Entrant-optimal learning in a contest game

Zeng Lian, Shuo Xu and Jie Zheng

Journal of Mathematical Economics, 2025, vol. 120, issue C

Abstract: We consider a private value single-prize asymmetric information Tullock contest between an incumbent and an entrant. The incumbent’s prize value is common knowledge, whereas the entrant is uncertain about her value and strategically acquires information to learn about it before the contest. Inspired by Roesler and Szentes (2017), we study how the entrant’s endogenous learning influences strategic contest effort choices. The entrant faces a tradeoff between more uncertainty about her value and less intense competition. If the entrant’s value is ex ante weakly lower than the incumbent’s value, full learning is the optimal strategy. However, if the entrant’s value is ex ante the higher one, no learning can be more advantageous than full learning.

Keywords: Tullock contest; Asymmetric information; Endogenous learning; Constrained information design (search for similar items in EconPapers)
JEL-codes: D72 D82 D83 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:mateco:v:120:y:2025:i:c:s0304406825000746

DOI: 10.1016/j.jmateco.2025.103157

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