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      The Productivity J-Curve: How Intangibles Complement General Purpose Technologies

      1 , 2 , 3
      American Economic Journal: Macroeconomics
      American Economic Association

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          Abstract

          General purpose technologies (GPTs) like AI enable and require significant complementary investments. These investments are often intangible and poorly measured in national accounts. We develop a model that shows how this can lead to underestimation of productivity growth in a new GPTs early years and, later, when the benefits of intangible investments are harvested, productivity growth overestimation. We call this phenomenon the Productivity J-curve. We apply our method to US data and find that adjusting for intangibles related to computer hardware and software yields a TFP level that is 15.9 percent higher than official measures by the end of 2017. (JEL E22, E23, G31, L63, L86)

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          Most cited references52

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          Technical Change and the Aggregate Production Function

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            A Contribution to the Theory of Economic Growth

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              A General Equilibrium Approach To Monetary Theory

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                Author and article information

                Journal
                American Economic Journal: Macroeconomics
                American Economic Journal: Macroeconomics
                American Economic Association
                1945-7707
                1945-7715
                January 01 2021
                January 01 2021
                : 13
                : 1
                : 333-372
                Affiliations
                [1 ]Stanford University, Stanford Digital Economy Laboratory, 366 Galvez Street, Room 238, Stanford, CA 94305, and NBER (email: )
                [2 ]University of Pennsylvania, Wharton School, 3730 Walnut St, Philadelphia, PA 19104 (email: )
                [3 ]University of Chicago Booth School of Business, 5807 S. Woodlawn Ave., Chicago, IL 60637, and NBER (email: )
                Article
                10.1257/mac.20180386
                a651cb94-6216-4cdb-8bcd-70fea44ad7a8
                © 2021
                History

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