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Anti-corruption policy making, discretionary power and institutional quality: An experimental analysis

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  • Boly, Amadou
  • Gillanders, Robert

Abstract

We analyse policymakers’ incentives to fight corruption under different institutional qualities. We find that ‘public officials’, even when non-corrupt, significantly distort anti-corruption institutions by choosing a lower detection probability when this probability applies to their own actions (legal equality), compared to a setting where it does not (legal inequality). More surprising perhaps is the finding that policy-makers do not choose a zero level of detection on average, even when it applies to them too. Finally, corruption is significantly lower when the detection probability is exogenously set, suggesting that the institutional power to choose detection can itself be corruptive.

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  • Boly, Amadou & Gillanders, Robert, 2018. "Anti-corruption policy making, discretionary power and institutional quality: An experimental analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 314-327.
    • Handle: RePEc:eee:jeborg:v:152:y:2018:i:c:p:314-327
    DOI: 10.1016/j.jebo.2018.05.007
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    2. Yuping Deng & Yanrui Wu & Helian Xu, 2020. "Political Connections and Firm Pollution Behaviour: An Empirical Study," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(4), pages 867-898, April.
    3. Mazhar Ummad & Iftikhar Komal, 2021. "Corruption Accusations and Bureaucratic Performance: Evidence from Pakistan," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 15(1), pages 60-71, January.
    4. Shuguang Jiang & Marie Claire Villeval, 2022. "Dishonesty in Developing Countries -What Can We Learn From Experiments?," Working Papers hal-03899654, HAL.
    5. Parra, Daniel & Muñoz-Herrera, Manuel & Palacio, Luis A., 2021. "The limits of transparency in reducing corruption," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 95(C).
    6. Jiang, Shuguang & Wei, Qian & Zhao, Lei, 2024. "Synergizing anti-corruption strategies: Group monitoring and endogenous crackdown – An experimental investigation," China Economic Review, Elsevier, vol. 85(C).
    7. Bahník, Štěpán & Vranka, Marek Albert, 2020. "Experimental test of the effects of punishment probability and size on the decision to take a bribe," OSF Preprints cfwvj, Center for Open Science.
    8. Richard Kasa & Gábor Réthi & György Hauber & Krisztina Szegedi, 2023. "Simulation of Corruption Decisions—An Agent-Based Approach," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    9. Weißmüller, Kristina Sabrina & Zuber, Anna, 2022. "Understanding the Micro-Foundations of Administrative Corruption in the Public Sector: Findings from a Systematic Literature Review," OSF Preprints z9bcy, Center for Open Science.
    10. DeAngelo, Gregory & Houser, Daniel & Romaniuc, Rustam, 2020. "Experimental public choice: An introduction to the special issue," Journal of Economic Behavior & Organization, Elsevier, vol. 175(C), pages 278-280.
    11. Boly, Amadou & Gillanders, Robert, 2017. "Effective anti-corruption policy-making: What can we learn from experimental economics?," PEGNet Policy Briefs 9/2017, PEGNet - Poverty Reduction, Equity and Growth Network, Kiel Institute for the World Economy (IfW Kiel).
    12. Bahník, Štěpán & Vranka, Marek A., 2022. "Experimental test of the effects of punishment probability and size on the decision to take a bribe," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    13. Banerjee, Ritwik & Boly, Amadou & Gillanders, Robert, 2022. "Anti-tax evasion, anti-corruption and public good provision: An experimental analysis of policy spillovers," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 179-194.

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    More about this item

    Keywords

    Anti-corruption; Embezzlement; Experimental economics; Institutions; Policy-making;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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