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Intangible Capital and Measured Productivity

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  • Ellen McGrattan

    (University of Minnesota)

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 use data from an updated U.S. input and output table to parameterize income and cost shares, 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 to estimate processes for latent sectoral TFPs that have common and sector-specific components. I do not use aggregate hours to estimate TFPs, but find that the predicted hours series compares closely with the actual series and accounts 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 at business-cycle frequencies, the model's common component of TFP is not correlated with the standard measures of aggregate TFP used in the macroeconomic literature. Adding financial frictions and stochastic shocks to financing constraints has a negligible impact on the results. (Copyright: Elsevier)

Suggested Citation

  • Ellen McGrattan, 2020. "Intangible Capital and Measured Productivity," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 37, pages 147-166, August.
  • Handle: RePEc:red:issued:20-182
    DOI: 10.1016/j.red.2020.06.007
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    2. van Rens, Thijs & Vukotic, Marija, 2020. "Delayed Adjustment and Persistence in Macroeconomic Models," The Warwick Economics Research Paper Series (TWERPS) 1245, University of Warwick, Department of Economics.
    3. Max Gillman, 2019. "A Human Capital Theory of Structural Transformation," CERGE-EI Working Papers wp648, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    4. Christian vom Lehn & Thomas Winberry, 2019. "Investment Networks, Sectoral Comovement, and the Changing U.S. Business Cycle," 2019 Meeting Papers 1158, Society for Economic Dynamics.
    5. Herkenhoff, Kyle F. & Ohanian, Lee E. & Prescott, Edward C., 2018. "Tarnishing the golden and empire states: Land-use restrictions and the U.S. economic slowdown," Journal of Monetary Economics, Elsevier, vol. 93(C), pages 89-109.
    6. Laurent Cavenaile & Pau Roldan-Blanco, 2021. "Advertising, Innovation, and Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 251-303, July.
    7. Carolina Hintzmann & Josep Lladós-Masllorens & Raul Ramos, 2021. "Intangible Assets and Labor Productivity Growth," Economies, MDPI, Open Access Journal, vol. 9(2), pages 1-21, May.
    8. Roldan-Blanco, Pau & Gilbukh, Sonia, 2021. "Firm dynamics and pricing under customer capital accumulation," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 99-119.
    9. Ye Li, 2018. "Fragile New Economy: The Rise of Intangible Capital and Financial Instability," 2018 Meeting Papers 1189, Society for Economic Dynamics.
    10. Andy Atkeson, 2020. "Alternative Facts Regarding the Labor Share," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 37, pages 167-180, August.
    11. Zuzana Molnarova, 2020. "Industry evidence and the vanishing cyclicality of labor productivity," Vienna Economics Papers 2001, University of Vienna, Department of Economics.
    12. Dongya Koh & Raül Santaeulàlia-Llopis, 2017. "Countercyclical Elasticity of Substitution," Working Papers 946, Barcelona Graduate School of Economics.
    13. Hansen, G.D. & Ohanian, L.E., 2016. "Neoclassical Models in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2043-2130, Elsevier.
    14. Gillman, Max, 2021. "Steps in industrial development through human capital deepening," Economic Modelling, Elsevier, vol. 99(C).

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    More about this item

    JEL classification:

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

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