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The Efficiency of Crackdowns: A Lab-in-the-Field Experiment in Public Transportations

Author

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  • Zhixin Dai

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

  • Fabio Galeotti

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

  • Marie Claire Villeval

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

Abstract

The concentration of high frequency controls in a limited period of time (" crackdowns ") constitutes an important feature of many law-enforcement policies around the world. In this paper, we offer a comprehensive investigation on the relative efficiency and effectiveness of various crackdown policies using a lab-in-the-field experiment with real passengers of a public transport service. We introduce a novel game, the daily public transportation game, where subjects have to decide, over many periods, whether to buy or not a ticket knowing that there might be a control. Our results show that (a) concentrated crackdowns are less effective and efficient than random controls; (b) prolonged crackdowns reduce fare-dodging during the period of intense monitoring but induces a burst of fraud as soon as they are withdrawn; (c) pre-announced controls induces more fraud in the periods without control. Overall, we also observe that real fare-dodgers fraud more in the experiment than non-fare-dodgers.

Suggested Citation

  • Zhixin Dai & Fabio Galeotti & Marie Claire Villeval, 2016. "The Efficiency of Crackdowns: A Lab-in-the-Field Experiment in Public Transportations," Working Papers halshs-01270808, HAL.
    • Handle: RePEc:hal:wpaper:halshs-01270808
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01270808
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    References listed on IDEAS

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    1. Zhixin Dai & Fabio Galeotti & Marie Claire Villeval, 2018. "Cheating in the Lab Predicts Fraud in the Field: An Experiment in Public Transportation," Management Science, INFORMS, vol. 64(3), pages 1081-1100, March.
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    Cited by:

    1. Zhixin Dai & Fabio Galeotti & Marie Claire Villeval, 2018. "Cheating in the Lab Predicts Fraud in the Field: An Experiment in Public Transportation," Management Science, INFORMS, vol. 64(3), pages 1081-1100, March.
    2. Fabio Galeotti & Valeria Maggian & Marie Claire Villeval, 2021. "Fraud Deterrence Institutions Reduce Intrinsic Honesty," The Economic Journal, Royal Economic Society, vol. 131(638), pages 2508-2528.
    3. Luigi Mittone & Matteo Ploner & Eugenio Verrina, 2021. "When the state does not play dice: aggressive audit strategies foster tax compliance," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 57(3), pages 591-615, October.
    4. 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).
    5. Benedetto Barabino & Cristian Lai & Alessandro Olivo, 2020. "Fare evasion in public transport systems: a review of the literature," Public Transport, Springer, vol. 12(1), pages 27-88, March.

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    More about this item

    Keywords

    Crackdowns; fraud; risk; monitoring; transportation; field experiment;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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