IDEAS home Printed from https://ideas.repec.org/p/grz/wpaper/2020-06.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: http://www100.uni-graz.at/vwlwww/forschung/RePEc/wpaper/2020-06.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. Melser, Daniel, 2005. "The Hedonic Regression Time-Dummy Method and the Monotonicity Axioms," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 485-492, October.
    3. Robert J. Hill & Daniel Melser, 2008. "Hedonic Imputation And The Price Index Problem: An Application To Housing," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 593-609, October.
    4. Lawani, Abdelaziz & Reed, Michael R. & Mark, Tyler & Zheng, Yuqing, 2019. "Reviews and price on online platforms: Evidence from sentiment analysis of Airbnb reviews in Boston," Regional Science and Urban Economics, Elsevier, vol. 75(C), pages 22-34.
    5. Donald R. Haurin & Jessica L. Haurin & Taylor Nadauld & Anthony Sanders, 2010. "List Prices, Sale Prices and Marketing Time: An Application to U.S. Housing Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 38(4), pages 659-685, Winter.
    6. Toomet, Ott & Henningsen, Arne, 2008. "Sample Selection Models in R: Package sampleSelection," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i07).
    7. Kennedy, Peter E, 1981. "Estimation with Correctly Interpreted Dummy Variables in Semilogarithmic Equations [The Interpretation of Dummy Variables in Semilogarithmic Equations]," American Economic Review, American Economic Association, vol. 71(4), pages 801-801, September.
    8. Rainer Schulz & Martin Wersing & Axel Werwatz, 2014. "Automated valuation modelling: a specification exercise," Journal of Property Research, Taylor & Francis Journals, vol. 31(2), pages 131-153, June.
    9. Mick Silver, 2016. "How to Better Measure Hedonic Residential Property Price Indexes," IMF Working Papers 2016/213, International Monetary Fund.
    10. McMillen, Daniel P., 1996. "One Hundred Fifty Years of Land Values in Chicago: A Nonparametric Approach," Journal of Urban Economics, Elsevier, vol. 40(1), pages 100-124, July.
    11. Robert J. Hill, 2013. "Hedonic Price Indexes For Residential Housing: A Survey, Evaluation And Taxonomy," Journal of Economic Surveys, Wiley Blackwell, vol. 27(5), pages 879-914, December.
    12. Lee, Lung-Fei, 1978. "Unionism and Wage Rates: A Simultaneous Equations Model with Qualitative and Limited Dependent Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 19(2), pages 415-433, June.
    13. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
    14. W. Erwin Diewert, 2003. "Hedonic Regressions. A Consumer Theory Approach," NBER Chapters, in: Scanner Data and Price Indexes, pages 317-348, National Bureau of Economic Research, Inc.
    15. Horn, Keren & Merante, Mark, 2017. "Is home sharing driving up rents? Evidence from Airbnb in Boston," Journal of Housing Economics, Elsevier, vol. 38(C), pages 14-24.
    16. Benjamin Edelman & Michael Luca & Dan Svirsky, 2017. "Racial Discrimination in the Sharing Economy: Evidence from a Field Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 9(2), pages 1-22, April.
    17. Alicia N. Rambaldi & D.S. Prasada Rao, 2013. "Econometric Modeling and Estimation of Theoretically Consistent Housing Price Indexes," CEPA Working Papers Series WP042013, School of Economics, University of Queensland, Australia.
    18. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    19. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    20. Kolbe, Jens & Schulz, Rainer & Wersing, Martin & Werwatz, Axel, 2020. "How useful is listings data for research?," FORLand Working Papers 19 (2020), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    21. Robert J. Hill & Michael Scholz, 2018. "Can Geospatial Data Improve House Price Indexes? A Hedonic Imputation Approach with Splines," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(4), pages 737-756, December.
    22. Shimizu, Chihiro & Nishimura, Kiyohiko G. & Watanabe, Tsutomu, 2016. "House prices at different stages of the buying/selling process," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 37-53.
    23. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-247, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robert J. Hill & Alicia N. Rambaldi & Michael Scholz, 2021. "Higher frequency hedonic property price indices: a state-space approach," Empirical Economics, Springer, vol. 61(1), pages 417-441, July.
