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Atlanta Marriott Marquis, Marquis Ballroom A
Hosted By:
American Economic Association
Dysfunction in the Real Estate Market
Paper Session
Sunday, Jan. 6, 2019 10:15 AM - 12:15 PM
- Chair: Edward L. Glaeser, Harvard University
Computer Vision and Real Estate: Do Looks Matter and Do Incentives Determine Looks?
Abstract
How much does the appearance of a house, or its neighbors, impact its price? Do events that impact the incentives facing homeowners, like foreclosure, impact the maintenance and appearance of a home? Using computer-vision techniques, we find that a one standard deviation improvement in the appearance of a home in Boston is associated with a .16 log point increase in the home’s value, or about $55,000 at the sample mean. The additional predictive power created by images is modest relative to location and basic home variables, but external images do outperform variables collected by in-person home assessors. A home’s value increases by .7 log points, when its neighbor’s visually predicted value increases by one log point, and more visible neighbors have a larger price impact than less visible neighbors. Homes that went through foreclosure during the 2008-09 financial crisis experienced a .04 log point decline in their appearance-related value, relative to comparable homes, suggesting that foreclosures reduced the incentives to maintain the housing stock. We do not find more depreciation of appearance in rental properties, or more upgrading of appearance by owners before resale.Gentrification and the Amenity Value of Crime Reductions: Evidence from Rent Deregulation
Abstract
Gentrification involves large-scale neighborhood change whereby new residents and improved amenities increase property values. In this paper, we study whether and how much public safety improvements are capitalized by the housing market after an exogenous shock to the gentrification process. We use variation induced by the sudden end of rent control in Cambridge, Massachusetts in 1995 to examine within-Cambridge variation in reported crime across neighborhoods with different rent-control levels, abstracting from the prevailing city-wide decline in criminal activity. Using detailed location-specific incident-level criminal activity data assembled from Cambridge Police Department archives for the years 1992 through 2005, we find robust evidence that rent decontrol caused overall crime to fall by 16 percent—approximately 1,200 reported crimes annually—with the majority of the effect accruing through reduced property crime. By applying external estimates of criminal victimization’s economic costs, we calculate that the crime reduction due to rent deregulation generated approximately $10 million (in 2008 dollars) of annual direct benefit to potential victims. Capitalizing this benefit into property values, this crime reduction accounts for 15 percent of the contemporaneous growth in the Cambridge residential property values that is attributable to rent decontrol. Our findings establish that reductions in crime are an important part of gentrification and generate substantial economic value. They also show that standard cost-of-crime estimates are within the bounds imposed by the aggregate price appreciation due to rent decontrol.Collusion in Brokered Markets
Abstract
The residential real estate agency market presents a puzzle for economic theory: agent entry is common and agents' costs to provide service are low, yet commissions on real estate transactions have remained constant and high for decades. We model the real estate agency market, and other brokered markets, as a repeated extensive form game; in our game, brokers first post prices for customers and then choose which agents on the other side of the market to facilitate transactions with. We show that monopoly prices can be sustained (for a fixed discount factor) regardless of the number of brokers through strategies that condition willingness to transact with each broker on that broker's initial posted price. Our results can thus rationalize why this market exhibits both fierce competition for customers and pricing high above marginal cost; moreover, our model can help explain why agents and platforms who have tried to reduce commissions have had trouble entering the market.Discussant(s)
Benjamin Keys
,
University of Pennsylvania
Peter Coles
,
Airbnb
Eric Zwick
,
University of Chicago
Charles Gordon Nathanson
,
Northwestern University
JEL Classifications
- R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location
- D4 - Market Structure, Pricing, and Design