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A Unified Model of Learning to Forecast Brown Bag Seminar

Speaker: Professor George Evans, University of Oregon and University of St Andrews

Abstract: We propose a model of boundedly rational and heterogeneous expectations that unifies adaptive learning, k-level reasoning, and replicator dynamics. Level-0 forecasts evolve over time via adaptive learning. Agents revise over time their depth of reasoning in response to forecast errors, observed and counterfactual. The unified model makes sharp predictions for when and how fast markets converge in Learning-to-Forecast Experiments, including novel predictions for individual and market behavior in response to announced events. We present experimental results that support these predictions. Macroeconomic applications to the cost of disinflation and to forward guidance illustrate the explanatory power of the unified model.

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