Research On The Relationship Between Housing Price And Human Capital Based On Spatial Dubin Model

In recent years,the rising housing price leads to the cross-regional movement of labor force,which leads to the change of population size and population structure within the region.Housing price should be rationalized to meet the needs of different levels of human capital.Based on the relevant data of 35 large and medium-sized cities in China from 2006 to 2018,housing price was selected as the explanatory variable,human capital as the explained variable,and GDP per capita,environmental greening level,medical and health level and transportation level as the control variables.The common panel model and spatial measurement model were established respectively to study the impact of housing price changes on human capital.Firstly,the stationary test,co-integration test and Hausman test were performed on the panel data to establish a common panel regression model.Then,according to the longitude and latitude of 35 large and medium-sized cities in China,the spatial weight matrix of geographical distance was established,global spatial autocorrelation test,local spatial autocorrelation test,LM test,Robust LM test,Wald test,LR test and joint significance test were conducted,and a spatial durbin model with time and space double fixation was established.Finally,the spillover effect of housing price on human capital is analyzed through the results of indirect effect.The following conclusions are drawn:(1)the regression results of the ordinary panel model show that the housing price has a positive u-shaped relationship with the level of human capital,which is a non-linear relationship.In other words,the increase of housing price will lead to the decrease and then the increase of human capital level.The improvement of medical and health care level is conducive to the improvement of regional human capital level,but the result is not significant,and the improvement of transportation level will reduce regional human capital level.(2)the results of global spatial autocorrelation test and local spatial autocorrelation test show that there is a significant positive correlation between housing price and human capital level in China.In addition,through the Moran scatter diagram and LISA cluster diagram,it is found that most cities fall in the first quadrant(HH)or the third quadrant(LL),that is,housing price and human capital level have a strong spatial cluster effect.(3)the regression results of the spatial durbin model with both time and space fixed show that there is a positive u-shaped relationship between housing price and human capital level,that is,the human capital level will decline first and then rise with the continuous rise of housing price,which is consistentwith the results of the ordinary panel model.(4)spillover effect the results show that the level of human capital has a significant positive spatial spillover effect,and the increase of housing prices in neighboring cities will also promote the improvement of human capital level in the city.Among the control variables,at the significance level of 5%,the improvement of per capita GDP in neighboring areas is conducive to the improvement of human capital level,and the impact of per capita GDP in neighboring areas on human capital level is greater than that of per capita GDP in this region.The improvement of health care level and environmental greening level in this region and neighboring regions is conducive to the improvement of human capital level in this region.The improvement of transportation level in this region or neighboring regions has little impact on the improvement of human capital level in this region.Comprehensive the above conclusions,the paper puts forward the following Suggestions: to establish a rational system of housing prices,curb housing prices too fast growth,establish and improve the housing security system,to promote the development of the real estate market health steady;Increase the investment of human capital,pay attention to the accumulation of human capital,optimize the allocation of human capital;Improve the level of public health services and infrastructure construction to enhance its own attractiveness;For upgrading the industrial structure,optimize the industrial structure configuration.