IDEAS home Printed from https://ideas.repec.org/a/anr/reveco/v12y2020p471-501.html
   My bibliography  Save this article

Revealed Preference Analysis of School Choice Models

Author

Listed:
  • Nikhil Agarwal
  • Paulo Somaini

Abstract

Preferences for schools are important determinants of equitable access to high-quality education, effects of expanded choice on school improvement, and school choice mechanism design. Standard methods for estimating consumer preferences are not applicable in education markets because students do not always get their first-choice school. This review describes recently developed methods for using rich data from a school choice mechanism to estimate student preferences. Our objectives are to present a unifying framework for these methods and to help applied researchers decide which techniques to use. After laying out methodological issues, we provide an overview of empirical results obtained using these models and discuss some open questions.

Suggested Citation

  • Nikhil Agarwal & Paulo Somaini, 2020. "Revealed Preference Analysis of School Choice Models," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 471-501, August.
    • Handle: RePEc:anr:reveco:v:12:y:2020:p:471-501
    DOI: 10.1146/annurev-economics-082019-112339
    as

    Download full text from publisher

    File URL: https://doi.org/10.1146/annurev-economics-082019-112339
    Download Restriction: Full text downloads are only available to subscribers. Visit the abstract page for more information.
    File URL: https://libkey.io/10.1146/annurev-economics-082019-112339?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matteo Bobba & Tim Ederer & Gianmarco León-Ciliotta & Christopher A. Neilson & Marco Nieddu, 2021. "Teacher compensation and structural inequality: Evidence from centralized teacher school choice in Perú," Economics Working Papers 1788, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Peng Shi, 2022. "Optimal Priority-Based Allocation Mechanisms," Management Science, INFORMS, vol. 68(1), pages 171-188, January.
    3. Amel Awadelkarim & Arjun Seshadri & Itai Ashlagi & Irene Lo & Johan Ugander, 2023. "Rank-heterogeneous Preference Models for School Choice," Papers 2306.01801, arXiv.org.
    4. Delaney, Judith M. & Devereux, Paul J., 2021. "High School Rank in Math and English and the Gender Gap in STEM," Labour Economics, Elsevier, vol. 69(C).
    5. Schwartz, Jacob & Song, Kyungchul, 2024. "The law of large numbers for large stable matchings," Journal of Econometrics, Elsevier, vol. 241(1).
    6. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo Somaini & Daniel Waldinger, 2021. "Equilibrium Allocations Under Alternative Waitlist Designs: Evidence From Deceased Donor Kidneys," Econometrica, Econometric Society, vol. 89(1), pages 37-76, January.
    7. Alfred Galichon & Bernard Salani'e, 2021. "Cupid's Invisible Hand: Social Surplus and Identification in Matching Models," Papers 2106.02371, arXiv.org, revised Jan 2023.
    8. Derek Neal & Joseph Root, 2024. "The Provision of Information and Incentives in School Assignment Mechanisms," NBER Chapters, in: New Directions in Market Design, National Bureau of Economic Research, Inc.
    9. Jessie Bruhn & Christopher Campos & Eric Chen, 2023. "Who Benefits from Remote Schooling? Self-Selection and Match Effects," Working Papers 2023-004, Brown University, Department of Economics.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:anr:reveco:v:12:y:2020:p:471-501. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: http://www.annualreviews.org (email available below). General contact details of provider: http://www.annualreviews.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.