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  • 标题:Measuring the Welfare Loss to Landowners of Future Geographic Shifts In the Suitable Habitat for Vegetation Due to Climate Change
  • 本地全文:下载
  • 作者:Howard, Peter H.
  • 期刊名称:Journal of Food Distribution Research
  • 印刷版ISSN:0047-245X
  • 出版年度:2011
  • 出版社:Food Distribution Research Society
  • 摘要:Scientists predict that global warming will cause suitable habitat ranges to shift for many plant species, including blue oak in California. If proximity to particular land cover types significantly affects human welfare, any such shifts will affect household welfare, resulting in an indirect cost that is currently unaccounted for in the climate change literature. Using a hedonic pricing model, the marginal values of blue oaks and the land cover types most likely to replace them are estimated at multiple spatial scales using single family residences sold in Kern County from 1997 to 2003. In addition to the common identification problems of specification error and omitted variable bias, the variables measuring the degree of proximity of a property to land cover types are endogenous. To identify the marginal values of land cover types at multiple spatial scales using two-stage least squares, instrumental variables are developed using soil data. The results show that the value of blue oaks and other land cover types capitalize at different spatial scales, and these values differ at these various scales. The overall welfare effect of a marginal loss of blue oaks depends on the spatial distribution of the surrounding population, its spatial relationship with respect to blue oaks, and the type of vegetation that replaces blue oaks. With respect to the goal of maximizing social welfare, these results suggest that blue oaks should be preserved from agricultural and urban development in some, but not all, situations.
  • 关键词:Hedonic;Multi-scale capitalization;Housing demand;Species distribution model;Climate change;Displacement of native species;Vegetation movement;Geographic Information System (GIS);Amenity value;Land use
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