Uncovering the determinants of corruption

Michael Jetter and Christopher Parmeter

No 2016-02, Working Papers from University of Miami, Department of Economics

Abstract: Identifying the real causes of corruption has proven difficult because of limited data availability, lack of a unifying theoretical framework, and endogeneity concerns. Combining data for a comprehensive list of 36 potential determinants of corruption across 123 countries (including 87 percent of the world population), we use Instrumental Variable Bayesian Model Averaging to account for model uncertainty and endogeneity. In addition to income levels, the extent of primary schooling emerges as a powerful predictor of lower corruption levels. Rule of law and FDI matter particularly in developing countries. Finally, we find some evidence for trade freedom, political rights, government size, and religious fractionalization to contain corruption. These findings offer feasible avenues for policymakers, as corruption does not seem to be driven by deeply rooted cultural attributes.

Keywords: Corruption; Bayesian Model Averaging; Primary Education; Instrumental Variable Bayesian Model Averaging Publication Status: Under Review (search for similar items in EconPapers)
JEL-codes: C11 D73 K42 O11 O57 (search for similar items in EconPapers)
Date: 2016-03-16
New Economics Papers: this item is included in nep-env
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Citations: View citations in EconPapers (1)

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