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?