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When less is more: Rationing and rent dissipation in stochastic contests

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  • Faravelli, Marco
  • Stanca, Luca

Abstract

This paper shows how to maximize revenue when a contest is noisy. We consider a case where two or more contestants bid for a prize in a stochastic contest where all bidders value the prize equally. We show that, whenever a Tullock contest yields under-dissipation, the auctioneerʼs revenue can be increased by optimally fixing the number of tickets. In particular, in a stochastic contest with proportional probabilities, it is possible to obtain (almost) full rent dissipation. We test this hypothesis with a laboratory experiment. The results indicate that, as predicted, revenue is significantly higher in a lottery with rationing than in a standard lottery. On the other hand, an alternative rationing mechanism that does not limit total expenditures fails to increase revenue relative to a standard lottery.

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  • Faravelli, Marco & Stanca, Luca, 2012. "When less is more: Rationing and rent dissipation in stochastic contests," Games and Economic Behavior, Elsevier, vol. 74(1), pages 170-183.
    • Handle: RePEc:eee:gamebe:v:74:y:2012:i:1:p:170-183
    DOI: 10.1016/j.geb.2011.05.008
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    2. Bayer, Ralph-Christopher, 2016. "Cooperation and distributive conflict," Games and Economic Behavior, Elsevier, vol. 97(C), pages 88-109.
    3. Roman M. Sheremeta, 2013. "Overbidding And Heterogeneous Behavior In Contest Experiments," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 491-514, July.
    4. Subhasish M. Chowdhury & Anwesha Mukherjee & Theodore L. Turocy, 2020. "That’s the ticket: explicit lottery randomisation and learning in Tullock contests," Theory and Decision, Springer, vol. 88(3), pages 405-429, April.
    5. Ian A. MacKenzie & Markus Ohndorf, 2016. "Caps on Coasean transfers," Oxford Economic Papers, Oxford University Press, vol. 68(2), pages 566-584.
    6. Damian S. Damianov & Ronald Peeters, 2018. "Prize‐Based Mechanisms For Fund‐Raising: Theory And Experiments," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1562-1584, July.
    7. Chen, Hong & Feng, Qun & Cao, Jing, 2014. "Rent-seeking mechanism for safety supervision in the Chinese coal industry based on a tripartite game model," Energy Policy, Elsevier, vol. 72(C), pages 140-145.
    8. Fallucchi, Francesco & Renner, Elke & Sefton, Martin, 2013. "Information feedback and contest structure in rent-seeking games," European Economic Review, Elsevier, vol. 64(C), pages 223-240.
    9. Paan Jindapon & Zhe Yang, 2020. "Free riders and the optimal prize in public‐good funding lotteries," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 22(5), pages 1289-1312, September.
    10. Subhasish M. Chowdhury & Patricia Esteve‐González & Anwesha Mukherjee, 2023. "Heterogeneity, leveling the playing field, and affirmative action in contests," Southern Economic Journal, John Wiley & Sons, vol. 89(3), pages 924-974, January.
    11. Liu, Xuyuan & Lu, Jingfeng, 2017. "Optimal prize-rationing strategy in all-pay contests with incomplete information," International Journal of Industrial Organization, Elsevier, vol. 50(C), pages 57-90.
    12. Sara Godoy & Miguel Meléndez-Jiménez & Antonio Morales, 2015. "No fight, no loss: underinvestment in experimental contest games," Economics of Governance, Springer, vol. 16(1), pages 53-72, February.

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    More about this item

    Keywords

    Stochastic contests; Rent seeking; Laboratory experiments;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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