Elsevier

Economic Analysis and Policy

Volume 56, December 2017, Pages 126-134
Economic Analysis and Policy

Full length article
Human capital and FDI: How does corruption affect the relationship?

https://doi.org/10.1016/j.eap.2017.08.007Get rights and content

Abstract

Can corruption affect the relationship between human capital and FDI for a host country? This paper explores the interactive impact of corruption and human capital on FDI. In particular, we investigate whether countries with higher or lower corruption levels benefit differently in terms of FDI inflow following an equal improvement in the level of human capital. Employing an extensive panel data and robust identification strategies, our results suggest that if the corruption score of a highly corrupt country becomes comparable to that of a low corruption country, FDI inflow will rise by almost 40 percent for an equivalent rise in human capital stock. The results remain robust for various measures of human capital.

Introduction

An extensive literature focuses on the determinants of Foreign Direct Investment (FDI) and that has identified human capital to be a key variable in attracting FDI1 to developing countries (see, Eicher and Kalaitzidakis, 1997; Blomström and Kokko, 2003a; Kar and Sinha, 2014 for a brief survey; etc.). At the same time, factors like corruption continue to hurt various economic attributes of a country (see, Al-Sadig, 2009; Smarzynska and Wei, 2002; etc.). While the literature documents both the beneficial impact of human capital and the harmful effects of corruption on FDI inflows, but such discussions appear in isolation. Therefore, the question of whether changes in the level of human capital affect FDI despite a certain degree of corruption in a country seems a crucial question to ask. In fact, the interactive impact of human capital and corruption in the context of FDI inflows has not been explored in this literature. Our paper seeks to understand whether a fall in the level of corruption makes human capital more productive in terms of its attractiveness to foreign direct investors. In the context of developing countries, the answers to such questions seem particularly important in view of the complex coexistence of the rising stock of human capital and the substantial corruption that exists in various economic spheres.

With regard to the pattern of trade and capital movements across borders, it has been observed that the superior technology and extent of human capital stock in a host country are major determinants in attracting Multinational Corporations (MNCs) to (re)locate their production bases (viz. Borensztein et al., 1998). It has been argued previously in the literature that the spillover effect of human capital Markusen and Trofimenko (2009), Ritchie (2002) is mainly associated with the advanced training of employees by MNCs and the dispersal of these employees towards other firms, many of which have local ownership. In terms of procedures, it seems that the source country’s managerial and technological experts work with the MNCs to train the host country workers regarding innovative marketing procedures, production organization, inventory management and an array of other production related aspects. Other than gaining higher real wages, local workers also become more productive. MNC related knowledge spillovers are captured not only by those directly linked with the MNCs but also other suppliers, distribution channels, quality control institutions, etc. Several significant contributions by Blomström and Persson (1983), Blomström (1986), Blomström et al. (1994), Blomström et al. (2000) and Blomström and Kokko (2003b) have reiterated the fact that FDI inflows afford complex interactions with human capital, whereby the once widely anticipated technology and human capital spillover effects are neither automatic nor instantaneous.2 Furthermore, the relationship is likely to be non-linear and bi-causal. Technology-intensive FDI may only be attracted to a country offering a large stock of skilled workers. However, the micro-foundations of such interactions are rather limited (Markusen and Trofimenko, 2009). In addition, estimates of change in human capital in the host country are mostly a comparison of the levels in the pre- and post-FDI regimes rather than the rate of change. In this context, the interaction between FDI and human capital culminating in higher levels of growth has been quite intensively discussed in Mallick and Moore (2008).

Indeed, the relationship between FDI and human capital is quite complex and has the potential to generate ambiguity for countries that have varying levels of corruption. As such, an extensive literature has already explored the relationship between corruption and economic growth (Mironov, 2005; Mo, 2001; Mauro, 1995 to mention a few). For instance, in a second-best world with distortions caused by ill-functioning institutions, corruption can compensate bad governance and attract more FDI (Shleifer and Vishny, 1993; Bardhan, 1997; Kaufmann and Wei, 1999; Aidt, 2003; Meon and Sekkat, 2005; Bellos and Subasat, 2012, etc.).3 However, it is quite well-known that corruption reduces efficiency by generating greater rent-seeking behaviour and misallocating talent. Investment suffers due to higher transaction costs and uncertainty (Acemoglu and Verdier, 1998; Murphy and Vishny, 1993; Murphy, Sleifer and Vishny, 1991). Corruption can deter FDI by increasing direct costs (bribery), by creating artificial bottlenecks, and by weakening transparency and protection of property rights. It also hurts FDI by increasing the risk of breached contracts, by reducing the quality of government services and infrastructure, by creating an uneven playing field in favour of the local firms (‘local capture’), and by distorting prices of public utilities or trade protection (Resmini, 2000; Hellman et al., 2002; Bevan and estrin, 2004; and Caetano and Caleiro, 2005).

Relatively fewer studies have investigated the impact of corruption on human capital. In this context, an important theoretical paper by Ehrlich and Lui (1999) explores the negative impact of corruption on human capital accumulation. The authors suggest that in the presence of corruption, more time has to be invested in political capital in order to improve the bureaucratic power of individuals rather than spending the same time and effort on making the education sector more productive. Based on this argument, greater corruption levels of countries should make human capital ineffective, thereby tempering the beneficial impact of human capital on FDI. Thus, other than creating a direct impediment to FDI, corruption can also make FDI less beneficial via the negative effect on human capital. To sum up, pervasive corruption is very likely to inhibit the productive impact of human capital on FDI.

Our contribution to the literature investigates the interactive impact of human capital and corruption on FDI inflows, synthesizing the two strands of literature discussed above. We hypothesize that the impact of human capital on FDI inflows is negative in the presence of corruption. Corruption raises transaction costs; it also raises the need for investing in political capital, and diverts resources to unproductive investments. All these factors can make human capital less beneficial in the context of FDI.

