پویایی بازار مسکن: مدارک و شواهد از بازگشت به میانگین و تغییرناپذیری رو به پایین

House prices often exhibit serial correlation and mean reversion. Using two large panel datasets, this paper analyzes the price dynamics in two significantly different types of markets, cyclical (or volatile) and non-cyclical (or tame), by applying an autoregressive mean reversion (ARMR) model. Our results show that cyclical markets have larger AR coefficients than non-cyclical markets. As a result, house prices in cyclical markets tend to have larger price cycles. We also find that the upward periods have larger AR coefficients than the downward periods. This demonstrates that house prices are likely to overshoot the equilibrium in appreciating markets while experiencing downward rigidity during periods of decline. The model developed in this paper can produce a forecast with rich house price dynamics across markets. Our results can also be used to determine how house prices in overvalued markets will ultimately adjust.