房价波动的空间效应:估计方法与我国实证  

The Spatial Effects of Housing Prices:Method and Evidence from China

作　　者：谭政勋[1] 周利[1] 

机构地区：[1]暨南大学金融系金融研究所,广东广州510632

出　　处：《数理统计与管理》2013年第3期401-413,共13页Journal of Applied Statistics and Management

基　　金：国家社会科学基金项目(12BJY161);教育部人文社会科学项目(09YJA790087);广东省优秀博士学位论文项目(sybzzxm201032)的资助

摘　　要：本文首次提出处理房价波动差异性的方法,并利用CCE估计法探讨了35个大中城市房价波动的空间效应。我国房价波动存在明显的空间效应,不同城市的房价波动具有较强的趋同性和横截面相关;同时,不同城市房价波动存在一定的差异和明显的领先滞后关系。房价均值、收入均值、贷款均值,均对房价波动有显著影响,在共同因素作用下,不同城市房价具有很强的截面相关、房价波动表现出趋同性。经济越发达的城市,不仅房价高、增长快,而且房价运行的独立性越强;而经济落后的城市,其房价容易受到外部地区房价的影响。房价高增长城市的人均可支配收入和贷款对房价的拉动作用大于房价低增长城市、波动性也更大。贷款在短期内是驱动我国房价波动的主要因素,但长期内,贷款对房价的拉动力比人均可支配收入要小得多。This paper puts forward a method of dealing housing price differences firstly, studying the spatial effects of housing price and reasons in 35 cities by the common correlated effects estimator. Housing price exists obvious spatial effects, which is illustrated by the strong convergences and cross dependences in different cities. Meanwhile, housing price in different city has certain variances and significant lead-lag relationships. Average price, average income and average loan have evident impact on housing price. With common factors, housing price in different cities has strong cross dependence and convergence. Housing price in more developed cities grows higher and faster, and run more dependently. But housing price in less developed cities is more vulnerable to external influence. Per capita disposable income and loan in higher-price cities drive more than in lower-price cities to the housing price. So is the volatility. In the short run, loan mainly drives housing price fluctuations, while in the long run, per capita disposable income plays a bigger role than loan to the housing price.

关 键 词：房价波动 空间效应 CCE估计 最大似然估计 

分 类 号：O212[理学—概率论与数理统计]