Arbeitspapier

Learning and the market for housing

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.

Language
Englisch

Bibliographic citation
Series: MNB Working Papers ; No. 2015/4

Classification
Wirtschaft
Business Fluctuations; Cycles
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
Housing Supply and Markets
Subject
housing market
DSGE
signal extraction
Bayesian estimation

Event
Geistige Schöpfung
(who)
Rots, Eyno
Event
Veröffentlichung
(who)
Magyar Nemzeti Bank
(where)
Budapest
(when)
2015

Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Rots, Eyno
  • Magyar Nemzeti Bank

Time of origin

  • 2015

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