邻近供水水库和水坝:对房价的影响是否存在空间异质性?

Jeffrey P. Cohen, Joseph J. Danko, Ke Yang
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引用次数: 4

摘要

了解居住在水库、水坝和未开发土地附近的影响的空间变化对解释住宅物业价值很重要。虽然有大量文献研究靠近水坝和水库对房价的影响,但鲜为人知的研究试图确定不同的个体房屋是否受到不同的影响,取决于它们的位置和销售年限。我们研究了2001年至2015年间在康涅狄格州巴克汉姆斯特德(Barkhamstead)出售的房产。我们利用非参数回归技术来考虑主要水库、水坝和未开发土地区域对各种房价的不同影响,这取决于它们的位置和出售时间。我们发现,在大多数情况下,靠近水坝导致房屋销售价格较低,这些影响的程度因地理空间和时间而异。一种差异中的差异方法表明,在最近的住房危机之后,支付距离大坝距离的意愿有所下降。总的来说,在这个乡村小镇,未开发的土地被视为一种便利设施。靠近水库的影响迹象各不相同——一些物业因靠近水库而受益,而另一些物业因靠近水库而销售价格较低。我们还控制了其他关键的住房特征和环境变量,如海拔、卧室和浴室的数量、房产的年龄、销售年份、平方英尺和面积等。我们为几个关键变量生成了系数的符号和大小的地图,以说明空间异质性。
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Proximity to a Water Supply Reservoir and Dams: Is There Spatial Heterogeneity in the Effects on Housing Prices?
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 Barkhamstead, Connecticut that sold between 2001 and 2015. We utilize non-parametric regression techniques to allow for the possibility that the major reservoirs, dams and undevelopable land areas, affect various house prices differently, depending on their locations and when they are sold. We find that for the most part, proximity to dams leads to lower housing sale prices, with the magnitudes of these effects varying across geographic space and over time. A difference-in-differences approach indicates that the willingness to pay for distance from the dams decreased after the most recent housing crisis. In general, undevelopable land area is valued as an amenity in this rural town. The signs of the effects of proximity to the reservoir vary - some properties benefit from proximity while others experience lower sale prices when they are closer to the reservoir. We also control for other key housing characteristics and environmental variables, such as elevation, numbers of bedrooms and baths, age of properties, year of sale, square footage and acreage, and others. We generate maps of the signs and magnitudes of the coefficients for several of the key variables to illustrate the spatial heterogeneity.
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Geographically Overlapping Real Estate Assets, Liquidity Spillovers, and Liquidity Multiplier Effects A Review and Extension of Merger and Acquisition Research between REITs and General Corporations Proximity to a Water Supply Reservoir and Dams: Is There Spatial Heterogeneity in the Effects on Housing Prices?
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