Determinantes de la corrupción en México: aplicación con enfoque bayesiano

Héctor Flores Márquez; Adrián Jiménez Gómez

doi:10.29105/ensayos43.1-3

Authors

Héctor Flores Márquez Benemérita Universidad Autónoma de Puebla https://orcid.org/0000-0002-1766-5266
Adrián Jiménez Gómez Benemérita Universidad Autónoma de Puebla https://orcid.org/0000-0002-8909-9056

DOI:

https://doi.org/10.29105/ensayos43.1-3

Keywords:

Corruption, Bayesian Model Averaging, Instrumental Variables, Determinants of corruption

Abstract

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.

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Author Biographies

Héctor Flores Márquez, Benemérita Universidad Autónoma de Puebla

Héctor Flores Márquez, tiene los grados de Maestro en Economía por la Benemérita Universidad Autónoma de Puebla, y Doctor en Ciencias Económicas por el Instituto Politécnico Nacional. Actualmente es Posdoctorante de la Facultad de Economía de la Benemérita Universidad Autónoma de Puebla. Es miembro del Sistema Nacional de Investigadoras e Investigadores Nivel I.

Adrián Jiménez Gómez, Benemérita Universidad Autónoma de Puebla

Adrián Jiménez Gómez tiene los grados de Maestro en Economía por El Colegio de México, Master in Arts y PhD in Economics por la Universidad de Warwick. Actualmente es profesor- investigador de la Facultad de Economía de la Benemérita Universidad Autónoma de Puebla. Es miembro del Sistema Nacional de Investigadoras e Investigadores Nivel Candidato. Ha publicado artículos sobre estimaciones econométricas sobre la demanda de trabajo. El más reciente es “An Estimation of Jobs Lost in Mexico during 2020 as a Result of the COVID-19: a Cointegration Approach”, publicado en el Brazilian Journal of Health Review en 2020.

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