Costly Information Acquisition in Centralized Matching Markets

Rustamdjan Hakimov, Dorothea Kübler and Siqi Pan
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Siqi Pan: University of Melbourne

No 280, Rationality and Competition Discussion Paper Series from CRC TRR 190 Rationality and Competition

Abstract: Every year during school and college admissions, students and their parents devote considerable time and effort to acquiring costly information about their own preferences. In a market where students are ranked by universities based on exam scores, we explore ways to reduce wasteful information acquisition that is, to help students avoid acquiring information about their out-of-reach schools or universities using a market design approach. We find that, both theoretically and experimentally, a sequential serial dictatorship mechanism leads to less wasteful information acquisition and higher student welfare than a direct serial dictatorship mechanism. This is because the sequential mechanism informs students about which universities are willing to admit them, thereby directing their search. Additionally, our experiments show that the sequential mechanism has behavioral advantages because subjects deviate from the optimal search strategy less frequently under the sequential than under the direct mechanism. We also investigate the effects of providing historical cutoff scores under the direct mechanism. We find that the cutoff provision can increase student welfare, especially when the information costs are high, although the effect is weaker than that of a sequential mechanism.

Keywords: matching market; deferred acceptance; information acquisition; game theory; lab experiment (search for similar items in EconPapers)
JEL-codes: C92 D47 (search for similar items in EconPapers)
Date: 2021-02-26
New Economics Papers: this item is included in nep-des and nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Journal Article: Costly information acquisition in centralized matching markets (2023)
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