Dataset for "Matching in the large: An experimental study"

DOI

We compare the performance of the Boston Immediate Acceptance (IA) and Gale--Shapley Deferred Acceptance (DA) mechanisms in a laboratory setting where we increase the number of participants per match. In our experiment, we first increase the number of students per match from 4 to 40; when we do so, participant truth-telling increases under DA but decreases under IA, leading to a decrease in efficiency under both mechanisms. Furthermore, we find that DA remains more stable than IA, regardless of scale. We then further increase the number of participants per match to 4,000 through the introduction of robots. When robots report their preferences truthfully, we find that scale has no effect on human best response behavior. By contrast, when we program the robots to draw their strategies from the distribution of empirical human strategies, we find that our increase in scale increases human ex-post best responses under both mechanisms.

College students in Beijing, China.

All sessions are conducted in Chinese at the Experiment Economics Laboratory and the Finance Simulation Laboratory at Beijing Normal University between June 2012 and May 2013. The subjects are students from Beijing Normal University and the Beijing University of Posts and Telecommunications. No subject participates more than once. We conduct 12 independent sessions for the all-human treatments and 320 independent observations for the human–robot treatments, with a total of 736 subjects. The exchange rate is 5 experiment points for 1 RMB for all sessions. Each subject also receives a participation fee of 5 RMB. The average earning (including participation fee) is 63.8 RMB.

Identifier
DOI https://doi.org/10.3886/E103521V1
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:766805
Provenance
Creator Chen, Yan; Jiang, Ming; Kesten, Onur; Robin, Stéphane; Zhu, Min
Publisher ICPSR - Interuniversity Consortium for Political and Social Research
Contributor National Science Foundation; Agence Nationale de la Recherche; National Natural Science Foundation of China; ANR; Shanghai Pujiang Program
Publication Year 2020
Rights Download; This study is freely available to the general public via web download.
OpenAccess true
Contact ICPSR - Interuniversity Consortium for Political and Social Research
Representation
Resource Type Dataset; experimental data
Discipline Social Sciences