Andrew Kloosterman

dblp:162/2527 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
0009-0001-0477-5749ORCID · reported

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Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2023 Rankings-Dependent Preferences: A Real Goods Matching Experiment
abstract
In strategyproof mechanisms, it is always an optimal strategy for agents to truthfully report their private information to the mechanism. This theoretical property is clearly appealing, as it gives a mechanism designer the ability to predict play and make meaningful statements about other criteria such as welfare. However, a growing body of empirical evidence has documented significant deviations from truthful reporting in such mechanisms. This issue is particularly important in matching markets, the focus in this paper.
Andrew Kloosterman, Peter Troyan
EC1