Computer Vision and Real Estate: Do Looks Matter and Do Incentives Determine Looks?

Working Paper: NBER ID: w25174

Authors: Edward L. Glaeser; Michael Scott Kincaid; Nikhil Naik

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 $68,000 at the sample mean. The additional predictive power created by images is small 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 .4 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.

Keywords: computer vision; real estate; housing prices; foreclosure; home appearance

JEL Codes: C40; G21; R30; Z11


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Home appearance (R21)Home value (R31)
Neighbors' predicted value (C21)Subject home's value (Y20)
Foreclosure (G33)Home appearance-related value (R21)

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