地理科学进展 ›› 2005, Vol. 24 ›› Issue (1): 97-104.doi: 10.11820/dlkxjz.2005.01.011

• 城市地理与GIS应用 • 上一篇    下一篇

城市居民对居住区位的偏好:支付意愿梯度模型的估计

郑思齐1, 符育明2, 刘洪玉1   

  1. 1. 清华大学房地产研究所, 北京 100084;
    2. 新加坡国立大学, 房地产系, 新加坡 117566
  • 收稿日期:2004-11-01 修回日期:2004-12-01 出版日期:2005-01-25 发布日期:2005-01-25
  • 作者简介:郑思齐(1977-),女(满),天津人,博士,清华大学房地产研究所讲师,主要研究方向为城市经济学、房地产经济学。E-mail:zhengsq00@mails.tsinghua.edu.cn
  • 基金资助:

    国家自然科学基金重点课题(编号:79930500)资助。

Urban Households' Location Preference: The Estimation of Willingness-To-Pay Grapient Model

ZHENG Siqi1, FU Yuming2, LIU Hongyu1   

  1. 1. Institute of Real Estate Studies, Tsinghua University, Beijing 100084, China;
    2. Department of Real Estate, National University of Singapore, Singapore 117566
  • Received:2004-11-01 Revised:2004-12-01 Online:2005-01-25 Published:2005-01-25

摘要:

利用翔实的社会调查数据,本文考察了我国城市居民对居住区位的偏好和支付意愿,以及影响支付意愿相对水平的各项因素。首先,本文对影响居民对居住区位支付意愿高低(即支付意愿梯度)的因素进行了理论分析,将其分为两组,一组是家庭个体特征,一组是城市形态特征,同时分析了支付意愿梯度与这些因素之间的相关关系。在初步分析的基础上,本文建立了支付意愿梯度模型,利用北京、上海、广州、武汉和重庆五城市的调研数据对模型参数进行了估计。模型估计结果显示,高收入群体仍倾向于居住在距离市中心偏近的位置。另外,工作地点、对环境的偏好、城市规模和郊区基础设施完善程度都会从各方面影响支付意愿的梯度值。

关键词: 居住区位, 支付意愿, 支付意愿梯度

Abstract:

Using data from a unique-designed survey, this paper examines the willingness to pay (WTP') for residential location of urban residents in China, and the determinants of the relative levels of the WTP'. Firstly, the paper theoretically analyzes the determinants of the gradient of the WTP', and classifies them into two groups: household characteristics and urban attributes. Secondly, the correlation coefficients among the WTP' and those determinant variables are analyzed. Based on above theoretical and descriptive analysis, a model of willingness-to-pay gradient is established and estimated, using samples of the households from Beijing, Shanghai, Guangzhou, Wuhan and Chongqing. Empirical results show that higher-income people still prefer to live near the city center, due to the immature state of infrastructure construction and service in suburb. Working place, preference pattern of environment, city size and the infrastructure construction in suburb will all influence WTP' in different ways. These empirical findings have important implications for policy-makers and developers.

Key words: gradient of willingness-to-pay, residential location, willingness-to-pay