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Data Revisions of Aggregate Hours Worked: Implications for the Europe-U.S. Hours Gap

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Abstract

In this article, we document that the Organisation for Economic Co-operation and Development (OECD) and the Conference Board?s Total Economy Database (TED) have substantially revised their measures of hours worked over time. Relying on the data used by Rogerson (2006) and Ohanian et al. (2008), we find that, for 2003, hours worked per person in Europe is 18 percent lower than hours worked in the United States. Using the 2016 releases of the same data for 2003 yields a gap that is 40 percent smaller?that is, only 11 percent lower. Using labor force survey data, which are less subject to data revisions, we find a Europe-U.S. hours gap of ?19 percent.

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  • 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.
    • Handle: RePEc:fip:fedlrv:00113
    DOI: doi.org/10.20955/r.101.45-56
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    References listed on IDEAS

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    1. Alberto Alesina & Edward Glaeser & Bruce Sacerdote, 2005. "Work and Leisure in the U. S. and Europe: Why so Different?," Harvard Institute of Economic Research Working Papers 2068, Harvard - Institute of Economic Research.
    2. Kelly S. Ragan, 2013. "Taxes and Time Use: Fiscal Policy in a Household Production Model," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(1), pages 168-192, January.
    3. Ohanian, Lee & Raffo, Andrea & Rogerson, Richard, 2008. "Long-term changes in labor supply and taxes: Evidence from OECD countries, 1956-2004," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1353-1362, November.
    4. Edward C. Prescott, 2004. "Why do Americans work so much more than Europeans?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 28(Jul), pages 2-13.
    5. Katharine G. Abraham & John Haltiwanger & Kristin Sandusky & James R. Spletzer, 2013. "Exploring Differences in Employment between Household and Establishment Data," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 129-172.
    6. 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.
    7. Cara McDaniel, 2011. "Forces Shaping Hours Worked in the OECD, 1960-2004," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(4), pages 27-52, October.
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    Cited by:

    1. Magnus Reif & Mewael F. Tesfaselassie & Maik H. Wolters, 2021. "Technological Growth and Hours in the Long Run: Theory and Evidence," Economica, London School of Economics and Political Science, vol. 88(352), pages 1016-1053, October.

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    More about this item

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

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