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Unpacking Skill Bias: Automation and New Tasks

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  • Daron Acemoglu
  • Pascual Restrepo

Abstract

We extend the canonical model of skill-biased technical change by modeling the allocation of tasks to factors and allowing for automation and the creation of new tasks. In our model, factor prices depend on the set of tasks they perform. Automation can reduce real wages and generate sizable changes in inequality associated with small productivity gains. New tasks can increase or reduce inequality depending on whether they are performed by skilled or unskilled workers. Industry-level data suggest that automation significantly contributed to the rising skill premium, while new tasks reduced inequality in the past but have contributed to inequality recently.

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  • Daron Acemoglu & Pascual Restrepo, 2020. "Unpacking Skill Bias: Automation and New Tasks," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 356-361, May.
    • Handle: RePEc:aea:apandp:v:110:y:2020:p:356-61
    DOI: 10.1257/pandp.20201063
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    1. Ezra Oberfield & Devesh Raval, 2021. "Micro Data and Macro Technology," Econometrica, Econometric Society, vol. 89(2), pages 703-732, March.
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    Cited by:

    1. Consolo, Agostino & Cette, Gilbert & Bergeaud, Antonin & Labhard, Vincent & Osbat, Chiara & Kosekova, Stanimira & Anyfantaki, Sofia & Basso, Gaetano & Basso, Henrique & Bobeica, Elena & Ciapanna, Eman, 2021. "Digitalisation: channels, impacts and implications for monetary policy in the euro area," Occasional Paper Series 266, European Central Bank.
    2. Fierro, Luca Eduardo & Caiani, Alessandro & Russo, Alberto, 2022. "Automation, Job Polarisation, and Structural Change," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 499-535.
    3. Ryosuke Shimizu & Shohei Momoda, 2021. "Does Automation Technology increase Wage?," Discussion papers ron343, Policy Research Institute, Ministry of Finance Japan.
    4. Jean-Philippe Deranty & Thomas Corbin, 2022. "Artificial Intelligence and work: a critical review of recent research from the social sciences," Papers 2204.00419, arXiv.org.
    5. Nenci, Silvia & Fusacchia, Ilaria & Giunta, Anna & Montalbano, Pierluigi & Pietrobelli, Carlo, 2022. "Mapping global value chain participation and positioning in agriculture and food: stylised facts, empirical evidence and critical issues," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 11(2), July.
    6. Henrik Schwabe & Fulvio Castellacci, 2020. "Automation, workers’ skills and job satisfaction," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-26, November.
    7. Christian Gunadi & Hanbyul Ryu, 2021. "Does the rise of robotic technology make people healthier?," Health Economics, John Wiley & Sons, Ltd., vol. 30(9), pages 2047-2062, September.
    8. Shimizu, Ryosuke & Momoda, Shohei, 2023. "Does automation technology increase wage?," Journal of Macroeconomics, Elsevier, vol. 77(C).
    9. Lindner, Attila & Muraközy, Balázs & Reizer, Balázs & Schreiner, Ragnhild, 2022. "Firm-level technological change and skill demand," LSE Research Online Documents on Economics 117905, London School of Economics and Political Science, LSE Library.
    10. Azio Barani, 2021. "Innovazione tecnologica e lavoro: automazione, occupazione e impatti socio-economici," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 0(114), pages 51-79.
    11. Dedola, Luca & Ehrmann, Michael & Hoffmann, Peter & Lamo, Ana & Paz-Pardo, Gonzalo & Slacalek, Jiri & Strasser, Georg, 2023. "Digitalisation and the economy," Working Paper Series 2809, European Central Bank.
    12. Toon Van Overbeke, 2023. "Conflict or cooperation? Exploring the relationship between cooperative institutions and robotisation," British Journal of Industrial Relations, London School of Economics, vol. 61(3), pages 550-573, September.
    13. Raja Bentaouet Kattan & Kevin Macdonald & Harry Anthony Patrinos, 2021. "The Role of Education in Mitigating Automation’s Effect on Wage Inequality," LABOUR, CEIS, vol. 35(1), pages 79-104, March.
    14. Freeman, Richard B. & Yang, Buyuan & Zhang, Baitao, 2023. "Data deepening and nonbalanced economic growth," Journal of Macroeconomics, Elsevier, vol. 75(C).
    15. Claudia Fontanari & Antonella Palumbo, 2023. "Permanent scars: The effects of wages on productivity," Metroeconomica, Wiley Blackwell, vol. 74(2), pages 351-389, May.
    16. Ballestar, María Teresa & García-Lazaro, Aida & Sainz, Jorge & Sanz, Ismael, 2022. "Why is your company not robotic? The technology and human capital needed by firms to become robotic," Journal of Business Research, Elsevier, vol. 142(C), pages 328-343.
    17. Ryosuke Shimizu & Shohei Momoda, 2020. "Does Automation Technology increase Wage?," KIER Working Papers 1039, Kyoto University, Institute of Economic Research.

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    More about this item

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education

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