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The Airbnb Rent-Premium and the Crowding-Out of Long-Term Rentals

Author

Listed:
  • Robert J. Hill

    (University of Graz, Austria)

  • Norbert Pfeifer

    (University of Graz, Austria)

  • Miriam Steurer

    (University of Graz, Austria)

Abstract

Concerns about crowding out of long-term rentals have led many cities to impose limits on the number of days per year that properties can be let via Airbnb or other short-term rental platforms. The effectiveness of such limits depends on the size of the Airbnb rent premium (i.e., how much more landlords can earn on Airbnb). We estimate these Airbnb rent premia for each of 170 000 Airbnb and long-term rental apartments in Sydney, Australia, using both hedonic and matching methods. The estimated premia on Airbnb apartments are not distorted by selection bias. We find that between 2015 and 2018, the Airbnb rent premium fell as Airbnb supply increased. Premia were fairly stable across neighborhoods, although larger and more expensive properties and those managed by owners of multiple Airbnb properties had higher premia. After adjusting for extra costs incurred by landlords on Airbnb, we find that, on average, tax-paying landlords break even after 220 days on Airbnb. A proposed 180-day per year Airbnb limit would therefore incentivize most landlords to prefer the long-term rental market. However, a much lower 138-day limit would be needed for tax-avoiding landlords.

Suggested Citation

  • Robert J. Hill & Norbert Pfeifer & Miriam Steurer, 2020. "The Airbnb Rent-Premium and the Crowding-Out of Long-Term Rentals," Graz Economics Papers 2020-06, University of Graz, Department of Economics.
  • Handle: RePEc:grz:wpaper:2020-06
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    References listed on IDEAS

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    More about this item

    Keywords

    Airbnb rent premium; regulating the sharing economy; hedonic prediction; characteristic matching; marginal landlord;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development

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