Learning as a Rational Foundation for Macroeconomics and Finance
George Evans () and
Seppo Honkapohja ()
No 8340, CEPR Discussion Papers from C.E.P.R. Discussion Papers
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; E-stability; least-squares; monetary policy; persistent learning dynamics (search for similar items in EconPapers)
JEL-codes: C62 D83 D84 E32 (search for similar items in EconPapers)
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Working Paper: Learning as a rational foundation for macroeconomics and finance (2011)
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