Spatial Econometric Analysis On House Price Of Chinese Provinces

Since1998, China has began a comprehensive market-oriented reform of the realestate industry, and promote it to monetization, commercialization and marketizationoverall. During the past two decades, the real estate industry has made a greatdevelopment, and is playing an increasingly important role in the national economy. It hasgradually become an important pillar industry of China’s national economy. However, therapid expansion of the real estate industry has lesd to a rapidly climbing of housing price,and a tremendous pressure of the residents purchasing houses. Rising house prices hasaroused great concern of the government, society and academia, and housing prices havebecome the focus of the government’s macroeconomic control. Although the govermenthas introduced a series of stringent price control policies, the regulation and controlresults are not satisfactory. This requires more scientific analysis of the real estate industry.Any economic behavior has more or less contact with the others in geographical space,and previous studies have ignored the space interaction that may exist in housing pricesbetween the various provinces and cities. This paper has made a spatial econometricanalysis of China’s housing prices through the introduction of the spatial weight matrix.Compared to traditional econometric models, space model is better adapted to thecharacteristics of regional data, and the empirical results are more credible. The resultsshow that there is space interaction in China’s housing prices. The calculation of Moran ’Iindex of China’s housing prices in1998-2010shows that the housing prices of differentprovinces have a significant positive correlation, and are not randomly distributed in thespatial distribution. There is bound to the intrinsic link that provinces with relatively highor low housing prices tend to cluster in space. And there is a high degree of spatialstability in most of the province and its neighborhood housing prices. In this paper,weanalyze the spatial dependence of housing prices through the traditional linear model, thespatial lag model and spatial error model.After weighing the pros and cons of them,wefinally establish the spatial lag model to make further analysis of the spatial characteristicsof the housing price. And we mainly analyze the spatial heterogeneity of impact ofurbanization on the housing price through the establishment of geographically weightedregression model. The results show that the geographically weighted regression model is also superior to the traditional linear model, and is closer to reality. The spatial effects ofhousing prices require for a nationwide co-ordination arrangements of the regulation ofChina’s housing prices. The regulation effects may not be obvious if we proceed onlyfrom the local. Purely rely on the provinces and cities on the regulation of housing priceswill be counter productive. Provinces and municipalities should make joint cooperation tocoordinate the management of the real estate market, thus promote the sounddevelopment of the real estate market.