Abstract
This study explored risk transfer among the housing markets of five major cities in China, comprising three first-tier cities (i.e., Beijing, Shanghai, and Shenzhen) and two second-tier cities (i.e., Tianjin and Chongqing). House price index data from January 2001 to June 2017 and a vector autoregressive–multivariate generalized autoregressive conditional heteroscedasticity model were employed to estimate correlations among these cities related to house price returns and volatility. In addition, volatility impulse-response functions were estimated to determine interactions among housing market risk in different cities. The results revealed that first-tier cities were more likely to transfer risk to second-tier cities, and that Beijing’s housing market exerted the greatest influence on risk in other cities’ housing markets. To consider the influence of the 2008 global financial crisis, data collected before and after the crisis were divided into two groups for subsequent investigation. The results revealed that these cities became more closely interrelated after the financial crisis, thereby escalating the risk of impulse influences. Finally, this study evaluated the influences of macroeconomic impulses on the housing markets of the three first-tier cities, indicating that real estate in these three cities can protect investors against inflation. The evidence presented in this paper can serve as a reference for the Chinese government regarding risk control.
Highlights
During the 19th Chinese Communist Party National Congress held in October 2017, a guideline for the development of the residential housing market in China was proposed, namely that “houses are for living, not for flipping”
China has only quasi-real estate investment trust (REIT) offered through private placement (REITs generally refer to publicly offered real estate funds); this shows the cautiousness of China’s supervisory authorities in relation to housing market risk control
Weng and Gong [33] used the house price indices (HPIs) of ten major Chinese cities from January 2005 to December 2014 to analyze volatility spillover effects and identify the determinants of price co-movement across China’s regional housing markets; the results revealed that house prices in cities are primarily influenced by population, income, mortgage rates, policy factors, and macroeconomic conditions at the national level
Summary
During the 19th Chinese Communist Party National Congress held in October 2017, a guideline for the development of the residential housing market in China was proposed, namely that “houses are for living, not for flipping”. In the 2016–2017 policy campaign, the State Council, China Securities Regulatory Commission, and Ministry of Housing and Urban–Rural Development all vigorously promoted the release of REITs. Under the increasing risk of a housing market bubble, these government agencies claimed that the promotion of rental property-based REITs enables housing to return to its original function of providing a living space, thereby contributing to healthy and orderly development in the housing industry (please refer to an official notice by the Chinese government: House Building (2017), No 153). This study adopted a model to simultaneously estimate co-movement of returns and risks among different markets and correlation between house price returns and volatility to produce a volatility impulse-response function This enabled quantifying house price risk variation in first-tier cities with respect to the macroeconomic impulse.
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