Robots and Jobs: Evidence from US Labor Markets

Abstract 

As robots and other computer-assisted technologies take over tasks previously performed by labor, there is increasing concern about the future of jobs and wages. We analyze the effect of the increase in industrial robot usage between 1990 and 2007 on US local labor markets. Using a model in which robots compete against human labor in the production of different tasks, we show that robots may reduce employment and wages, and that the local labor market effects of robots can be estimated by regressing the change in employment and wages on the change in exposure to robots in each local labor market—defined from the national penetration of robots into each industry and the local distribution of employment across industries. Using this approach, we estimate large and robust negative effects of robots on employment and wages. We show that commuting zones most affected by robots in the post-1990 era were on similar trends to others before 1990, and that the impact of robots is distinct and only weakly correlated with the prevalence of routine jobs, the impact of imports from China, and overall capital utilization. According to our estimates, each additional robot reduces employment by about seven workers, and one new robot per thousand workers reduces wages by 1.2 to 1.6 percent.

Introduction

In 1930, John Maynard Keynes famously predicted the rapid technological progress of the next 100 years, but also conjectured that this would translate into widespread “technological unemployment:” 

“We are being afflicted with a new disease of which some readers may not have heard the name, but of which they will hear a great deal in the years to come — namely, technological unemployment.” 

More than two decades later, Wassily Leontief would foretell of similar problems for workers: 

“Labor will become less and less important. . . More and more workers will be replaced by machines. I do not see that new industries can employ everybody who wants a job”(Leontief, 1952). 

Though these predictions did not come true in the decades that followed, there is renewed concern that with the striking advances in automation, robotics, and artificial intelligence, we are on the verge of —or perhaps we are already— seeing them realized (e.g., Brynjolfsson and McAfee, 2012; Ford, 2016). The mounting evidence that the automation of a range of low-skill and medium-skill occupations has contributed to wage inequality and employment polarization (e.g., Autor, Levy and Murnane, 2003; Goos and Manning, 2007; Michaels, Natraj and Van Reenen, 2014) adds to these worries. 

These concerns notwithstanding, we have little systematic evidence of the equilibrium impact of these new technologies, and especially of robots, on employment and wages. One line of research (exemplified by Frey and Osbourne, 2013) investigates how feasible it is to automate existing jobs given current and presumed technological advances. Based on the tasks that workers perform, Frey and Osborne (2013) classify 702 occupations by how susceptible they are to automation. They conclude that over the next two decades, 47 percent of US workers are at the risk of automation. Using a related methodology, McKinsey puts the same number at 45 percent, while the World Bank estimates that 57 percen of the jobs in the OECD could be automated over the next two decades (World Development Report, 2016). Even if these studies were on target on what can be technologically feasible,1 these numbers do not correspond to the equilibrium impact of automation on employment and wages. First, even if the presumed technological advances materialize, there is no guarantee that firms would choose to automate; that would depend on the costs of substituting machines for labor and how much wages change in response to this threat. Second, the labor market impacts of new technologies depend not only on where they hit but also on the adjustment in other parts of the economy. For example, other sectors and occupations might expand to soak up the labor freed from the tasks that are now performed by machines and productivity improvements due to new machines may even expand employment in affected industries (Acemoglu and Restrepo, 2016). 

In this paper we move beyond these feasibility studies and estimate the equilibrium impact of one type of automation technology, industrial robots, on US labor markets. The International Federation of Robotics—IFR for short—defines an industrial robot as “an automatically controlled, reprogrammable, and multipurpose [machine]” (IFR, 2014). That is, industrial robots are machines that do not need a human operator and that can be programmed to perform several manual tasks such as welding, painting, assembling, handling materials, or packaging. Textile looms, elevators, cranes, transportation bands or coffee makers are not industrial robots as they have a unique purpose, cannot be reprogrammed to perform other tasks, and/or require a human operator. Although this definition excludes other types of capital that may also replace labor—most notably software and human-operated machines—it enables an internationally and temporally comparable measurement of industrial robots, which are argued to have already deeply impacted the labor market and expected to transform it in the decades to come.

by Daron Acemoglu, MIT and Pascual Restrepo, Yale and Boston University |  Read more: (pdf)