| Creators |
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| Publication date |
2025
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| Description |
Can machine learning support better governance? This study uses a tree-based gradient-boosted classifier to predict corruption in Brazilian municipalities using budget data as predictors. The trained model offers a predictive measure of corruption, which we validate through replication and extension of previous corruption studies. Our policy simulations show that machine learning can significantly enhance corruption detection: compared to random audits, a machine-guided targeted policy could detect almost twice as many corrupt municipalities for the same audit rate.
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| Publisher |
ICPSR - Interuniversity Consortium for Political and Social Research
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| Organisations |
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Faculty of Economics and Business (FEB) - Amsterdam School of Economics Research Institute (ASE-RI)
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| Document type |
Dataset
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| Related publication |
A Machine Learning Approach to Analyze and Support Anticorruption Policy
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| DOI |
https://doi.org/10.3886/e197821 |
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