of regional and country-specific studies. This studytherefore complements the work of Fry (1993), Agosin and Mayer (2000), and Sylwester (2005)by using a larger set of 42 SSA countries in studying the effect of FDI dependence on economicgrowth. The data and measures used in the empirical investigation are discussed in the next section.

3. Methodology and data

Two basic regressions are analyzed. The first regression deals with the determinants of growthand the second deals with the determinants of domestic investment. The growth equation weestimate is that used by many authors in FDI-growth studies (Borensztein et al., 1998; Kumar& Pradhan, 2002; Makki & Somwaru, 2004; Nath, 2005). We use a panel data set for 42 SSAcountries for the period 1990–2003. We estimate a pooled time-series cross-section regression ofthe form

Y = β0 + β1Xit + β2Zit + μi + εit (1)

where Y is the Real GDP per capita growth rate for country i in year t; β0 is the constant term, βisare the coefficients to be estimated. Xit is a vector of variables including; the stock of human capital(SEC), the degree of openness of the economy (OPEN), gross domestic investment (GDI), andforeign direct investment (FDI). Z is a set of additional variables that are included as determinantsof growth in cross-country growth studies, including government consumption, inflation rate,geographical location, and political risk (a proxy measure for institutional infrastructure). μi

represents the country-specific effect which is assumed to be time invariant, and εit is the classicaldisturbance error component. The fixed effects specification allows us to control for unobservedcountry heterogeneity and the associated omitted variable bias, which seriously afflicts cross-country regressions (Basu & Guariglia, 2004; Prasad, Rajan, & Subramanian, 2006).

Finally, following Islam (1995), a dynamic fixed effects panel data model is specified thattakes into account the correlation between previous and subsequent values of growth, besidesaccounting for separate country effects. The lagged dependent variable helps to capture shortrun autoregressive behavior of the dependent variable. In the second set of regressions, domesticinvestment (DI) is used as the dependent variable and is regressed on the independent variables

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Table 1List of countries.

Angola Cote d’Ivoire Malawia SenegalBenin Equatorial Guinea Malia SeychellesBotswanaa Ethiopiaa Mauritania South AfricaBurkina Fasoa Gabon Mauritius SudanBurundia Gambia Mozambique Swazilanda

Cameroon Ghana Namibia TanzaniaCape Verde Guinea Sierra Leone TogoCentral African Republica Guinea Bissau Nigeria Ugandaa

Chada Kenya Rwandaa Zambiaa

Comoros Lesothoa Sao Tome and Principe Zimbabwea

Congo Rep. Madagascar

a Landlocked country.

used in the growth equation. However, we also include the growth rate variable (Y), the lag ofthe growth rate (Yt−1), lag of FDI (FDIt−1) and the lag of DI (DIt−1) as additional regressors.This is to capture the dynamic relationship between FDI, DI, and economic growth (Agosin &Mayer, 2000; Kumar & Pradhan, 2002). The second regression equation we estimate is specifiedas follows:

DI = β0 + β1Xit + β2Zit + Y + Yt−1 + FDIt−1 + DIt−1 + μi + εit (2)

The β0, βis, Xit, and Zit notations are as explained in the growth equation above.The study employed panel data from 1990 to 2003 to empirically examine the impact of FDI

on economic growth in 42 SSA countries. The study focused on this period because this is theperiod in which most SSA countries received large amounts of FDI inflows, due in part to the largeproceeds generated from privatization in the 1990s (Nellis, 2006). The sample of 42 countriesused in the study is shown in Table 1.

FDI inflows are subtracted from gross fixed investment to calculate domestic investment toprevent double counting (Kumar & Pradhan, 2002; Nath, 2005). Human capital is proxied bythe secondary school enrollment and the trade (exports plus imports) share as a percentage ofGDP) is a proxy for the degree of integration of a country in the world economy. In additionto the explanatory variables discussed, a measure of political risk, which is an indication of thepolitical and institutional infrastructure, is included in the analysis as this might influence howFDI impacts the host country’s economy. The political risk is a composite measure of 12 factorsand it includes factors like law and order, government stability, bureaucratic quality, corruption,and democratic accountability. The geographical location variable is included in the regressionbecause recent growth literature suggests that the direct effects of geographical location explaina large portion of the variance in the income per capita across countries (Acemoglu, Jackson &Robinson, 2003; Redding & Venables, 2004). In this study, a landlocked measure is employed,in which a dummy variable is showing whether or not a country has access to the sea or ocean.The variables, symbols, and sources of data collection are summarized in Table 2.

