Does Airbnb Reduce Matching Frictions in the Housing Market?

39 Pages Posted: 16 Sep 2021

See all articles by Abdollah Farhoodi

Abdollah Farhoodi

University of Toronto - Department of Economics

Nazanin Khazra

University of Toronto

Peter Christensen

University of Illinois at Urbana-Champaign

Date Written: September 14, 2021

Abstract

There is growing concern about the impact of the home-sharing markets on housing affordability, yet the underlying mechanisms are not well-studied. We use a theoretical model to provide key results on the mechanisms through which home-sharing can improve the quality of matches between buyers and sellers in the housing market. We then test these predictions empirically using daily Airbnb data for the entire U.S. and a novel shift-share approach. We find that an increase in Airbnb increases house prices, reduces total sales, increases for-sales inventory, increases sellers' time on the market, and reduces the probability of selling a house. The empirical evidence supports the hypothesis that Airbnb has reduced matching frictions in the housing market. We then examine heterogeneous responses to Airbnb using Generalized Random Forest (GRF). Consistent with our theoretical model, results from the GRF model indicate that locations with a less elastic housing supply respond more to the Airbnb growth.

Keywords: Sharing Economy, House Prices, Matching

JEL Classification: R31, C78, L86

Suggested Citation

Farhoodi, Abdollah and Khazra, Nazanin and Christensen, Peter, Does Airbnb Reduce Matching Frictions in the Housing Market? (September 14, 2021). Available at SSRN: https://ssrn.com/abstract=3923826 or http://dx.doi.org/10.2139/ssrn.3923826

Abdollah Farhoodi (Contact Author)

University of Toronto - Department of Economics ( email )

150 St George
Toronto, Ontario M5S3G7
Canada

Nazanin Khazra

University of Toronto ( email )

Toronto, Ontario M5S 3G8
Canada

Peter Christensen

University of Illinois at Urbana-Champaign ( email )

601 E John St
Champaign, IL 61820
United States

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