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Harley Frazis

Bureau of Labor Statistics, USA

I am happy to be contributing an accessible account of ours and others research on labor economics to a broader audience

IZA World of Labor role

Author

Current position

Research Economist

Research interest

Labor economics, working hours, training, time use

Positions/functions as a policy advisor

Member, Interagency Working Group on Expanded Measures of Enrollment and Attainment, 2009–2017

Qualifications

PhD Economics, University of Wisconsin-Madison, 1988

Selected publications

  • “How to think about time-use data: What inferences can we make about long- and short-run time use from time diaries?” Annals of Economics and Statistics Number 105/106 (2012): 231–246 (with J. Stewart).

  • “Reexamining the returns to training: Functional form, magnitude, and interpretation.” Journal of Human Resources 40:2 (2005), 453–476 (with M. Loewenstein).

  • "What can time-use data tell us about hours of work?" Monthly Labor Review 127:12 (2004): 3–9 (with J. Stewart).

  • “Estimating linear regressions with mismeasured, possibly endogenous, binary explanatory variables.” Journal of Econometrics 117:1 (2003): 151–178 (with M. Loewenstein).

  • “Correlates of training: An analysis using both employer and employee characteristics.” Industrial and Labor Relations Review 53:3 (2000): 443–462 (with M. Gittleman and M. Joyce).

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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