What Predicts Corruption?
33 Pages Posted: 13 Feb 2019 Last revised: 24 Dec 2020
Date Written: December 23, 2020
Abstract
The ability to predict corruption is crucial to policy. Using rich micro-data from Brazil, we show that multiple machine learning models display high levels of performance in predicting municipality-level corruption in public spending. We then quantify which individual municipality features and groups of similar characteristics have the highest predictive power. We find that 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.
Keywords: Corruption, Machine Learning, Prediction, Private Sector
JEL Classification: H5
Suggested Citation: Suggested Citation