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The MNC as an agent of change for host-country institutions: FDI and corruption

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Abstract

Most empirical research examines how the institutional environment of corruption shapes the behavior of multinational corporations (MNCs). In this study, we would like to highlight the other side of the picture: how the presence of MNCs may shape the institutional environment of corruption over time. We propose three avenues through which the MNCs may have an impact on its host institutions: regulatory pressure effect, demonstration effect, and professionalization effect. Based on extensive data on foreign direct investment and corruption for a large sample of countries over the last 30 years, the empirical results are generally consistent with our hypothesis. Such findings provide a glimmer of hope for the future of the host country where corruption is prevalent.

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Notes

  1. We benefited much from the insights of DiMaggio and Powell (1983), who discuss institutional isomorphism. Isomorphism is a constraining process that forces one unit in a population to resemble other units that face a similar set of environmental conditions. Our proposed three effects correspond to their three mechanisms of isomorphism: coercive isomorphism, mimetic isomorphism, and normative isomorphism. However, the focus of DiMaggio and Powell is on isomorphism. In order not to confuse readers who are familiar with institutional theory, we use three other terms to represent the effects through which the MNC may shape the host-country institution over time.

  2. Our hypothesis is on an average effect. First, some MNCs may still engage in corrupt transactions to facilitate their operation. Second, there are also foreign direct investment flows among developed countries where both the home and host countries do not experience a high level of corruption. In that case, the corruption-reduction effect may be minimal. To examine this latter point, in our robustness tests, we exclude OECD countries from our sample of host countries. The findings are generally robust. Because of space constraints the tables of these additional findings are not included in this paper, but will be made available to readers upon request.

  3. Robertson and Watson (2004) find empirical support for their hypothesis. They use a 1- and 2-year lag time between the predictor variable (FDI) and the dependent variable (corruption). Their result reflects more on the short-term effect. On the other hand, the focus of this paper is on the long-term effect of FDI on corruption, because the suggested three effects take time to realize.

  4. The corruption perception index is a continuous scale variable, taking values from 0 to 10: the higher the value, the less corrupt the country is. To make the scaling more intuitive, we rescale the corruption perception index by deducting it from 10, so that a 0 on the new scale signifies a corruption-free country and a 10 represents an absolutely corrupt country.

  5. To check for other institutional control variables, instead of the political and legal variables, we also used a variable that denotes the religious orientation of the country – the percentage of the population that follows Protestantism. Religion appears to be a dominant influence on the institutional environment of countries, showing a significant correlation with our legal and political variables. Our results are robust to such specification, showing that countries with past FDI exhibit a lower rate of corruption, after controlling for religion. The coefficient on FDI is –0.385, significant at the 1% level. Also, countries with a dominant protestant influence display a lower incidence of corruption. In addition, we considered a much broader measure of institutional development (instead of the political and legal variables we have) from Kaufmann et al. (1999). This measure reflects the institutional quality, based on measures of voice and accountability, political stability and absence of violence, government effectiveness, regulatory burden, law and order, and freedom from graft. The results show a robust negative relation between FDI and corruption. The coefficient estimate is −0.139, which is significant at the 10% level. The results using religious orientation or institutional development as controls are not reported in the tables because of space constraints. They will be made available to readers upon request.

  6. For reasons outlined earlier, we focus on the power distance and individualism attributes of national culture. Although not reported (for brevity), the results using the other two attributes – masculinity and uncertainty avoidance – provide qualitatively similar evidence. Again for brevity, we use the overall average FDI over the entire period 1970–1997 as the FDI variable. However, the results are robust when we use the decade averages instead.

  7. Secondary school enrollment is a standard measure of human capital in the literature of economic growth (e.g., Barro, 1991).

  8. We follow a two-step procedure, in which we predict the level of FDI using our two instruments in the first step, and then use the predicted FDI values and other predetermined variables to explain variations in corruption. The test for the validity of the instruments using GMM estimation does not support the hypothesis. However, in this test, the set of instruments includes both the two instrumental variables we specified and the six exogenous explanatory variables in the model, because, with only two instruments, the model will be under-identified. Nevertheless, this result reflects the difficulty of finding good instruments in our context and suggests that readers should interpret our instrumental variables results with this limitation in mind.

  9. In this study, we do not use the change of corruption level as our main dependent variable. Transparency International computes the Corruption Perception Index as a composite of a number of independent surveys. As explained in Robertson and Watson (2004, 390), the sources used differ from year to year. Hence, the CPI is suitable for cross-sectional comparisons but unsuitable for longitudinal comparisons. To alleviate the concern of varying sources over time, we use the average corruption levels of two broad periods to compute the difference. Nevertheless, readers should interpret the findings with such a limitation in mind.

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Acknowledgements

We would like to thank the four guest editors of this special issue, the participants at the JIBS ‘Three Lenses’ conference, and our colleague Kendall Roth for valuable suggestions. We also gratefully acknowledge the support of the Center for International Business Education and Research (CIBER) at the University of South Carolina for this research project.

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Authors and Affiliations

  1. Moore School of Business, University of South Carolina, Columbia, SC, USA

    Chuck C Y Kwok

  2. Stephen M Ross School of Business, University of Michigan, Ann Arbor, MI, USA

    Solomon Tadesse

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  1. Chuck C Y Kwok
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  2. Solomon Tadesse
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Correspondence to Solomon Tadesse.

Additional information

Accepted by Peter Rodriguez, 28 February 2006. This paper has been with the author for two revisions.

Appendix A. Variables and sources

Appendix A. Variables and sources

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Kwok, C., Tadesse, S. The MNC as an agent of change for host-country institutions: FDI and corruption. J Int Bus Stud 37, 767–785 (2006). https://doi.org/10.1057/palgrave.jibs.8400228

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  • DOI: https://doi.org/10.1057/palgrave.jibs.8400228

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