What predicts corruption?

Using rich micro data from Brazil, we show that multiple popular machine learning models display extremely high levels of performance in predicting municipality-level corruption in public spending. Measures of private sector activity, financial development, and human capital are the strongest predic...

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Detalles Bibliográficos
Autores Principales: Colonnelli, Emanuele, Gallego, Jorge A., Prem, Mounu
Otros Autores: Facultad de Economía
Formato: Documento de trabajo (Working Paper)
Lenguaje:Inglés (English)
Publicado: 2019
Materias:
H5
Acceso en línea:http://repository.urosario.edu.co/handle/10336/19026
Descripción
Sumario:Using rich micro data from Brazil, we show that multiple popular machine learning models display extremely high levels of performance in predicting municipality-level corruption in public spending. Measures of private sector activity, financial development, and human capital are the strongest predictors of corruption, while public sector and political features play a secondary role. Our findings have implications for the design and cost-effectiveness of various anti-corruption policies.