Corruption Determinants, Geography, and Model Uncertainty

TL;DR

This study investigates the key factors influencing corruption levels across countries by accounting for spatial spillovers, identifying the Rule of Law as the most significant determinant through robust Bayesian model averaging.

Contribution

It introduces a spatial Bayesian model averaging approach to identify robust corruption determinants, accounting for spatial spillovers among countries.

Findings

Rule of Law is the most persistent determinant of corruption

Spatial spillovers significantly influence corruption levels

Identified key predictors among 39 variables

Abstract

This paper aims to identify the robust determinants of corruption after integrating out the effects of spatial spillovers in corruption levels between countries. In other words, we want to specify which variables play the most critical role in determining the corruption levels after accounting for the effects that neighbouring countries have on each other. We collected the annual data of 115 countries over the 1985-2015 period and used the averaged values to conduct our empirical analysis. Among 39 predictors of corruption, our spatial BMA models identify Rule of Law as the most persistent determinant of corruption.