Biasing Unbiased Dynamic Contests

44 Pages Posted: 29 May 2018 Last revised: 2 Oct 2018

See all articles by Stefano Barbieri

Stefano Barbieri

Tulane University - Department of Economics

Marco Serena

Max Planck Institute for Tax Law and Public Finance

Date Written: August 8, 2018

Abstract

We consider a best-of-three Tullock contest between two ex-ante identical players. An effort-maximizing designer commits to a vector of player-specific biases (advantages or disadvantages). In our benchmark model the designer chooses victory-dependent biases (i.e., the biases depend on the record of matches won by players); the effort-mazimizing biases eliminate the discouragement effect, leaving players equally likely to win each match and the overall contest. We contrast our benchmark model with one where the designer chooses victory-independent biases; the effort-maximizing biases leave players unequally likely to win each match and the overall contest. This result holds in Tullock contests and all-pay auctions, as well as under maximization of total effort and winner's effort. The appeal of our result comes from the players being ex-ante identical; thus, it challenges the conventional wisdom of optimality of unbiased contests. Our result has also an applied interest, as it shows that alternating biases, as when teams alternate home and away games, may increase total effort as opposed to an unbiased contest.

Suggested Citation

Barbieri, Stefano and Serena, Marco, Biasing Unbiased Dynamic Contests (August 8, 2018). Working Paper of the Max Planck Institute for Tax Law and Public Finance No. 2018-06. Available at SSRN: https://ssrn.com/abstract=3180545 or http://dx.doi.org/10.2139/ssrn.3180545

Stefano Barbieri

Tulane University - Department of Economics ( email )

New Orleans, LA 70118
United States

Marco Serena (Contact Author)

Max Planck Institute for Tax Law and Public Finance ( email )

Marstallplatz 1
Munich, 80539
Germany

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