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Agent-based models of the labor market

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  • Neugart, Michael
  • Richiardi, Matteo

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.
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  • Neugart, Michael & Richiardi, Matteo, 2018. "Agent-based models of the labor market," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 110862, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  • Handle: RePEc:dar:wpaper:110862
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/110862/
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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.
    10. 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.
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    15. Bernardo Alves Furtado, 2018. "Modeling tax distribution in metropolitan regions with PolicySpace," Papers 1901.02391, arXiv.org.
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    20. 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.
    21. 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.
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    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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