ABSTRACT
This study investigates cointegration between monthly housing prices from one hundred Chinese cities for years 2010–2019, utilising both time-invariant and time-varying approaches. Their wavelet transformations are further explored for cointegration at the scale of greater than five years. Also studied is quantitative importance of housing price information of one city to another. Empirical results show different price relationships across different pairs of cities. While cointegrating patterns are heterogeneous across tested pairs, we present many relatively stable cointegrating relationships, which tend to be aggregated results of price relationships of different scales. Housing price information of certain cities could be reflected in that of other cities at a relatively large magnitude. The results here should be of use to investors and policymakers in the housing market.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Xiaojie Xu
Xiaojie Xu obtained Ph.D. from North Carolina State University in 2015 and is a quantitative risk manager. Dr. Xu’s research areas include applied econometrics and economic forecasting.
Yun Zhang
Yun Zhang obtained Ph.D. from North Carolina State University in 2015 and is a quantitative expert. Dr. Zhang’s research areas include applied statistics and machine learning.