Robots at Work

By Georg Graetz, Guy Michaels. Review of Economics and Statistics, 2015

1,500 citations recorded by the source corpus.

Abstract We analyze for the first time the economic contributions of modern industrial robots, which are flexible, versatile, and autonomous machines. We use novel panel data on robot adoption within industries in seventeen countries from 1993 to 2007 and new instrumental variables that rely on robots’ comparative advantage in specific tasks. Our findings suggest that increased robot use contributed approximately 0.36 percentage points to annual labor productivity growth, while at the same time raising total factor productivity and lowering output prices. Our estimates also suggest that robots did not significantly reduce total employment, although they did reduce low-skilled workers’ employment share.

Subfields: Economics and Econometrics, General Health Professions, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/f2d582c675ac69cc5da0b54d9b1fe53329f01820

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In General Health Professions

In Sociology and Political Science

Citations in the corpus

Artificial Intelligence, Automation, and Work (2018, neutral): “…in the late 1980s, which automated many of the remaining labor-intensive tasks in manufacturing, including machining, welding, painting, palletizing, assembly, material handling, and quality control (Ayres and Miller 1983; Groover et al. 1986; Graetz and Michaels 2015; Acemoglu and Restrepo 2017).”
Did Austerity Cause Brexit? (2019, neutral): “, 2013; Scheve and Slaughter, 2004; Grossman and Rossi-Hansberg, 2008), structural transformation (Rogerson, 2008; Rodrik, 2016), the rise of automation (Caprettini and Voth, 2015; Graetz and Michaels, 2015), skill-biased technological change more broadly (Acemoglu, 1998; Autor et al.”
Robots, Tasks and Trade (2018, positive): “19 The IFR data are regarded as the best source of information on industrial robots (Graetz and Michaels, 2018; Acemoglu and Restrepo, 2017b).”
Political machinery: did robots swing the 2016 US presidential election? (2018, background): “Although the causes of this detachment are still being debated, a growing body of work has identified automation as one of the prime forces driving the shifts in income shares along the occupational wage distribution (Autor et al., 2003, 2006; Autor and Dorn, 2013; Graetz and Michaels, 2015; Michael”
The Rise of Robots in China (2019, background): “Several recent studies have investigated the link between robots and jobs using data aggregated at the country or industry level (for example, Graetz and Michaels 2018; Acemoglu and Restrepo 2017, 2018).”
Benign Effects of Automation: New Evidence from Patent Texts (2018, neutral): “Magerman, Looy, and Song (2010) note that there is almost no research which uses the actual texts of the patent document, although this has been recommended as early as Griliches (1990). An exception is Bessen and Hunt (2007), who identify software patents by searching patent texts for keywords.”