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Finite Horizon Learning

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  • Branch, William
  • Evans, George W
  • McGough, Bruce

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: Eulerequation 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://repo.sire.ac.uk/handle/10943/319
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Bibliographic Info

Paper provided by Scottish Institute for Research in Economics (SIRE) in its series SIRE Discussion Papers with number 2012-16.

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Date of creation: 2012
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Handle: RePEc:edn:sirdps:319

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Related research

Keywords: Planning horizon; bounded rationality; dynamic optimization; adpative learning; Ramsey Model;

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References

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  1. Bruce Preston, 2003. "Learning about monetary policy rules when long-horizon expectations matter," Working Paper 2003-18, Federal Reserve Bank of Atlanta.
  2. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
  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. 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.
  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. Liam Graham, 2011. "Individual rationality, model-consistent expectations and learning," CDMA Working Paper Series 201112, Centre for Dynamic Macroeconomic Analysis.
  4. Hommes, Cars & Zhu, Mei, 2014. "Behavioral learning equilibria," Journal of Economic Theory, Elsevier, vol. 150(C), pages 778-814.

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