Working Paper: CEPR ID: DP6250
Authors: Giacomo Carboni; Martin Ellison
Abstract: We respond to the challenge of explaining the Great Inflation by building a coherent framework in which both learning and uncertainty play a central role. At the heart of our story is a Federal Reserve that learns and then disregards the Phillips curve as in Sargent's Conquest of American Inflation, but at all times takes into account that its view of the world is subject to considerable uncertainties. Allowing Federal Reserve policy to react to these perceived uncertainties improves our ability to explain the Great Inflation with a learning model. Bayesian MCMC estimation results are encouraging and favour a model where policy reacts to uncertainty over a model where uncertainty is ignored. The posterior likelihood is higher and the internal Federal Reserve forecasts implied by the model are closer to those reported in the Greenbook.
Keywords: Great Inflation; Learning; Monetary Policy; Uncertainty
JEL Codes: E52; E58; E65
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Assumption of policy ignoring uncertainty (D81) | Implausibly large errors in internal forecasts of unemployment (E27) |
| Allowing policy to internalize uncertainty (D89) | Decrease in forecast errors (C53) |
| Federal Reserve's learning process and its ability to react to uncertainty (E58) | Enhanced explanatory framework for the great inflation (E31) |
| Incorporating uncertainty into policy decisions (D80) | Better fit of the learning model to observed inflation dynamics (C51) |
| Policy reacting to uncertainty (D81) | Higher posterior likelihood (C52) |
| Policy reacting to uncertainty (D81) | Improved internal forecasts (C53) |