The Impact Of Population Structure Imbalance On House Prices

House price is one of the people’s livelihood issues that Chinese residents focus on,which affects each resident’s consumption expenditure and investment plan.At the same time,with the development of social economy,China’s population structure shows a trend of deviation from equilibrium,which is mainly reflected in the imbalance of population gender structure and age structure,the significant increase of male population over female population,the decline of birth rate,the deepening of population aging and so on.As housing carries the functions of family savings and investment,pension,marriage Housing and school district housing in our society,once the real estate value foam bursts and house prices fluctuate violently,it will pose a great threat to the social harmony and stability of our country.Therefore,the main problem of this paper is to explore whether the imbalance of population structure will have a severe impact on the fluctuation of house prices,analyze the correlation between them,and provide suggestions for the stable development of China’s real estate market and the balanced growth of population structure.This paper adopts a combination of theoretical analysis and empirical test.In the theoretical analysis part,firstly,the signal theory is used to analyze the mechanism of the imbalance of population gender structure on house prices,and it is considered that the imbalance of gender ratio mainly affects house prices by intensifying the competition in the marriage market.The proportion of men in the marriage market is higher than that of women,and the competition is becoming increasingly fierce.Participants tend to carry out signal transmission in the marriage competition by configuring real estate,so as to avoid "adverse selection" caused by information asymmetry.Secondly,this paper uses the life cycle hypothesis and supply-demand theory to analyze the relationship between population age structure and house price,specifically discusses the impact of the growth of elderly dependency ratio and child dependency ratio on house price,and puts forward relevant hypotheses.In the empirical test part,this paper analyzes the inter provincial panel data of 30 provinces and cities in China(excluding Hong Kong,Macao,Taiwan and Tibet)from 2007 to 2019.Considering the spatial correlation characteristics of China’s house price and population structure,this paper establishes a time fixed effect spatial Doberman model,uses the spatial weight matrix combining economic development level and geographical distance,and analyzes the population gender The impact of age structure imbalance on China’s house prices.The results show that there is a positive correlation between China’s population gender structure and house prices,and has a significant spatial spillover effect,that is,the gender ratio imbalance not only promotes the increase of local house prices,but also drives the rise of house prices in surrounding areas.The impact of population age structure imbalance on house prices is mainly reflected in that the deepening of aging has a positive boosting effect on house prices in the region,the increase of the proportion of children’s support is significantly positively correlated with house price fluctuations,and both have no significant correlation with house prices in adjacent areas.Based on the spatial Doberman model,through the heterogeneity test,it is found that the population gender ratio and elderly dependency ratio have a significant positive impact on house prices in the economically developed areas of eastern China,and the significance gradually decreases in the economically backward areas of central and Western China.The child dependency ratio has a significant inhibitory effect on house prices in the eastern region,but promotes the rise of house prices in the central and western regions.According to the research results,this paper puts forward practical policy suggestions to improve the imbalance of population gender and age structure and reduce the impact on supply and demand in the real estate market.