IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-04495637.html
   My bibliography  Save this paper

Airbnb and rents: evidence from Berlin

Author

Listed:
  • Tomaso Duso

    (DIW Berlin - German Institute for Economic Research, DIW Berlin - Deutsches Institut für Wirtschaftsforschung, TU - Technical University of Berlin / Technische Universität Berlin)

  • Claus Michelsen

    (DIW Berlin - Deutsches Institut für Wirtschaftsforschung, University of Potsdam = Universität Potsdam)

  • Maximilian Schäfer

    (DIW Berlin - Deutsches Institut für Wirtschaftsforschung, TU - Technical University of Berlin / Technische Universität Berlin)

  • Kevin Ducbao Tran

    (DIW Berlin - Deutsches Institut für Wirtschaftsforschung, TU - Technical University of Berlin / Technische Universität Berlin)

Abstract

Cities worldwide have regulated peer-to-peer short-term rental platforms claiming that those platforms remove apartments from the long-term housing market, causing an in- crease in rents. Establishing and quantifying such a causal link is, however, challenging. We investigate two policy changes in Berlin to first assess how effective they were in regulating Airbnb, the largest online peer-to-peer short-term rental platform. We document that the policy changes reduced the number of entire homes listed on Airbnb substantially, by eight to ten listings per square kilometer. In particular the introduction of limitations on the misuse of regular rental apartments as short-term accommodations, also strongly reduced the average number of days per year that Airbnb listings are available for booking. In a second step, we then use this policy-induced change in Airbnb supply to assess the impact of Airbnb on rents in the city. Our results suggest that each nearby apartment on Airbnb increases average monthly rents by at least seven cents per square meter. This effect is larger for Airbnb listings that are available for rent for a larger part of the year. Further analyses suggest some effect heterogeneity across the city. In particular, areas with lower Airbnb density tend to be affected more by additional Airbnb listings.

Suggested Citation

  • Tomaso Duso & Claus Michelsen & Maximilian Schäfer & Kevin Ducbao Tran, 2020. "Airbnb and rents: evidence from Berlin," Working Papers hal-04495637, HAL.
  • Handle: RePEc:hal:wpaper:hal-04495637
    DOI: 10.2139/ssrn.3676909
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:hal:wpaper:hal-04495637. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.