Abstract
This paper argues that boom-bust behavior in asset prices can be explained by a model in which boundedly rational agents learn the process for prices. The novel feature of the model is that learning operates in both the demand for assets and the supply of credit. Interactions between agents on either side of the market create complementarities in their respective beliefs, yielding strong internal propagation. The model is applied to US housing markets. Quantitative exercises explain the recent boom-bust in US house prices from observed fundamentals whilst replicating key moments of housing market variables at business cycle frequencies.
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