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Finite Horizon Learning

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Author Info

  • William Branch
  • George W. Evans
  • Bruce McGough

Abstract

Incorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the literature: Euler-equation learning, which assumes that consumption decisions are made to satisfy the one-step-ahead perceived Euler equation, and infinite-horizon learning, in which consumption today is determined optimally from an infinite-horizon optimization problem with given beliefs. In our approach, agents hold a finite forecasting/planning horizon. We find for the Ramsey model that the unique rational expectations equilibrium is E-stable at all horizons. However, transitional dynamics can differ significantly depending upon the horizon.

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File URL: http://www.st-andrews.ac.uk/economics/CDMA/papers/wp1204.pdf
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Bibliographic Info

Paper provided by Centre for Dynamic Macroeconomic Analysis in its series CDMA Working Paper Series with number 201204.

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Date of creation: 25 Jan 2012
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Handle: RePEc:san:cdmawp:1204

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Related research

Keywords: Planning horizon; bounded rationality; dynamic optimization; adaptive learning; Ramsey model.;

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References

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  1. James Bullard & Kaushik Mitra, 2002. "Learning about monetary policy rules," Working Papers 2000-001, Federal Reserve Bank of St. Louis.
  2. Preston, Bruce, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," MPRA Paper 830, University Library of Munich, Germany.
  3. Roger Guesnerie, 2005. "Assessing Rational Expectations 2: "Eductive" Stability in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262072580, January.
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Cited by:
  1. Liam Graham, 2011. "Individual rationality, model-consistent expectations and learning," CDMA Working Paper Series 201112, Centre for Dynamic Macroeconomic Analysis.
  2. Isabelle SALLE (GREThA, CNRS, UMR 5113) & Martin ZUMPE (GREThA, CNRS, UMR 5113) & Murat YILDIZOGLU (GREThA, CNRS, UMR 5113) & Marc-Alexandre SENEGAS (GREThA, CNRS, UMR 5113), 2012. "Modelling Social Learning in an Agent-Based New Keynesian Macroeconomic Model," Cahiers du GREThA 2012-20, Groupe de Recherche en Economie Théorique et Appliquée.
  3. Evans, George W. & Honkapohja, Seppo, 2011. "Learning as a Rational Foundation for Macroeconomics and Finance," CEPR Discussion Papers 8340, C.E.P.R. Discussion Papers.
  4. Hommes, Cars & Zhu, Mei, 2014. "Behavioral learning equilibria," Journal of Economic Theory, Elsevier, vol. 150(C), pages 778-814.

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