Social Learning and Monetary Policy Rules

Bibliographic Data

ID9707632
AuthorsJasmina Arifovic (Simon Fraser University), James Bullard (Federal Reserve Bank of St. Louis), James B Bullard (0000-0002-1142-6803, Federal Reserve Bank of St. Louis), Olena Kostyshyna (0000-0003-0429-4897, Portland State University)
Year2013
Volume123
Issue567
Pages38-76
Publication date2013-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe Economic Journal (JOURNAL)
Journal identifiersISSN: 0013-0133 • E-ISSN: 1468-0297
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1111/j.1468-0297.2012.02525.x
OpenAlexW3122949278
LanguageEN
Citations received2
References cited37

We analyse the effects of social learning in a monetary policy context. Social learning might be viewed as more descriptive of actual learning behaviour in complex market economies. In our model, Taylor Principle governs uniqueness and expectational stability of rational expectations equilibrium (REE) under homogeneous recursive algorithms. We find that the Taylor Principle is not necessary for convergence to REE minimum state variable (MSV) equilibrium under social learning. Sunspot equilibria exist in the indeterminate region. Our agents cannot co‐ordinate on a sunspot equilibrium in general form specification, however, they can co‐ordinate on common factor specification. We contribute to the use of genetic algorithm learning in stochastic environments

Context (archaeology · Convergence (economics · Econometrics · Economics · Keynesian economics · Machine learning · Macroeconomics · Mathematical economics · Monetary policy · Rational expectations · Social learning · Stability (learning theory · Uniqueness · Variable (mathematics · Complex Systems and Time Series Analysis · Computer Science · Economic theories and models · Mathematics · Monetary Policy and Economic Impact · Psychology · Social Psychology

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