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The effect of automation on the labor market: An approach using firm-level microdata

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  • Camilo Levenier

Abstract

This study analyzes the relationship between machines and employment across different workers' income quintiles, utilizing firm-level and worker-level microdata for Chile from 2009 to 2023, considering a total of 80,000 firms and 2,900,000 workers. To investigate this dynamic, a panel regression is used, modeling employment as a function of machines and a set of other covariates. Additionally, a generalized propensity score is used to address the endogeneity problem. The results indicate that the relationship between machines and employment is predominantly negative, especially for workers in the middle-income quintiles and for certain economic sectors such as business services, transport, and information & communication. Furthermore, the results suggest that the relationship between machines and employment in high-income quintiles has been positive, supporting the idea that technological development requires highly qualified workers. Overall, the results suggest that automation has had heterogeneous effects on employment in the Chilean labor market, and these effects are smaller than those suggested by the literature.

Suggested Citation

  • Camilo Levenier, 2025. "The effect of automation on the labor market: An approach using firm-level microdata," Working Papers Central Bank of Chile 1048, Central Bank of Chile.
    • Handle: RePEc:chb:bcchwp:1048
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    References listed on IDEAS

    as
    1. Gallipoli, Giovanni & Makridis, Christos A., 2018. "Structural transformation and the rise of information technology," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 91-110.
    2. Peña, Jennifer & Prades, Elvira, 2024. "International sourcing during COVID-19: How did Chilean firms fare?," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(1).
    3. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    4. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    5. Kosuke Imai & Marc Ratkovic, 2014. "Covariate balancing propensity score," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 243-263, January.
    6. Berg, Andrew & Buffie, Edward F. & Zanna, Luis-Felipe, 2018. "Should we fear the robot revolution? (The correct answer is yes)," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 117-148.
    7. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
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