Abstract

FLORES MARQUEZ, Héctor  and  JIMENEZ GOMEZ, Adrián. Determinants of corruption in Mexico: application with a Bayesian Approach. Ens. Rev. econ. [online]. 2024, vol.43, n.1, pp.51-82.  Epub Feb 11, 2025. ISSN 2448-8402.  https://doi.org/10.29105/ensayos43.1-3.

The objective of the research is to identify robust determinants of corruption in Mexico. The Bayesian Model Average (BMA) methodology is proposed to analyze 25 possible determinants simultaneously in a sample that includes the 32 states, covering the period 2015-2020. The BMA builds 33,554,432 possible combinations of models to extract the most robust determinants. Similarly, the BMA with instrumental variables (IVBMA) is used to consider possible endogeneity problems. The results indicate that institutional factors are the best predictors of corruption, that is, the rule of law, democracy, education and government efficiency, show a significant association with corruption.

Keywords : Corruption; Bayesian Model Averaging; Instrumental Variables; Determinants of corruption.

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