Financial Innovation, the Discovery of Risk, and the U.S. Credit Crisis

By Emine Boz and Enrique Mendoza

Uncertainty about the riskiness of new financial products was an important factor behind the U.S. credit crisis. We show that a boom-bust cycle in debt, asset prices and consumption characterizes the equilibrium dynamics of a model with a collateral constraint in which agents learn “by observation” the true riskiness of a new financial environment. Early realizations of states with high ability to leverage assets into debt turn agents optimistic about the persistence of a high-leverage regime. The model accounts for 69 percent of the household debt buildup and 53 percent of the rise in housing prices during 1997-2006, predicting a collapse in 2007.

What distinguishes this paper from others is that there is imperfect information about the data generating process. Households learn in a Bayesian way the parameters of the process as data accumulates. Along the way, they may be too optimistic, and this leads to over-accumulation of debt and increases in real estate prices. New information can lead to rapid decreases in house prices. Did we face such a case of Bayesian learning gone wrong?


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