MIT study looks at the links between automation, inequality and jobs
In many parts of the U.S., robots have been replacing workers over the last few decades. But to what extent, really? Some technologists have forecast that automation will lead to a future without work, while other observers have been more skeptical about such scenarios.
Now a study co-authored by an MIT professor puts firm numbers on the trend, finding a very real impact — although one that falls well short of a robot takeover. The study also finds that in the U.S., the impact of robots varies widely by industry and region, and may play a notable role in exacerbating income inequality.
“We find fairly major negative employment effects,” MIT economist Daron Acemoglu says, although he notes that the impact of the trend can be overstated.
From 1990 to 2007, the study shows, adding one additional robot per 1,000 workers reduced the national employment-to-population ratio by about 0.2 percent, with some areas of the U.S. affected far more than others.
This means each additional robot added in manufacturing replaced about 3.3 workers nationally, on average.
That increased use of robots in the workplace also lowered wages by roughly 0.4 percent during the same time period.
“We find negative wage effects, that workers are losing in terms of real wages in more affected areas, because robots are pretty good at competing against them,” Acemoglu says.
The paper, “Robots and Jobs: Evidence from U.S. Labor Markets,” appears in advance online form in the Journal of Political Economy. The authors are Acemoglu and Pascual Restrepo PhD ’16, an assistant professor of economics at Boston University.
Displaced in Detroit
To conduct the study, Acemoglu and Restrepo used data on 19 industries, compiled by the International Federation of Robotics (IFR), a Frankfurt-based industry group that keeps detailed statistics on robot deployments worldwide. The scholars combined that with U.S.-based data on population, employment, business, and wages, from the U.S. Census Bureau, the Bureau of Economic Analysis, and the Bureau of Labor Statistics, among other sources.
The researchers also compared robot deployment in the U.S. to that of other countries, finding it lags behind that of Europe. From 1993 to 2007, U.S. firms actually did introduce almost exactly one new robot per 1,000 workers; in Europe, firms introduced 1.6 new robots per 1,000 workers.
“Even though the U.S. is a technologically very advanced economy, in terms of industrial robots’ production and usage and innovation, it’s behind many other advanced economies,” Acemoglu says.
In the U.S., four manufacturing industries account for 70 percent of robots: automakers (38 percent of robots in use), electronics (15 percent), the plastics and chemical industry (10 percent), and metals manufacturers (7 percent).
Across the U.S., the study analyzed the impact of robots in 722 commuting zones in the continental U.S. — essentially metropolitan areas — and found considerable geographic variation in how intensively robots are utilized.
Given industry trends in robot deployment, the area of the country most affected is the seat of the automobile industry. Michigan has the highest concentration of robots in the workplace, with employment in Detroit, Lansing, and Saginaw affected more than anywhere else in the country.
“Different industries have different footprints in different places in the U.S.,” Acemoglu observes. “The place where the robot issue is most apparent is Detroit. Whatever happens to automobile manufacturing has a much greater impact on the Detroit area [than elsewhere].”
In commuting zones where robots were added to the workforce, each robot replaces about 6.6 jobs locally, the researchers found. However, in a subtle twist, adding robots in manufacturing benefits people in other industries and other areas of the country — by lowering the cost of goods, among other things. These national economic benefits are the reason the researchers calculated that adding one robot replaces 3.3 jobs for the country as a whole.
The inequality issue
In conducting the study, Acemoglu and Restrepo went to considerable lengths to see if the employment trends in robot-heavy areas might have been caused by other factors, such as trade policy, but they found no complicating empirical effects.
The study does suggest, however, that robots have a direct influence on income inequality. The manufacturing jobs they replace come from parts of the workforce without many other good employment options; as a result, there is a direct connection between automation in robot-using industries and sagging incomes among blue-collar workers.
“There are major distributional implications,” Acemoglu says. When robots are added to manufacturing plants, “The burden falls on the low-skill and especially middle-skill workers. That’s really an important part of our overall research [on robots], that automation actually is a much bigger part of the technological factors that have contributed to rising inequality over the last 30 years.”
So while claims about machines wiping out human work entirely may be overstated, the research by Acemoglu and Restrepo shows that the robot effect is a very real one in manufacturing, with significant social implications.
“It certainly won’t give any support to those who think robots are going to take all of our jobs,” Acemoglu says. “But it does imply that automation is a real force to be grappled with.”
Robots help some firms, even while workers across industries struggle
“When you look at use of robots at the firm level, it is really interesting because there is an additional dimension,” says Acemoglu. “We know firms are adopting robots in order to reduce their costs, so it is quite plausible that firms adopting robots early are going to expand at the expense of their competitors whose costs are not going down. And that’s exactly what we find.”
