An Empirical Research On The Correlation Between Population Aging And Housing Price In China

In the 21 st century, China has officially entered the aging society. And the population aging has begun to cause impacts on various aspects of China. Given the important position and role of housing market in Chinese national economy, the potential impact of aging demographic structure on housing prices gradually becomes one of the focuses of social concern.Based on the life cycle theory, this thesis constructs a new overlapping generation(OLG) model. Unlike the traditional OLG model, this thesis extends the life period of the representative individual from two to three. Considering the background of China’s unique cultural tradition, bequest motive of the representative individual is also introduced into the OLG model. Then on the basis of the theoretical analysis framework, four variables are set and used to establish the vector auto-regression(VAR) model. Johansen cointegration test, Granger causality test, impulse responses analysis and variance decompositions analysis, etc. are applied to examine and analyze the VAR model.The results of theoretical analysis show that population aging in China will have some negative effecton housing prices. And the results of the empirical analysis reflect that the demographic factors are long-term influencing factors with time-lag effect. The impact of changes from the demographic factors on housing prices may not appear in the short term. But as the population aging continues, it can be predicted that its negative effect on housing prices will gradually increase, and thus housing prices will inevitably have some volatility. It can be found that there are some differences between the results of empirical and theoretical analysis. In view of the background of China’s unique social development and cultural tradition, this thesis gives some probable reasons for such differences, makes some predictions of the future trend of housing market and housing price, and finally puts forward some suggestions for the government department.