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Unemployment insurance claims and economic activity

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Abstract

Economic forecasters pay especially close attention to labor market indicators during periods of economic uncertainty. Labor market data are thought to provide early evidence about changes in the course of the economy. This article examines whether monthly changes in labor market indicators are useful for predicting real GDP. It then examines whether weekly changes in initial and continuing unemployment insurance claims are useful for helping to predict changes in important labor market indicators. Incoming monthly data on nonfarm payroll jobs and the index of aggregate weekly hours help predict changes in real GDP growth, but data on the civilian unemployment rate do not. The authors also find that unemployment insurance claims help to predict changes in monthly labor variables. As others have found, these predictions work best in periods of recession. However, this article shows that there was also some predictive ability during the 1990s expansion.

Suggested Citation

  • William T. Gavin & Kevin L. Kliesen, 2002. "Unemployment insurance claims and economic activity," Review, Federal Reserve Bank of St. Louis, vol. 84(May), pages 15-28.
    • Handle: RePEc:fip:fedlrv:y:2002:i:may:p:15-28:n:v.84no.3
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    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. Daniel M. Chin & Preston J. Miller, 1996. "Using monthly data to improve quarterly model forecasts," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 20(Spr), pages 16-33.
    3. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    4. Jerry L. Jordan, 1992. "What monetary policy can and cannot do," Economic Commentary, Federal Reserve Bank of Cleveland, issue May.
    5. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    6. Margaret M. McConnell, 1998. "Rethinking the value of initial claims as a forecasting tool," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 4(Nov).
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    Cited by:

    1. Min Jeong Kim & Dohyoung Kwon, 2023. "Dynamic asset allocation strategy: an economic regime approach," Journal of Asset Management, Palgrave Macmillan, vol. 24(2), pages 136-147, March.
    2. John Carter Braxton, 2013. "Revisiting the use of initial jobless claims as a labor market indicator," Research Working Paper RWP 13-03, Federal Reserve Bank of Kansas City.
    3. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    4. Sardar, Naafey & Qureshi, Irfan, 2024. "Revisiting the relationship between oil supply news shocks and U.S. economic activity: Role of the zero lower bound," Energy Economics, Elsevier, vol. 132(C).
    5. Kevin L. Kliesen & David C. Wheelock, 2012. "How well do initial claims forecast employment growth over the business cycle and over time?," Economic Synopses, Federal Reserve Bank of St. Louis.
    6. 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.
    7. Hassan Mohammadi & Daniel Rich, 2013. "Dynamics of Unemployment Insurance Claims: An Application of ARIMA-GARCH Models," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 41(4), pages 413-425, December.
    8. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.

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    Keywords

    Unemployment; Labor market;

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