Market Frictions, Arbitrage, and the Capitalization of Amenities
The price-amenity arbitrage is a cornerstone of spatial economics, as the response of land and house prices to shifts in the quality of local amenities and public goods is typically used to reveal households' willingness to pay for amenities. With informational, time, and cash constraints, households' ability to arbitrage across locations with different amenities (demographics, crime, education, housing) depends on their ability to compare locations and to finance the swap of houses. Arbitrageurs with deep pockets and better search and matching technology can take advantage of price dispersions and unexploited trade opportunities. We develop a disaggregated search and matching model of the housing market with endogenously bargained prices, identified on transaction-level data from the universe of deeds for 6,400+ neighborhoods of the Chicago metropolitan area, matched with school-level test scores and geocoded criminal offenses. Price-amenity gradients reflect preferences and the capitalization of trading opportunities, which are arbitraged away in the frictionless limit. Thus the time-variation in hedonic pricing coefficients partly reflects the time variation in search and credit frictions. Our model is able to explain that, between the peak of the housing boom and its trough, the sign of the price-amenity gradient flipped, due to the decline in trading opportunities in lower-amenity neighborhoods and due to the lower capitalization of trading opportunities in house prices.
We would like to thank Joël David, Morris Davis, Mariacristina De Nardi, Anthony Heyes, Matthew E. Kahn, Patrick Kehoe, Adam Lavecchia, Robert Lucas, Fabrizio Perri, Hashem Pesaran for helpful comments, as well as the audience of the Federal Reserve of Minneapolis seminar series, the University of Southern California’s conference on housing and the macroeconomy, the meeting of the Canadian Economics Association, and seminar series at the University of Ottawa and Université Laval. The authors acknowledge financial support from HEC, INET, and USC. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.