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Baysian Model Averaging, Learning and Model Selection

Author

Listed:
  • Mitra, Kaushik
  • Evans, George W.
  • Honkapohja, Seppo
Abstract
Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.

Suggested Citation

  • Mitra, Kaushik & Evans, George W. & Honkapohja, Seppo, 2012. "Baysian Model Averaging, Learning and Model Selection," SIRE Discussion Papers 2012-11, Scottish Institute for Research in Economics (SIRE).
    • Handle: RePEc:edn:sirdps:314
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    File URL: http://hdl.handle.net/10943/314
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    References listed on IDEAS

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    1. In-Koo Cho & Noah Williams & Thomas J. Sargent, 2002. "Escaping Nash Inflation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(1), pages 1-40.
    2. Young, H. Peyton, 2004. "Strategic Learning and its Limits," OUP Catalogue, Oxford University Press, number 9780199269181.
    3. Thomas J. Sargent & Noah Williams, 2005. "Impacts of Priors on Convergence and Escapes from Nash Inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 360-391, April.
    4. McGough, Bruce, 2003. "Statistical Learning With Time-Varying Parameters," Macroeconomic Dynamics, Cambridge University Press, vol. 7(1), pages 119-139, February.
    5. Timothy Cogley & Thomas J. Sargent, 2005. "The conquest of US inflation: Learning and robustness to model uncertainty," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 528-563, April.
    6. George W. Evans & Seppo Honkapohja, 2009. "Learning and Macroeconomics," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 421-451, May.
    7. Bullard, James, 1992. "Time-varying parameters and nonconvergence to rational expectations under least squares learning," Economics Letters, Elsevier, vol. 40(2), pages 159-166, October.
    8. Bray, Margaret M & Savin, Nathan E, 1986. "Rational Expectations Equilibria, Learning, and Model Specification," Econometrica, Econometric Society, vol. 54(5), pages 1129-1160, September.
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    Cited by:

    1. Audzei, Volha, 2023. "Learning and cross-country correlations in a multi-country DSGE model," Economic Modelling, Elsevier, vol. 120(C).
    2. Carlos Carvalho & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2023. "Anchored Inflation Expectations," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 1-47, January.
    3. Fabrizio Coricelli & Zorobabel Bicaba, 2015. "Learning to open up: Capital account liberalizations in the post-Bretton Woods era," Working Papers halshs-01267264, HAL.
    4. Tortorice, Daniel L, 2018. "The business cycle implications of fluctuating long run expectations," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 266-291.
    5. Vidakovic, Neven, 2014. "Exchange rate regime and household's choice of debt," MPRA Paper 54219, University Library of Munich, Germany.

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    More about this item

    Keywords

    Learning dynamics; Bayesian model averaging; grain of truth; self-referential systems;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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