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Employment and the business cycle

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  • Marcelle, Chauvet
  • Jeremy, Piger

Abstract

The Great Recession of 2007-2009 has not only caused a large wealth loss, it was also followed by a sluggish subsequent recovery. Two years after officially emerging from the recession, the economy was still growing at a low pace and payroll employment was far from reaching its previous peak. However, assessment of the employment situation was markedly different across different series. The two most important employment series, payroll employment (ENAP) and civilian employment (TCE), have recently been displaying divergent patterns. This has been a source of great uncertainty regarding labor market conditions. This paper investigates the differences in the cyclical dynamics of these series and the implications for monitoring business cycle on a current basis. Univariate and multivariate Markov switching models are applied to revised and real time unrevised data. We find that the main differences across these series occur around recessions. The employment measures have diverged considerably around the last three recessions in 1990-1991, in 2001, and in 2007-2009, but especially during their subsequent recoveries. In particular, while the probabilities of recession for models that include ENAP depict jobless recoveries, the probabilities of recessions from models with TCE fall right around the trough of the last three recessions, as determined by the NBER. This significantly impacts the identification of turning points in multivariate models in sample and in recursive real time analysis, with models that use TCE being more accurate compared to the NBER dating, and delivering faster call of troughs in real time. Models that include ENAP series, on the other hand, yield delays in signaling business cycle troughs, especially the most recent ones.

Suggested Citation

  • Marcelle, Chauvet & Jeremy, Piger, 2010. "Employment and the business cycle," MPRA Paper 46642, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:46642
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    References listed on IDEAS

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    1. Marcelle Chauvet & James D. Hamilton, 2006. "Dating Business Cycle Turning Points," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 1-54, Emerald Group Publishing Limited.
    2. Marcelle Chauvet & Jeremy M. Piger, 2003. "Identifying business cycle turning points in real time," Review, Federal Reserve Bank of St. Louis, vol. 85(Mar), pages 47-61.
    3. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    4. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    5. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
    6. Nicholas Haltom & Vanessa D. Mitchell & Ellis W. Tallman, 2005. "Payroll employment data: measuring the effects of annual benchmark revisions," Economic Review, Federal Reserve Bank of Atlanta, vol. 90(Q 2), pages 1-23.
    7. Watson, Mark W, 1994. "Business-Cycle Durations and Postwar Stabilization of the U.S. Economy," American Economic Review, American Economic Association, vol. 84(1), pages 24-46, March.
    8. Chinhui Juhn & Simon M. Potter, 1999. "Explaining the recent divergence in payroll and household employment growth," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 5(Dec).
    9. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    10. James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2007. "Normalization in Econometrics," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 221-252.
    11. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    12. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
    13. Kitchen, John, 2003. "A Note on the Observed Downward Bias in Real-Time Estimates of Payroll Jobs Growth in Early Expansions," MPRA Paper 21070, University Library of Munich, Germany.
    14. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    15. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    16. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    17. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    18. James H. Stock & Mark W. Watson, 2010. "Indicators for Dating Business Cycles: Cross-History Selection and Comparisons," American Economic Review, American Economic Association, vol. 100(2), pages 16-19, May.
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    Cited by:

    1. Howard J. Wall, 2023. "Sex and the business cycle," Applied Economics, Taylor & Francis Journals, vol. 55(17), pages 1958-1971, April.
    2. Wall, Howard, 2023. "The Great, Greater, and Greatest Recessions of US States," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 53(1), January.
    3. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    4. Eiji Goto & Jan P.A.M. Jacobs & Tara M. Sinclair & Simon van Norden, 2023. "Employment reconciliation and nowcasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1007-1017, November.

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    More about this item

    Keywords

    Employment; Business Cycle; Turning Point; Real Time; Markov-Switching; Dynamic Factor Model; Jobless Recovery;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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