Indeed, as the study shows, a 20 percentage point increase in robot use in manufacturing from 2010 to 2015 led to a 3.2 percent decline in industry-wide employment. And yet, for firms adopting robots during that timespan, employee hours worked rose by 10.9 percent, and wages rose modestly as well.
A new paper detailing the study, “Competing with Robots: Firm-Level Evidence from France,” will appear in the May issue of the American Economic Association: Papers and Proceedings. The authors are Acemoglu, who is an Institute Professor at MIT; Clair Lelarge, a senior research economist at the Banque de France and the Center for Economic Policy Research; and Pascual Restrepo Phd ’16, an assistant professor of economics at Boston University.
A French robot census
To conduct the study, the scholars examined 55,390 French manufacturing firms, of which 598 purchased robots during the period from 2010 to 2015. The study uses data provided by France’s Ministry of Industry, client data from French robot suppliers, customs data about imported robots, and firm-level financial data concerning sales, employment, and wages, among other things.
The 598 firms that did purchase robots, while comprising just 1 percent of manufacturing firms, accounted for about 20 percent of manufacturing production during that five-year period.
“Our paper is unique in that we have an almost comprehensive [view] of robot adoption,” Acemoglu says.
The manufacturing industries most heavily adding robots to their production lines in France were pharmaceutical companies, chemicals and plastic manufacturers, food and beverage producers, metal and machinery manufacturers, and automakers.
The industries investing least in robots from 2010 to 2015 included paper and printing, textiles and apparel manufacturing, appliance manufacturers, furniture makers, and minerals companies.
The firms that did add robots to their manufacturing processes became more productive and profitable, and the use of automation lowered their labor share — the part of their income going to workers — between roughly 4 and 6 percentage points. However, because their investments in technology fueled more growth and more market share, they added more workers overall.
By contrast, the firms that did not add robots saw no change in the labor share, and for every 10 percentage point increase in robot adoption by their competitors, these firms saw their own employment drop 2.5 percent. Essentially, the firms not investing in technology were losing ground to their competitors.
This dynamic — job growth at robot-adopting firms, but job losses overall — fits with another finding Acemoglu and Restrepo made in a separate paper about the effects of robots on employment in the U.S. There, the economists found that each robot added to the work force essentially eliminated 3.3 jobs nationally.
“Looking at the result, you might think [at first] it’s the opposite of the U.S. result, where the robot adoption goes hand in hand with destruction of jobs, whereas in France, robot-adopting firms are expanding their employment,” Acemoglu says. “But that’s only because they’re expanding at the expense of their competitors. What we show is that when we add the indirect effect on those competitors, the overall effect is negative and comparable to what we find the in the U.S.”
Superstar firms and the labour share issue
The competitive dynamics the researchers found in France resemble those in another high-profile piece of economics research recently published by MIT professors. In a recent paper, MIT economists David Autor and John Van Reenen, along with three co-authors, published evidence indicating the decline in the labor share in the U.S. as a whole was driven by gains made by “superstar firms,” which find ways to lower their labor share and gain market power.
While those elite firms may hire more workers and even pay relatively well as they grow, labor share declines in their industries, overall.
“It’s very complementary,” Acemoglu observes about the work of Autor and Van Reenen. However, he notes, “A slight difference is that superstar firms [in the work of Autor and Van Reenen, in the U.S.] could come from many different sources. By having this individual firm-level technology data, we are able to show that a lot of this is about automation.”
So, while economists have offered many possible explanations for the decline of the labor share generally — including technology, tax policy, changes in labor market institutions, and more — Acemoglu suspects technology, and automation specifically, is the prime candidate, certainly in France.
“A big part of the [economic] literature now on technology, globalization, labor market institutions, is turning to the question of what explains the decline in the labor share,” Acemoglu says. “Many of those are reasonably interesting hypotheses, but in France it’s only the firms that adopt robots — and they are very large firms — that are reducing their labor share, and that’s what accounts for the entirety of the decline in the labor share in French manufacturing. This really emphasizes that automation, and in particular robots, is a critical part in understanding what’s going on.”
Job-replacing tech has directly driven the income gap since the late 1980s, economists report.
Modern technology affects different workers in different ways. In some white-collar jobs — designer, engineer — people become more productive with sophisticated software at their side. In other cases, forms of automation, from robots to phone-answering systems, have simply replaced factory workers, receptionists, and many other kinds of employees.
Now a new study co-authored by an MIT economist suggests automation has a bigger impact on the labor market and income inequality than previous research would indicate — and identifies the year 1987 as a key inflection point in this process, the moment when jobs lost to automation stopped being replaced by an equal number of similar workplace opportunities.
“Automation is critical for understanding inequality dynamics,” says MIT economist Daron Acemoglu, co-author of a newly published paper detailing the findings.