4. Empirical results

The results of FDI and growth regression are reported in Table 3, which indicates that FDIis positive and significantly correlated with economic growth only in the OLS, but not when thecountry-specific effects are controlled for. The results indicate that the contemporaneous FDI

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Table 2Variables, symbols, and sources of data collection.

Variable Symbol Source of data

FDI share in GDP FDI World Development Indicators (2006): CD ROMDI share in GDP DI World Development Indicators (2006): CD ROMReal GDP growth rate Y World Economic Outlook (2000) and Global

Development Network Growth DatabaseRate of inflation INF World Development Indicators (2006): CD ROMGovernment consumption CONS World Development Indicators (2006): CD ROMTrade share in GDP OPEN Global Development Network Growth DatabasePolitical risk POLRISK International Country Risk Guide (Political Risk

Services Group).Secondary school enrollment SEC Global Development Network Growth DatabaseLandlocked LLOCK http://www.un.org/special-rep/ohrlls/lldc/list.htm

is negatively correlated with economic growth, while lagged FDI is positively correlated witheconomic growth. In both cases, however, the coefficients are not significant. The study’s findingssupport Carkovic and Levine’s (2002) argument that after controlling for country-specific factors,FDI does not have a positive impact on economic growth. The lack of positive effect of FDI maybe due to the low level of the development of financial markets in SSA. On the other hand, it ispossible that the absorptive capacity of most of the countries in the region have not reached thethreshold needed to make use of the technology, knowledge, and other skills associated with FDI.

Domestic investment, however, is positive and significantly correlated with economic growthin both the OLS and fixed effects estimations. A one percent point increase in the domesticinvestment is associated with between 0.16 and 0.19 percentage point increase in per capitaGDP growth rate. Of the macroeconomic variables, inflation is never significant in any of modelspecifications, while the government consumption variable is negative and significantly correlatedwith economic growth in both the OLS and fixed effects estimations. The institutional variableis positive and significantly correlated with economic growth in all model specifications. Thisfinding is consistent with many other studies that show that a country’s economic growth rate isaffected by the quality of its institutions (Makki & Somwaru, 2004; Rodrik, 2006). The landlockedvariable is negative and significantly correlated with economic growth, which provides supportto Bosker and Garretsen’s (2006) study that showed that being landlocked plays a significant rolein explaining world income differences.

4.1. Foreign direct investment and domestic investment

We analyze the effect of FDI on DI controlling for other macroeconomic and institutionalvariables as in the growth regressions and the results are reported in Table 4. The inclusion of thelagged dependent variable (DIt−1) helps to correct the serial correlation as seen in the improvementof the DW (2.02 in the OLS and 1.93 in the fixed effects).

The results indicate that FDI is negative and significantly correlated with domestic investmentin all the model specifications. However, the lagged FDI is positive and significantly correlatedwith domestic investment at 1% level in both the OLS and fixed effects estimations. A one percentincrease in FDI is associated with a decrease in of about 0.51–0.82% in DI in the current periodand one percent increase in FDI from the past year is expected to lead to an increase of about0.26–0.46% in the current year. Taking account of the magnitude and sign of the FDI coefficient,

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Table 3Regression coefficients for the impact of FDI on growth.

