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Chaos Before Order: Productivity Patterns in U.S. Manufacturing

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Listed:
  • Cindy Cunningham
  • Sabrina Wulff Pabilonia
  • Jay Stewart
  • Lucia Foster
  • Cheryl Grim
  • John Haltiwanger
  • Zoltan Wolf

Abstract

Within-industry productivity dispersion is pervasive and exhibits substantial variation across countries, industries, and time. We build on prior research that explores the hypothesis that periods of innovation are initially associated with a surge in business start-ups, followed by increased experimentation that leads to rising dispersion potentially with declining aggregate productivity growth, and then a shakeout process that results in higher productivity growth and declining productivity dispersion. Using novel detailed industrylevel data on total factor productivity and labour productivity dispersion from the Dispersion Statistics on Productivity dataset along with novel measures of entry rates from the Business Dynamics Statistics and productivity growth data from the Bureau of Labor Statistics for U.S. manufacturing industries, we find support for this hypothesis, especially for the high-tech industries. An increase in entry rates in a two-year period t is associated with an increase in dispersion and decrease in aggregate productivity growth in two-year period t+1 and a decrease in dispersion and increase in aggregate productivity growth in two-year period t+2.

Suggested Citation

  • 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.
    • Handle: RePEc:sls:ipmsls:v:41:y:2021:6
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    File URL: http://www.csls.ca/ipm/41/IPM_41_Cunningham.pdf
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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.
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    3. John C. Haltiwanger, 2022. "Entrepreneurship during the COVID-19 Pandemic: Evidence from the Business Formation Statistics," Entrepreneurship and Innovation Policy and the Economy, University of Chicago Press, vol. 1(1), pages 9-42.
    4. Emin Dinlersoz & Timothy Dunne & John Haltiwanger & Veronika Penciakova, 2021. "Business Formation: A Tale of Two Recessions," AEA Papers and Proceedings, American Economic Association, vol. 111, pages 253-257, May.
    5. Gort, Michael & Klepper, Steven, 1982. "Time Paths in the Diffusion of Product Innovations," Economic Journal, Royal Economic Society, vol. 92(367), pages 630-653, September.
    6. Mark Doms & Eric J. Bartelsman, 2000. "Understanding Productivity: Lessons from Longitudinal Microdata," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 569-594, September.
    7. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
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    Cited by:

    1. G. Jacob Blackwood & Cindy Cunningham & Matthew Dey & Lucia Foster & Cheryl Grim & John C. Haltiwanger & Rachel L. Nesbit & Sabrina Pabilonia & Jay Stewart & Cody Tuttle & Zoltan Wolf, 2023. "Opening the Black Box: Task and Skill Mix and Productivity Dispersion," NBER Chapters, in: Technology, Productivity, and Economic Growth, National Bureau of Economic Research, Inc.
    2. Lucia Foster & Alex He, 2022. "Technology and productivity growth," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(3), pages 111-119, July.

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