Research On Spatial Correlation Of Housing Prices In Yangtze River Urban Agglomeration

Since the 18th National Congress of the Communist Party of China,the central government has gradually strengthened the coordinated economic development of strategic regions,such as the "Belt and Road",the Beijing-Tianjin-Hebei business district,the Pearl River Delta urban agglomeration,and the Yangtze River Economic Belt,so as to form the open and connected development of different regions in China.,Thereby narrowing the gap in regional economic development.At the same time,coordinated regional development is also one of the requirements for achieving sustainable development,and will become our country's basic policy for coordinating regional development for a long time.Jiangsu Province is a major economic province in our country,and its internal regional development is seriously unbalanced.The economic development of various regions is basically unrelated or coordinated,and the overall effect of economic development in the three regions of Southern Jiangsu,Central Jiangsu and Northern Jiangsu is not good.In order to coordinate the economic development of various regions within Jiangsu Province,the "1+3" functional zone strategy came into being.Among the"1+3" strategy,the Yangtze River City Group with strong economic strength is the most supportive of the overall situation.It is a region with the best development foundation in Jiangsu and one of the regions with the strongest economic strength in the country.According to the current data,the real estate economy is still a pillar of the national economy of the Yangtze River urban agglomeration,and its position in the national economy will become more and more important in the short term,which will profoundly affect the development of other industries and is not conducive to the sustainable development of the regional economy.This article starts with the sales price of residential commercial housing and studies the spatial correlation of housing prices in the Yangtze River urban agglomeration.Due to the limitation of statistical data,this paper only selects 7 cities in the Yangtze River urban agglomeration,and excludes Taizhou City.Take the sales price of residential commercial houses in each city as the research index.This article explains the geographic spatial relevance of housing prices in four steps:(1)This article first sorts out the related theories of "spatial correlation" and lays a theoretical foundation for the study of spatial correlation.First of all,the spatial correlation theory emphasizes that the connections between things and phenomena in geographical space are universal.The growth pole theory explains the directionality of the connections between housing prices and the inevitability of the emergence of contact centers.The ripple-spillover effect theory summarizes the spatial connections.For directional conductivity,the transmission mechanism theory provides a research direction for the housing price transmission path.(2)Second,according to the heterogeneity of the development of the real estate market,the development of housing prices in the cities within the Yangtze River urban agglomeration is not synchronized.Taking the price of residential commercial houses as the attribute index,the cities studied are divided into three categories using K-center clustering:Nanjing and Suzhou are first-class cities;Zhenjiang,Yangzhou,and Nantong are second-class cities;Wuxi and Changzhou are third-class cities.(3)Third,establish a hybrid panel model from a global perspective to determine the cross-sectional correlation among cities.Taking into account the heterogeneity of the real estate market,the impact of various indicators on housing prices varies from city to city,so this paper establishes a mixed panel model of three types of cities from a local perspective,and finds that the coefficients and directions of the impact of each explanatory variable on housing prices are different depending on the city category.(4)Finally,VAR models are established according to the three types of cities,and the impulse response function values and variance decomposition results are analyzed to find out the housing price transmission direction,transmission period,and housing price fluctuation contribution rate between cities.This study clarified the objective existence of spatial correlation of housing prices on a theoretical basis,and then integrated statistical methods such as K-center clustering,panel data regression,impulse response function,and variance decomposition,to study housing prices relevance in geographic space from both global and local levels.This article not only extends the research methods of the spatial conductivity of housing prices,but also enriches the range of research objects in the existing literature.