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Endogenous matching functions: an agent-based computational approach

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  • Neugart, Michael

Abstract

The matching function has become a popular tool in labor economics. It relates job creation (a flow variable) to two stock variables: vacancies and job searchers. In most studies the matching function is considered to be exogenous and assumed to have certain properties. The present study, instead, looks at the properties of an endogenous matching function. For this purpose we have programmed an agent-based computational labor market model with endogenous job creation and endogenous job search behavior. Our~simulations suggest that the endogenous matching technology is subject to decreasing returns to scale. The Beveridge curve reveals substitutability of job searchers and vacancies for a small range of inputs, but is flat for relatively high numbers of job searchers and vertical for relatively high numbers of vacancies. Moreover, the matching technology changes with labor market policies. This raises concerns about the validity of labor market policy evaluations conducted with flow models of the labor market that employ exogenous matching functions.

Suggested Citation

  • Neugart, Michael, 2004. "Endogenous matching functions: an agent-based computational approach," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 57291, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:57291
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/57291/
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    References listed on IDEAS

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    1. Stephen Machin & Alan Manning, 2002. "The Structure of Wages in What Should be a Competitive Labour Market," CEP Discussion Papers dp0532, Centre for Economic Performance, LSE.
    2. Matteo Richiardi, 2004. "A Search Model Of Unemployment And Firm Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 203-221.
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    Cited by:

    1. Neugart, Michael, 2006. "Labor market policy evaluation with an agent-based model," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2006-113, WZB Berlin Social Science Center.
    2. Richard Freeman, 2005. "Labour market institutions without blinders: The debate over flexibility and labour market performance," International Economic Journal, Taylor & Francis Journals, vol. 19(2), pages 129-145.
    3. Wozniak, Marcin, 2016. "Job placement agencies in an artificial labor market," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-54.
    4. 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).
    5. 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.
    6. Christian Martin & Michael Neugart, 2009. "Shocks and Endogenous Institutions: An Agent-based Model of Labor Market Performance in Turbulent Times," Computational Economics, Springer;Society for Computational Economics, vol. 33(1), pages 31-46, February.
    7. Richard B. Freeman, 2007. "Labor Market Institutions Around the World," NBER Working Papers 13242, National Bureau of Economic Research, Inc.
    8. Simon Gemkow & Michael Neugart, 2011. "Referral hiring, endogenous social networks, and inequality: an agent-based analysis," Journal of Evolutionary Economics, Springer, vol. 21(4), pages 703-719, October.
    9. 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.
    10. Neugart, Michael, 2008. "Labor market policy evaluation with ACE," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 418-430, August.
    11. Károly Takács & Flaminio Squazzoni, 2015. "High Standards Enhance Inequality in Idealized Labor Markets," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(4), pages 1-2.
    12. Cardullo, Gabriele & Guerci, Eric, 2019. "Interpreting the Beveridge curve. An agent-based approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 84-100.
    13. Rose, Giuseppe, 2013. "Endogenous ranking in a two-sector urn-ball matching process," Economics Discussion Papers 2013-40, Kiel Institute for the World Economy (IfW Kiel).
    14. Wozniak, Marcin, 2016. "Job placement agencies in an agent-based model of the local labor market with the long-term unemployed and on-the-job flows," Economics Discussion Papers 2016-24, Kiel Institute for the World Economy (IfW Kiel).

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    More about this item

    JEL classification:

    • B21 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Microeconomics
    • B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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