Data and Code for: Improving Efficiency of On-Campus Housing: An Experimental Study

Principal Investigator(s): View help for Principal Investigator(s) Yan Chen, University of Michigan; Tayfun Sönmez, Boston College

Version: View help for Version V2

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Project Citation:

Chen, Yan, and Sönmez, Tayfun. Data and Code for: Improving Efficiency of On-Campus Housing: An Experimental Study. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-09-29. https://doi.org/10.3886/E119541V2

Project Description

Summary: This paper investigates a class of matching problems—the assignment of indivisible items to agents where some agents have prior claims to some of the items. As a running example, we will refer to the indivisible items as houses. House allocation problems are not only of theoretical interest, but also of practical importance. A house allocation mechanism assigns a set of houses (or offices, tasks, etc.) to prospective tenants, allotting at most one house to each tenant. Rents are exogenously given and there is no medium of exchange, such as money. In general some houses will have existing tenants, some houses will be empty, and some applicants for housing will be new (e.g., freshmen). The canonical examples are assignment of college students to dormitory rooms and public housing units. Other examples are assignment of offices and tasks to individuals.

Scope of Project

Subject Terms: market design; house allocation; matching; top trading cycles

JEL Classification:
      D61 Allocative Efficiency; Cost-Benefit Analysis
      R31 Housing Supply and Markets
      R38 Production Analysis and Firm Location: Government Policy

Geographic Coverage: United States

Time Period(s): 9/1999 – 9/2000

Universe: undergraduate students at the University of Michigan.

Data Type(s): experimental data

Collection Notes:

Laboratory experiments conducted at the University of Michigan.

Methodology

Sampling: 480 subjects

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Published Versions

V2 [2020-09-29]

V1 [2020-09-17]

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