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Learning stability in economics with heterogeneous agents

Listed author(s):
  • Honkapohja, Seppo
  • Mitra, Kaushik

An economy exhibits structural heterogeneity when the forecasts of different agents have different effects on the determination of aggregate variables. We study how different forms of heterogeneity in structure, forecasts and adaptive learning rules affect the conditions for convergence of adaptive learning towards rational expectations equilibrium. Results are applied to the market model with supply lags, a New Keynesian model of interest rate setting and the monetary inflation model with heterogenous agents. JEL Classification: D83, C62, E30

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Paper provided by European Central Bank in its series Working Paper Series with number 0120.

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Date of creation: Jan 2002
Handle: RePEc:ecb:ecbwps:20020120
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  8. Thomas J. Sargent & Noah Williams, 2003. "Impacts of priors on convergence and escapes from Nash inflation," FRB Atlanta Working Paper 2003-14, Federal Reserve Bank of Atlanta.
  9. Evans, George W. & Honkapohja, Seppo, 2002. "Adaptive learning and monetary policy design," Research Discussion Papers 29/2002, Bank of Finland.
  10. George W. Evans & Seppo Honkapohja, "undated". "Economic Dynamics with Learning: New Stability Results," Computing in Economics and Finance 1997 51, Society for Computational Economics.
  11. Honkapohja, Seppo & Evans, George W., 2000. "Expectations and the stability problem for optimal monetary policies," Discussion Paper Series 1: Economic Studies 2000,10, Deutsche Bundesbank, Research Centre.
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  24. Chryssi Giannitsarou, 2003. "Heterogeneous Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(4), pages 885-906, October.
  25. George W. Evans & Seppo Honkapohja, 2002. "Monetary Policy, Expectations and Commitment," University of Oregon Economics Department Working Papers 2002-11, University of Oregon Economics Department, revised 01 Feb 2004.
  26. Marimon, Ramon & Sunder, Shyam, 1993. "Indeterminacy of Equilibria in a Hyperinflationary World: Experimental Evidence," Econometrica, Econometric Society, vol. 61(5), pages 1073-1107, September.
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  28. Cho, In-Koo & Sargent, Thomas J., 2000. "Escaping Nash inflation," Working Paper Series 0023, European Central Bank.
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  37. Evans, George W & Honkapohja, Seppo, 1995. "Local Convergence of Recursive Learning to Steady States and Cycles in Stochastic Nonlinear Models," Econometrica, Econometric Society, vol. 63(1), pages 195-206, January.
  38. Marcet, Albert & Sargent, Thomas J, 1989. "Convergence of Least-Squares Learning in Environments with Hidden State Variables and Private Information," Journal of Political Economy, University of Chicago Press, vol. 97(6), pages 1306-1322, December.
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