Working Paper: CEPR ID: DP8340
Authors: George W. Evans; Seppo Honkapohja
Abstract: Expectations play a central role in modern macroeconomics. The econometric learning approach, in line with the cognitive consistency principle, models agents as forming expectations by estimating and updating subjective forecasting models in real time. This approach provides a stability test for RE equilibria and a selection criterion in models with multiple equilibria. Further features of learning, such as discounting of older data, use of misspecified models, or heterogeneous choice by agents between competing models, generate novel learning dynamics. Empirical applications are reviewed and the roles of the planning horizon and structural knowledge are discussed. We develop several applications of learning to macroeconomic policy: the scope of Ricardian equivalence, appropriate specification of interest-rate rules, implementation of price-level targeting to achieve learning-stability of the optimal RE equilibrium and whether under learning price-level targeting can rule out the deflation trap at the zero-lower-bound.
Keywords: Asset prices; Business cycles; Cognitive consistency; Estability; Least-squares; Monetary policy; Persistent learning dynamics
JEL Codes: C62; D83; D84; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| learning (C91) | convergence towards rational expectations (D84) |
| boundedly rational agents using past data (D80) | learning correct model parameters (C52) |
| learning dynamics (C69) | multiple equilibria or cycles (D50) |
| learning (C91) | implications for economic policy (F68) |
| price-level targeting under learning conditions (E31) | rational expectations steady state (C62) |