Abstract
This paper introduces the concept of a Forecast Combination Equilibrium to model boundedly rational agents who combine a menu of different forecasts using insights from the forecasting literature to mimic the behavior of actual forecasters. The equilibrium concept is consistent with rational expectations under certain conditions, while also permitting multiple, distinct, self-fulfilling equilibria, many of which are stable under least squares learning. The equilibrium concept is applied to a simple Lucas-type monetary model where agents engage in constant gain learning. The combination of multiple equilibria and learning is sufficient to replicate some key features of inflation data, such as time-varying volatility and periodic bouts of high inflation or deflation in a model that experiences only i.i.d. random shocks.
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