OLS FE

1 2 3 4 6 7 8 10

Yt−1 −0.103* (0.054) −0.113** (0.054) −0.187*** (0.069) −0.234*** (0.057) 0.270*** (0.359) −0.218*** (0.055)FDI 0.224** (0.093) 0.256*** (0.097) 0.260*** (0.097) 0.414*** (0.154) 0.107 (0.118) 0.153 (0.127) (0.081) (0.202) 0.155 (0.116)DI 0.183*** (0.041) 0.204*** (0.045) 0.204*** (0.045) 0.223*** (0.065) 0.164*** (0.058) 0.199*** (0.062) 0.127 (0.113) 0.188*** (0.057)LGINF 0.380 (0.568) 0.767 (0.685) 0.536 (0.694) 0.031 (1.050) −1.1664 (1.227) −1.380 (1.817) −1.356 (0.995)CONS −0.120** (0.047) −0.125** (0.049) 0.159*** (0.052) −0.125 (0.052) −0.197** (0.080) −0.192** (0.085) −0.224* (0.115) −0.224*** (0.079)OPEN −0.029*** (0.010) −0.032*** (0.011) −0.026** (0.011) −0.040** (0.015) −0.016 (0.015) −0.020 (0.016) −.095*** (0.035) −0.019 (0.015)POLRISK 0.142*** (0.0255) 0.161*** (0.027) 0.156*** (0.027) 0.188*** (0.040) 0.152*** (0.040) 0.188*** (0.043) 0.262*** (0.061) 0.192*** (0.040)Landlocked −1.119* (0.604)SEC −0.020 (0.019)FDIt−1 0.155 (0.116)Constant −8.427*** (1.762) −10.426*** (2.048) −8.86*** (2.209) −10.597*** (2.861) −5.85* (3.52) −7.725** (4.085) −1.473 (5.948) −6.613* (3.447)DW 2.20 2.05 2.04 1.85 2.44 2.08 2.07 2.08N 346 320 320 166 346 320 166 346R2 adjusted 0.184 0.200 0.20 0.18 0.24 0.28 0.310 0.28

Note: t-Statistics in parentheses.* Significant at the 10% level.

** Significant at the 5% level.*** Significant at the 1% level.

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Table 4Regression coefficients for the impact of FDI on domestic investment.

OLS FE

11 12 13 14 15 16

DIt−1 0.708*** (0.033) 0.736*** (0.034) 0.198*** (0.506) 0.533*** (0.049)FDI −.816*** (0.114) −0.514*** (0.075) −0.720*** (0.078) −0.772*** (0.108) −0.728*** (0.095) −0.748*** (0.093)LGINF 1.595** (0.752) 1.182** (0.571) 0.750 (0.533) −0.015 (0.995) 1.366 (0.986) 1.686* (0.973)CONS 0.121* (0.065) 0.056 (0.043) 0.078** (0.038) 0.085 (0.079) 0.025 (0.069) 0.083 (0.069)OPEN 0.034** (0.014) 0.017* (0.009) 0.013 (0.008) 0.039*** (0.015) 0.016 (0.013) 0.015 (0.013)POLRISK 0.102*** (0.032) 0.030 (0.022) −0.006 (0.022) 0.100** (0.039) 0.094*** (0.034) 0.044 (0.036)Landlocked −0.484 (0.745) −0.012 (0.498)FDIt−1 0.456*** (0.085) 0.264*** (0.099)Y 0.139*** (0.043) 0.135*** (0.047)Yt−1 0.055 (0.042) 0.076 (0.047)Constant 5.989*** (2.506) −0.213 (1.808) 1.772 (1.658) 9.025*** (3.433) 0.198 (3.352) 0.665 (3.315)DW 0.428 2.02 2.21 0.87 1.93 2.08N 0.346 320 320 346 320 320R2 adjusted 0.168 0.657 0.696 0.564 0.703 0.716

Note: t-Statistics in parentheses.* Significant at the 10% level.

** Significant at the 5% level.*** Significant at the 1% level.

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the result suggests a net crowding out effect of FDI on domestic investment. Kumar and Pradhan(2002) argued that FDI may have a negative effect on the current period’s domestic investmentbecause it erodes market share of domestic investors, but exert a positive effect on domesticinvestment in later periods because of the generation of backward linkages.

5. Policy implications and concluding remarks

The study shows that though the flow of FDI increased for SSA countries in the 1990s, theincrease did not lead to a proportionate positive impact of FDI on economic growth. However,domestic investment and institutional infrastructure are positive and significantly correlated witheconomic growth. Further, the crowding out effect of domestic investment suggests that anypositive effect of FDI on economic growth may be due to increase in total factor productivityrather than augmentation of domestic capital. The results of the study have policy implications.

First, is the idea of targeted approach to FDI, which suggests that some types of FDI projects arebetter than others (Alfaro & Charlton, 2007). Policy makers should therefore focus on promotionalresources to attract some types of FDI and regulate others.

