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Intangible Capital and Measured Productivity

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  • Ellen R. McGrattan

Abstract

Because firms invest heavily in R&D, software, brands, and other intangible assets—at a rate close to that of tangible assets—changes in measured GDP, which does not include all intangible investments, understate the actual changes in total output. If changes in the labor input are more precisely measured, then it is possible to observe little change in measured total factor productivity (TFP) coincidentally with large changes in hours and investment. This mismeasurement leaves business cycle modelers with large and unexplained labor wedges accounting for most of the fluctuations in aggregate data. To address this issue, I incorporate intangible investments into a multi-sector general equilibrium model and parameterize income and cost shares using data from an updated U.S. input and output table, with intangible investments reassigned from intermediate to final uses. I employ maximum likelihood methods and quarterly observations on sectoral gross outputs for the United States over the period 1985–2014 to estimate processes for latent sectoral TFPs—that have common and sector-specific components. Aggregate hours are not used to estimate TFPs, but the model predicts changes in hours that compare well with the actual hours series and account for roughly two-thirds of its standard deviation. I find that sector-specific shocks and industry linkages play an important role in accounting for fluctuations and comovements in aggregate and industry-level U.S. data, and I find that the model’s common component of TFP is not correlated at business cycle frequencies with the standard measures of aggregate TFP used in the macroeconomic literature.

Suggested Citation

  • Ellen R. McGrattan, 2017. "Intangible Capital and Measured Productivity," NBER Working Papers 23233, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:23233
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    References listed on IDEAS

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    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
    2. Chen, Kaiji & Song, Zheng, 2013. "Financial frictions on capital allocation: A transmission mechanism of TFP fluctuations," Journal of Monetary Economics, Elsevier, vol. 60(6), pages 683-703.
    3. Carol Corrado & John Haltiwanger & Dan Sichel, 2005. "Measuring Capital in the New Economy," NBER Books, National Bureau of Economic Research, Inc, number corr05-1.
    4. Larrain, Borja & Yogo, Motohiro, 2008. "Does firm value move too much to be justified by subsequent changes in cash flow," Journal of Financial Economics, Elsevier, vol. 87(1), pages 200-226, January.
    5. Karnizova Lilia, 2012. "News Shocks, Productivity and the U.S. Investment Boom-Bust Cycle," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(1), pages 1-50, June.
    6. Corrado, Carol & Haltiwanger, John & Sichel, Daniel (ed.), 2005. "Measuring Capital in the New Economy," National Bureau of Economic Research Books, University of Chicago Press, edition 0, number 9780226116129, December.
    7. repec:eee:maches:2 is not listed on IDEAS
    8. repec:eee:macchp:v2-1013 is not listed on IDEAS
    9. Carol Corrado & John Haltiwanger & Daniel Sichel, 2005. "Introduction to "Measuring Capital in the New Economy"," NBER Chapters,in: Measuring Capital in the New Economy, pages 1-10 National Bureau of Economic Research, Inc.
    10. Frédéric Boissay & Fabrice Collard & Frank Smets, 2016. "Booms and Banking Crises," Journal of Political Economy, University of Chicago Press, vol. 124(2), pages 489-538.
    11. Brinca, P. & Chari, V.V. & Kehoe, P.J. & McGrattan, E., 2016. "Accounting for Business Cycles," Handbook of Macroeconomics, Elsevier.
    12. Dupor, Bill, 1999. "Aggregation and irrelevance in multi-sector models," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 391-409, April.
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    Cited by:

    1. Kyle F. Herkenhoff & Lee E. Ohanian & Edward C. Prescott, 2017. "Tarnishing the Golden and Empire States: Land-Use Restrictions and the U.S. Economic Slowdown," NBER Working Papers 23790, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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