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What predicts corruption?

Author

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  • E Colonnelli
  • J.A. Gallego
  • M Prem

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.

Suggested Citation

  • E Colonnelli & J.A. Gallego & M Prem, 2019. "What predicts corruption?," Documentos de Trabajo 17144, Universidad del Rosario.
  • Handle: RePEc:col:000092:017144
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    Cited by:

    1. Gallego, Jorge & Prem, Mounu & Vargas, Juan F., 2020. "Corruption in the Times of Pandemia," SocArXiv js8by, Center for Open Science.
    2. Jhorland Ayala-García & Jaime Bonet-Mor�n & Gerson Javier P�rez-Valbuena & Eduardo Jos� Heilbron-Fern�ndez & J�ssica Dayana Suret-Leguizam�n, 2022. "La corrupción en Colombia: un análisis integral," Documentos de Trabajo Sobre Economía Regional y Urbana 20080, Banco de la República, Economía Regional.
    3. Gallego, Jorge & Prem, Mounu & Vargas, Juan F., 2022. "Predicting Politicians' Misconduct: Evidence from Colombia," SocArXiv 5dp8t, Center for Open Science.
    4. Colonnelli, Emanuele & Lagaras, Spyridon & Ponticelli, Jacopo & Prem, Mounu & Tsoutsoura, Margarita, 2022. "Revealing corruption: Firm and worker level evidence from Brazil," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1097-1119.
    5. Gustavo J. Bobonis & Luis Raúl Cámara Fuertes & Harold J. Toro & Julie Wilson, 2021. "Development and Decay: Political Organization, Economic Conditions, and Municipal Corruption in Puerto Rico, 1952-2015," Working Papers tecipa-687, University of Toronto, Department of Economics.
    6. Elliott Ash & Sergio Galletta & Tommaso Giommoni, 2025. "A Machine Learning Approach to Analyze and Support Anticorruption Policy," American Economic Journal: Economic Policy, American Economic Association, vol. 17(2), pages 162-193, May.
    7. Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.

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