Spatial Differentiation of Urban Housing Prices in Guangdong Province and Its Influencing Factors

Abstract

In the context of the central government’s policies on housing prices themed on “adjust measures to local conditions and classifying macro-control”, it is of great significance to study the convergence and the differences of housing prices. Taking the urban area of Guangdong province as an economic unit, this paper explores the spatial heterogeneity of housing price in Guangdong Province during 1995-2014 and the spatial heterogeneity of its impact factors by means of ESDA and GWR models. The study found that the spatial structure of housing prices in the region shows a certain circle structure, while the housing prices in the Pearl River Delta region are relatively high, there is a big difference in housing prices between Zhongshan, Huizhou and other cities. In most of the cities in eastern, western and northern Guangdong, the price of housing is low, which is extremely different from the price of housing of cities in the Pearl River Delta, there is also a huge difference between the housing price of Shantou and that of its surrounding cities. The influencing factors of housing prices in different cities show a localized characteristic of unbalanced linkage. The difference between the impact of GDP per capita and the floor space of buildings completed on housing prices is the largest in the two time sections. In the middle and late time of the real estate development, the relevancy degree between housing prices and GDP per capita is no longer obvious, and is more affected by the urbanization rate and population migration, especially in western Guangdong. The completion of housing area and loan balance has the greatest sensitivity to urban housing prices in western Guangdong. The former has the least sensitivity to the Pearl River Delta region. The latter has the least sensitivity to housing price in eastern Guangdong Province. The amount of the investment in real estate development has the greatest sensitivity to Meizhou, Chaozhou, Shantou and Jieyang prices produced the largest inhibition effect, the inhibition effect of the western part of the smallest. Therefore, we should combine the current situation of housing prices in different regions with the spatial effect mechanism of impact factors and promote the healthy development of real estate economy according to local conditions. The main contribution of this paper lies in: Firstly, for the first time we use ESDA-GWR model to systematically analyze the evolution of city level characteristics and spatial correlation of Guangdong Province and the spatial difference of impact factor driving prices fluctuation, as well as to solve the problem of regional differentiation regulation policies provide the basis. Secondly, we use the theory of real estate cycle to analyze the difference between demand and supply factors of housing prices in driving the fluctuation of housing prices in different cities, which provides the basis for adopting differentiated short-term and long-term regulatory policies and regional regulation and control policies. But there are also the limitations of Guangdong Province.