Determinantes de la corrupción en México: aplicación con enfoque bayesiano
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https://doi.org/10.29105/ensayos43.1-3Palabras clave:
corrupción, promedio de modelos bayesiano, variables instrumentales, determinantes de corrupciónResumen
El objetivo de la investigación es identificar determinantes robustos de la corrupción en México. Se plantea la metodología del Promedio de Modelos Bayesiano (BMA por sus siglas en inglés) para analizar 25 posibles determinantes de manera simultánea en una muestra que contempla las 32 entidades federativas, abarcando el período de 2015-2020. El BMA construye 33,554,432 combinaciones posibles de modelos para extraer los determinantes más robustos. Del mismo modo, se utiliza el BMA con variables instrumentales (IVBMA) para considerar los posibles problemas de endogeneidad. Los resultados indican que los factores institucionales son los mejores predictores de la corrupción, esto es, el Estado de Derecho, la democracia, la educación y la eficiencia del gobierno, muestran una asociación significativa con la corrupción.
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