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Research papers on Automation and the labor market

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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 · 2,253 citations

    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 · 2,198 citations

    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 e

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

    David Deming · 2017 · The Quarterly Journal of Economics · 1,626 citations

    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

  4. Robots and Jobs: Evidence from US Labor Markets

    Daron Acemoğlu, Pascual Restrepo · 2017 · National Bureau of Economic Research · 904 citations

    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

  5. The Risk of Automation for Jobs in OECD Countries

    Melanie Arntz, Terry Gregory, Ulrich Zierahn · 2016 · OECD social employment and migration working papers · 840 citations

    In recent years, there has been a revival of concerns that automation and digitalisation might after all result in a jobless future. The debate has been fuelled by studies for the US and Europe arguing that a substantial share of jobs is at “risk of computerisation”. These studies follow an occupation-based approach proposed by Frey and Osborne (2013), i.e. they assume that whole occupations rather than single job-tasks are automated by technology. As we argue, this might lead to an overestimation of job automatibility, as occupations labelled as high-risk occupations often still contain a substantial share of tasks that are hard to automate. Our paper serves two purposes. Firstly, we estima

  6. Artificial Intelligence, Automation and Work

    Daron Acemoğlu, Pascual Restrepo · 2018 · National Bureau of Economic Research · 670 citations

    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 de

  7. The Adjustment of Labor Markets to Robots

    Wolfgang Dauth, Sebastian Findeisen, Jens Suedekum, et al. · 2021 · Journal of the European Economic Association · 522 citations

    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 Webb · 2019 · Economics of Innovation eJournal · 463 citations

    I develop a new method to predict the impacts of a technology on occupations. I use the overlap between the text of job task descriptions and the text of patents to construct a measure of the exposure of tasks to automation. I first apply the method to historical cases such as software and industrial robots. I establish that occupations I measure as highly exposed to previous automation technologies saw declines in employment and wages over the relevant periods. I use the fitted parameters from the case studies to predict the impacts of artificial intelligence. I find that, in contrast to software and robots, AI is directed at high-skilled tasks. Under the assumption that the historical patt

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

    David Autor, Anna Salomons · 2018 · National Bureau of Economic Research · 406 citations

    Many technological innovations replace workers with machines, but this capital-labor substitution need not reduce aggregate labor demand because it simultaneously induces four countervailing responses: own-industry output effects; cross-industry input-output effects; between-industry shifts; and final demand effects. We quantify these channels using four decades of harmonized cross-country and industry data, where we measure automation as industry-level movements in total factor productivity (TFP) that are common across countries. We find that automation displaces employment and reduces labor's share of value-added in the industries in which it originates (a direct effect). In the case of em

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

    David Autor, David Autor, Anna Salomons, et al. · 2018 · Brookings Papers on Economic Activity · 365 citations

    Many technological innovations replace workers with machines, but this capital-labor substitution need not reduce aggregate labor demand because it simultaneously induces four countervailing responses: own-industry output effects; cross-industry input-output effects; between-industry shifts; and final demand effects. We quantify these channels using four decades of harmonized cross-country and industry data, where we measure automation as industry-level movements in total factor productivity (TFP) that are common across countries. We find that automation displaces employment and reduces labor's share of value-added in the industries in which it originates (a direct effect). In the case of em

  12. Adjusting to Robots: Worker-Level Evidence

    W. Dauth, S. Findeisen, Jens Suedekum, et al. · 2018 · 119 citations

    We estimate the effect of industrial robots on employment, wages, and the composition of jobs in German labor markets between 1994 and 2014. We find that the adoption of industrial robots had no effect on total employment in local labor markets specializing in industries with high robot usage. Robot adoption led to job losses in manufacturing that were offset by gains in the business service sector. We analyze the impact on individual workers and find that robot adoption has not increased the risk of displacement for incumbent manufacturing workers. They stay with their original employer, and many workers adjust by switching occupations at their original workplace. The loss of manufacturing

  13. Automation, unemployment, and the role of labor market training

    B. Schmidpeter, R. Winter‐Ebmer · 2021 · European Economic Review · 60 citations

    Abstract We provide comprehensive evidence on the consequences of automation risk on the career of unemployed workers and the mitigating role of labor market training. Using almost two decades of administrative data for Austria, we find that a higher risk of automation reduces the job finding probability; a problem which has increased over the past years. This development is associated with increasing re-employment wages and job stability. We also present new aspects of public training in times of technological progress. Provided training counteracts the negative impact of automation on the job finding probability. Its efficiency has declined over the past years, however.

