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Challenges to Mismeasurement Explanations for the US Productivity Slowdown

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  • Chad Syverson

Abstract

The United States has been experiencing a slowdown in measured labor productivity growth since 2004. A number of commentators and researchers have suggested that this slowdown is at least in part illusory because real output data have failed to capture the new and better products of the past decade. I conduct four disparate analyses, each of which offers empirical challenges to this "mismeasurement hypothesis." First, the productivity slowdown has occurred in dozens of countries, and its size is unrelated to measures of the countries' consumption or production intensities of information and communication technologies (ICTs, the type of goods most often cited as sources of mismeasurement). Second, estimates from the existing research literature of the surplus created by internet-linked digital technologies fall far short of the $3 trillion or more of "missing output" resulting from the productivity growth slowdown. Third, if measurement problems were to account for even a modest share of this missing output, the properly measured output and productivity growth rates of industries that produce and service ICTs would have to have been multiples of their measured growth in the data. Fourth, while measured gross domestic income has been on average higher than measured gross domestic product since 2004—perhaps indicating workers are being paid to make products that are given away for free or at highly discounted prices—this trend actually began before the productivity slowdown and moreover reflects unusually high capital income rather than labor income (i.e., profits are unusually high). In combination, these complementary facets of evidence suggest that the reasonable prima facie case for the mismeasurement hypothesis faces real hurdles when confronted with the data.

Suggested Citation

  • Chad Syverson, 2017. "Challenges to Mismeasurement Explanations for the US Productivity Slowdown," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 165-186, Spring.
  • Handle: RePEc:aea:jecper:v:31:y:2017:i:2:p:165-86
    Note: DOI: 10.1257/jep.31.2.165
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    References listed on IDEAS

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    1. John G. Fernald, 2015. "Productivity and Potential Output before, during, and after the Great Recession," NBER Macroeconomics Annual, University of Chicago Press, vol. 29(1), pages 1-51.
    2. Ellis Connolly & Linus Gustafsson, 2013. "Australian Productivity Growth: Trends and Determinants," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 46(4), pages 473-482, December.
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    4. Agha, Leila, 2014. "The effects of health information technology on the costs and quality of medical care," Journal of Health Economics, Elsevier, vol. 34(C), pages 19-30.
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    6. João Paulo Pessoa & John Van Reenen, 2014. "The UK Productivity and Jobs Puzzle: Does the Answer Lie in Wage Flexibility?," Economic Journal, Royal Economic Society, vol. 0(576), pages 433-452, May.
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    8. Michael Elsby & Bart Hobijn & Ayseful Sahin, 2013. "The Decline of the U.S. Labor Share," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 44(2 (Fall)), pages 1-63.
    9. Rosston Gregory L. & Savage Scott J & Waldman Donald M, 2010. "Household Demand for Broadband Internet in 2010," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-45, September.
    10. Gregory Rosston & Scott Savage & Donald Waldman, 2010. "Household Demand for Broadband Internet Service," Discussion Papers 09-008, Stanford Institute for Economic Policy Research, revised Feb 2010.
    11. Shane Greenstein & Ryan C. McDevitt, 2009. "The Broadband Bonus: Accounting for Broadband Internet's Impact on U.S. GDP," NBER Working Papers 14758, National Bureau of Economic Research, Inc.
    12. Chad Syverson, 2013. "Will History Repeat Itself? Comments on “Is the Information Technology Revolution Over?”," International Productivity Monitor, Centre for the Study of Living Standards, vol. 25, pages 37-40, Spring.
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    More about this item

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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