Residential Real Estate Pricing
Friday, Jan. 4, 2019 10:15 AM - 12:15 PM
- Chair: Paul Anglin, University of Guelph
The Cross-Section of Expected Housing Returns
AbstractThis paper performs a large-scale empirical asset pricing analysis of the cross-section of residential real-estate returns. Using monthly housing returns for 9,831 different zip codes across 178 Metropolitan Statistical Areas (MSAs), we estimate, for each MSA, a multifactor model with systematic housing-market risk (U.S. and local MSA) and idiosyncratic zip code-specific housing risk. We find that U.S. and MSA housing risks are positively priced in 26% and 22% of the MSAs, respectively. The evidence that MSA-level housing-market risk is priced in roughly a fifth of all MSAs runs counter to the common belief that the U.S. housing market is locally segmented. We also find that idiosyncratic risk is positively priced only in 22% of the MSAs, suggesting that the under-diversification of households' real estate portfolios is not widely priced. In the last part of the paper, we link MSA variation in the pricing of risk to MSA fundamentals. We find that illiquidity is important for the pricing of the U.S. housing-market risk, while homeownership increases the probability that MSA-level risk is positively priced. Idiosyncratic risk is more likely to be positively priced in MSAs with less undevelopable land and lower liquidity, indicating that under-diversification is more binding when households face fewer housing supply constraints and more illiquidity.
Toxic Assets: How the Housing Market Responds to Environmental Information Shocks
AbstractIn March 2000, a number of polluting industries, including fossil fuel power plants, were added to the list publicly reporting pollution releases in the Toxics Release Inventory (TRI). Employing microdata from Zillow, which contain information on millions of property transactions and detailed corresponding home characteristics, we examine how housing markets respond to new information about reported toxic pollution by nearby facilities. We investigate this using a regression discontinuity design, which exploits the discrete information shock with fine microdata over time and space. Contrary to prior findings that TRI information does not influence household actions, we find the additional TRI data caused households to revise priors on ambient pollution levels, leading to an immediate reduction in home prices near the most toxic plants after the release. Effects appear isolated to homes within just a few miles of reporting facilities. From a policy standpoint, the results imply that there remains a role for government as provider of information that markets subsequently incorporate into prices.
What's Lost in the Aggregate: Lessons from a Local Index of Housing Supply Elasticities
AbstractA growing divergence between supply and demand has led to the current "housing affordability crisis," but little is systematically understood about the local factors that created this divergence. We estimate the first municipality-level index of housing supply elasticities in Los Angeles County, using a structural vector auto-regression model with sign restrictions to identify the effect of a positive demand shock. We find that these supply elasticities are lower than previous estimates, illustrating the degree to which supply is restricted in local housing markets. We document significant heterogeneity across the metropolitan area. The supply curve is less elastic in lower-income, higher-density central cities, pushing construction out to the periphery and contributing to urban sprawl, longer commute times, less agglomeration, and suboptimal allocation of housing.
- R2 - Household Analysis
- G1 - General Financial Markets