Valuing Curb Appeal

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, neighbo...

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Bibliographic Details
Published inThe journal of real estate finance and economics Vol. 60; no. 1-2; pp. 111 - 133
Main Authors Johnson, Erik B, Tidwell, Alan, Villupuram, Sriram V
Format Journal Article
LanguageEnglish
Published New York Springer US 01.02.2020
Springer Nature B.V
Subjects
Classification
Economics
Economics and Finance
Financial Services
Housing market
Learning
Neighborhoods
Property
Property values
Regional/Spatial Science
Residential buildings
Strength
Machine learning
Hedonic valuation
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Summary: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.
ISSN:0895-5638
1573-045X
DOI:10.1007/s11146-019-09713-z