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Learning and structural change in macroeconomic data

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Abstract

We include learning in a standard equilibrium business cycle model with explicit growth. We use the model to study how the economy's agents could learn in real time about the important trend-changing events of the postwar era in the U.S., such as the productivity slowdown, increased labor force participation by women, and the \"new economy\" of the 1990s. We find that a large fraction of the observed variance of output relative to trend can be attributed to structural change in our model. However, we also find that the addition of learning and occasional structural breaks to the standard and widely-used growth model results in a balanced growth puzzle, as our approach cannot completely account for observed trends in U.S. aggregate consumption and investment. Finally, we argue that a model-consistent detrending approach, such as the one we suggest here, is necessary if the goal is to obtain an accurate assessment of an equilibrium business cycle model.

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  • James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2004-016
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    Cited by:

    1. Kozicki, Sharon & Tinsley, P.A., 2005. "Permanent and transitory policy shocks in an empirical macro model with asymmetric information," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1985-2015, November.
    2. Patrick Pintus & Jacek Suda, 2019. "Learning Financial Shocks and the Great Recession," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 31, pages 123-146, January.
    3. KevinX.D. Huang & Zheng Liu & Tao Zha, 2009. "Learning, Adaptive Expectations and Technology Shocks," Economic Journal, Royal Economic Society, vol. 119(536), pages 377-405, March.
    4. James Bullard & Stefano Eusepi, 2005. "Did the Great Inflation Occur Despite Policymaker Commitment to a Taylor Rule?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 324-359, April.
    5. James Murray, 2008. "Empirical Significance of Learning in a New Keynesian Model with Firm-Specific Capital," CAEPR Working Papers 2007-027, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    6. Carlos Hamilton Araujo & James B. Bullard & Seppo Honkapohja, 2009. "Panel discussion," Review, Federal Reserve Bank of St. Louis, vol. 91(Jul), pages 383-395.
    7. Pintus, P. A. & Suda, J., 2013. "Learning Leverage Shocks and the Great Recession," Working papers 440, Banque de France.
    8. Fout, Hamilton B. & Francis, Neville R., 2011. "Information-consistent learning and shifts in long-run productivity," Economics Letters, Elsevier, vol. 111(1), pages 91-94, April.
    9. James Bullard & Aarti Singh, 2012. "Learning And The Great Moderation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 375-397, May.
    10. Yu-chin Chen & Pisut Kulthanavit, 2008. "Adaptive Learning and Monetary Policy: Lessons from Japan," Working Papers UWEC-2008-12-P, University of Washington, Department of Economics, revised Oct 2008.
    11. Sharon Kozicki & Peter A. Tinsley, 2005. "Perhaps the FOMC did what it said it did : an alternative interpretation of the Great Inflation," Research Working Paper RWP 05-04, Federal Reserve Bank of Kansas City.
    12. Kozicki, Sharon & Tinsley, P.A., 2009. "Perhaps the 1970s FOMC did what it said it did," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 842-855, September.
    13. Branch, William A. & Evans, George W., 2006. "A simple recursive forecasting model," Economics Letters, Elsevier, vol. 91(2), pages 158-166, May.
    14. repec:zbw:cfswop:wp200341 is not listed on IDEAS
    15. Yu-chin Chen & Pisut Kulthanavit, 2016. "Monetary Policy with Imperfect Knowledge in a Small Open Economy," PIER Discussion Papers 28., Puey Ungphakorn Institute for Economic Research, revised May 2016.

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