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Opening the Black Box: Task and Skill Mix and Productivity Dispersion

Author

Listed:
  • Blackwood, G.Jacob

    (Amherst College)

  • Cunningham, Cindy

    (U.S. Bureau of Labor Statistics)

  • Dey, Matt

    (US Bureau of Labor Statistics)

  • Foster, Lucia

    (U.S. Census Bureau)

  • Grim, Cheryl

    (U.S. Census Bureau)

  • Haltiwanger, John C.

    (University of Maryland)

  • Nesbit, Rachel

    (University of Maryland)

  • Pabilonia, Sabrina Wulff

    (U.S. Bureau of Labor Statistics)

  • Stewart, Jay

    (U.S. Bureau of Labor Statistics)

  • Tuttle, Cody

    (University of Texas at Austin)

  • Wolf, Zoltan

    (U.S. Census Bureau)

Abstract

An important gap in most empirical studies of establishment-level productivity is the limited information about workers' characteristics and their tasks. Skill-adjusted labor input measures have been shown to be important for aggregate productivity measurement. Moreover, the theoretical literature on differences in production technologies across businesses increasingly emphasizes the task content of production. Our ultimate objective is to open this black box of tasks and skills at the establishment-level by combining establishment-level data on occupations from the Bureau of Labor Statistics (BLS) with a restricted-access establishment-level productivity dataset created by the BLS-Census Bureau Collaborative Micro-productivity Project. We take a first step toward this objective by exploring the conceptual, specification, and measurement issues to be confronted. We provide suggestive empirical analysis of the relationship between within-industry dispersion in productivity and tasks and skills. We find that within-industry productivity dispersion is strongly positively related to within-industry task/skill dispersion.

Suggested Citation

  • Blackwood, G.Jacob & Cunningham, Cindy & Dey, Matt & Foster, Lucia & Grim, Cheryl & Haltiwanger, John C. & Nesbit, Rachel & Pabilonia, Sabrina Wulff & Stewart, Jay & Tuttle, Cody & Wolf, Zoltan, 2022. "Opening the Black Box: Task and Skill Mix and Productivity Dispersion," IZA Discussion Papers 15594, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp15594
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    References listed on IDEAS

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    1. Ryan A. Decker & John Haltiwanger & Ron S. Jarmin & Javier Miranda, 2020. "Changing Business Dynamism and Productivity: Shocks versus Responsiveness," American Economic Review, American Economic Association, vol. 110(12), pages 3952-3990, December.
    2. Jan De Loecker & Pinelopi K. Goldberg & Amit K. Khandelwal & Nina Pavcnik, 2016. "Prices, Markups, and Trade Reform," Econometrica, Econometric Society, vol. 84, pages 445-510, March.
    3. Cindy Cunningham & Sabrina Wulff Pabilonia & Jay Stewart & Lucia Foster & Cheryl Grim & John Haltiwanger & Zoltan Wolf, 2021. "Chaos Before Order: Productivity Patterns in U.S. Manufacturing," International Productivity Monitor, Centre for the Study of Living Standards, vol. 41, pages 138-152, Fall.
    4. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    5. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    6. Kristin Fairman & Lucia Foster & C.J. Krizan & Ian Rucker, 2008. "An Analysis of Key Differences in Micro Data: Results from the Business List Comparison Project," Working Papers 08-28, Center for Economic Studies, U.S. Census Bureau.
    7. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    8. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    9. Paul Schreyer, 2001. "The OECD Productivity Manual: A Guide to the Measurement of Industry-Level and Aggregate Productivity," International Productivity Monitor, Centre for the Study of Living Standards, vol. 2, pages 37-51, Spring.
    10. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    11. Dunne, Timothy & Haltiwanger, John & Troske, Kenneth R., 1997. "Technology and jobs: secular changes and cyclical dynamics," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 46(1), pages 107-178, June.
    12. Lucia Foster & John Haltiwanger & Cody Tuttle, 2022. "Rising Markups or Changing Technology?," Working Papers 22-38, Center for Economic Studies, U.S. Census Bureau.
    13. G. Jacob Blackwood & Lucia S. Foster & Cheryl A. Grim & John Haltiwanger & Zoltan Wolf, 2021. "Macro and Micro Dynamics of Productivity: From Devilish Details to Insights," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 142-172, July.
    14. Nikolas Zolas & Zachary Kroff & Erik Brynjolfsson & Kristina McElheran & David Beede & Catherine Buffington & Nathan Goldschlag & Lucia Foster & Emin Dinlersoz, 2020. "Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey," Working Papers 20-40, Center for Economic Studies, U.S. Census Bureau.
    15. Devesh R. Raval, 2019. "The micro elasticity of substitution and non‐neutral technology," RAND Journal of Economics, RAND Corporation, vol. 50(1), pages 147-167, March.
    16. Handel, Michael J., 2016. "The O-NET content model: strengths and limitations," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 49(2), pages 157-176.
    17. David Card & John E. DiNardo, 2002. "Skill-Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles," Journal of Labor Economics, University of Chicago Press, vol. 20(4), pages 733-783, October.
    18. Handel, Michael J., 2016. "The O-NET content model: strengths and limitations," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 49(2), pages 157-176.
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    More about this item

    Keywords

    manufacturing; tasks; skills; productivity;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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