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The Dynamic Relationship Between Permanent and Transitory Components of U.S. Business Cycle

Author

Listed:
  • Chang-Jin Kim

    (Korea University)

  • Jeremy Piger

    (Board of Governors)

  • Richard Startz

Abstract

This paper investigates the relationship between permanent and transitory components of U.S. recessions in an empirical model allowing for business cycle asymmetry. Using a common stochastic trend representation for real GDP and consumption, we divide real GDP into permanent and transitory components, the dynamics of which are different in booms vs. recessions. We find evidence of substantial asymmetries in postwar recessions, and that both the permanent and transitory component have contributed to these recessions. We also allow for the timing of switches from boom to recession for the permanent component to be correlated with switches from boom to recession in the transitory component. The parameter estimates suggest a specific pattern of recessions: switches in the permanent component lead switches in the transitory component both when entering and leaving recessions.

Suggested Citation

  • Chang-Jin Kim & Jeremy Piger & Richard Startz, 2003. "The Dynamic Relationship Between Permanent and Transitory Components of U.S. Business Cycle," Working Papers UWEC-2003-36, University of Washington, Department of Economics.
    • Handle: RePEc:udb:wpaper:uwec-2003-36
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    Cited by:

    1. Martin Iseringhausen & Hauke Vierke, 2019. "What Drives Output Volatility? The Role of Demographics and Government Size Revisited," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 849-867, August.
    2. Chin Nam Low & Heather Anderson & Ralph D. Snyder, 2006. "Beveridge-Nelson Decomposition with Markov Switching," Monash Econometrics and Business Statistics Working Papers 17/06, Monash University, Department of Econometrics and Business Statistics.
    3. Danilo Leiva-Leon, 2017. "Measuring Business Cycles Intra-Synchronization in US: A Regime-switching Interdependence Framework," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 513-545, August.
    4. Okimoto, Tatsuyoshi & Takaoka, Sumiko, 2022. "The credit spread curve distribution and economic fluctuations in Japan," Journal of International Money and Finance, Elsevier, vol. 122(C).
    5. Attfield, Cliff & Temple, Jonathan R.W., 2010. "Balanced growth and the great ratios: New evidence for the US and UK," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 937-956, December.
    6. MeiChi Huang & Tzu-Chien Wang, 2015. "Housing-bubble vulnerability and diversification opportunities during housing boom–bust cycles: evidence from decomposition of asset price returns," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(2), pages 605-637, March.
    7. Eo, Yunjong & Morley, James, 2023. "Does the Survey of Professional Forecasters help predict the shape of recessions in real time?," Economics Letters, Elsevier, vol. 233(C).
    8. Zeynep Senyuz, 2011. "Factor analysis of permanent and transitory dynamics of the US economy and the stock market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 975-998, September.
    9. Yunjong Eo & James Morley, 2022. "Why Has the U.S. Economy Stagnated since the Great Recession?," The Review of Economics and Statistics, MIT Press, vol. 104(2), pages 246-258, May.
    10. Richard G. Anderson & Marcelle Chauvet & Barry Jones, 2015. "Nonlinear Relationship Between Permanent and Transitory Components of Monetary Aggregates and the Economy," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 228-254, February.
    11. James Morley, 2019. "The business cycle: periodic pandemic or rollercoaster ride?," International Journal of Economic Policy Studies, Springer, vol. 13(2), pages 425-431, August.
    12. Maddalena Cavicchioli, 2023. "Trend and cycle decomposition of Markov switching (co)integrated time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1381-1406, December.

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