What predicts corruption?

Emanuele Colonnelli, Jorge Gallego and Mounu Prem

No 17144, Documentos de Trabajo from Universidad del Rosario

Abstract: 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.

Pages: 21
Date: 2019-02-08
New Economics Papers: this item is included in nep-big and nep-cmp
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Citations: View citations in EconPapers (6)

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Related works:
Chapter: What predicts corruption? (2022)
Working Paper: What Predicts Corruption? (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:col:000092:017144

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