It's Not Always Best to Be First

Working Paper: CEPR ID: DP12887

Authors: Aner Sela

Abstract: We study a model with n agents, each of whom has both a linear reward function that increases in the agent's effort and an effort constraint. However, since the effort (output) of the players has a negative effect on society the designer imposes a punishment such that the agent with the highest effort who caused the greatest damage is punished. We analyze the equilibrium of this model with either symmetric or asymmetric agents. At all the equilibrium points, all the agents are active and all have positive expected payoffs. We characterize the properties of the agents' equilibrium strategies and compare them to the well-known equilibrium strategies of the all-pay auction in which the agent with the highest effort wins a prize.

Keywords: contests; winner's curse

JEL Codes: C72; D44


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
effort output (E23)negative payoff due to punishment (D91)
asymmetric values for punishment (C72)expected total effort (C13)
stronger agent's reward function (C73)higher expected payoff (G40)
model's structure (C52)agent incentives to participate (L85)
symmetric agents exert positive effort (C72)positive expected payoffs (D84)

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