Our empirical analysis offers some surprising results. Using an extensive panel of 107 countries over the period 1984 to 2009, we show that human capital has a non-negative impact on FDI inflows even for highly corrupt countries. We find the impact to be positive and significant but small. However, there is an unambiguous benefit to reducing corruption. Less corrupt countries benefit more from an increase in human capital accumulation. In terms of economic significance, we show that if for a highly corrupt country (e.g., Lebanon) the corruption score becomes comparable to that of a relatively less corrupt country ( e.g., Chile, which is also in OECD), FDI inflows will rise by almost 40% for an equal rise in the stock of human capital. We test our results with various alternative measures of human capital.

The data and empirical methodology are described in Sections 2 Data, 3 Empirical methodology, respectively. In Section 4, we present the benchmark results and robustness analysis is presented in Section 5. Section 6 concludes.

Section snippets

Data

The dependent variable, namely foreign direct investment (FDI) as a percentage of GDP, is collected from the World Development Indicators (WDI, 2013 online database). FDI consists of equity capital, reinvestment of earnings and other capital. Further, as WDI explains, direct investment “is a category of cross-border investment associated with a resident in one economy having control or a significant degree of influence on the management of an enterprise that is resident in another economy.

Empirical methodology

In order to evaluate our hypothesis, we test the following specification FDIit=β0+β1FDIit1+β2HCit+β3HCCorrit+β4Corrit+j=1JαjXjit+β5γi+β6θt+ϵit.

Here, FDIit represents FDI inflows for country i in time t . Similarly, FDIit1, which denotes FDI inflows for country i in period t1, captures the persistence of the dependent variable. FDI in the past period should influence the current level of FDI inflows. While Corrit is the measure of corruption for country i in time t , HCit

Benchmark results

As mentioned above, System GMM is our preferred estimator. Dynamic panel data (DPD) models like fixed effect estimates suffer from inconsistent estimates due to the presence of unobserved panel-level effects that are correlated with the lagged dependent variable. GMM estimators take care of this inconsistency. Additionally, GMM estimators take into account country fixed effects and are constructed to handle the presence of heteroskedasticity and autocorrelation within countries (see Roodman,

Robustness

We use primary enrolment as a percentage of net enrolment and total primary completion rate as a percentage of the relevant age group as alternate measures of human capital for robustness checks. As opposed to human capital measured by secondary enrolment,these can be considered as measures of low-skilled human capital. FDI inflows can benefit from both skilled and low-skilled human capital accumulation. Further, the need for building political capital in the presence of corruption can be more

Conclusion

By employing panel data for 107 countries, we examined the interactive effect of human capital and corruption on FDI inflows. Employing System GMM estimators helped us combat several challenges arising for panel data estimates, including endogeneity. Our results show that human capital plays a significant role in attracting FDI to host countries, and thus, supports previous findings. The main contribution of the paper lies in emphasizing that benefits of human capital on FDI can be further

References (61)

  • MarkusenJ.R. et al.

    Teaching locals new tricks: Foreign experts as a channel of knowledge transfers

    J. Dev. Econ.

    (2009)
  • MoP.H.

    Corruption and economic growth

    J. Comparative Econ.

    (2001)
  • NoorbakhshF. et al.

    Human capital and FDI inflows to developing countries: New empirical evidence

    World Dev.

    (2001)
  • SchneiderFriedrich et al.

    Economic and political determinants of foreign direct investment

    World Dev.

    (1985)
  • TiwariA.K. et al.

    Economic growth and FDI in asia: A panel-data approach

    Econ. Anal. Policy

    (2011)
  • WindmeijerF.

    A finite sample correction for the variance of linear efficient two-step GMM estimators

    J. Econom.

    (2005)
  • AidtT.S.

    Economic analysis of corruption

    Econom. J.

    (2003)
  • Al-SadigA.

    The effects of corruption on FDI inflows

    Cato J.

    (2009)
  • Al-SadigA.

    The effects of foreign direct investment on private domestic investment: evidence from developing countries

    Empir. Econom.

    (2013)
  • Alonso-BorregoC. et al.

    Symmetrically normalized instrumental-variable estimation using panel data

    J. Bus. Econom. Statist.

    (1999)
  • ArellanoM. et al.

    Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations

    Rev. Econom. Stud.

    (1991)
  • ArellanoM. et al.

    Another look at the instrumental-variable estimation of error components models

    J. Econometrics

    (1995)
  • Artige, L., Nicolini, R., 2005. Evidence on the Determinants of Foreign Direct Investment: The Case of Three European...
  • BardhanP.

    Corruption and development

    J. Econom. Lit.

    (1997)
  • BaumC.F. et al.

    Instrumental variables and GMM: estimation and testing

    Stata J.

    (2003)
  • BellosS. et al.

    Governance and foreign direct investment: a panel gravity model approach

    Int. Rev. Appl. Econ.

    (2012)
  • BlomströmM.

    Foreign investment and productive efficiency: the case of Mexico

    J. Ind. Econ.

    (1986)
  • Blomström, M., Kokko, A. 2003a. The economics of foreign direct investment incentives. NBER Working Paper No. 9489,...
  • Blomström, M., Kokko, A., 2003b. Human capital and inward FDI. CEPR Discussion Paper No. 3762,...
  • BlomströmM. et al.

    Foreign Direct Investment: Firm and Host Country Strategies

    (2000)
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    We thank the editor and the referees for their invaluable comments and suggestions. The comments have greatly improved our paper. We also sincerely thank Dr. Tushar Das for thoroughly editing and proof-reading our article.

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