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Papers on “automation robots employment labor market wages”

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1. Automation and New Tasks: How Technology Displaces and Reinstates Labor

   Daron Acemoğlu, Pascual Restrepo · 2019 · The Journal of Economic Perspectives · 2,492 cites

   We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor—the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which lab

2. Skills, Tasks and Technologies: Implications for Employment and Earnings

   Daron Acemoğlu, David Autor · 2010 · National Bureau of Economic Research · 2,202 cites

   A central organizing framework of the voluminous recent literature studying changes in the returns to skills and the evolution of earnings inequality is what we refer to as the canonical model, which elegantly and powerfully operationalizes the supply and demand for skills by assuming two distinct skill groups that perform two different and imperfectly substitutable tasks or produce two imperfectly substitutable goods.Technology is assumed to take a factor-augmenting form, which, by complementing either high or low skill workers, can generate skill biased demand shifts.In this paper, we argue that despite its notable successes, the canonical model is largely silent on a number of central emp

3. Robots at Work

   Georg Graetz, Guy Michaels · 2018 · The Review of Economics and Statistics · 1,973 cites

   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 shar

4. The Growing Importance of Social Skills in the Labor Market*

   David Deming · 2017 · The Quarterly Journal of Economics · 1,682 cites

   Abstract The labor market increasingly rewards social skills. Between 1980 and 2012, jobs requiring high levels of social interaction grew by nearly 12 percentage points as a share of the U.S. labor force. Math-intensive but less social jobs—including many STEM occupations—shrank by 3.3 percentage points over the same period. Employment and wage growth were particularly strong for jobs requiring high levels of both math skill and social skills. To understand these patterns, I develop a model of team production where workers “trade tasks” to exploit their comparative advantage. In the model, social skills reduce coordination costs, allowing workers to specialize and work together more efficie

5. Robots and Jobs: Evidence from US Labor Markets

   Daron Acemoğlu, Pascual Restrepo · 2017 · National Bureau of Economic Research · 914 cites

   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 exposure to robots in each local labor market-defined from the national penetration of robots into each industry and the local distribution of employment a

6. Artificial Intelligence, Automation and Work

   Daron Acemoğlu, Pascual Restrepo · 2018 · National Bureau of Economic Research · 707 cites

   We summarize a framework for the study of the implications of automation and AI on the demand for labor, wages, and employment.Our task-based framework emphasizes the displacement effect that automation creates as machines and AI replace labor in tasks that it used to perform.This displacement effect tends to reduce the demand for labor and wages.But it is counteracted by a productivity effect, resulting from the cost savings generated by automation, which increase the demand for labor in non-automated tasks.The productivity effect is complemented by additional capital accumulation and the deepening of automation (improvements of existing machinery), both of which further increase the demand

7. The Adjustment of Labor Markets to Robots

   Wolfgang Dauth, Sebastian Findeisen, Jens Suedekum, et al. · 2021 · Journal of the European Economic Association · 545 cites

   Abstract We use detailed administrative data to study the adjustment of local labor markets to industrial robots in Germany. Robot exposure, as predicted by a shift-share variable, is associated with displacement effects in manufacturing, but those are fully offset by new jobs in services. The incidence mostly falls on young workers just entering the labor force. Automation is related to more stable employment within firms for incumbents, and this is driven by workers taking over new tasks in their original plants. Several measures indicate that those new jobs are of higher quality than the previous ones. Young workers also adapt their educational choices, and substitute away from vocational

8. The Impact of Artificial Intelligence on the Labor Market

   Michael A. Webb · 2019 · SSRN Electronic Journal · 466 cites