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Social Learning and Monetary Policy Rules

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  • Jasmina Arifovic
  • James Bullard
  • Olena Kostyshyna

Abstract

We analyze the effects of social learning in a widely-studied monetary policy context. Social learning might be viewed as more descriptive of actual learning behavior in complex market economies. Ideas about how best to forecast the economy's state vector are initially heterogeneous. Agents can copy better forecasting techniques and discard those techniques which are less successful. We seek to understand whether the economy will converge to a rational expectations equilibrium under this more realistic learning dynamic. A key result from the literature in the version of the model we study is that the Taylor Principle governs both the uniqueness and the expectational stability of the rational expectations equilibrium when all agents learn homogeneously using recursive algorithms. We find that the Taylor Principle is not necessary for convergence in a social learning context. We also contribute to the use of genetic algorithm learning in stochastic environments.
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Suggested Citation

  • Jasmina Arifovic & James Bullard & Olena Kostyshyna, 2013. "Social Learning and Monetary Policy Rules," Economic Journal, Royal Economic Society, vol. 123(567), pages 38-76, March.
  • Handle: RePEc:ecj:econjl:v:123:y:2013:i:567:p:38-76
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    References listed on IDEAS

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    1. Seppo Honkapohja & Kaushik Mitra, 2006. "Learning Stability in Economies with Heterogeneous Agents," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(2), pages 284-309, April.
    2. James B. Bullard, 2006. "The learnability criterion and monetary policy," Review, Federal Reserve Bank of St. Louis, issue May, pages 203-217.
    3. George W. Evans & Seppo Honkapohja, 2003. "Expectations and the Stability Problem for Optimal Monetary Policies," Review of Economic Studies, Oxford University Press, vol. 70(4), pages 807-824.
    4. Chryssi Giannitsarou, 2003. "Heterogeneous Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(4), pages 885-906, October.
    5. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
    6. Honkapohja, Seppo & Mitra, Kaushik, 2005. "Performance of monetary policy with internal central bank forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 627-658, April.
    7. Branch, William A. & Evans, George W., 2006. "Intrinsic heterogeneity in expectation formation," Journal of Economic Theory, Elsevier, vol. 127(1), pages 264-295, March.
    8. Arifovic, Jasmina, 2000. "Evolutionary Algorithms In Macroeconomic Models," Macroeconomic Dynamics, Cambridge University Press, vol. 4(03), pages 373-414, September.
    9. Honkapohja, Seppo & Mitra, Kaushik, 2004. "Are non-fundamental equilibria learnable in models of monetary policy?," Journal of Monetary Economics, Elsevier, vol. 51(8), pages 1743-1770, November.
    10. repec:cup:macdyn:v:4:y:2000:i:3:p:373-414 is not listed on IDEAS
    11. Michael Woodford, 2001. "The Taylor Rule and Optimal Monetary Policy," American Economic Review, American Economic Association, vol. 91(2), pages 232-237, May.
    12. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    13. Negroni, Giorgio, 2003. "Adaptive expectations coordination in an economy with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 28(1), pages 117-140, October.
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