The Empirical Study Of Relationship Between Population Structure And Commercial Housing Price

Housing problem is a livelihood issue that must be taced in China today. in China, the price of house, adjusted by policies many times, has been overheating since 1998, when China’s real estate market became market-oriented and monetary. House has characters of not only consumer goods but also investment goods, and housing price is very important for a family. So stable housing price is very important for social stability. Housing supply and demand are main factors of housing market, and they are essential for the residential price formation. Housing supply is decided by the government and real estate developers, while housing demand mainly comes from the people. In recent years, China’s population structure is changing. The aging of the population has become an important social problem and urbanization has changed the population structure of the urban and rural areas. Changes of population structure influence people’s housing demand and thus influence residential price.This paper takes Shanghai as the research object and uses the VAR model to research the relationship between Shanghai population structure and the commercial housing price, based on data from 1994 to 2012. In this paper, the population structure is divided into three substructures: natural population structure, socio-economic population structure and the geographical population structure. And this paper selects corresponding indexes for each substructure. For natural population structure, the selected indexes are sex ratio, dependency ratio and the proportion of labor force; for the socio-economic population structure, the indexes are family size, personal disposable income and Industrial structure of population; for the geographical population structure, this paper select the proportion of non-agricultural population and migration as the index. In the empirical study, this paper uses unit root test, Johensan cointegration test, Granger causality test, and impulse response function and variance decomposition method. The results are as follows: from the natural population structure aspect, sex ratio and dependency ratio have long-term negative effects on commercial housing price while the proportion of labor force has positive effects on commercial housing price and has greater impact in the long-term; from the socio-economic population structure aspect, family size has negative effects on commercial housing price in the long-term while personal disposable income has positive effects. But the variance of the housing price changes mainly comes from changes of family size; from the geographical population structure aspect, both the proportion of non-agricultural population and migration have positive effects on commercial housing price in the long-term and migration is the main reason for housing price fluctuations. At the end of the paper, some advices are offered for the future development of Shanghai.