  14. Death by Robots? Automation and Working-Age Mortality in the United States.

    R. O'Brien, E. Bair, A. Venkataramani · 2021 · Demography · 55 citations

    The decline of manufacturing employment is frequently invoked as a key cause of worsening U.S. population health trends, including rising mortality due to "deaths of despair." Increasing automation-the use of industrial robots to perform tasks previously done by human workers-is one structural force driving the decline of manufacturing jobs and wages. In this study, we examine the impact of automation on age- and sex-specific mortality. Using exogenous variation in automation to support causal inference, we find that increases in automation over the period 1993-2007 led to substantive increases in all-cause mortality for both men and women aged 45-54. Disaggregating by cause, we find evidenc

  15. Is an Army of Robots Marching on Chinese Jobs?

    Osea Giuntella, Tianyi Wang · 2019 · SSRN Electronic Journal · 43 citations

    A handful of studies have investigated the effects of robots on workers in advanced economies. According to a recent report from the World Bank (2016), 1.8 billion jobs in developing countries are susceptible to automation. Given the inability of labor markets to adjust to rapid changes, there is a growing concern that the effect of automation and robotization in emerging economies may increase inequality and social unrest. Yet, we still know very little about the impact of robots in developing countries. In this paper we analyze the effects of exposure to industrial robots in the Chinese labor market. Using aggregate data from Chinese prefectural cities (2000-2016) and individual longitudin

  16. Testing the Employment Impact of Automation, Robots and AI: A Survey and Some Methodological Issues

    Laura Barbieri, Chiara Mussida, M. Piva, et al. · 2019 · SSRN Electronic Journal · 37 citations

    The present technological revolution, characterized by the pervasive and growing presence of robots, automation, Artificial Intelligence and machine learning, is going to transform societies and economic systems. However, this is not the first technological revolution humankind has been facing, but it is probably the very first one with such an accelerated diffusion pace involving all the industrial sectors. Studying its mechanisms and consequences (will the world turn into a jobless society or not?), mainly considering the labor market dynamics, is a crucial matter. This paper aims at providing an updated picture of main empirical evidence on the relationship between new technologies and em

  17. Offshoring, Automation, Low-Skilled Immigration, and Labor Market Polarization

    Federico S. Mandelman, A. Zlate · 2022 · American Economic Journal: Macroeconomics · 34 citations

    We show that the observed polarization of employment toward the high- and low-skill occupations disappears when only native workers are considered. Instead, low-skilled immigration explains employment growth at the low tail of the skill distribution. Moreover, while employment rose, wages remained subdued in low-skill occupations. A data-disciplined structural model accounts for this evidence: Offshoring and automation negatively affect middle-skill occupations but enhance employment and wages for the high-skilled. Low-skill employment is sheltered from offshoring and automation, as it consists of manual, non-tradable services. However, low-skilled immigration depresses low-skill wages and e

  19. Automation, Bargaining Power, and Labor Market Fluctuations

    S. Leduc, Zheng Liu · 2024 · American Economic Journal: Macroeconomics · 28 citations

    We argue that the threat of automation weakens workers’ bargaining power in wage negotiations, dampening wage adjustments and amplifying unemployment fluctuations. We make this argument based on a business cycle model with labor market search frictions, generalized to incorporate automation decisions. In the model, procyclical automation threats create endogenous real wage rigidity that amplifies labor market fluctuations. The automation mechanism is consistent with empirical evidence. It is also quantitatively important for explaining the large volatilities of unemployment and vacancies relative to that of real wages, a puzzling observation through the lens of standard business cycle models

  20. Monopsony Power in the Labor Market: From Theory to Policy

    Jose Azar, Ioana Marinescu · 2024 · Annual Review of Economics · 25 citations

    Labor markets are not perfectly competitive: Monopsony power enables employers to pay workers less than the marginal revenue product of labor. We review three theoretical frameworks explaining monopsony power. Oligopsony models attribute it to strategic interactions among a limited number of firms. Job differentiation models cite imperfect job substitution and heterogeneous worker preferences. Search-and-matching models point to search frictions hindering instantaneous access to all available jobs. We then develop a theory-informed discussion of the empirical evidence on antitrust policies, policies that reduce barriers to job switching, and policies countering monopsony's effects on workers

  22. The cause and consequence of robot adoption in China: Minimum wages and firms’ responses

    Richard B. Freeman, Xueyue Liu, Zhikuo Liu, et al. · 2024 · Fundamental Research · 6 citations

    We study the cause and consequence of firms’ robot adoption in China using novel panel data related to robots imported by firms in China from 2001 to 2012, when more than 80% of China’s robots were imported. We find that the rising minimum wages affect firms’ robot adoption and the effect is more significant for routine-intensive, labor-intensive and large firms. Moreover, employing robots significantly increases firms’ productivity, labor employment, average wages, and market share. These findings suggest that productivity gains from automation are partially passed on to workers in the form of more employment and higher labor income.

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