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http://hdl.handle.net/10419/248447

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Aiding applicants: Leveling the playing field within the immediate acceptance mechanism

[working paper]

Basteck, Christian
Mantovani, Marco

Corporate Editor
Wissenschaftszentrum Berlin für Sozialforschung gGmbH

Abstract

In school choice problems, the widely used manipulable Immediate Acceptance mechanism (IA) disadvantages unsophisticated applicants, but may ex-ante Pareto dominate any strategy-proof alternative. In these cases, it may be preferable to aid applicants within IA, rather than to abandon it. In a labor... view more

In school choice problems, the widely used manipulable Immediate Acceptance mechanism (IA) disadvantages unsophisticated applicants, but may ex-ante Pareto dominate any strategy-proof alternative. In these cases, it may be preferable to aid applicants within IA, rather than to abandon it. In a laboratory experiment, we first document a substantial gap in strategy choices and outcomes between subjects of higher and lower cognitive ability under IA. We then test whether disclosing information on past applications levels the playing field. The treatment is effective in partially reducing the gap between applicants of above- and below-median cognitive ability and in curbing ability segregation across schools, but may leave the least able applicants further behind.... view less

Keywords
school choice; deprivation; cognitive ability; segregation; laboratory experiment

Classification
Sociology of Education

Free Keywords
immediate acceptance; mechanism design; strategy-proofness

Document language
English

Publication Year
2021

City
Berlin

Page/Pages
35 p.

Series
Discussion Papers / Wissenschaftszentrum Berlin für Sozialforschung, Forschungsschwerpunkt Markt und Entscheidung, Abteilung Verhalten auf Märkten, SP II 2021-203

Handle
http://hdl.handle.net/10419/248447

Status
Published Version; reviewed

Licence
Deposit Licence - No Redistribution, No Modifications


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.