Sorting through global corruption determinants: Institutions and education matter – Not culture
Michael Jetter () and
World Development, 2018, vol. 109, issue C, 279-294
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.
Keywords: Bayesian model averaging; Corruption; Political institutions; Instrumental variable Bayesian model averaging (search for similar items in EconPapers)
JEL-codes: C11 D73 O11 K42 O57 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:wdevel:v:109:y:2018:i:c:p:279-294
Access Statistics for this article
World Development is currently edited by O. T. Coomes
More articles in World Development from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().