A Study On The Impact Of Population Structure Change On Housing Prices In China

As a basic and leading industry,the real estate industry plays an important role in the development of national economy.From 1987 to 2017,the annual growth rate of the average house price in China reached 10.20%,far exceeding the deposit rate in the same period.But at the same time,the real estate market also contains huge risks.In order to control this risk,a very important task is to clarify the influencing factors of real estate prices and their impact on housing prices.Relevant theoretical and empirical studies at home and abroad show that there are many factors driving the rise of housing prices,such as residents'income,urbanization rate,supply and demand relationship,residents' living standard,loan benchmark interest rate,population structure and so on.In recent years,due to the gradual decline of the demographic dividend in China,the absolute and relative number of labor force are declining,so the population structure factor has attracted more and more attention of scholars.Because the essential attribute of real estate is the residential function,the population structure factor has a very close relationship with the real estate market.By studying the impact of population structure changes on housing prices in China,and improving the government's regulatory policies,and making them more effective,it will promote the stable operation of the real estate market and even the national economy in China.Through qualitative analysis,this paper analyses the dynamic changes of population structure and the mechanism of the impact of population structure changes on housing prices,and finds that the changes of urbanization rate,population growth rate,total dependency ratio and other related indicators of population structure have a greater impact on housing prices.On the basis of qualitative analysis,the VAR vector autoregressive model is adopted,the population structure related variables are taken as the concerned variables,and the control variables such as GDP per capita,the proportion of employed population in tertiary industry,the benchmark lending interest rate and the total fertility rate are taken as the independent variables,and the housing price is taken as the dependent variable to model.Through variance decomposition analysis,the contribution degree of each variable to housing price change is obtained.The analysis of variance shows that the contribution degree of each independent variable to the change of house price from large to small is per capita GDP,house price itself,total dependency ratio,loan benchmark interest rate,ratio of money supply to GDP,proportion of tertiary industry employment population,population growth rate,urbanization rate and total fertility rate,including total dependency ratio,population growth rate and urbanization rate.The total contribution of population structure-related variables to housing price change is 9.41%,which is roughly in line with China's national conditions.Because the population structure changes smoothly in the study area,it may reduce the impact on housing prices.However,based on future population trends,the impact of population structure change on housing prices may become greater.Finally,based on the above conclusions,some suggestions are put forward for population age structure,total fertility rate,benchmark lending rate and housing industry policy.