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The Town Airbnb and the Country Airbnb under Covid-19
[Airbnb des villes et des champs à l’épreuve de la Covid-19]

Author

Listed:
  • Yuheng Ling

    (Hainan Normal University [Haikou, China])

  • Yacine Allam

    (aivancity School for Technology, Business & Society [Cachan])

  • Marie-Laure Breuille

    (CESAER - Centre d'économie et de sociologie rurales appliquées à l'agriculture et aux espaces ruraux - UBFC - Université Bourgogne Franche-Comté [COMUE] - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Dijon - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

  • Camille Grivault

    (CESAER - Centre d'économie et de sociologie rurales appliquées à l'agriculture et aux espaces ruraux - UBFC - Université Bourgogne Franche-Comté [COMUE] - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Dijon - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

  • Julie Le Gallo

    (CESAER - Centre d'économie et de sociologie rurales appliquées à l'agriculture et aux espaces ruraux - UBFC - Université Bourgogne Franche-Comté [COMUE] - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Dijon - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

Abstract

In this article, we analyze the determinants of the supply of short term rentals through the activity of the Airbnb platform throughout metropolitan France. Based on the partitioning of the territory into city catchment areas, we highlight significant spatial heterogeneity, with highly attractive centers and, in contrast, less sought-after secondary centers. Depending on the period of restriction, the number of listings dropped from 10.03% during the first lockdown to 34.7% with the vaccination pass, although the effects varied according to the type of area. It mainly affected central towns, followed by secondary and main towns, and, to a very limited extent, rural areas outside city catchment areas, but had no significant impact on the surrounding areas in terms of available supply. Significant differences in the number of dwelling, occupancy rates and revenue generated are also apparent, depending on the type of listing (entire home or private room) or the host type (private or professional), reflecting in particular different ways of adjusting to the health crisis, through prices or quantities offered, and by zone.JEL classification: C33, L83, R31, Z32.

Suggested Citation

  • Yuheng Ling & Yacine Allam & Marie-Laure Breuille & Camille Grivault & Julie Le Gallo, 2024. "The Town Airbnb and the Country Airbnb under Covid-19 [Airbnb des villes et des champs à l’épreuve de la Covid-19]," Post-Print hal-04919893, HAL.
  • Handle: RePEc:hal:journl:hal-04919893
    DOI: 10.4000/12lph
    as

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    More about this item

    Keywords

    spatial heterogeneity; location touristique meublée; Covid-19;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development

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