Imperfect information and the house price in a general-equilibrium model |
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| Affiliation: | 1. Charles University, Prague and University of Ss. Cyril and Methodius in Trnava, Slovakia;2. Central Bank of Hungary, Vienna University of Economics and Business and Masaryk University, Brno;3. National Bank of Slovakia, Charles University, Prague and Vienna University of Economics and Business, Austria;4. Vienna University of Economics and Business, Austria;1. School of Finance, Shanghai University of Finance and Economics, 777 Guoding Road, Shanghai 200433, China;2. DeGroote School of Business, McMaster University, Canada;3. China Academy of Financial Research, Shanghai Jiao Tong University, 211 West Huaihai Road, Shanghai 200030, China |
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| Abstract: | 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 an endogenous market for housing, I consider the case of rational expectations subject to imperfect information 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 over the baseline case with perfect information. Under imperfect information, agents rely on learning to form expectations, which improves the ability of the model to generate realistic low-frequency house-price dynamics. However, as long as the agents form expectations rationally, the improvement is limited. Furthermore, to confine price inertia within the housing market is a challenge for the general-equilibrium approach. |
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