Within industries adopting automation, the study shows, the average “displacement” (or job loss) from 1947-1987 was 17 percent of jobs, while the average “reinstatement” (new opportunities) was 19 percent. But from 1987-2016, displacement was 16 percent, while reinstatement was just 10 percent. In short, those factory positions or phone-answering jobs are not coming back.
“A lot of the new job opportunities that technology brought from the 1960s to the 1980s benefitted low-skill workers,” Acemoglu adds. “But from the 1980s, and especially in the 1990s and 2000s, there’s a double whammy for low-skill workers: They’re hurt by displacement, and the new tasks that are coming, are coming slower and benefitting high-skill workers.”
The new paper, “Unpacking Skill Bias: Automation and New Tasks,” will appear in the May issue of the American Economic Association: Papers and Proceedings. The authors are Acemoglu, who is an Institute Professor at MIT, and Pascual Restrepo PhD ’16, an assistant professor of economics at Boston University.
Low-skill workers: Moving backward
The new paper is one of several studies Acemoglu and Restrepo have conducted recently examining the effects of robots and automation in the workplace. In a just-published paper, they concluded that across the U.S. from 1993 to 2007, each new robot replaced 3.3 jobs.
In still another new paper, Acemoglu and Restrepo examined French industry from 2010 to 2015. They found that firms that quickly adopted robots became more productive and hired more workers, while their competitors fell behind and shed workers — with jobs again being reduced overall.
In the current study, Acemoglu and Restrepo construct a model of technology’s effects on the labor market, while testing the model’s strength by using empirical data from 44 relevant industries. (The study uses U.S. Census statistics on employment and wages, as well as economic data from the Bureau of Economic Analysis and the Bureau of Labor Studies, among other sources.)
The result is an alternative to the standard economic modeling in the field, which has emphasized the idea of “skill-biased” technological change — meaning that technology tends to benefit select high-skilled workers more than low-skill workers, helping the wages of high-skilled workers more, while the value of other workers stagnates. Think again of highly trained engineers who use new software to finish more projects more quickly: They become more productive and valuable, while workers lacking synergy with new technology are comparatively less valued.
However, Acemoglu and Restrepo think even this scenario, with the prosperity gap it implies, is still too benign. Where automation occurs, lower-skill workers are not just failing to make gains; they are actively pushed backward financially. Moreover, Acemoglu and Restrepo note, the standard model of skill-biased change does not fully account for this dynamic; it estimates that productivity gains and real (inflation-adjusted) wages of workers should be higher than they actually are.
More specifically, the standard model implies an estimate of about 2 percent annual growth in productivity since 1963, whereas annual productivity gains have been about 1.2 percent; it also estimates wage growth for low-skill workers of about 1 percent per year, whereas real wages for low-skill workers have actually dropped since the 1970s.
“Productivity growth has been lackluster, and real wages have fallen,” Acemoglu says. “Automation accounts for both of those.” Moreover, he adds, “Demand for skills has gone down almost exclusely in industries that have seen a lot of automation.”
Why “so-so technologies” are so, so bad
Indeed, Acemoglu says, automation is a special case within the larger set of technological changes in the workplace. As he puts it, automation “is different than garden-variety skill-biased technological change,” because it can replace jobs without adding much productivity to the economy.
Think of a self-checkout system in your supermarket or pharmacy: It reduces labor costs without making the task more efficient. The difference is the work is done by you, not paid employees. These kinds of systems are what Acemoglu and Restrepo have termed “so-so technologies,” because of the minimal value they offer.
“So-so technologies are not really doing a fantastic job, nobody’s enthusiastic about going one-by-one through their items at checkout, and nobody likes it when the airline they’re calling puts them through automated menus,” Acemoglu says. “So-so technologies are cost-saving devices for firms that just reduce their costs a little bit but don’t increase productivity by much. They create the usual displacement effect but don’t benefit other workers that much, and firms have no reason to hire more workers or pay other workers more.”
To be sure, not all automation resembles self-checkout systems, which were not around in 1987. Automation at that time consisted more of printed office records being converted into databases, or machinery being added to sectors like textiles and furniture-making. Robots became more commonly added to heavy industrial manufacturing in the 1990s. Automation is a suite of technologies, continuing today with software and AI, which are inherently worker-displacing.
“Displacement is really the center of our theory,” Acemoglu says. “And it has grimmer implications, because wage inequality is associated with disruptive changes for workers. It’s a much more Luddite explanation.”
After all, the Luddites — British textile mill workers who destroyed machinery in the 1810s — may be synonymous with technophobia, but their actions were motivated by economic concerns; they knew machines were replacing their jobs. That same displacement continues today, although, Acemoglu contends, the net negative consequences of technology on jobs is not inevitable. We could, perhaps, find more ways to produce job-enhancing technologies, rather than job-replacing innovations.
“It’s not all doom and gloom,” says Acemoglu. “There is nothing that says technology is all bad for workers. It is the choice we make about the direction to develop technology that is critical.”