The Productivity J-Curve: How Intangibles Complement General Purpose Technologies
Erik BrynjolfssonStanford University, Stanford Digital Economy Laboratory, 366 Galvez Street, Room 238, Stanford, CA 94305, and NBER (email: )Daniel RockUniversity of Pennsylvania, Wharton School, 3730 Walnut St, Philadelphia, PA 19104 (email: )Chad SyversonUniversity of Chicago Booth School of Business, 5807 S. Woodlawn Ave., Chicago, IL 60637, and NBER (email: )
2020en
ABI
Аннотация
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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