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Modeling Automation

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  • Daron Acemoglu
  • Pascual Restrepo

Abstract

Modeling automation as factor-augmenting technological change has unappealing implications. Instead, modeling it as the process of machines replacing tasks previously performed by labor is both descriptively realistic and leads to distinct and plausible predictions. In contrast to factor-augmenting technological change, the automation of tasks always reduces the labor share and can reduce the equilibrium wage (for realistic parameter values). This approach to automation underscores the role of new tasks, changes in the comparative advantage of labor, the possibility that machines become more productive in automated tasks, and the elasticity of substitution and capital accumulation in the adjustment of the economy.

Suggested Citation

  • Daron Acemoglu & Pascual Restrepo, 2018. "Modeling Automation," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 48-53, May.
    • Handle: RePEc:aea:apandp:v:108:y:2018:p:48-53
    Note: DOI: 10.1257/pandp.20181020
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    References listed on IDEAS

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    1. Daron Acemoglu & Pascual Restrepo, 2016. "The Race Between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment," NBER Working Papers 22252, National Bureau of Economic Research, Inc.
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    Cited by:

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    3. Jacobs, Arthur, 2023. "Capital-augmenting technical change in the context of untapped automation opportunities," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 155-166.
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    6. Zhu, Jun & Zhang, Jingting & Feng, Yiqing, 2022. "Hard budget constraints and artificial intelligence technology," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    7. Leblebicioğlu, Asli & Weinberger, Ariel, 2021. "Openness and factor shares: Is globalization always bad for labor?," Journal of International Economics, Elsevier, vol. 128(C).
    8. Leone, Fabrizio, 2021. "Foreign Ownership and Robot Adoption," CEPREMAP Working Papers (Docweb) 2111, CEPREMAP.
    9. Bertani, Filippo & Ponta, Linda & Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2021. "The complexity of the intangible digital economy: an agent-based model," Journal of Business Research, Elsevier, vol. 129(C), pages 527-540.
    10. Jeffrey L. Furman & Florenta Teodoridis, 2020. "Automation, Research Technology, and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering," Organization Science, INFORMS, vol. 31(2), pages 330-354, March.
    11. Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2021. "Impact of robotics on manufacturing: A longitudinal machine learning perspective," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    12. Mr. Andrew Berg & Lahcen Bounader & Nikolay Gueorguiev & Hiroaki Miyamoto & Mr. Kenji Moriyama & Ryota Nakatani & Luis-Felipe Zanna, 2021. "For the Benefit of All: Fiscal Policies and Equity-Efficiency Trade-offs in the Age of Automation," IMF Working Papers 2021/187, International Monetary Fund.
    13. de Vries, Gaaitzen J. & Gentile, Elisabetta & Miroudot, Sébastien & Wacker, Konstantin M., 2020. "The rise of robots and the fall of routine jobs," Labour Economics, Elsevier, vol. 66(C).
    14. David M. Williams, 2021. "Pay and Productivity in Canada: Growing Together, Only Slower than Ever," International Productivity Monitor, Centre for the Study of Living Standards, vol. 40, pages 3-26, Spring.
    15. Kraft, Kornelius & Lammers, Alexander, 2021. "The Effects of Reforming a Federal Employment Agency on Labor Demand," IZA Discussion Papers 14629, Institute of Labor Economics (IZA).
    16. Ebeke, Christian H. & Eklou, Kodjovi M., 2023. "Automation and the employment elasticity of fiscal policy," Journal of Macroeconomics, Elsevier, vol. 75(C).
    17. García-Vega, María, 2022. "R&D restructuring during the Great Recession and young firms," International Journal of Industrial Organization, Elsevier, vol. 81(C).
    18. Takahashi, Harutaka & Le Riche, Antoine, 2021. "A dynamic theory of the declining aggregated labor income share: Intangible capital vs. tangible capital," Research in Economics, Elsevier, vol. 75(1), pages 104-118.
    19. Harald Sander, 2019. "A European Policy Agenda in and for the New Global Economy," Book, University of Warsaw, Faculty of Management, edition 1, volume 1, number y:2019:v:1:ch:3:p:56-87 edited by Justin Yifu Lin & Alojzy Z. Nowak, June.
    20. Pang, Ziyun, 2022. "A Note on Economic Growth and Labor Automation," MPRA Paper 112457, University Library of Munich, Germany.
    21. Alonso, Cristian & Berg, Andrew & Kothari, Siddharth & Papageorgiou, Chris & Rehman, Sidra, 2022. "Will the AI revolution cause a great divergence?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 18-37.
    22. MORIKAWA Masayuki, 2020. "Heterogeneous Relationships between Automation Technologies and Skilled Labor: Evidence from a Firm Survey," Discussion papers 20004, Research Institute of Economy, Trade and Industry (RIETI).
    23. Yasin Yilmaz, 2021. "Transition to the Digital Economy, Its Measurement and the Relationship between Digitalization and Productivity," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 71(1), pages 283-316, June.

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    More about this item

    JEL classification:

    • D33 - Microeconomics - - Distribution - - - Factor Income Distribution
    • 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

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