Can Learning Explain Boom-Bust Cycles in Asset Prices? An Application to the US Housing Boom

46 Pages Posted: 18 Oct 2016

See all articles by Colin Caines

Colin Caines

Board of Governors of the Federal Reserve System

Date Written: 2016-10

Abstract

Explaining asset price booms poses a difficult question for researchers in macroeconomics: how can large and persistent price growth be explained in the absence large and persistent variation in fundamentals? 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 key 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, providing an additional source of propagation. In contrast, the paper shows why learning involving only one side on the market, which has been the focus of most of the literature, cannot plausibly explain persistent and large price booms. Quantitatively, the model explains recent experiences in US housing markets. A single unanticipated mortgage rate drop generates 20 quarters of price growth whilst capturing the full appreciation in US house prices in the early 2000s. The model is able to generate endogenous liberalizations in household lending conditions during price booms, consistent with US data, and replicates key volatilities of housing market variables at business cycle frequencies.

Keywords: Learning, Non-rational expectations, House prices, Boom-bust cycles

JEL Classification: E30, E17, D83, G12, R30

Suggested Citation

Caines, Colin, Can Learning Explain Boom-Bust Cycles in Asset Prices? An Application to the US Housing Boom (2016-10). FRB International Finance Discussion Paper No. 1181, Available at SSRN: https://ssrn.com/abstract=2854045 or http://dx.doi.org/10.17016/IFDP.2016.1181

Colin Caines (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th St. and Constitution Ave.
Washington, DC 20551
United States

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