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Competition, training, heterogeneity persistence, and aggregate growth in a multi-agent evolutionary model

Author

Listed:
  • Gérard Ballot

    (Université Paris II and ERMES-CNRS, ERMES, Université Paris II, 92, rue d'Assas 75006 Paris, France)

  • Erol Taymaz

    (Middle East Technical University, 06531 Ankara, Turkey)

Abstract

We use the framework of a multi-agent based macroeconomic model to analyse the possibility in the long run of the coexistence of two alternative types of firm behaviour towards the accumulation of human capital, training and poaching, and its aggregate outcomes. Besides R&D, we assume that firms need workers endowed with general human capital (or competencies) in order to innovate but also, although to much lower extent, in order to imitate innovations. Firms can either train workers or poach trained workers. Firms are assigned a type, and experiments compare the outcomes of the change of key parameters. The main results are: i) the coexistence of trainers and poachers is possible in the long run, and can even be beneficial to the economy when poachers raid inefficient trainers, ii) trainers fare somewhat better than poachers do, iii) mobility costs have a major negative impact on aggregate performance.

Suggested Citation

  • Gérard Ballot & Erol Taymaz, 2000. "Competition, training, heterogeneity persistence, and aggregate growth in a multi-agent evolutionary model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 3(01n04), pages 335-351.
    • Handle: RePEc:wsi:acsxxx:v:03:y:2000:i:01n04:n:s0219525900000248
    DOI: 10.1142/S0219525900000248
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    Cited by:

    1. Olivier Goudet & Jean-Daniel Kant & Gérard Ballot, 2017. "WorkSim: A Calibrated Agent-Based Model of the Labor Market Accounting for Workers’ Stocks and Gross Flows," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 21-68, June.
    2. Eliasson, Gunnar, 2023. "Bringing markets back into economics," Journal of Economic Behavior & Organization, Elsevier, vol. 216(C), pages 686-710.

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