Data and Code for Productivity J-Curve
- Brynjolfsson, Erik (Massachusetts Institute of Technology)
- Rock, Daniel (Massachusetts Institute of Technology)
- Syverson, Chad (University of Chicago)
AbstractGeneral 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 U.S. data and find that adjusting for intangibles related to computer hardware and software yields a TFP level that is 15.9% higher than official measures by the end of 2017.
Is version of
Brynjolfsson, Erik, Daniel Rock, and Chad Syverson. “The Productivity J-Curve: How Intangibles Complement General Purpose Technologies.” American Economic Journal: Macroeconomics, n.d.
Update Metadata: 2020-12-30 | Issue Number: 1 | Registration Date: 2020-12-30