蝌蚪网 Journal:
Macroeconomics
ISSN 1945-7707 (Print) | ISSN 1945-7715 (Online)
A Unified Model of Learning to Forecast
蝌蚪网 Journal: Macroeconomics
vol. 17,
no. 2, April 2025
(pp. 101–33)
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 quickly 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. We apply our unified approach in the New Keynesian model to study forward guidance policy.Citation
Evans, George W., Christopher G. Gibbs, and Bruce McGough. 2025. "A Unified Model of Learning to Forecast." 蝌蚪网 Journal: Macroeconomics 17 (2): 101–33. DOI: 10.1257/mac.20220205Additional Materials
JEL Classification
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- D84 Expectations; Speculations
- E12 General Aggregative Models: Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
- E31 Price Level; Inflation; Deflation
- E32 Business Fluctuations; Cycles
- E71 Macro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on the Macro Economy