地理学报

地理学报 ›› 2006, Vol. 61 ›› Issue (6): 604-612.doi: 10.11821/xb200606004

• 区域规划与产业经济 • 上一篇    下一篇

上海市住房价格梯度及其影响因素分析

石忆邵1, 李木秀2   

  1. 1. 同济大学测量与国土信息工程系,上海200092;
    2. 同济大学经济与管理学院,上海200092
  • 收稿日期:2005-11-29 修回日期:2006-03-11 出版日期:2006-06-25 发布日期:2006-06-25
  • 作者简介:石忆邵(1963-), 男， 博士， 教授， 博士生导师。主要从事城市与区域发展研究。 E-mail: shiyishao@mail.tongji.edu.cn
  • 基金资助:

    国家自然科学基金项目(40371034)

The Analysis of the Housing Price Gradient and Its Impact Factors of Shanghai City

SHI Yishao1, LI Muxiu2   

  1. 1. Department of Surveying and Land Information Engineering, Tongji University, Shanghai 200092, China;
    2. Institute of Economics and Management, Tongji University, Shanghai 200092, China
  • Received:2005-11-29 Revised:2006-03-11 Online:2006-06-25 Published:2006-06-25
  • Supported by:

    National Natural Science Foundation of China, No.40371034

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被引次数

119

摘要：

选择从上海市中心区至宝山区的一条南北向区段,通过采集沿线内环以内、内环和中环之间、中环和外环之间以及外环以外四个区间内二手房、新房的价格样本,分析其价格梯度差,发现二手房价格一般要高于新房价格,但其价格递减速度比新房更快。根据实际情况,提取繁华程度、市场供求比例、地理区位、交通条件、人口状况、基础设施、环境质量七个影响住房价格的主要因子,运用多元回归分析方法对样本区域的房地产价格进行分析,得出了多元线性回归方程,并进行了回归分析效果检验;最后分别运用偏相关系数分析法和单项因子权重度量法来估算各因子的影响程度。结果表明,二手房市场和新房市场具有明显差异,市场供求是影响二手房价格的最主要因子,而环境质量则是影响新开楼盘价格的首要因子;繁华程度和交通条件的重要影响作用在本次回归模型中没有得到验证。

关键词: 住房价格, 价格梯度, 影响因子, 多元线性回归分析, 权指数, 上海市

Abstract:

By selecting the South-North line from urban central district to Baoshan district of Shanghai, and collecting housing price data along the line where both the second-hand houses and newly developed houses are located inside the inner ring, between the inner ring and the middle ring, between the middle ring and the outer ring, outside the outer ring, the authors analyze the price gradients. It has been found that the prices of second-hand houses are generally higher than the prices of newly developed houses, but the former is faster than the latter in the speed of price decrease successively. Then according to the practical circumstances, seven influencing factors are selected such as flourishing degree, ratio between supply and demand, geographical location, traffic conditions, population situation, basic facilities and environmental quality are selected and by means of the multivariate linear regression method, the influencing factors of housing price gradients are discussed. Finally, the affected degree of factors is evaluated by applying partial relation coefficient analysis method and single factor weighted index method. The results show that the second-hand housing market differs obviously from the newly developed housing market. The ratio between supply and demand is the most important influencing factor on the second-hand housing prices while the environmental quality is the most important influencing factor on the prices of newly developed houses. However, the important effects of the flourishing degree and traffic conditions are not verified in the present study.

Key words: housing price, price gradient, influencing factors, multivariate linear regression analysis, weighted index, Shanghai city