ABSTRACT: This paper studies
adaptive learning with multiple models. An agent operating in a
environment is award of potential model misspecification, and tries to detect it, in real-time, using an econometric
specification test. If the current model passes the test, it is used to construct an optimal policy. If it fails the test, a new
model is selected from a fixed set of models. As the rate of coefficient updating decreases, one model becomes
dominant, and is used almost always. Dominant models can be characterized using the tools of large deviations theory.
The analysis is applied to Sargent's (1999) Phillips Curve model.
Heterogeneous Beliefs and Tests of Present Value Models (with T. Walker and C. Whiteman) forthcoming in Review of Economic Studies
ABSTRACT: This paper develops a
dynamic asset pricing model with persistent heterogeneous beliefs. The
features competitive traders who receive idiosyncratic signals of an underlying fundamentals process. We adapt
Futia's (1981) frequency domain methods to derive conditions on the fundamentals that guarantee noninvertibility of the
mapping between market data and the underlying shocks to agents' information sets. When these conditions are satisfied,
agents must 'forecast the forecasts of others'. The paper provides an explicit analytical characterization of the resulting
higher-order belief dynamics. These additional dynamics can account for observed violations of variance bounds, predictability
of excess returns, and rejections of cross-equation restrictions. (slides)