IDEAS home Printed from https://ideas.repec.org/p/tut/cremwp/2018-11.html

Can Whistleblower Programs Reduce Tax Evasion? Experimental Evidence

Author

Listed:
  • David Masclet

    (Univ Rennes, CNRS, CREM - UMR 6211, F-35000 Rennes, France and CIRANO)

  • Claude Montmarquette

    (Centre interuniversitaire de recherche en analyse des organisations (CIRANO), Montréal, Québec (Canada))

  • Nathalie Viennot-Briot

    (Centre interuniversitaire de recherche en analyse des organisations (CIRANO), Montréal, Québec (Canada))

Abstract

There are many ways of tackling tax evasion. The traditional strategies implemented by tax authorities fight fiscal fraud through audit and penalties. However, there also exist a plethora of unconventional methods, such as whistleblower programs. Although there is a rich economic literature on tax evasion, auditing and penalties, tax agencies’ heavy reliance on whistleblower programs has mostly been ignored. We ran an experiment in which taxpayers can punish tax evaders by reporting them to the authorities, even though it is costly for them to do so and despite the lack of any material benefit from doing so. Information on other taxpayers' compliance rates together with the opportunity to report tax evaders has a positive and a very significant effect on the level of income reported. Observing the compliance rates of other participants alone does not suffice to increase tax revenues, while the mere threat of being reported significantly increases revenues.

Suggested Citation

  • David Masclet & Claude Montmarquette & Nathalie Viennot-Briot, 2018. "Can Whistleblower Programs Reduce Tax Evasion? Experimental Evidence," Economics Working Paper Archive (University of Rennes & University of Caen) 2018-11, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
  • Handle: RePEc:tut:cremwp:2018-11
    as

    Download full text from publisher

    File URL: https://ged.univ-rennes1.fr/nuxeo/site/esupversions/8ae0bc9b-baa0-4925-9a34-5c88174652dd?inline
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Pawlewicz, Katarzyna & Senetra, Adam, 2024. "Religious involvement in the context of public moral standards and sustainable social development – A case study of Polish voivodeships," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    3. Burgstaller, Lilith & Pfeil, Katharina, 2024. "Why whistleblowing does not deter collaborative tax evasion," Freiburg Discussion Papers on Constitutional Economics 24/3, Walter Eucken Institut e.V..
    4. Spagnolo, Giancarlo & Nyreröd, Theo, 2021. "A Fresh Look at Whistleblower Rewards," SITE Working Paper Series 56, Stockholm School of Economics, Stockholm Institute of Transition Economics.
    5. Rustam Romaniuc & Dimitri Dubois & Eugen Dimant & Adrian Lupusor & Valeriu Prohnitchi, 2022. "Understanding cross-cultural differences in peer reporting practices: evidence from tax evasion games in Moldova and France," Public Choice, Springer, vol. 190(1), pages 127-147, January.
    6. Philipp Chapkovski & Luca Corazzini & Valeria Maggian, 2021. "Does Whistleblowing on Tax Evaders Reduce Ingroup Cooperation?," Working Papers 2021:20, Department of Economics, University of Venice "Ca' Foscari".
    7. Xiaohan Liu & Jianmin Liu & Jia Liu & Jinguang Wu & Yu Hao, 2025. "Does a reduction in the pension insurance contribution ratio promote firm productivity? Evidence from a quasinatural experiment in China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(1), pages 665-688, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tut:cremwp:2018-11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: GERMAIN Lucie (email available below). General contact details of provider: https://edirc.repec.org/data/crmrefr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.