This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

« Back to Results

Residential Real Estate Pricing

Paper Session

Friday, Jan. 5, 2018 10:15 AM - 12:15 PM

Loews Philadelphia, Washington A
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Anthony Yezer, George Washington University

Do Airbnb Properties Affect House Prices?

Stephen Sheppard
,
Williams College
Andrew Udell
,
Dropbox

Abstract

A central complaint concerning Airbnb focuses on the impact of short-term rental properties on the value of residential property. A report prepared by the Office of the Attorney General of the State of New York lists these impacts among a number of concerns: do Airbnb rentals provide a black market in unsafe hotels? Do short-term rentals make New York City less affordable? Is the influx of out-of-town visitors upsetting the quiet of longstanding residential neighborhoods? These concerns pose difficulties because they imply different impacts on the values of residential properties. If short-term rentals provided via Airbnb create a concentration of what are effectively unsafe hotels, upsetting quiet residential neighborhoods, they would generate a local concentration of externalities that might be expected to depress property values rather than make housing less affordable. Alternatively, if these externality effects are modest relative to the impacts of space diverted from providing housing for residents to providing short-term accommodation for visitors, then local concentration of Airbnb properties may increase house prices. Perhaps because of this confusion, it is possible to find divergent viewpoints expressed about the impacts of Airbnb in the popular press and in consultant reports, but (to our knowledge) no careful study that estimates the direct impact of Airbnb rental availability on house prices. This paper presents such a study in the context of New York City.

The Sharing Economy and Housing Affordability: Evidence from Airbnb

Edward Kung
,
University of California-Los Angeles
Kyle Barron
,
University of California-Los Angeles

Abstract

We assess the impact of Airbnb on residential house prices and rental rates. Using publicly available data scraped from Airbnb covering 16 cities, we regress zipcode level house prices and rental rates on the number of Airbnb listings, controlling for zipcode level effects, arbitrary city level time trends, and unobserved zipcode level shocks using a shift-share instrument based on internet search interest for Airbnb interacted with how attractive a zipcode is for tourists. We find that on average, Airbnb has a modest, positive effect on house prices and a precisely estimated zero effect on rental rates. However, the effect on rental rates is positive and statistically significant in zipcodes with higher shares of renters, and when the units listed on Airbnb are more substitutable with the long term rental market. We present a simple model to rationalize these findings.

Think Globally, Aggregate Locally: Index Consistency in the Presence Asymmetric Appreciation

Thom Malone
,
Harvard University
Christian Redfearn
,
University of Southern California

Abstract

This paper highlights the role of housing submarkets that are often overlooked in the construction of aggregate housing price indexes. These local dynamics can present sources of significant bias in aggregate indexes if the sample of sold homes is not representative of the stock as a whole. We address both asymmetric appreciation and nonrandom selection across submarkets. We derive the conditions under which generalizing typically estimated parameters to the housing stock is possible, but provides evidence that these conditions are generally violated in practice. Specifically, it appears that internal metropolitan dynamics produce uneven appreciation and sales rates that lead to biased estimates of aggregate price because the sample on which they are based is representative neither of the stock nor its appreciation. The proposed solution is to estimate local indexes, aggregating these indexes by the housing stock they represent rather than by their share in the observed sample of sales. Local indexes better capture local hedonic pricing and land values than do the “global” indexes. Pooling local observations and the pooling the resulting local indexes suggest that submarket price and volume dynamics should not be ignored when making inferences about aggregate house prices.

U.S. Metropolitan House Price Dynamics

Steven Bourassa
,
Florida Atlantic University
Janne Engblom
,
University of Turku
Martin Hoesli
,
University of Geneva
Elias Oikarinen
,
University of Turku

Abstract

Using data for the 50 largest U.S. Metropolitan Statistical Areas (MSAs), this study contributes to the literature on regional heterogeneity in house price dynamics in several ways. We use recent advances in panel econometrics that allow for regional heterogeneity, cross-sectional dependence, and nonstationary but cointegrated data. We formally test for regional differences and explore the relationships between the price elasticity of housing supply and the income elasticity of prices, as well as bubble size and duration. The estimated mean long-term elasticity of house prices with respect to aggregate personal income is 0.86 across MSAs, but varies considerably between cities. Short-term momentum and reversion dynamics also show substantial regional heterogeneity. The dynamics are significantly associated with the price elasticity of housing supply. The long-term income elasticity generally is greater, short-term momentum is stronger, and adjustment towards the long-term fundamental price level is weaker in the more supply-inelastic MSAs. Hence, while house price cycles around long-term fundamental price levels typically are highly synchronized across MSAs within the same region, house price bubbles tend to be larger and longer-lasting in the MSAs with more inelastic housing supply.
Discussant(s)
Daniel Broxterman
,
Florida State University
Chun Kuang
,
East Carolina University
William Larson
,
U.S. Federal Housing Finance Agency
Eric Rosenblatt
,
Fannie Mae
JEL Classifications
  • R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location
  • C3 - Multiple or Simultaneous Equation Models; Multiple Variables