Agosin and Mayer (2000) and Mwilima (2003) have noted that FDI has been more produc-tive in Asia (especially China, Taiwan, and South Korea) than all the regions of the developingworld because of the targeted approach, which involved screening of investment applications andgranting differential incentives to different firms. Further, China, for example, permits repatria-tion of profits only out of net foreign exchange earnings (Keshava, 2008). In the case of Africa,Ndikumana and Verick (2008) have noted that the limited effect of FDI could be attributed tothe lack of synergies between FDI and domestic investment. Similarly, Dupasquier and Osakwe(2005) assert that unlike Africa that receives FDI mostly in primary sectors, most Asian FDIwent into the secondary sector thereby contributing to the diversification of the export base. TheUNCTAD report (2007) indicates the negative effect of FDI in Africa derives from the fact thatmost FDI is targeted at the primary sector, a lack of competition and a distorted regulatory andincentive framework. The problem with tax incentives or rebates, for example, is that it benefitsshort-term investments in footloose industries such as banking and general services that can easilyquit one jurisdiction for another (Pigato, 2000).

Second, the level of technological spillover to the host country is dependent on the absorptivecapacity of its citizens, which is related to the ability of a firm to recognize the value of newexternal information, assimilate it, and apply it to commercial ends (Cohen and Levinthal, 1990;Marcin, 2007). Lumbila (2005) claims that Africa will be able to take advantage of FDI onlyif meets some basic conditions since the impact of FDI on economic growth is constrained byAC in terms of trained workforce, basic infrastructure network, and depth and efficiency of thefinancial system. Similarly, Ayanwale (2007) asserts that the lack of significant effect of FDI oneconomic growth in Nigeria could be attributed to the low level of education. It is of interest tonote that the most important recipient of FDI in SSA in the 1990s in terms of GDP (22%) wasLesotho, but economic growth decelerated over the same period. More importantly, FDI flowsto Botswana declined over the same period, but the economy continued to grow (Ajayi, 2006).This is not to suggest that FDI is not needed in the SSA region, but rather that FDI’s growthenhancing effect is possible only when it stimulates AC of the host country’s citizens (Carkovic& Levine, 2002; Makki & Somwaru, 2004). It is important to note that even in China and otherAsian countries where FDI has been known to be more effective, Keshava (2008) has shown thatdomestic investment is more effective than FDI in promoting growth.

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Finally, FDI has both costs and benefits. Thus, MNEs can be agents of both development andunderdevelopment of the host country depending on what types of investment and what the profitsfrom the investments are used for. Though we do appreciate Tandon’s (2002) assertion that theforeign investor is in business for profit and not for development, the peculiar case of SSA (thepoorest region of the world) points to the fact that MNEs in the region must be developmentoriented to be able capture the hearts and minds of the people (and consequently their money).The assumption is that in the long run, the growth of the economies would lead to a higher level ofincome and therefore higher purchasing power of the citizens and subsequently market expansionfor the MNEs. A win–win situation for both MNE and host country. On the part of the SSAcountries, governments must take the issue of regional integration more seriously than it is beingcurrently pursued. The UNCTAD report (2005), for instance, has noted that the way forward forSSA countries to attract quality FDI is to begin to think regionally. The review and findings ofthe study have some implications for future research. First, the many different findings suggestthat country-specific studies may provide more information as to the real effect of FDI. Second,there is the need to ascertain how the various types of FDI (resource seeking, efficiency seeking,and market seeking) affect economic growth.

We conclude by stating that FDI is not inherently virtuous—its impact depends on the overallincentive and capability structure of the host country. Thus, attracting FDI is only one part ofthe story. The other is how FDI impacts on the wider local economy. In this respect, we haveargued that SSA countries need to be cautious and critical in the kind of FDI they attract; that theopen door policy to attract all kinds of FDI will not yield the desired benefits. Like Loungani andRazin (2001) and Albuquerque (2000), however, we argue that no matter what the effect of FDIon the host economy, without it, there is a possibility that the host country could be poorer. In theend, the extent to which a country can take advantage of FDI depends on its initial conditions,which we describe here as AC in terms of the level of education, basic physical infrastructure, andappropriateness of institutions. This is consistent with the UN’s Monterrey Consensus recognitionthat however globalized the world might be; development as well as financing it starts from homeor within. What makes the difference then is the policy space that notes that FDI is necessary butnot sufficient for economic growth.

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