IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp9925.html
   My bibliography  Save this paper

Can Transparency of Information Reduce Embezzlement? Experimental Evidence from Tanzania

Author

Listed:
  • Di Falco, Salvatore

    (University of Geneva)

  • Magdalou, Brice

    (University of Montpellier 1)

  • Masclet, David

    (University of Rennes)

  • Villeval, Marie Claire

    (CNRS, GATE)

  • Willinger, Marc

    (University of Montpellier 1)

Abstract

Embezzlement is a major concern in various settings. By means of a sequential modified dictator game, we investigate theoretically and experimentally whether making information more transparent and reducing the number of intermediaries in transfer chains can reduce embezzlement and improve the recipients' welfare. Consistent with reference-dependent preferences in terms of moral ideal, we show that the impact of transparency is conditional on the length of the transfer chain and on the position of the intermediaries in the chain. Its direct effect on image encourages honesty. Its indirect effect via expectations plays in the opposite direction, motivating individuals to embezzle more when they expect that the following intermediary will embezzle less. Senders react positively to a reduction of the length of the chain but negatively to transparency.

Suggested Citation

  • Di Falco, Salvatore & Magdalou, Brice & Masclet, David & Villeval, Marie Claire & Willinger, Marc, 2016. "Can Transparency of Information Reduce Embezzlement? Experimental Evidence from Tanzania," IZA Discussion Papers 9925, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9925
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp9925.pdf
    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. Attanasi, Giuseppe & Rimbaud, Claire & Villeval, Marie Claire, 2019. "Embezzlement and guilt aversion," Journal of Economic Behavior & Organization, Elsevier, vol. 167(C), pages 409-429.
    2. Ye-Feng Chen & Shu-Guang Jiang & Marie Claire Villeval, 2015. "The Tragedy of Corruption. Corruption as a social dilemma," Working Papers 1531, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    3. Chen, Yefeng & Jiang, Shuguang & Villeval, Marie Claire, 2016. "The Tragedy of Corruption," IZA Discussion Papers 10175, Institute of Labor Economics (IZA).
    4. Johannes Abeler & Daniele Nosenzo & Collin Raymond, 2019. "Preferences for Truth‐Telling," Econometrica, Econometric Society, vol. 87(4), pages 1115-1153, July.
    5. Daniel Parra & Manuel Munoz-Herrera & Luis Palacio, 2019. "The limits of transparency as a means of reducing corruption," Working Papers 20190026, New York University Abu Dhabi, Department of Social Science, revised May 2019.
    6. Giulia Mugellini & Sara Della Bella & Marco Colagrossi & Giang Ly Isenring & Martin Killias, 2021. "Public sector reforms and their impact on the level of corruption: A systematic review," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(2), June.
    7. Cappelen, Alexander W. & Fjeldstad, Odd-Helge & Mmari, Donald & Sjursen, Ingrid Hoem & Tungodden, Bertil, 2021. "Understanding the resource curse: A large-scale experiment on corruption in Tanzania," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 129-157.
    8. Luca Corazzini & Christopher Cotton & Tommaso Reggiani, 2020. "Delegation and coordination with multiple threshold public goods: experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1030-1068, December.
    9. Garbarino, Ellen & Slonim, Robert & Villeval, Marie Claire, 2019. "Loss aversion and lying behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 379-393.
    10. García-Gallego, Aurora & Georgantzis, Nikos & Jaber-López, Tarek & Michailidou, Georgia, 2020. "Audience effects and other-regarding preferences against corruption: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 159-173.

    More about this item

    Keywords

    embezzlement; corruption; dishonesty; transparency; 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

    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:iza:izadps:dp9925. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.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.