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Automation and labor market polarization in an evolutionary model with heterogeneous workers

Author

Listed:
  • Florent Bordot
  • Andre Lorentz

Abstract

The purpose of this paper is to investigate the mechanisms underlying the relationship between automation and labor market polarization. To do so, we build an agent-based model (ABM) in which workers, heterogeneous in nature and level of skills, interact endogenously on a decentralized labor market with firms producing goods requiring specific set of skills to realize the tasks necessary for the production process. The two scenarios considered, with and without automation, confirm that automation is indeed a key factor in polarizing the structure of skill demand and increasing wage inequality. This result emerges even without reverting to the routine-based technical change (RBTC) hypothesis usually found in the literature, giving some support to the complexity-based technical change (CBTC) hypothesis. Finally, we also highlight that the impact of automation on the distribution of skill demand and wage inequality is correlated with the velocity of technical change.

Suggested Citation

  • Florent Bordot & Andre Lorentz, 2021. "Automation and labor market polarization in an evolutionary model with heterogeneous workers," LEM Papers Series 2021/32, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    • Handle: RePEc:ssa:lemwps:2021/32
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    Cited by:

    1. Patrick Mellacher, 2021. "Growth, Inequality and Declining Business Dynamism in a Unified Schumpeter Mark I + II Model," Papers 2111.09407, arXiv.org, revised Nov 2023.
    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. Patrick Llerena & Corentin Lobet & André Lorentz, 2025. "Two halves don’t make a whole: instability and idleness emerging from the co-evolution of the production and innovation processes," Review of Evolutionary Political Economy, Springer, vol. 6(3), pages 459-497, December.
    4. Borsato, Andrea & Lorentz, André, 2023. "The Kaldor–Verdoorn law at the age of robots and AI," Research Policy, Elsevier, vol. 52(10).
    5. 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.

    More about this item

    Keywords

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E14 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Austrian; Evolutionary; Institutional
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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