We compare the performance of alternative recursive forecasting models. A simple constant gain algorithm, used widely in the learning literature, both forecasts well out of sample and also provides the best fit to the Survey of Professional Forecasters.
How does a boundedly rational optimizing agent make decisions? Can such an agent learn to behave rationally? We address these questions in a standard regulator environment. Our behavioral primitive is anchored to the shadow price of the state vector. The regulator forecasts the value of an additional unit of the state tomorrow, and uses this forecast to… (More)
We introduce the concept of a Misspecification Equilibrium to dynamic macroeconomics. A Misspecification Equilibrium occurs in a stochastic process when agents forecast optimally given that they must choose from a list of misspecified econometric models. With appropriate restrictions on the asymp-totic properties of the exogeneous process and on the… (More)
We examine local strong rationality (LSR) in multivariate models with both forward-looking expectations and predetermined variables. Given hypothetical common knowledge restrictions that the dynamics will be close to those of a specified minimal state variable solution, we obtain eductive stability conditions for the solution to be LSR. In the saddlepoint… (More)
We study the properties of the generalized stochastic gradient (GSG) learning in forward-looking models. GSG algorithms are a natural and convenient way to model learning when agents allow for parameter drift or robustness to parameter uncertainty in their beliefs. The conditions for convergence of GSG learning to a rational expectations equilibrium are… (More)
Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions… (More)
This paper studies long-run inflation targets and stability in an imperfect information environment. When central banks set an inflation target that is not fully communicated, agents draw inferences about inflation from recent data and remain alert to structural change in their econometric model by forming expectations from a forecasting model that is… (More)