IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/34103.html
   My bibliography  Save this paper

Employment and the business cycle

Author

Listed:
  • 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 34103, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:34103
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/34103/1/MPRA_paper_34103.pdf
    File Function: original version
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Marcelle Chauvet & James D. Hamilton, 2005. "Dating Business Cycle Turning Points," NBER Working Papers 11422, National Bureau of Economic Research, Inc.
    2. Marcelle Chauvet & Jeremy M. Piger, 2003. "Identifying business cycle turning points in real time," Review, Federal Reserve Bank of St. Louis, issue 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, issue 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, June.
    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, June.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, Elsevier.

    More about this item

    Keywords

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

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:34103. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter) or (Rebekah McClure). General contact details of provider: http://edirc.repec.org/data/vfmunde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.