Benign Effects of Automation: New Evidence from Patent Texts

By Katja Mann, Lukas Püttmann. Review of Economics and Statistics, 2018

150 citations recorded by the source corpus.

Abstract We provide a new measure of automation based on patents and study its employment effects. Classifying all U.S. patents granted between 1976 and 2014 as automation or nonautomation patents, we document a strong rise in the number and share of automation patents. We link patents to their industries of use and to commuting zones. To estimate the effect of automation, we use an instrumental variables strategy that relies on innovations developed independently from U.S. labor market trends. We find that automation technology has a positive effect on employment in local labor markets, driven by job growth in the service sector.

Subfields: Economics and Econometrics, Management of Technology and Innovation

View Paper: https://www.semanticscholar.org/paper/e6e3ee10ce7709d8bc4a7cf842d49b41b9dfa087

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Citations in the corpus

Exposure of occupations to technologies of the fourth industrial revolution (2021, methodology): “Mann & Püttmann (2017) use patent exposure per industry and identify a positive overall impact of automation patents on employment.”
The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality (2014, unknown): “Panel C reports the share of automation patents according to Mann and Puttmann (2018). See further details in Section 4.”
Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses (2021, background): “…that developments in AI may pose to workers (e.g., Jordan, 2018; Stark, 2017; Wacker, 2017), and a stream of research has begun to examine how AI and automation may affect the workforce (e.g., Acemoglu & Restrepo, 2018; Arntz, Gregory, & Zierahn, 2016; Frey & Osborne, 2017; Mann & Püttmann, 2017).”
Technology, Vintage-Specific Human Capital, and Labor Displacement: Evidence from Linking Patents with Occupations∗ (2022, background): “The main focus of these papers is how 5In related work, Mann and Püttmann (2018); Dechezleprêtre, Hémous, Olsen, and Zanella (2021) use patent text with different classification algorithms to identify automation patents in more recent periods, though they do not relate these patents with specific…”
New Frontiers: The Origins and Content of New Work, 1940–2018 (2022, methodology): “We build on Kogan et al. (2019); Mann and Püttmann (2020); Webb (2020), who devise textual analysis methods to identify innovations recorded in patents that potentially overlap the tasks performed by occupations, as well as papers by Brynjolfsson and Mitchell (2017); Brynjolfsson et al. (2018);…”