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作者

Erik B Johnson;Alan Tidwell;Sriram V Villupuram

来源

JOURNAL OF REAL ESTATE FINANCE AND ECONOMICS,Vol.60,Issue1,P.111-133

语言

英文

关键字

Machine learning;Hedonic valuation

作者单位

Economics, Finance and Legal Studies, Culverhouse College of CommerceUniversity of AlabamaTuscaloosaUSA;Finance and Real Estate, College of BusinessUniversity of Texas at ArlingtonArlingtonUSA

摘要

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.