摘要
在西安市选择一条过市中心的南北向带状区域,分析沿线市中心、二环以内、二三环之间以及三环以外四个区间内新建住房和二手房的价格梯度差,发现各样本区域新建住房价格一般要高于二手房价格,价格递减速度比二手房要快,并且北方向的两类住房价格递减都要快于南方向,波动性也较大。根据实际情况,提取繁华程度、交通便捷度、人口状况、区域环境、基础设施、地理区位、市场供求七个影响住房价格的主要因子,运用多种数理统计分析方法对其进行分析研究。结果表明:新建住房市场和二手房市场虽有差异,但主导因子基本保持一致。繁华程度、区域环境和基础设施是影响两类住房价格的最主要因子,人口因子对新建住房价格影响较大,而二手房则受地理区位影响较大。市场供求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。
By selecting the South - North zone of Xi＇ an, the authors analyze price data along the band where both the newly developed houses and secondhand houses are located in the urban central district, inside the second ring, between the second ring and the third ring, outside the third ring. It has been found that the prices of newly developed houses are generally higher than the prices of second - hand houses, but the former is faster than the latter in the speed of price decrease successively. At the same time, the price of houses of urbannorthern is faster than the urban - southern in the speed of price decrease and the fluctuation of price is also heavier. Then according to the practical circumstances, seven influencial factors are selected such as flourishing degree, traffic conditions, population situation, environmental quality, basic facilities, geographical location, supply and demand of market are selected. The results show that though the newly developed housing market differs from the second-hand housing market, but the main factors are hardly coincident, flourishing degree, distractional environment and basic facilities are the most important influencing factors on both the newly developed houses and the second - hand housing prices, furthermore, population situation is largely affect on the newly development houses, while geographical location is largely influenced on second- hand house price. However, the important effects of the supply and demand of market and traffic conditions are not verified in the present study.
出处
《统计与信息论坛》
CSSCI
2008年第12期37-42,共6页
Journal of Statistics and Information
基金
教育部哲学社会科学研究重大课题攻关项目《西部经济发展与生态环境重建研究》(04JZD00010)
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
西安市
housing price
price gradient
influencing factors
multivariate linear regression analysis
weighted index
Xi＇an city
