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Research on the Impact of Aging and New Generation in the Population Structure on China’s Real Estate Price Volatility

Zhaocai Cui(School of Economics, Shandong University of Technology)
Zhixin Zhang(School of Economics, Shandong University of Technology)
Cheng Li(School of Economics, Shandong University of Technology)


To clarify the internal mechanism of the influence of the aging population and the new generation on housing prices is helpful to scientifically analyze and predict the trend of housing prices and the aging population and the new generation. This paper uses the intergenerational overlap model of the two periods as the theoretical basis, and uses the provincial panel data from 1998 to 2018 to study the impact of the elderly population and the new generation on the price fluctuations of commercial housing. The results of the study show that on the whole, both the aging population and the new generation have promoted the rise in commodity housing prices. However, the regional heterogeneity is significant. The aging population has the most significant impact on housing price increases in developed and general developed areas, and has no significant impact on housing price increases in other places. The new generation has a negative impact on housing prices in backward areas and a positive impact on housing prices in other areas. Looking further, using the ARIMA model to predict housing prices in the next 10 years, it is concluded that housing prices will show a slow upward trend in the next 10 years. Therefore, the government can ensure the stable development of the real estate market by revitalizing the second-hand housing market and implementing housing projects.


Commodity housing prices; Aging population; New generation; ARIMA

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Zou, J., Yu, T.H., Wang, D.B., 2015. Research on regional differences between population aging and housing prices: An Empirical Analysis Based on Panel Cointegration Model. Financial Research. (11), 64-79.

He, Q., Gan, J.Y., Liu, F.G., et al., 2018. Does the countercyclical factor determine the trend of RMB exchange rate. Economic Theory and Economic Management. (05), 57-70.

Luo, Y.M., Liu, Y.H., 2011. Financial agglomeration, human capital and housing price: Based on the panel VAR model. Finance and Trade Research. 22(04), 93-101.

Wang, J.J., Xie, Y., 2016. Whether the rise of house prices promotes urban sprawl: An Empirical Study Based on the panel data of 35 large and medium-sized cities in China. Financial Science. (05), 103-111.

Ding, Z.Y., 2013. Urban differentiation of housing price to income ratio in China . Journal of East China Normal University (philosophy and social sciences). 45(03), 121-127+155.

Deng, H.Q., Huang, G., Xu, Sh., 2019. The impact of population structure change on housing demand: An Empirical Analysis Based on provincial panel data from 2002 to 2016. Journal of central China Normal University. (5), 51-59.

Hamilton, B.W., 1991. The baby boom, the baby bust, and the housing market: A second look. Regional Science and Urban Economics. (4).

Xu, J.W., Xu, Q.Y., He, F., 2012. Demographic factors behind housing price rise: international experience and Chinese evidence. World Economy. 35(01), 24-42.

Li, T.P., Peng, B., Shao, H.M., 2017. Has the aging population pushed up China’s housing prices? —— Empirical analysis based on provincial dynamic panel data. Journal of China University of Geosciences (Social Science Edition). 17(05), 105-115.

Zou, J., 2017. Regional Differences between Population Aging and House Price Fluctuation. Economic Jingwei. (1), 94-99.

Gu, H.J., Zhou, X.Y., Zhang, Ch.Y., 2017. Two children in an all-round way and the influence of population age structure change on housing consumption. China Population Resources and Environment. 27(11), 31-38.

Qi, H.Q., Yan, H.Ch., 2018. Has the aging population inhibited China’s economic growth? Economic Review. (06), 28-40.



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