The Impact of Culture on Corruption, Gross Domestic Product, and Human Development

Abstract

The evidence of culture’s impact on corruption and its consequences is still inconclusive despite several investigations: (1) Sometimes, theory is lacking and causes and consequences seem exchangeable. Based on psychological research on the distribution and use of power, we predicted that a steeper distribution of power induces more corruption and elaborated its negative consequences in a complex causal model. (2) For measuring power distribution, pervading national culture, we augmented Hofstede’s ‘Power Distance’ with three additional indicators into a reversed, more reliable and valid culture composite called “Power Balanced Freedom” (PBF). (3) Instead of the usual regression and instrument approaches, which cannot estimate multiple causal chains including causal feedback, a non-recursive path analysis was employed with data from 85 nations. PBF predicted less national Corruption (62%), with positive effects on Gross Domestic Product (GDP, 72%) and Inequality Adjusted Human Development (IHDI, 66%, including Life Expectancy, Income, and Education). The often expected reverse effect of GDP on Corruption was not significant. Contrary to influential authors from economics, culture variables are the most important predictors of corruption and its consequences. Nonetheless, our extended model supports the main thrust of their ideas and adds more precision. Our conceptual distinction of the uses of power and our empirical measure PBF reflect Kant’s ethical imperative: freedom and autonomy for everyone. Widely shared life chances as measured by IHDI reflect utilitarian, consequentialist ideas. These different ethical approaches are connected in the confirmed causal model, in line with Rawls’ first and second principle of justice.

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Notes

  1. 1.

    Transparency International distinguishes grand, petty and political corruption which all take place in the public sphere. Grand corruption is done by high-level officials diverting large sums of money, petty corruption by mid- and low-level officials exploiting normal citizens, and political corruption again by high-level officials who change political rules in order to increase their power, status, and wealth.

  2. 2.

    Note that instead of “affiliation” and “power,” terms used by Leary (1957), the originator of this circumplex, these dimensions are sometimes termed “friendly-hostile” and “dominant-submissive” as behavioral dimensions or “communion” and “agency,” e.g., Abele and Wojciszke (2013). In fact, these two dimensions are universal dimensions resulting from the feeling dimensions of valence and control, being expressed in non-verbal and verbal communication, and showing up in behavior and personality (Scholl 2013).

  3. 3.

    Some of these authors use other terms for a similar distinction to promotive and restrictive control.

  4. 4.

    English translation cited from Wikipedia’s site ‘Categorical imperative.’

  5. 5.

    Kipnis (1976) does not use the verbal distinctions “promotive” and “restrictive,” but Buschmeier (1995) showed that the more restrictive the tactics and bases of power are, the more they are used against the interests and autonomy of the other(s), whereas the opposite holds for promotive control.

  6. 6.

    In terms of multi-level analysis, this would be a top-down cross-level effect. Since only the national level data are available from the used culture surveys, this effect cannot be tested with our data.

  7. 7.

    Different from Hoyle (2012), these authors use the term „path analysis“ only for structural approaches with manifest variables.

  8. 8.

    In the discussion, Husted (1999) avoids causal terminology and speaks of correlates of corruption which does not correct the regression estimates.

  9. 9.

    Collinearity complicates this description because correlated effects of exogenous variables have to be added for the decomposition of correlations. Thus, the lower collinearity is, the more precise the estimation of the model will be.

  10. 10.

    Two later-developed dimensions by Hofstede were omitted in the current study, because less country data were available.

  11. 11.

    We are grateful to Evert Van de Vliert for this personal recommendation.

  12. 12.

    In case of missing values, averages represent the remaining dimensions.

  13. 13.

    The extended data set is publicly available at https://www.researchgate.net/publication/326156903_Power_distribution_and_Corruption.

  14. 14.

    The complete path model with the feedback effect of GDP on Corruption is shown in the supplement S1 on https://www.researchgate.net/publication/326156988_Supplementary_Material_for_The_Impact_of_Culture_on_Corruption_Gross_Domestic_Product_and_Human_Development_S1_Nonrecursive_model_with_feedback_from_GDP_to_Low_Corruption the recalculated model with filled missings is shown as supplement S2 on the same website.

  15. 15.

    If only Power Distance and Individualism (Hofstede) and In-Group collectivism (GLOBE) would be retained in that index, then Press Freedom would be the only additional predictor of Corruption. This points to the important role of an independent press for the fight against corruption; it is also contained in PBF’s Freedom Index.

  16. 16.

    This analysis is available from the first author.

  17. 17.

    Regrettably, the authors don’t describe fully their Global Economic Freedom Index and the reference is missing.

  18. 18.

    Cited from Pieper (2017, p. 231), own translation.

  19. 19.

    Own translation.

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Acknowledgements

Many thanks to Peter Graeff, Michael Johnston, Nils Köbis, Johann Graf Lambsdorff, Stefan Melnik and Evert van de Vliert for helpful commentaries and to all authors and institutions who made their multi-nations data available. We especially thank the section editor, Dr. Suhaib Riaz, and the anonymous reviewers for their valuable suggestions for improving the paper.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Scholl, W., Schermuly, C.C. The Impact of Culture on Corruption, Gross Domestic Product, and Human Development. J Bus Ethics 162, 171–189 (2020). https://doi.org/10.1007/s10551-018-3977-0

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Keywords

  • Corruption
  • Cross cultural differences
  • Economics
  • Human development
  • Power distribution
  • Psychology