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Agent-based models of the labor market

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  • Michael Neugart
  • Matteo G. Richiardi

Abstract

We review the literature on agent-based labor market models by tracing its roots to the microsimulation literature, and surveying a selection of contributions made since the work by Bergmann (1974) and Eliasson (1976). Agent-based models have been applied to explain stylized facts of labor markets as well as for labor market policy evaluations. They also constitute a major part in agent-based macroeconomic models. Besides reviewing the various results achieved, we discuss modeling choices with respect to agents’ behavior and the structure of interaction. Our overall assessment is that agent-based labor market models have given us valuable insights into the functioning of labor markets and the consequences of labor market policies, and that they will increasingly become an essential tool of analysis, in particular when the construction of large macro-models is involved.

Suggested Citation

  • Michael Neugart & Matteo G. Richiardi, 2012. "Agent-based models of the labor market," LABORatorio R. Revelli Working Papers Series 125, LABORatorio R. Revelli, Centre for Employment Studies.
    • Handle: RePEc:cca:wplabo:125
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    5. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    6. Neugart, Michael & Zaharieva, Anna, 2018. "Social Networks, Promotions, and the Glass-Ceiling Effect," Center for Mathematical Economics Working Papers 601, Center for Mathematical Economics, Bielefeld University.
    7. Damdinsuren, Erdenebulgan & Zaharieva, Anna, 2023. "Expectation formation and learning in the labour market with on-the-job search and Nash bargaining," Labour Economics, Elsevier, vol. 81(C).
    8. Bernardo Alves Furtado, 2022. "PolicySpace2: Modeling Markets and Endogenous Public Policies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 25(1), pages 1-8.
    9. Bauermann, Tom, 2020. "Governmental policies to reduce unemployment during recessions: Insights from an ABM," Ruhr Economic Papers 847, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
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    11. Jung-Seung Yang, 2022. "Dynamics of Firm’s Investment in Education and Training: An Agent-based Approach," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1317-1351, December.
    12. Bernardo Alves Furtado & Isaque Daniel Rocha Eberhardt, 2016. "A Simple Agent-Based Spatial Model of the Economy: Tools for Policy," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-12.
    13. Rolf Aaberge & Ugo Colombino, 2018. "Structural Labour Supply Models and Microsimulation," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 162-197.
    14. Georg Jäger & Laura S. Zilian & Christian Hofer & Manfred Füllsack, 2019. "Crowdworking: working with or against the crowd?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 761-788, December.
    15. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    16. Bernardo Alves Furtado, 2018. "Modeling tax distribution in metropolitan regions with PolicySpace," Papers 1901.02391, arXiv.org.
    17. André Veski & Kaire Põder, 2018. "Zero-intelligence agents looking for a job," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 615-640, October.
    18. Matteo G. Richiardi, 2017. "The Future of Agent-Based Modeling," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 271-287, March.
    19. Guilmi, Corrado Di & Fujiwara, Yoshi, 2022. "Dual labor market, financial fragility, and deflation in an agent-based model of the Japanese macroeconomy," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 346-371.
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    21. Furtado, Bernardo Alves & Eberhardt, Isaque Daniel Rocha, 2015. "Modelo espacial simples da economia: uma proposta teórico-metodológica [A simple spatial economic model: a proposal]," MPRA Paper 67005, University Library of Munich, Germany.
    22. Herbert Dawid & Jasper Hepp, 2022. "Distributional effects of technological regime changes: hysteresis, concentration and inequality dynamics," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 137-167, April.
    23. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
    24. Mário Amorim-Lopes & Álvaro Almeida & Bernardo Almada-Lobo, 2019. "Physician Emigration: Should they Stay or Should they Go? A Policy Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 905-931, October.
    25. Mário Amorim Lopes & Álvaro Almeida & Bernardo Almada-Lobo, 2017. "Physician emigration: should they stay or should they go? A policy analysis," FEP Working Papers 585, Universidade do Porto, Faculdade de Economia do Porto.

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