Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We use a dynamic hierarchical factor model to identify the national, regional and local factors of the city-level housing price growth in China. During the zero-lower-bound (ZLB) episode in the U.S., local factors account for 78% of variations in the month-on-month city-level housing price growth. However, as the time horizon extends, the national factor gets a larger variance share, reaching 51% in a half-year horizon. This indicates that the city-level housing price growth in China is more of a national phenomenon in the long run. We then use a VAR model to investigate the driving forces of the national factor and find that monetary policy and hot money shocks affect the national housing price growth significantly. A tightening monetary policy shock has a significant negative impact on the national factor, which lasts for more than 2 years. An increase in hot money inflows causes a significant but transitory rise in the national factor. Moreover, we find that the quantitative easing measure adopted by the U.S. Fed is behind the surge of capital inflows into China.