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Why Do BLS Hours Series Tell Different Stories About Trends in Hours Worked?

In: Labor in the New Economy

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  • Harley Frazis
  • Jay Stewart

Abstract

Hours worked is an important economic indicator. In addition to being a measure of labor utilization, average weekly hours are inputs into measures of productivity and hourly wages, which are two key economic indicators. However, the Bureau of Labor Statistics' two hours series tell very different stories. Between 1973 and 2007 average weekly hours estimated from the BLS's household survey (the Current Population Survey or CPS) indicate that average weekly hours of nonagricultural wage and salary workers decreased slightly from 39.5 to 39.3. In contrast, average hours estimated from the establishment survey (the Current Employment Statistics survey or CES) indicate that hours fell from 36.9 to 33.8 hours per week. Thus the discrepancy between the two surveys increased from about two-and-a-half hours per week to about five-and-a-half hours. Our goal in the current study is to reconcile the differences between the CPS and CES estimates of hours worked and to better understand what these surveys are measuring. We examine a number of possible explanations for the divergence of the two series: differences in workers covered, multiple jobholding, differences in the hours concept (hours worked vs. hours paid), possible overreporting of hours in CPS, and changes in the length of CES pay periods. We can explain most of the difference in levels, but cannot explain the divergent trends.
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Suggested Citation

  • Harley Frazis & Jay Stewart, 2010. "Why Do BLS Hours Series Tell Different Stories About Trends in Hours Worked?," NBER Chapters, in: Labor in the New Economy, pages 343-372, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberch:10828
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    References listed on IDEAS

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    1. Peter Kuhn & Fernando Lozano, 2005. "The Expanding Workweek? Understanding Trends in Long Work Hours Among U.S. Men, 1979-2004," NBER Working Papers 11895, National Bureau of Economic Research, Inc.
    2. Harley Frazis & Jay Stewart, 2007. "Where Does the Time Go? Concepts and Measurement in the American Time Use Survey," NBER Chapters, in: Hard-to-Measure Goods and Services: Essays in Honor of Zvi Griliches, pages 73-97, National Bureau of Economic Research, Inc.
    3. Daniel S. Hamermesh, 1990. "Shirking or Productive Schmoozing: Wages and the Allocation of Time at Work," ILR Review, Cornell University, ILR School, vol. 43(3), pages 121-1-133-, April.
    4. Katharine G. Abraham & James R. Spletzer & Jay C. Stewart, 1998. "Divergent Trends in Alternative Wage Series," NBER Chapters, in: Labor Statistics Measurement Issues, pages 293-325, National Bureau of Economic Research, Inc.
    5. Daniel S. Hamermesh & Harley Frazis & Jay Stewart, 2005. "Data Watch: The American Time Use Survey," Journal of Economic Perspectives, American Economic Association, vol. 19(1), pages 221-232, Winter.
    6. James R. Spletzer & Katharine G. Abraham & Jay C. Stewart, 1999. "Why Do Different Wage Series Tell Different Stories?," American Economic Review, American Economic Association, vol. 89(2), pages 34-39, May.
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    Cited by:

    1. Champagne, Julien & Kurmann, André & Stewart, Jay, 2017. "Reconciling the divergence in aggregate U.S. wage series," Labour Economics, Elsevier, vol. 49(C), pages 27-41.
    2. Andrew S. Green, 2017. "Hours Off the Clock," Working Papers 17-44, Center for Economic Studies, U.S. Census Bureau.
    3. Julien Champagne & André Kurmann & Jay Stewart, 2016. "Reconciling the Differences in Aggregate U.S. Wage Series," Staff Working Papers 16-1, Bank of Canada.
    4. Michael C. Burda & Daniel S. Hamermesh & Jay Stewart, 2013. "Cyclical Variation in Labor Hours and Productivity Using the ATUS," American Economic Review, American Economic Association, vol. 103(3), pages 99-104, May.
    5. Loukas Karabarbounis, 2014. "The Labor Wedge: MRS vs. MPN," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(2), pages 206-223, April.
    6. Lachowska, Marta & Mas, Alexandre & Woodbury, Stephen A., 2022. "How reliable are administrative reports of paid work hours?," Labour Economics, Elsevier, vol. 75(C).
    7. Daniel Borowczyk-Martins & Etienne Lalé, 2019. "Employment Adjustment and Part-Time Work: Lessons from the United States and the United Kingdom," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 389-435, January.
    8. Alexander Bick & Bettina Brüggemann & Nicola Fuchs‐Schündeln, 2019. "Hours Worked in Europe and the United States: New Data, New Answers," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(4), pages 1381-1416, October.
    9. Jay Stewart & Harley Frazis, 2019. "The importance and challenges of measuring work hours," IZA World of Labor, Institute of Labor Economics (IZA), pages 1-95, July.
    10. Alexander Bick & Bettina Brüggemann & Nicola Fuchs-Schündeln, 2019. "Data Revisions of Aggregate Hours Worked: Implications for the Europe-U.S. Hours Gap," Review, Federal Reserve Bank of St. Louis, vol. 101(1), pages 45-56.
    11. Harley Frazis & Jay Stewart, 2009. "Comparing Hours per Job in the CPS and the ATUS," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 93(1), pages 191-195, August.

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    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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