Bayesian analysis of Hong Kong's housing price dynamics

This paper uses a Bayesian vector-autoregressive model with sign restrictions to estimate the underlying drivers of Hong Kong's housing price dynamics in the short run. While existing studies are useful in analysing housing valuation, little attention has been paid to the short-run dynamics. In contrast, the present paper identifies short-run drivers of housing prices using structural identification with theoretical underpinnings. We find that among the shocks that we have identified, bank lending shock and housing supply shock were the main factors affecting Hong Kong's housing prices. Low mortgage rates were another key factor that led to the significant increase in housing prices after the global financial crisis.