Abstract
House prices in the main cities of China have been rising to historically high levels. Unsustainable growth of housing prices might cause financial crises and damage the whole economy. This research aims to detect whether bubbles dominate China?s real estate market. It begins by systematically analysing the features of China?s real estate sector, followed by proposing a theoretical framework to identify the fundamentals of house prices and decompose house prices into cyclical and bubble components. It then applies the vector error correction model and other econometric techniques to testify the theoretical framework with data of seven Chinese cities from 2008M01 to 2017M12. The main findings of this research include the following four parts. Firstly, the residential housing market of Shanghai was exposed to the irrational bubble issue, but the rest six cities examined were at safe positions. Secondly, both long-run and short-run relationships between economic fundamentals and house prices have been verified. Thirdly, economic regulations also have significant effects on house prices. Finally, this research suggests that the root cause of the high housing prices in major cities in China is due to the excessive capital injection into the residential property market.
Highlights
Fourteen lags allow us to capture the possible effects on the dynamics of housing prices caused by the historical changes one year earlier, with an extra two months included to increase the accuracy of our estimation
With the rapid development of the real estate market, house prices soared to extremely high levels in big cities in China
Frequent administrative adjustments of the residential housing markets and high home ownership ratio are unique features of China’s residential property markets. This contribution proposes a theoretical framework to identify the fundamentals of house prices and decompose house prices into cyclical and bubble components and using econometric techniques to support the theoretical framework
Summary
Olivier Blanchard and Mark Watson (1982) first present the concept of the housing bubble and define housing bubbles as the portion of the house prices, which exceeds the fundamental values of houses. The indirect testing method takes two steps to detect housing bubbles It first determines the fundamental values of house prices and applies statistical tests to capture the existence and scales of housing bubbles. They point out that bubbles are not a significant feature in big Chinese cities during the period from 2005 to 2010. The fundamental value regression approach is relatively accurate in testing and gauging bubbles; previous studies focused on modelling house prices and acknowledged long-term determinants in efficient and free markets, such as interest rates, disposable income and GDP growth. This research uses the price decomposition method to scale the bubble component and detect housing bubble episodes, which have never been applied in real estate markets in mainland China
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