Name File Type Size Last Modified
  Data and Code 04/14/2020 05:36:PM
  __MACOSX 02/26/2020 05:35:PM
capInputWeights.csv text/csv 117.6 KB 05/17/2018 11:21:AM
capInvest.csv text/csv 23.5 KB 12/26/2019 01:48:PM
capShares.csv text/csv 78 KB 05/17/2018 11:18:AM
capStocks.csv text/csv 39.1 KB 12/27/2019 04:24:PM
jCurveDataConstructor.ipynb text/plain 887.2 KB 02/26/2020 12:36:PM
jcurveFig1data.csv text/csv 9.4 KB 08/29/2018 12:06:PM
missingGDPCalculationTable.csv text/csv 15.1 KB 02/13/2019 12:53:PM
quarterly_tfp.csv text/csv 72.4 KB 05/17/2018 11:20:AM

Project Citation: 

Brynjolfsson, Erik, Rock, Daniel, and Syverson, Chad. Data and Code for Productivity J-Curve. Nashville, TN: American Economic Association [publisher], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-12-30. https://doi.org/10.3886/E117947V1

Project Description

Summary:  View help for Summary 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 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.

Scope of Project

JEL Classification:  View help for JEL Classification
      D24 Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
      E01 Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
      E22 Investment; Capital; Intangible Capital; Capacity
      O33 Technological Change: Choices and Consequences; Diffusion Processes


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