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Electoral cycles in perceived corruption: International empirical evidence

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  • Potrafke, Niklas

Abstract

I examine whether elections influence perceived corruption in the public sector. Perceived corruption in the public sector is measured by the reversed Transparency International's Perception of Corruption Index (CPI). The dataset includes around 100 democracies over the period 2012-2016, a sample for which the CPI is comparable across countries and over time. The results show that the reversed CPI was about 0.4 points higher in election years than in other years, indicating that perceived corruption in the public sector increased before elections. The effect is especially pronounced before early elections (1.0 points) compared to regular elections (0.4 points). Future research needs to investigate why perceived corruption in the public sector increased before elections.

Suggested Citation

  • Potrafke, Niklas, 2019. "Electoral cycles in perceived corruption: International empirical evidence," Munich Reprints in Economics 78256, University of Munich, Department of Economics.
    • Handle: RePEc:lmu:muenar:78256
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    Cited by:

    1. Uberti, Luca J., 2022. "Corruption and growth: Historical evidence, 1790–2010," Journal of Comparative Economics, Elsevier, vol. 50(2), pages 321-349.
    2. Klaus Gründler & Niklas Potrafke & Timo Wochner, 2019. "Korruption und Wirtschaftswachstum," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(18), pages 27-33, September.
    3. Gründler, Klaus & Potrafke, Niklas, 2019. "Corruption and economic growth: New empirical evidence," European Journal of Political Economy, Elsevier, vol. 60(C).
    4. Rajeev K. Goel & Michael A. Nelson, 2021. "Direct and indirect influences of political regimes on corruption," Social Science Quarterly, Southwestern Social Science Association, vol. 102(4), pages 1569-1589, July.
    5. Gutmann, Jerg & Padovano, Fabio & Voigt, Stefan, 2020. "Perception vs. experience: Explaining differences in corruption measures using microdata," European Journal of Political Economy, Elsevier, vol. 65(C).
    6. Yingying Shi, 2024. "Corruption, technical efficiency and total factor productivity growth: empirical evidence from China," Economic Change and Restructuring, Springer, vol. 57(6), pages 1-24, December.
    7. Yang Li & Hu WenXiu & Su ZhenXing, 2023. "Impact of Local Official Corruption on Local Government Debt in China: The Mediating Role of Government Investment Efficiency," SAGE Open, , vol. 13(3), pages 21582440231, July.
    8. Joshua D. Ammons & Shishir Shakya, 2024. "Revolutions and corruption," Public Choice, Springer, vol. 201(1), pages 355-376, October.
    9. Cazals, Antoine & Léon, Florian, 2023. "Perception of political instability in election periods: Evidence from African firms," Journal of Comparative Economics, Elsevier, vol. 51(1), pages 259-276.
    10. Olmos, Lorena & Bellido, Héctor & Román-Aso, Juan A., 2020. "The effects of mega-events on perceived corruption," European Journal of Political Economy, Elsevier, vol. 61(C).
    11. Rajeev K. Goel & Michael A. Nelson, 2025. "Election campaign finance bans and corruption: effectiveness across parliamentary and presidential democracies," Constitutional Political Economy, Springer, vol. 36(2), pages 129-156, June.
    12. Marino, Domenico, 2025. "Dynamics of corruption: Theoretical explanatory model and empirical results," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 658(C).
    13. Praveen Kumar, 2023. "How does Corruption Affect Innovation? - New Evidence from Macro-level Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(4), pages 925-941, December.
    14. Pavlo Blavatskyy, 2021. "Obesity of politicians and corruption in post‐Soviet countries," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 29(2), pages 343-356, April.
    15. Le Moglie, Marco & Turati, Gilberto, 2019. "Electoral cycle bias in the media coverage of corruption news," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 140-157.
    16. Florian Dorn, 2021. "Elections and Government Efficiency," ifo Working Paper Series 363, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    17. Ivanović, Vladan & Uberti, Luca J. & Imami, Drini, 2023. "Opportunistic privatization," European Journal of Political Economy, Elsevier, vol. 80(C).
    18. Toke Aidt & Zareh Asatryan & Lusine Badalyan & Friedrich Heinemann, 2020. "Vote Buying or (Political) Business (Cycles) as Usual?," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 409-425, July.
    19. Wochner, Timo, 2022. "Part-time parliamentarians? Evidence from outside earnings and parliamentary activities," European Journal of Political Economy, Elsevier, vol. 75(C).

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • H11 - Public Economics - - Structure and Scope of Government - - - Structure and Scope of Government
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General

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