Tiered Housing Allocation with Preannounced Rankings: An Experimental Analysis

We study in the laboratory a variant of the house allocation with existing tenants problem where subjects are partitioned into tiers with hierarchical privileges, and they know their position in the priority queue before making their decision. We evaluate the performance of the modified versions of...

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Bibliographic Details
Published inJournal of economics & management strategy Vol. 25; no. 1; pp. 133 - 160
Main Authors Carrillo, Juan D., Singhal, Saurabh
Format Journal Article
LanguageEnglish
Published Cambridge Blackwell Publishing Ltd 01.03.2016
Blackwell
Wiley Subscription Services, Inc
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ISSN1058-6407
1530-9134
DOI10.1111/jems.12143

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Summary:We study in the laboratory a variant of the house allocation with existing tenants problem where subjects are partitioned into tiers with hierarchical privileges, and they know their position in the priority queue before making their decision. We evaluate the performance of the modified versions of three well‐known mechanisms: Top Trading Cycle (TTC), Gale‐Shapley, and Random Serial Dictatorship (RSD) with Squatting Rights. For all three mechanisms, we find low rates of participation (around 40%), high rates of truth‐telling conditional on participation (around 90%), high proportions of fair allocations (above 90%), and significant efficiency losses. We also observe differences across mechanisms: RSD is ranked highest in efficiency and TTC is ranked lowest in fairness. We then show that position in the queue has a positive and significant impact on participation whereas tier has little effect on behavior. Finally, the individual analysis reveals that the majority of subjects who do not play according to the theory still follow discernible patterns of participation and preference revelation.
Bibliography:Appendix C: Sample of Instructions (tTTC mechanism)
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We thank Ricardo Alonso, Manuel Castro, Arya Gaduh, Brijesh Pinto, Smriti Sharma, and the audience at various seminars for helpful comments, and Chris Crabbe for developing the software. We thank the LUSK center for Real Estate and the Microsoft Corporation for financial support. Juan D. Carrrillo also gratefully acknowledges the support of the National Science Foundation, grant SES 1425062. All remaining errors are our own.
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ISSN:1058-6407
1530-9134
DOI:10.1111/jems.12143