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Project Description

Summary:  View help for Summary Deferred Acceptance (DA), a widely implemented algorithm, is meant to improve allocations: under classical preferences, it induces preference-concordant rankings. However, recent evidence shows that—in both real, large-stakes applications and experiments—participants frequently play seemingly dominated, significantly costly, strategies that avoid small chances of good outcomes. We show theoretically why, with
expectations-based loss aversion, this behavior may be partly intentional. Reanalyzing existing experimental data on random serial dictatorship (a restriction of DA), we
show that such reference-dependent preferences, with a degree and distribution of loss
aversion that explain common levels of risk aversion elsewhere, fit the data better than
no-loss-aversion preferences.

Scope of Project

Subject Terms:  View help for Subject Terms lab experiment; discrete choice; maximum likelihodd
JEL Classification:  View help for JEL Classification
      B49 Economic Methodology: Other
      D47 Market Design
      D82 Asymmetric and Private Information; Mechanism Design
      D84 Expectations; Speculations
      D91 Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
Data Type(s):  View help for Data Type(s) experimental data

Methodology

Data Source:  View help for Data Source Li, S. (2017). Obviously Strategy-Proof Mechanisms. American Economic Review,
107(11):3257–87.

Unit(s) of Observation:  View help for Unit(s) of Observation Decisions (in a lab experiment)

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