Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share

By David H. Autor, A. Salomons. 2018

Is automation a labor-displacing force? This possibility is both an age-old concern and at the heart of a new theoretical literature considering how labor immiseration may result from a wave of ‘brilliant machines,’ which is in part motivated by declining labor shares in many developed countries. Comprehensive evidence on this labor-displacing channel is at present limited. Using the recent model of Acemoglu and Restrepo (2018b) as an analytical frame, we first outline the various channels through which automation impacts labor ́s share of output. We then turn to empirically estimating the employment and labor share impacts of productivity growth—an omnibus measure of technological change—using data on 28 industries for 18 OECD countries since 1970. Our main findings are that although automation—whether measured by Total Factor Productivity growth or instrumented by foreign patent flows or robot adoption—has not been employment-displacing, it has reduced labor’s share in value-added. We disentangle the channels through which these impacts occur, including: own-industry effects, cross-industry input-output linkages, and final demand effects accruing through the contribution of each industry’s productivity growth to aggregate incomes. Our estimates indicate that the labor share-displacing effects of productivity growth, which were essentially absent in the 1970s, have become more pronounced over time, and are most substantial in the 2000s. This finding is consistent with automation having become in recent decades less labor-augmenting and more labor-displacing. 1 Autor: MIT Department of Economics, Cambridge, MA 02142 (dautor@mit.edu); Salomons: Utrecht University School of Economics, 3584 EC Utrecht, The Netherlands; & Technology & Policy Research Initiative, Boston University (a.m.salomons@uu.nl). Paper prepared for the Brookings Papers on Economic Activity conference, March 2018. We thank Daron Acemoglu, Uwe Blien, Janice Eberly, Maarten Goos, John Haltiwanger, Richard Rogerson, James Stock, and Xianjia Ye for valuable input that improved the paper. We thank Daron Acemoglu, Georg Graetz, Guy Michaels, and Pascual Restrepo for sharing harmonized code on penetration of industrial robotics. And we think Pian Shu for sharing data on approved patent applications by industry and year of filing. Autor acknowledges funding from IBM Higher Education, Schmidt Sciences, and the Smith-Richardson Foundation. Salomons acknowledges funding from the Netherlands Organisation for Scientific Research.

Subfields: Economics & Operations Research

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Llama 2: Open Foundation and Fine-Tuned Chat Models (2023, background): “Lastly, broader societal issues like job displacement due to accelerated AI research and an over-reliance on LLMs leading to training data degradation are also pertinent considerations (Acemoglu and Restrepo, 2018; Autor and Salomons, 2018; Webb, 2019; Shumailov et al., 2023).”
Racing with or Against the Machine? Evidence from Europe (2016, unknown): “(2018) find robustly negative employment effects, whereas positive or weakly positive effects are found by others (Autor and Salomons 2018; Dauth et al. 2017; Graetz and Michaels 2018).”
Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World (2020, background): “…& Thompson, 2015); from sociology-informed information systems research (e.g., Leonardi & Barley, 2010), which addresses wider social and organizational consequences of technology use; and from labor economics with its emphasis on firm-level and labor market outcomes (e.g., Autor & Salomons, 2018).”
The Elusive Explanation for the Declining Labor Share (2021, background): “Autor and Salomons (2018) seek to derive a bottom-line number for the impact of automation on the labor share using variation in TFP growth across countries and industries.”
Automation fears: Drivers and solutions (2020, background): “From a supply-side perspective, Frey and Osborne (2017), Berg, Buffie, and Zanna (2018), and Autor and Salomons (2018), among others, find that the balance between the enhancement and substitution effects of ATs is definitely on the side of substitution.”
The impact of automation on employment: just the usual structural change? (2018, background): “[13]) and (thereby) creation of new sectors [20–22] may be required for a sustained and balanced growth path.”
Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey (2020, unknown): “4 instance, recent research has utilized nationwide or industry-level measures of robot diffusion (Acemoglu and Restrepo 2020, Graetz and Michaels 2017), information technology (Bessen 2002), or industry-level total factor productivity and patents (Autor and Salomons 2018) as proxies for automation.”
The Fall of the Labor Share and the Rise of Superstar Firms* (2017, unknown): “This evidence is consistent with the evidence across OECD countries in Autor and Salomons (2018), who find that the labor share fall was greater in those industries where TFP growth had been most rapid.”
Artificial Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth Industrial Revolution (2020, unknown): “…2002; Fischer & Reuber, 2011; Fleming, 2018; Garbuio & Lin, 2019; Glikson & Woolley, in press; Gregory et al., in press; Hoynes & Rothstein, 2019; Ireland et al., 2003; Kronblad, in press; Kumar et al., 2019; Nambisan et al., 2019; Salomons, 2018; Vaghely & Julien, 2010; Yoo et al., 2010).”