Valuing Curb Appeal
Erik B Johnson (),
Alan Tidwell () and
Sriram V Villupuram ()
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Erik B Johnson: University of Alabama
Alan Tidwell: University of Alabama
Sriram V Villupuram: University of Texas at Arlington
The Journal of Real Estate Finance and Economics, 2020, vol. 60, issue 1, No 7, 133 pages
Abstract We recover the value of curb appeal in residential housing by using photos obtained from Google Street View, a deep learning classification algorithm and a variety of hedonic controls. We show that own property curb appeal is worth about twice that of an across the street neighbor. Together, neighbor and own property curb appeal together may account for up to 7% of a house’s sale price. The curb appeal premium is more pronounced during times of housing market weakness and greater in neighborhoods with high average curb appeal. Results are robust to a variety of spatial controls and curb appeal specifications.
Keywords: Machine learning; Hedonic valuation (search for similar items in EconPapers)
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