Optimal contest design: Tuning the heat

Letina, Igor; Liu, Shuo; Netzer, Nick

doi:10.1016/j.jet.2023.105616

Cited by 8 publications

(3 citation statements)

References 48 publications

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“…By contrast, I find that when contestants have different and privately known types, the designer may find it optimal to utilize winner‐takes‐all or several descending prizes. The sharp contrast between my results and those of Letina, Liu, and Netzer (2023) highlights the role played by private information.…”

Section: Introductioncontrasting

confidence: 99%

“…Fang, Noe, and Strack (2020) characterize the optimal prize profile for noiseless contests. Letina, Liu, and Netzer (2023) take a unifying approach and allow the designer to choose both the prize profile and the contest format. With n contestants, they find that it is always optimal for the designer to utilize a nested Tullock contest with

n - 1

identical prizes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal contests with incomplete information and convex effort costs

Zhang

2024

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I investigate the design of effort‐maximizing mechanisms when agents have both private information and convex effort costs, and the designer has a fixed prize budget. I first demonstrate that it is always optimal for the designer to utilize a contest with as many participants as possible. Further, I identify a necessary and sufficient condition for the winner‐takes‐all prize structure to be optimal. When this condition fails, the designer may prefer to award multiple prizes of descending sizes. I also provide a characterization of the optimal prize allocation rule for this case. Finally, I illustrate how the optimal prize distribution evolves as the contest size grows.

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Section: Introductioncontrasting

confidence: 99%

n - 1

identical prizes.…”

Section: Introductionmentioning

confidence: 99%

Optimal contests with incomplete information and convex effort costs

Zhang

2024

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“…A loser-gets-nothing contest can be optimal when the contest designer can select both the prize structure and the contest-success function, seeLetina, Liu, and Netzer (2023).…”

mentioning

confidence: 99%

Player Strength and Effort in Contests

Giebe,

Gürtler

2024

SSRN Journal

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Costly information providing in binary contests

Simon,

Levy,

Sarne

2024

Ann Math Artif Intell

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Contests are commonly used as a mechanism for eliciting effort and participation in multi-agent settings. Naturally, and much like with various other mechanisms, the information provided to the agents prior to and throughout the contest fundamentally influences its outcomes. In this paper we study the problem of information providing whenever the contest organizer does not initially hold the information and obtaining it is potentially costly. As the underlying contest mechanism for our model we use the binary contest, where contestants’ strategy is captured by their decision whether or not to participate in the contest in the first place. Here, it is often the case that the contest organizer can proactively obtain and provide contestants information related to their expected performance in the contest. We provide a comprehensive equilibrium analysis of the model, showing that even when such information is costless, it is not necessarily the case that the contest organizer will prefer to obtain and provide it to all agents, let alone when the information is costly.

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Optimal contest design: Tuning the heat

Cited by 8 publications

References 48 publications

Optimal contests with incomplete information and convex effort costs

Optimal contests with incomplete information and convex effort costs

Player Strength and Effort in Contests

Costly information providing in binary contests

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