    2. Hill, Robert J. & Trojanek, Radoslaw, 2022. "An evaluation of competing methods for constructing house price indexes: The case of Warsaw," Land Use Policy, Elsevier, vol. 120(C).
    3. Chen, Jie & Chen, Yu & Hill, Robert J. & Hu, Pei, 2022. "The user cost of housing and the price-rent ratio in Shanghai," Regional Science and Urban Economics, Elsevier, vol. 92(C).
    4. Lepinteur, Anthony & Waltl, Sofie R., 2020. "Tracking Owners' Sentiments: Subjective Home Values, Expectations and House Price Dynamics," Department of Economics Working Paper Series 299, WU Vienna University of Economics and Business.
    5. Silver Mick, 2022. "Econometric Issues in Hedonic Property Price Indices: Some Practical Help," Journal of Official Statistics, Sciendo, vol. 38(1), pages 153-186, March.
    6. Daniel Melser, 2023. "Selection Bias in Housing Price Indexes: The Characteristics Repeat Sales Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 623-637, June.
    7. Wilmar Alexander Cabrera-Rodríguez & Juan Sebastián Mariño-Montaña & Carlos Andrés Quicazán-Moreno, 2019. "Modelos hedónicos con efectos espaciales: una aproximación al cálculo de índices de precios de vivienda para Bogotá," Borradores de Economia 1072, Banco de la Republica de Colombia.
    8. Ahlfeldt, Gabriel M. & Heblich, Stephan & Seidel, Tobias, 2023. "Micro-geographic property price and rent indices," Regional Science and Urban Economics, Elsevier, vol. 98(C).
    9. Lily Shen & Stephen L. Ross, 2019. "Information Value of Property Description: A Machine Learning Approach," Working papers 2019-20, University of Connecticut, Department of Economics, revised Sep 2020.
    10. Hill, Robert J. & Syed, Iqbal A., 2016. "Hedonic price–rent ratios, user cost, and departures from equilibrium in the housing market," Regional Science and Urban Economics, Elsevier, vol. 56(C), pages 60-72.
    11. Mick Silver, 2016. "How to Better Measure Hedonic Residential Property Price Indexes," IMF Working Papers 2016/213, International Monetary Fund.
    12. Adrian Pagan, 1986. "Two Stage and Related Estimators and Their Applications," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 517-538.
    13. Robert J. Hill & Alicia N. Rambaldi, 2022. "Hedonic Models and House Price Index Numbers," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 413-444, Springer.
    14. Jens Kolbe & Rainer Schulz & Martin Wersing & Axel Werwatz, 2021. "Real estate listings and their usefulness for hedonic regressions," Empirical Economics, Springer, vol. 61(6), pages 3239-3269, December.
    15. Shen, Lily & Ross, Stephen, 2021. "Information value of property description: A Machine learning approach," Journal of Urban Economics, Elsevier, vol. 121(C).
    16. Yuen Leng Chow & Isa E. Hafalir & Abdullah Yavas, 2015. "Auction versus Negotiated Sale: Evidence from Real Estate Sales," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(2), pages 432-470, June.
    17. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Incomplete panels and selection bias : A survey," Discussion Paper 1992-7, Tilburg University, Center for Economic Research.
    18. Eric Rasmusen, 1995. "Observed Choice, Estimation, and Optimism About Policy Changes," Econometrics 9506004, University Library of Munich, Germany, revised 16 Jun 1995.
    19. Chunfang Zhao & Yingliang Wu & Yunfeng Chen & Guohua Chen, 2023. "Multiscale Effects of Hedonic Attributes on Airbnb Listing Prices Based on MGWR: A Case Study of Beijing, China," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    20. Rama Lionel Ngenzebuke, 2016. "Female say on income and child outcomes: Evidence from Nigeria," WIDER Working Paper Series 134, World Institute for Development Economic Research (UNU-WIDER).

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:grz:wpaper:2020-06. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Michael Scholz (email available below). General contact details of provider: https://edirc.repec.org/data/vgrazat.html .

    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.