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Can Information Reduce Ethnic Discrimination? Evidence from Airbnb

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Listed:
  • Morgane Laouénan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, LIEPP - Laboratoire interdisciplinaire d'évaluation des politiques publiques (Sciences Po) - Sciences Po - Sciences Po)

  • Roland Rathelot

    (ENSAE - Ecole Nationale de la Statistique et de l'Analyse Economique - Ecole Nationale de la Statistique et de l'Analyse Economique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

Abstract

We use data from Airbnb to identify the mechanisms underlying discrimination against ethnic minority hosts. Within the same neighborhood, hosts from minority groups charge 3.2 percent less for comparable listings. Since ratings provide guests with increasingly rich information about a listing's quality, we can measure the contribution of statistical discrimination, building upon Altonji and Pierret (2001). We find that statistical discrimination can account for the whole ethnic price gap: ethnic gaps would disappear if all unobservables were revealed. Also, three-quarters (2.5 points) of the initial ethnic gap can be attributed to inaccurate beliefs of potential guests about hosts' average group quality.

Suggested Citation

  • Morgane Laouénan & Roland Rathelot, 2022. "Can Information Reduce Ethnic Discrimination? Evidence from Airbnb," Post-Print hal-03930675, HAL.
    • Handle: RePEc:hal:journl:hal-03930675
    DOI: 10.1257/app.20190188
    Note: View the original document on HAL open archive server: https://hal.science/hal-03930675v1
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    Cited by:

    1. Simonovits, Gábor & Simonovits, Bori, 2022. "Csökkenthető-e a diszkrimináció a megosztáson alapuló gazdaságban? Egy magyarországi telekocsioldalon végzett kísérleti kutatás eredményei [Can discrimination be decreased in the new platform econo," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1457-1474.
    2. Marius Brülhart & Gian-Paolo Klinke & Andrea Marcucci & Dominic Rohner & Mathias Thoenig, 2023. "Price and Prejudice: Housing Rents Reveal Racial Animus," CESifo Working Paper Series 10369, CESifo.
    3. Sekou Keita & Thomas Renault & Jérôme Valette, 2024. "The Usual Suspects: Offender Origin, Media Reporting and Natives’ Attitudes Towards Immigration," The Economic Journal, Royal Economic Society, vol. 134(657), pages 322-362.
    4. Chen, Yutong, 2024. "Does the gig economy discriminate against women? Evidence from physicians in China," Journal of Development Economics, Elsevier, vol. 169(C).
    5. Boto-García, David & Balado-Naves, Roberto & Mayor, Matías & Baños-Pino, José Francisco, 2023. "Consumers' demand for operational licencing: evidence from Airbnb in Paris," Annals of Tourism Research, Elsevier, vol. 100(C).
    6. Morris, J., 2023. "The Impact of Qualitative Reviews on Racial Statistical Discrimination: Evidence from Airbnb," Cambridge Working Papers in Economics 2331, Faculty of Economics, University of Cambridge.

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • L84 - Industrial Organization - - Industry Studies: Services - - - Personal, Professional, and Business Services

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