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Sorting through global corruption determinants: Institutions and education matter – Not culture

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  • Jetter, Michael
  • Parmeter, Christopher F.

Abstract

Identifying the robust determinants of corruption among cultural, economic, institutional, and geographical factors has proven difficult. From a policy perspective, it is important to know whether inherent, largely unchangeable attributes are responsible or if institutional and economic attributes are at work. Accounting for model uncertainty, we use Bayesian Model Averaging (BMA) to analyze a comprehensive list of 36 potential corruption determinants across 123 countries (covering 87 percent of the world population). The BMA methodology sorts through all 68,719,476,736 possible model combinations (236) in order to carve out the robust correlates. We then take a step toward alleviating endogeneity concerns in an Instrumental Variable BMA framework. Our results indicate that cultural factors are largely irrelevant, whereas particular economic and institutional characteristics matter. The rule of law emerges as the most persistent predictor with a posterior inclusion probability (PIP) in the true model of 1.00, whereas we find strong evidence for government effectiveness (PIP of 0.88), urbanization (0.85), and the share of women in parliament (0.80) as meaningful determinants of lower corruption levels. In developing countries, the extent of primary schooling enters as a powerful factor with a PIP of 1.00.

Suggested Citation

  • Jetter, Michael & Parmeter, Christopher F., 2018. "Sorting through global corruption determinants: Institutions and education matter – Not culture," World Development, Elsevier, vol. 109(C), pages 279-294.
  • Handle: RePEc:eee:wdevel:v:109:y:2018:i:c:p:279-294
    DOI: 10.1016/j.worlddev.2018.05.013
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    17. Bruns, Stephan B. & Ioannidis, John P.A., 2020. "Determinants of economic growth: Different time different answer?," Journal of Macroeconomics, Elsevier, vol. 63(C).
    18. Graf Lambsdorff, Johann, 2005. "Consequences and causes of corruption: What do we know from a cross-section of countries?," Passauer Diskussionspapiere, Volkswirtschaftliche Reihe V-34-05, University of Passau, Faculty of Business and Economics.
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    More about this item

    Keywords

    Bayesian model averaging; Corruption; Political institutions; Instrumental variable Bayesian model averaging;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Sorting through global corruption determinants: Institutions and education matter – Not culture (WD 2018) in ReplicationWiki

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