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What Predicts Corruption?

Serie

  • Documentos de trabajo

Resumen

  • 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.

fecha de publicación

  • 2019-02

Issue

  • 17144