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Jay Stewart

Bureau of Labor Statistics, USA, and IZA, Germany

All too often, academic research is inaccessible to policymakers. IZA’s World of Labor makes this research more accessible by providing policymakers with concise summaries of policy-relevant research on a wide range of topics

IZA World of Labor role

Author

Current position

Division Chief, Division of Productivity Research and Program Development, Bureau of Labor Statistics, USA

Research interest

Labor economics, productivity, hours measurement, time use research

Website

http://bit.ly/Stewart_IZApage

Past positions

Research Economist, Bureau of Labor Statistics, USA, 1991–2009; Visiting Assistant Professor, Tulane University, USA, 1989–1991

Qualifications

PhD Economics, University of California, Los Angeles, 1989

Selected publications

  • “Cyclical variation in labor hours and productivity using the ATUS?” American Economic Review Papers and Proceedings 103:3 (2013) (with M. Burda and D. S. Hamermesh).

  • “How does nonmarket production affect measured income inequality?” Journal of Population Economics 24:1 (2011) (with H. Frazis).

  • “Why do BLS hours series tell different stories about trends in hours worked?” In: Abraham, K. G., J. R. Spletzer, and M. J. Harper (eds). Labor in the New Economy, NBER Studies in Income and Wealth. Chicago: University of Chicago Press, 2010 (with H. Frazis).

article(s)

  • The importance and challenges of measuring work hours Updated

    Measuring work hours correctly is important, but different surveys can tell different stories

    Jay StewartHarley Frazis, July 2019
    Work hours are key components in estimating productivity growth and hourly wages as well as being a useful cyclical indicator in their own right, so measuring them correctly is important. The US Bureau of Labor Statistics (BLS) collects data on work hours in several surveys and publishes four widely used series that measure average weekly hours. The series tell different stories about average weekly hours and trends in those hours but qualitatively similar stories about the cyclical behavior of work hours. The research summarized here explains the differences in levels, but only some of the differences in trends.
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