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Loews Philadelphia, Washington A
American Real Estate and Urban Economics Association
Residential Real Estate Pricing
Friday, Jan. 5, 2018 10:15 AM - 12:15 PM
- Chair: Anthony Yezer, George Washington University
The Sharing Economy and Housing Affordability: Evidence from Airbnb
AbstractWe 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
AbstractThis 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
AbstractUsing 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.
Florida State University
East Carolina University
U.S. Federal Housing Finance Agency
- R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location
- C3 - Multiple or Simultaneous Equation Models; Multiple Variables