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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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    1. Prescott, Edward C., 1986. "Theory ahead of business-cycle measurement," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 11-44, January.
    2. repec:bla:scandj:v:93:y:1991:i:2:p:161-78 is not listed on IDEAS
    3. David Andolfatto & Paul Gomme, 2003. "Monetary Policy Regimes and Beliefs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(1), pages 1-30, February.
    4. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    5. Michael R. Pakko, 2002. "What Happens When the Technology Growth Trend Changes?: Transition Dynamics, Capital Growth and the 'New Economy'," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(2), pages 376-407, April.
    6. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    7. 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.
    8. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    9. Kahn, James A. & Rich, Robert W., 2007. "Tracking the new economy: Using growth theory to detect changes in trend productivity," Journal of Monetary Economics, Elsevier, vol. 54(6), pages 1670-1701, September.
    10. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    11. Julio J. Rotemberg, 2003. "Stochastic Technical Progress, Smooth Trends, and Nearly Distinct Business Cycles," American Economic Review, American Economic Association, vol. 93(5), pages 1543-1559, December.
    12. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    13. Packalen, M., 2000. "On the Learnability of Rational Expectations Equilibria in Three Business Cycle Models," University of Helsinki, Department of Economics 87, Department of Economics.
    14. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    15. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    16. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    17. King, Robert G. & Rebelo, Sergio T., 1999. "Resuscitating real business cycles," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 14, pages 927-1007, Elsevier.
    18. Kevin J. Lansing, 2002. "Real-time estimation of trend output and the illusion of interest rate smoothing," Economic Review, Federal Reserve Bank of San Francisco, pages 17-34.
    19. Burnside, Craig, 1998. "Detrending and business cycle facts: A comment," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 513-532, May.
    20. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : II. New directions," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 309-341.
    21. Cogley, Timothy, 2005. "How fast can the new economy grow? A Bayesian analysis of the evolution of trend growth," Journal of Macroeconomics, Elsevier, vol. 27(2), pages 179-207, June.
    22. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    23. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    24. J. B. Taylor & M. Woodford (ed.), 1999. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 1, number 1.
    25. Kevin J. Lansing, 2000. "Learning about a shift in trend output: implications for monetary policy and inflation," Proceedings, Federal Reserve Bank of San Francisco.
    26. Rotemberg, Julio J & Woodford, Michael, 1996. "Real-Business-Cycle Models and the Forecastable Movements in Output, Hours, and Consumption," American Economic Review, American Economic Association, vol. 86(1), pages 71-89, March.
    27. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
    28. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
    29. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    30. Jushan Bai & Robin L. Lumsdaine & James H. Stock, 1998. "Testing For and Dating Common Breaks in Multivariate Time Series," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 395-432.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    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. 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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