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作者

来源

HABITAT INTERNATIONAL,Vol.78,P.68-82

语言

英文

关键字

Housing price; Educational capitalization; Spatial heterogeneity; Geographically weighted regression; GEOGRAPHICALLY WEIGHTED REGRESSION; PROPERTY-VALUES; SCHOOL QUALITY; RAPID-TRANSIT; OPEN SPACES; HONG-KONG; DISTRICT; IMPACT; CHINA; HANGZHOU

作者单位

[Wen, Haizhen; Xiao, Yue; Zhang, Ling] Zhejiang Univ, Dept Civil Engn, Hangzhou 310058, Zhejiang, Peoples R China. [Wen, Haizhen; Xiao, Yue; Zhang, Ling] Zhejiang Univ, Ctr Real Estate Studying, Hangzhou 310058, Zhejiang, Peoples R China. [Hui, Eddie C. M.] Hong Kong Polytech Univ, Dept Bldg & Real Estate, Hong Kong, Hong Kong, Peoples R China. Zhang, L (reprint author), Zhejiang Univ, Dept Civil Engn, Hangzhou 310058, Zhejiang, Peoples R China. E-Mail: ningduwhz@hotmail.com; xiaoyuezju@qq.com; eddie.hui@polyu.edu.hk; zlcivil@163.com

摘要

Evaluating the capitalization effect of educational facilities via the real estate market has elicited considerable research attention. Although the spatial attribute of housing data is generally considered when constructing a hedonic price model, only a few studies investigated the spatial heterogeneity of educational capitalization in depth. To fill this gap, this study uses the housing data of 516 communities in Hangzhou, as well as constructs the hedonic price, spatial econometric and geographically weighted models to quantitatively evaluate the capitalization effect of educational facilities and explore whether space plays an important role in the capitalization of education. Results confirm that, from the perspective of educational quality or accessibility, kindergarten, primary school, junior high school, senior high school, and university significantly affect housing prices. Specifically, the quality of primary school and junior high school as well as the accessibility of university profoundly influence housing prices. The geographically weighted regression model (GWR) further reveals the existence of spatial heterogeneity in educational capitalization. Different types of educational facilities show significant spatial differences in the scope of influence and capitalization rate, thereby implying that homebuyers have different preferences for educational resources in different areas of the city. Comparisons of the three models affirm that the spatial econometric model can better handle problems caused by the spatial dependence of housing price, whereas the GWR has unique advantages in dealing with spatial heterogeneity and can obtain results that are substantially detailed.