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Learning and Macroeconomics

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Author Info

  • George W. Evans

    ()
    (University of Oregon Economics Department)

  • Seppo Honkapohja

    ()
    (University of Cambridge)

Abstract

Expectations play a central role in modern macroeconomic theories. The econometric learning approach models economic agents as forming expectations by estimating and updating forecasting models in real time. The learning approach provides a stability test for rational expectations and a selection criterion in models with multiple equilibria. In addition, learning provides new dynamics if older data is discounted, models are misspecified or agents choose between competing models. This paper describes the E-stability principle and the stochastic approximation tools used to assess equilibria under learning. Applications of learning to a number of areas are reviewed, including the design of monetary and fiscal policy, business cycles, self-fulfilling prophecies, hyperinflation, liquidity traps, and asset prices.

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Bibliographic Info

Paper provided by University of Oregon Economics Department in its series University of Oregon Economics Department Working Papers with number 2008-3.

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Length: 51
Date of creation: 11 Jul 2008
Date of revision:
Handle: RePEc:ore:uoecwp:2008-3

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Postal: 1285 University of Oregon, 435 PLC, Eugene, OR 97403-1285
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Web page: http://economics.uoregon.edu/
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Related research

Keywords: E-stability; least-squares; stochastic approximation; persistent learning dynamics; business cycles; monetary policy; asset prices; sunspots.;

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Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Learning in macroeconomics...
    by Mark Buchanan in The Physics of Finance on 2011-10-14 14:01:00
  2. Crazy economic models
    by Mark Buchanan in The Physics of Finance on 2011-10-11 13:27:00
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Cited by:
  1. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the initialization of adaptive learning algorithms: A review of methods and a new smoothing-based routine," Centre for Growth and Business Cycle Research Discussion Paper Series 175, Economics, The Univeristy of Manchester.
  2. Dietrichson, Jens, 2013. "Coordination Incentives, Performance Measurement and Resource Allocation in Public Sector Organizations," Working Papers 2013:26, Lund University, Department of Economics.
  3. George W. Evans, 2011. "Comment on "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing"," NBER Chapters, in: NBER Macroeconomics Annual 2011, Volume 26, pages 61-71 National Bureau of Economic Research, Inc.
  4. Paul Levine & Joseph Pearlman & Bo Yang, 2012. "Imperfect Information, Optimal Monetary Policy and Informational Consistency," School of Economics Discussion Papers 1012, School of Economics, University of Surrey.
  5. Giusto, Andrea, 2014. "Adaptive learning and distributional dynamics in an incomplete markets model," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 317-333.
  6. Bask, Mikael & Proaño, Christian R, 2012. "Optimal Monetary Policy under Learning in a New Keynesian Model with Cost Channel and Inflation Inertia," Working Paper Series 2012:7, Uppsala University, Department of Economics.
  7. Doshchyn, Artur & Giommetti, Nicola, 2013. "Learning, Expectations, and Endogenous Business Cycles," MPRA Paper 49617, University Library of Munich, Germany.
  8. 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.

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