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Private-Sector Corruption: Measurement and Cultural Origins

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Abstract

Research on corruption has made substantial progress in recent years. Yet, most studies still treat corruption as a homogenous phenomenon. This article argues that private-sector corruption can be distinguished conceptually from public-sector corruption, which has been in the spotlight of empirical research. We introduce the first indicator of private-sector corruption covering a large cross-section of countries. This new indicator is used to extend a recent empirical study on the cultural determinants of public-sector corruption (Kong and Volkema in Soc Indic Res 127(1):139–152, 2016). We find that self-serving leadership in high-income countries is associated with more corruption in both the public and the private sector. Furthermore, individualistic leadership in low-income countries is linked to reduced private-sector corruption. Next, we test a number of alternative cultural explanations for differences in private-sector corruption across countries. Overall, our results suggest that specific forms of corporate leadership culture matter for private-sector corruption, but also religious identity and trust play an important role.

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Notes

  1. This criticism holds true especially for empirical research, although already Coase (1979) has studied private-sector corruption in the US media sector. Theoretical studies generally have taken private-sector corruption more seriously (see, e.g., Rose-Ackerman 1975: 203).

  2. Another commonly referred to and frequently studied example of corruption in the private sector is competitive sports (see, e.g., Borghesi 2008; Deutscher et al. 2017; Duggan and Levitt 2002; Wolfers 2006), mostly because of unpredictable performance and the arbitrariness of referee decisions.

  3. Measuring private- and public-sector corruption separately can also be understood as a contribution to recent attempts in the New Institutional Economics to unbundle different groups of institutions (see, e.g., Acemoglu and Johnson 2005 or Voigt 2013).

  4. Although Jordan and the Solomon Islands are part of the GCB, that question is not covered for Jordan, and for the Solomon Islands data specifically on corruption in the military is not available.

  5. Answers were possible on a five-point Likert scale ranging from 1 (not at all corrupt) to 5 (extremely corrupt). We use the mean scores for each country, effectively interpreting the survey item according to a linear scale.

  6. These traits of factor analysis are not shared by principal component analysis, which tries to maximize the variance that is explained by the principal components.

  7. The results are virtually identical to those we obtain when we use instead the data from the 2010/11 wave of the GCB, which was the first wave to cover 100 countries and corruption in 11 segments of the private and the public sector. Earlier waves covered only significantly less countries and sectors.

  8. Correlations with the latest public-sector corruption indicators by Transparency International (CPI) and the World Bank (Control of Corruption) are even lower (at around r = 0.15) and insignificant. The even lower correlations are not surprising, as the timing and method of measurement differs from the GCB.

  9. "Appendix 1" shows detailed results. “Appendix 2” lists all countries covered by the data.

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Acknowledgements

The authors thank Dejun Tony Kong and Roger Volkema for sharing their data as well as Agnes Strauß, Anna Sunik, Cornelius Haasnoot, Erich Gundlach, Julia Grauvogel, Karsten Mau, Michael Stoffel, Nora ElBialy, Sabrina Maaß, Sönke Häseler, Stanley Winer, Stefan Voigt, Stephan Michel, the GIGA’s “Non-Democratic Regimes” research team, and participants of the European Political Science Association Conference for helpful comments and suggestions on earlier drafts of this paper.

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  1. Institute of Law and Economics, University of Hamburg, Johnsallee 35, 20148, Hamburg, Germany

    Jerg Gutmann

  2. GIGA German Institute of Global and Area Studies, Neuer Jungfernstieg 21, 20354, Hamburg, Germany

    Viola Lucas

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Appendices

Appendix 1

See Table 3.

Table 3 Private-sector corruption by region
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Appendix 2

See Table 4.

Table 4 Country sample
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Appendix 3

See Table 5.

Table 5 List of variables and data sources
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Appendix 4

See Table 6.

Table 6 Robust regression
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Appendix 5

See Table 7.

Table 7 Exploring other cultural determinants
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Gutmann, J., Lucas, V. Private-Sector Corruption: Measurement and Cultural Origins. Soc Indic Res 138, 747–770 (2018). https://doi.org/10.1007/s11205-017-1684-3

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