Ensaios em setor público : desempenho econômico e corrupção

Abstract

The aim of this study was to investigate the effects of corruption on economic performance in a sample of 40 European countries over the period 2001 to 2021. To this end, an exploratory spatial data analysis (AEDE) was conducted and subsequently estimated the dynamic economic performance model from the GMM estimation method without spatial effects and the dynamic Spatial Durbin Error Model (SDEM). The results pointed out a robust direct and indirect spatial relationship between corruption and GDP per capita of the countries in Europe, indicating that besides corruption itself, being neighbor to corrupt countries also induces the reduction of GDP per capita of the countries in Europe. In this sense, there is a need for coordinated anti-corruption policies among the countries, aiming to increase their levels of per capita income. The present study aims to analyze the relationship between corruption and economic performance in the 26 federative units of Brazil, excluding the Federal District, during the period from 2009 to 2018. To this end, a factor analysis using principal components was employed to create the corruption index, as proposed by Carraro et al. (2015). Dynamic spatial panel data models were also evaluated, using the GMM method in the absence of spatial dependence and the SDEM model, following the procedure indicated by LeSage (2014). The results revealed negative direct and indirect effects between corruption and economic performance, meaning that the values of these variables are also influenced by neighboring units. Therefore, to achieve better economic performance, Brazilian states would need the implementation of collective anti-corruption policies.