House is the cornerstone of the people’s good life,it’s closely related to everyone’s life.Since the reform of the housing system in 1998,China’s commercial housing prices have experienced rapid growth for more than ten years,many families to utter a sigh when facing the high housing prices,"difficult to buy a house" has become one of the main difficulties faced by people in their lives.At the same time,China’s population structure has also undergone tremendous changes,the population of labor force continues to decline,the birth rate continues to slump,and the aging trend has intensified.As a result,China ’s demographic dividend has gradually disappeared.On the other hand,with the development of the social economy,the quality of the population continues improve,the urban population and the trend of the population mobility continue to strengthen,profound changes are taking place in many dimensions of the population structure.It is a consensus that population is the basis for the long-term development of the housing market,with huge changes in multiple dimensions of the population structure,it has great practical significance to explore the relationship between population structure and commercial housing price fluctuations.Previous studies on population structure and commercial housing price fluctuations are mostly based on a single dimension of population structure,in order to fully explore the relationship between population structure and commercial housing price fluctuations,in this paper,multiple dimensions of population structure are incorporated into the analysis of population structure change commercial housing price fluctuations.In addition,in the research methods of population structure and commercial housing price fluctuations,most research used the traditional measurement methods from the time dimension,but through combing the changes in China’s population structure and commercial housing prices in recent years,it is found that the population structure and commercial housing prices presents the state of spatial agglomeration,areas with high commercial housing prices are adjacent to areas with high commercial housing prices,areas with low commercial housing prices are adjacent to areas with low commercial housing prices,and the spatial distribution of population structure is the same with the commercial housing prices.Therefore,this paper incorporates spatial factors into the study of population structure and commercial housing price fluctuations,and uses the spatial Dubin model to study the impact of population structure changes on commercial housing price fluctuation from 2000 to 2018 in 31 provinces and cities in China.The research results show that:(1)There is a significant spatial correlation and positive spillover effect in China’s housing prices,and the population structure also shows a strong spatial correlation.(2)The change of population structure not only affects the commercial housing prices in this area,but also affects the commercial housing prices in its neighboring areas through the effect of space spillovers.The child dependency ratio,population with higher education,urban population,and floating population have a significant positive spillover effect on commercial housing prices in neighboring areas,and the elderly dependency ratio has a significant negative spillover effect on commercial housing prices in neighboring areas.(3)Comprehensive direct effect and spillover effect,Child dependency ratio,population with higher education,urban population,and floating population have a significant promotion effect on commercial housing prices,the dependency ratio of old people is negatively correlated with commercial housing prices.(4)The positive impact of the population quality improvement brought by the higher education population on commercial housing prices masks the negative impact of changes in the age structure of the population on commercial housing prices.Finally,based on the results of the analysis,some suggestions were put forward to promote the healthy development of the commercial housing market and population structure. |