WP 2015/4–Eyno Rots: Learning and the Market for HousingPrint
House prices have inertia, which may be because housing-market participants need time to recognize long booms and recessions. Within a dynamic stochastic general-equilibrium model with markets for housing and defaultable mortgages, I consider the case of imperfect knowledge and learning about the persistence of exogenous shocks. I evaluate the performance of the model against the last 40 years of key U.S. macroeconomic data. Bayesian comparison strongly favors the model with learning over the baseline case with perfect knowledge, although additional assumptions about the learning process may be necessary for an adequate account of house-price dynamics.
JEL: E32, E37, R31.
Keywords: housing market, DSGE, signal extraction, Bayesian estimation.