北京市房价与地价的动态关系——基于结构方程模型的实证分析

城市房价与地价之间的关系错综复杂,不仅受多种因素的交织影响,相互之间也存在动态关系。研究房价与地价关系的传统方法,如Granger因果检验和回归分析等,无法刻画房价与地价之间多维的网络状关系,相比之下,结构方程模型能同时处理多个内生潜变量,且不受观测指标共线性的影响,为刻画地价与房价的交互作用提供了新的工具。从住房与土地市场的供需传导机制出发,推导出房价与地价的结构模型,以北京市为例,运用2003-2013年居住用地价格和2014年在售楼盘价格,与北京市GIS电子地图相匹配,提取商服中心可达性、公共交通可达性、道路可达性、商服繁华度、设施便利性等解释变量,构建地价与房价结构方程模型,分析二者之间的结构关系。

Dynamic relationship between housing price and land price in Beijing: Based on Structural Equation Modeling

The intricate relationship between urban housing price and land price is influenced by mingle factors and contains a dynamic interaction between each other. Traditional approaches for this topic, such as Granger test and multiple regression, are quite limited in studying the multidimensional relationship within them. In contrast, SEM (Structural Equation Modeling) can handle multiple endogenous latent variables simultaneously and overcome the collinearity of independent variables, so it could be an effective approach to characterize the interaction between urban housing price and land price. Under this background, this paper firstly deduces a theoretical structural model of land price and housing price based on the supply and demand chain of land and housing market. Then, a GIS database is built for Beijing by utilizing the residential land transaction price records from 2003 to 2013 and housing price published on housing-sale website in 2014. Within the SEM, five types of explanatory variables are included, namely, accessibility to important commercial centers, accessibility to public transport, accessibility to highway, concentration of commercial services and concentration of facilities. After that, four models (with all parameters estimated with PLS) are built taking account of the effect of spatial heterogeneity, spatial autocorrelation and the effect of floor-ground-area ratio. At last, this paper arrives at 4 conclusions: (1) Land price in the past has significant effect on current housing price. For the case of Beijing, the estimated factor is between 0.2 and 0.4. (2) Regarding the influence of different explanatory factors, some mainly affect the land price, such as the accessibility to highway and the concentration of commercial services; some mainly affect house price, such as the accessibility to public transport and the concentration of facilities; some affect both, such as the accessibility to important commercial centers. (3) Ground land price has greater effect on housing price than floor land price. The control of floor-ground-area ratio in Beijing's urban planning reduces the impact of land market on house market, as well as the impact of land supply and demand fluctuation on housing price. (4) With the SEM, this paper concludes the relationship between housing price and land price in shape of network instead of chain, also proves SEM to be an effective approach to study the complicated relationship between land market and housing market.