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Social Learning and Monetary Policy Rules

  • Jasmina Arifovic
  • James Bullard
  • Olena Kostyshyna

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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Article provided by Royal Economic Society in its journal The Economic Journal.

Volume (Year): 123 (2013)
Issue (Month): 567 (03)
Pages: 38-76

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Handle: RePEc:ecj:econjl:v:123:y:2013:i:567:p:38-76
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  1. 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.
  2. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
  3. George W. Evans & Seppo Honkapohja, 2003. "Expectations and the Stability Problem for Optimal Monetary Policies," Review of Economic Studies, Wiley Blackwell, vol. 70(4), pages 807-824, October.
  4. Kaushik Mitra & Seppo Honkapohja, 2004. "Are Non-Fundamental Equilibria Learnable in Models of Monetary Policy?," Royal Holloway, University of London: Discussion Papers in Economics 04/13, Department of Economics, Royal Holloway University of London, revised Jul 2004.
  5. 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.
  6. James B. Bullard, 2006. "The learnability criterion and monetary policy," Review, Federal Reserve Bank of St. Louis, issue May, pages 203-217.
  7. Seppo Honkapohja & Kaushik Mitra, 2002. "Learning Stability in Economies with Heterogenous Agents," CESifo Working Paper Series 772, CESifo Group Munich.
  8. Chryssi Giannitsarou, 2003. "Heterogeneous Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(4), pages 885-906, October.
  9. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-11, July.
  10. Branch, William A. & Evans, George W., 2006. "Intrinsic heterogeneity in expectation formation," Journal of Economic Theory, Elsevier, vol. 127(1), pages 264-295, March.
  11. Arifovic, Jasmina, 2000. "Evolutionary Algorithms In Macroeconomic Models," Macroeconomic Dynamics, Cambridge University Press, vol. 4(03), pages 373-414, September.
  12. Michael Woodford, 2001. "The Taylor Rule and Optimal Monetary Policy," American Economic Review, American Economic Association, vol. 91(2), pages 232-237, May.
  13. repec:cup:macdyn:v:4:y:2000:i:3:p:373-414 is not listed on IDEAS
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