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Using Agentization for Exploring Firm and Labor Dynamics

In: Emergent Results of Artificial Economics

Author

Listed:
  • Omar A. Guerrero

    (George Mason University)

  • Robert L. Axtell

    (George Mason University)

Abstract

Agentization is the process of rendering neoclassical models into computational ones. This methodological tool can be used to analyze and test neoclassical theories under a more flexible computational framework. This paper presents agentization and its methodological framework. We propose that, by classifying the assumptions of a neoclassical model, it is possible to systematically analyze their influence in the predictions of a theory. Furthermore, agentization allows the researcher to explore the potentials and limitations of theories. We present an example by agentizing the model of Gabaix (1999) for the emergence of Zipf laws. We show that the agentized model is able to reproduce the main features of the Gabaix process, without holding neoclassical assumptions such as equilibrium, rationality, agent homogeneity, and centralized anonymous interactions. Additionally, the model generates stylized facts such as tent-shaped firm growth rates distributions, and the employer-size wage premium. These regularities are not considered in the neoclassical model. Thus, allows the researcher to explore the boundaries and potentials of the theory.

Suggested Citation

  • Omar A. Guerrero & Robert L. Axtell, 2011. "Using Agentization for Exploring Firm and Labor Dynamics," Lecture Notes in Economics and Mathematical Systems, in: Sjoukje Osinga & Gert Jan Hofstede & Tim Verwaart (ed.), Emergent Results of Artificial Economics, pages 139-150, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-21108-9_12
    DOI: 10.1007/978-3-642-21108-9_12
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    Citations

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    Cited by:

    1. Gerard Ballot & Antoine Mandel & Annick Vignes, 2015. "Agent-based modeling and economic theory: where do we stand?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 199-220, October.
    2. Stephan Leitner & Friederike Wall, 2021. "Decision-facilitating information in hidden-action setups: an agent-based approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 323-358, April.
    3. Friederike Wall, 2017. "Learning To Incentivize In Different Modes Of Coordination," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 20(02n03), pages 1-29, March.
    4. S. Leitner & D.A. Behrens, 2015. "On the efficiency of hurdle rate-based coordination mechanisms," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 21(5), pages 413-431, September.
    5. Leitner, Stephan & Wall, Friederike, 2022. "Micro-level dynamics in hidden action situations with limited information," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 372-393.
    6. Khamdamov, T., 2022. "A brief overview of the evolution of computer simulations in economic research," Journal of the New Economic Association, New Economic Association, vol. 54(2), pages 189-207.
    7. Richard Bookstaber & Michael D. Foley & Brian F. Tivnan, 2015. "Market Liquidity and Heterogeneity in the Investor Decision Cycle," Working Papers 15-03, Office of Financial Research, US Department of the Treasury.
    8. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2020. "An Agent-Based Model of Delegation Relationships With Hidden-Action: On the Effects of Heterogeneous Memory on Performance," Papers 2009.07124, arXiv.org, revised Sep 2020.
    9. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2021. "Limited intelligence and performance-based compensation: An agent-based model of the hidden action problem," Papers 2107.03764, arXiv.org.
    10. Stephan Leitner & Doris Behrens, 2015. "On the fault (in)tolerance of coordination mechanisms for distributed investment decisions," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 251-278, March.
    11. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2021. "Effects of limited and heterogeneous memory in hidden-action situations," Papers 2105.12469, arXiv.org.
    12. Friederike Wall, 2016. "Agent-based modeling in managerial science: an illustrative survey and study," Review of Managerial Science, Springer, vol. 10(1), pages 135-193, January.
    13. Oldham, Matthew, 2020. "Quantifying the concerns of Dimon and Buffett with data and computation," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    14. Stephan Leitner & Friederike Wall, 2015. "Simulation-based research in management accounting and control: an illustrative overview," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 26(2), pages 105-129, August.

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