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作者

来源

JOURNAL OF HOUSING ECONOMICS,Vol.43,P.14-22

语言

英文

关键字

House prices; Real estate; Spatial dependence; Non-parametric regression; REGRESSION

作者单位

[Cohen, Jeffrey P.] Univ Connecticut, Ctr Real Estate, 2100 Hillside Rd,Unit 1041-RE, Storrs, CT 06269 USA. [Cohen, Jeffrey P.] Univ Connecticut, Sch Business, 2100 Hillside Rd,Unit 1041-RE, Storrs, CT 06269 USA. [Danko, Joseph J., III] Brown Univ, Spatial Struct Social Sci Initiat, Populat Training & Training Ctr, Providence, RI 02912 USA. [Yang, Ke] Univ Hartford, Barney Sch Business, 200 Bloomfield Ave, Hartford, CT 06117 USA. Cohen, JP (reprint author), Univ Connecticut, Ctr Real Estate, 2100 Hillside Rd,Unit 1041-RE, Storrs, CT 06269 USA.; Cohen, JP (reprint author), Univ Connecticut, Sch Business, 2100 Hillside Rd,Unit 1041-RE, Storrs, CT 06269 USA. E-Mail: jeffrey.cohen@business.uconn.edu; joseph_danko@brown.edu; Kyang@hartford.edu

摘要

An understanding of the spatial variation in the impacts of living near reservoirs, dams, and undevelopable land is important in explaining residential property values. While there is a body of literature on the effects of proximity to dams and reservoirs on housing prices, little known research attempts to determine if various individual houses are impacted differently depending on their locations and years of sale. We examine properties in Barkhamsted, Connecticut that sold between 2000 and 2015. We utilize non-parametric regression to allow for the possibility that bodies of water, dams and undevelopable land areas, affect various house prices differently, depending on their locations and when they are sold. We find that in general, undevelopable land area is valued as a disamenity in this rural town. With our semi-parametric estimation approach, we find the signs of the effects of proximity to the nearest body of water vary some properties benefit from proximity while others experience lower sale prices when they are closer to water. But on average, being far from the water lowers property values, after controlling for flood risk from being below the nearest dam. In other words, residents prefer to live near waterfronts. We also control for other key housing characteristics and environmental variables, such as elevation relative to the nearest dam, numbers of bedrooms and baths, age of properties, year of sale, square footage and acreage, and others. We plot the parameter estimates over time for some variables to demonstrate how the spatial heterogeneity changes after the recession that began in late 2008.