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Do Computers Make Output Harder to Measure?

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  • McGuckin, Robert H
  • Stiroh, Kevin J

Abstract

In recent years, U.S. productivity growth accelerated sharply in manufacturing, but has remained sluggish in the most computer-intensive service industries. This paper explores the possibility that information technology is generating output that is increasingly hard to measure in nonmanufacturing industries, which contributes to the divergence in industry productivity growth rates. Our results suggest that measurement error in 13 computer-intensive, nonmanufacturing industries increased between 0.74 and 1.57 percentage points per year in the 1990s, which understates annual aggregate productivity growth by 0.10 to 0.20 percentage points in the 1990s. This adds to an estimated 0.22 to 0.30 percentage point error from the increasing share of aggregate output in these hard-to-measure industries. Thus, increasing measurement problems may understate aggregate productivity growth by an additional 0.32 to 0.50 percentage points per year in the 1990s and play an important role in understanding recent productivity trends at the industry level. Copyright 2001 by Kluwer Academic Publishers

Suggested Citation

  • McGuckin, Robert H & Stiroh, Kevin J, 2001. "Do Computers Make Output Harder to Measure?," The Journal of Technology Transfer, Springer, vol. 26(4), pages 295-321, October.
    • Handle: RePEc:kap:jtecht:v:26:y:2001:i:4:p:295-321
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    Cited by:

    1. Bart van Ark & Robert Inklaar & Robert H. McGuckin, 2003. "ICT and Productivity in Europe and the United States Where Do the Differences Come From?," CESifo Economic Studies, CESifo Group, vol. 49(3), pages 295-318.
    2. Kevin J. Stiroh, 2002. "Information Technology and the U.S. Productivity Revival: What Do the Industry Data Say?," American Economic Review, American Economic Association, vol. 92(5), pages 1559-1576, December.
    3. Kevin J. Stiroh & Dale W. Jorgenson, 2000. "U.S. Economic Growth at the Industry Level," American Economic Review, American Economic Association, vol. 90(2), pages 161-167, May.
    4. Crafts, Nicholas, 2002. "The Solow Productivity Paradox in Historical Perspective," CEPR Discussion Papers 3142, C.E.P.R. Discussion Papers.
    5. Kapur, Basant K., 2012. "Progressive services, asymptotically stagnant services, and manufacturing: Growth and structural change," Journal of Economic Dynamics and Control, Elsevier, vol. 36(9), pages 1322-1339.
    6. Irene Bertschek & Michael Polder & Patrick Schulte, 2019. "ICT and resilience in times of crisis: evidence from cross-country micro moments data," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 28(8), pages 759-774, November.
    7. Polder, Michael & Bertschek, Irene & Schulte, Patrick, 2017. "ICT and Resilience in Times of Crisis: What Do the Meso-Level Data Say?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168274, Verein für Socialpolitik / German Economic Association.
    8. Sang-Yong Tom Lee & Xiao Jia Guo, 2004. "Information and Communications Technology (ICT) and Spillover: A Panel Analysis," Econometric Society 2004 Far Eastern Meetings 722, Econometric Society.
    9. Andrés Maroto-Sanchez, 2010. "Growth and productivity in the service sector: The state of the art," Working Papers 07/10, Instituto Universitario de Análisis Económico y Social.

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    More about this item

    JEL classification:

    • L8 - Industrial Organization - - Industry Studies: Services
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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