An Empirical Study On The Detection Of Real Estate Bubbles And Its Spatial Effect

China's real estate has experienced about 40 years of development since 1978.With China's reform and opening up,real estate has undergone the stages of starting,acceleration,hype,adjustment,regulation,counter-regulation,reflection and overall collation.Generally,the real estate price shows a growing trend.However,whether the real estate price truly reflects its value and whether there is a bubble have always been topics of constant discussion in the academic circle.Established against such background,this paper,employing new real estate price indices in the sample period 2003-2013 and utilizing new real estate bubble measurement methods---PWY and PSY methods,based on the premise of rational real estate bubble,has conducted an empirical study on the existence of real estate bubble in 30 first-tier and second-tier cities in China.The study has provided real-time measurement of real estate bubble at times of bubble occurrence and burst point.Based on the theoretical analysis of the influence factors related to real estate bubble,adopting dynamic short panel model,the present study has also analyzed the relationship between real estate bubble and its influencing factors.Finally,using a model of panel dynamic spatial econometric,it has made an analysis of space effect of the real estate bubble between different cities in China.Employing PWY and PSY methods,this paper has conducted an empirical study on the real estate bubble of 30 Chinese cities during the sample period from January 2003 to December 2013 based on the new data on residential real estate price index constructed and data on the corresponding rent price index.The results show that most of the 30 cities have real estate bubbles of varying degrees during the sample period.If the significant level is set at 5%,only two cities,namely Harbin and Shenyang,are found to have no real estate bubbles.If the significance level is set at 10%,only one city,Harbin,is rejected and there is no real estate bubble,while all the other 29 cities have bubbles to some extent,and the bubbles in different cities are different.Further regional analysis indicates that the proportion of cities with real estate bubbles in central and western China is significantly higher than that of the cities in eastern China.Meanwhile,PSY method is also used to measure the residential real estate bubble in 30 cities in real time,which provides a basis for the government to carry out macro-control policy of cutting the peak and leveling the valley,and provides an effective way for the government to implement early warning mechanism.Besides measuring the real estate bubble,taking the annual proportion of months in which real estate bubble occurs as the bubble size,based on the multiple factors influencing real estate bubble and relevant data on 30 cities,this paper has constructed a short dynamic panel model to analyze factors influencing real estate bubble.The results indicate that per capita saving,land leasing,per capital leasing floor price,per capita residential real estate investment have a significant and positive impact on the real estate bubble,while per capita completed housing area,per capita GDP and per capita disposable income have a significant and negative impact on the real estate bubble and factors including population size,per capita domestic loans,inflation and per capita planned floor area of sold land have little influence on the formation of the real estate bubble.In addition,taking into account the urban space adjacent weights,the paper has analyzed the effect of the real estate bubble.The results suggest that real estate bubbles among the cities are not random,or independent of the real estate bubbles of other areas.Instead,they are influenced by the bubbles of other cities and factors related to economic behavior.There exists significant spatial correlation between real estate bubbles in the 30 cities.Through the selection of the panel spatial econometric model,it is found that the construction of the panel space durbin model is the most appropriate.Results of empirical analysis suggest that among the spatial correlation effects,the real estate bubble foam lag,the spatial interaction terms,the per capita income,the price level,the per capita real estate investment,per capita land leasing and land leasing spatial interaction have a significant influence on the real estate bubble.Meanwhile,panel space durbin model was used to calculate the corresponding variables of direct effect,spatial spillover effect and total effect.It is found that spatial spillover effect brought about by each variable accounts for between 13%-59% of total growth effect,further confirming the impact of spatial spillover effect brought by various factors on the real estate bubble in China.Among these factors,the land leasing price of the floor has the largest spatial spillover effect,constituting 59% of the spatial spillover effect,which provides a direction for the government to carry out macro-control on the real estate.Based on the new real estate price index data and the new real estate bubble measurement methods,this paper has empirically measured real estate bubble in China,analyzed its influencing factors,constructed dynamic short panel model and the spatial econometric model,and demonstrated the spatial effect of the real estate bubble.However,this paper is not without limitation.When studying real estate bubble,it did not consider the subsequent effects of the real estate bubble on the real estate and the economy.Also when studying the spatial transmission mechanism of the real estate price bubble,it did not explore the spatial effect and transmission relationship between different clusters,such as the eastern,central and western regions.Due to the lack of data,the corresponding panel analysis and spatial effect analysis cannot extend to the present time.Because of the lack of data,non-residential real estate bubble is not investigated.Therefore,these need to be examined in future research.