| Influence of Spatial Features on Land and Housing Prices |
| |
| 作者姓名： | 高晓路 ASAMIYasushi |
| |
| 作者单位： | [1]JapanSocietyforthePromotionofScience;DepartmentofUrbanResearch,NationalInstituteforLandandInfrastructureManagement,Japan; [2]CenterforSpatialInformationScience,theUniversityofTokyo,Tokyo113-8654,Japan |
| |
| 基金项目： | Supported by the Special Coordination Funds for Promoting Sci-ence and Technology, and the Research Grant-In-Aid provided by the Ministry of Education, Culture, Sports, Science, and Technol-ogy, Japan |
| |
| 摘 要： | The analysis of hidden spatial features is crucial for the improvement of hedonic regression models for analyzing the structure of land and housing prices. If critical variables representing the influence of spatial features are omitted in the models, the residuals and the coefficients estimated usually exhibit some kind of spatial pattern. Hence, exploration of the relationship between the spatial patterns and the spatial features essentially leads to the discovery of omitted variables. The analyses in this paper were based on two exploratory approaches: one on the residual of a global regression model and the other on the geographically weighted regression (GWR) technique. In the GWR model, the regression coefficients are allowed to differ by location so more spatial patterns can be revealed. Comparison of the two approaches shows that they play supplementary roles for the detection of lot-associated variables and area-associated variables.
|
| 关 键 词： | 空间特点 空间变化 衰退模型 GWR 住宅价格 |
| 收稿时间： | 10 July 2003 |
Influence of Spatial Features on Land and Housing Prices |
| |
| Xiaolu Gao, &#x;෯,Yasushi Asami.Influence of Spatial Features on Land and Housing Prices[J].Tsinghua Science and Technology,2005,10(3):344-353. |
| |
| Authors: | Xiaolu Gao &#x;෯ Yasushi Asami |
| |
| Institution: | aJapan Society for the Promotion of Science; Department of Urban Research, National Institute for Land and Infrastructure Management, Japan;bCenter for Spatial Information Science, the University of Tokyo, Tokyo 113–8654, Japan |
| |
| Abstract: | The analysis of hidden spatial features is crucial for the improvement of hedonic regression models for analyzing the structure of land and housing prices. If critical variables representing the influence of spatial features are omitted in the models, the residuals and the coefficients estimated usually exhibit some kind of spatial pattern. Hence, exploration of the relationship between the spatial patterns and the spatial features essentially leads to the discovery of omitted variables. The analyses in this paper were based on two exploratory approaches: one on the residual of a global regression model and the other on the geographically weighted regression (GWR) technique. In the GWR model, the regression coefficients are al- lowed to differ by location so more spatial patterns can be revealed. Comparison of the two approaches shows that they play supplementary roles for the detection of lot-associated variables and area-associated variables. |
| |
| Keywords: | spatial features spatial variation regression model residual geographically weighted regres- sion (GWR) |
| 本文献已被 CNKI 维普 万方数据 ScienceDirect 等数据库收录！ |
