Evaluation of Housing Price Control Policies Based on a Sensitivity Analysis and Nonstationary Markov Chain Simulation: Empirical Evidence from China

ABSTRACT

This study evaluates housing price control policies in China between 2006 and 2016. A panel regression is employed to diagnose the explicit effects of these policies on housing supply and demand, followed by a nonstationary Markov model and t-copula to assess the policy sensitivity of the real-estate sector and the banking sector. This paper presents two important discoveries. First, total social welfare, represented by the sector fundamentals, is extremely sensitive to even tiny shocks from policy adjustments. Second, the current policies effectively restrain the supply of housing but not housing demand. As a result, the current policies fail to achieve their intended outcome by, on the one hand, driving up housing prices with a declining supply of housing and stable demand and, on the other, harming total social welfare. The empirical economic conditions in China are consistent with our findings.

KEY WORDS:

• housing price control policies
• nonstationary Markov chain
• stress testing

Acknowledgment

The authors thank Ms. Debra Soled for copyediting this manuscript.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 71473204] and Fundamental Research Funds for the Central Universities [grant number JBK1802013].