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Evolution Of Worker-Employer Networks And Behaviors Under Alternative Non-Employment Benefits: An Agent-Based Computational Study

In: Industry And Labor Dynamics The Agent-Based Computational Economics Approach

Author

Listed:
  • MARK PINGLE

    (Department of Economics, University of Nevada, Reno, Nevada 89557-0016, USA)

  • LEIGH TESFATSION

    (Department of Economics, Iowa State University, Ames, Iowa, 50011-1070, USA)

Abstract

This study experimentally tests the effects of a non-employment payment on work-site behaviors and market efficiency in the context of an agent-based computational labor market model with autonomous strategically-interacting workers and employers. On average, we find that a low but positive non-employment payment is most efficient, especially over the short and intermediate run. A high non-employment payment encourages those who enter employment relationships to be cooperative, but the cost of the non-employment payment program significantly reduces efficiency. Having no non-employment payment encourages the formation of employment relationships, but non-cooperation is common and this reduces efficiency. These “average” results should be viewed with caution, however. Because of strong network and learning effects, quite different paths and ultimate outcomes can result from the same initial structural conditions.

Suggested Citation

  • Mark Pingle & Leigh Tesfatsion, 2004. "Evolution Of Worker-Employer Networks And Behaviors Under Alternative Non-Employment Benefits: An Agent-Based Computational Study," World Scientific Book Chapters, in: Roberto Leombruni & Matteo Richiardi (ed.), Industry And Labor Dynamics The Agent-Based Computational Economics Approach, chapter 8, pages 129-163, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789812702258_0008
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    1. Tesfatsion, Leigh, 1995. "A Trade Network Game with Endogenous Partner Selection," ISU General Staff Papers 199505010700001034, Iowa State University, Department of Economics.
    2. McFadzean, David & Tesfatsion, Leigh, 1999. "A C++ Platform for the Evolution of Trade Networks," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 109-134, October.
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    4. Nickell, Stephen & Layard, Richard, 1999. "Labor market institutions and economic performance," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 46, pages 3029-3084, Elsevier.
    5. Tesfatsion, Leigh, 1998. "Preferential Partner Selection in Evolutionary Labor Markets: A Study in Agent-Based Computational Economics," Staff General Research Papers Archive 2048, Iowa State University, Department of Economics.
    6. Pingle, Mark & Tesfatsion, Leigh, 2001. "Non-Employment Benefits and the Evolution of Worker-Employer Cooperation: Experiments with Real and Computational Agents," ISU General Staff Papers 200106010700001053, Iowa State University, Department of Economics.
    7. Acemoglu, Daron & Shimer, Robert, 2000. "Productivity gains from unemployment insurance," European Economic Review, Elsevier, vol. 44(7), pages 1195-1224, June.
    8. McFadzean, David & Stewart, Deron & Tesfatsion, Leigh, 2000. "A Computational Laboratory for Evolutionary Trade Network," ISU General Staff Papers 200008010700001051, Iowa State University, Department of Economics.
    9. MacLeod, W Bentley & Malcomson, James M, 1998. "Motivation and Markets," American Economic Review, American Economic Association, vol. 88(3), pages 388-411, June.
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    11. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    12. Hamermesh, Daniel S., 1999. "LEEping into the future of labor economics: the research potential of linking employer and employee data," Labour Economics, Elsevier, vol. 6(1), pages 25-41, March.
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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. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    3. John Duffy & M. Utku Unver, 2003. "Asset Price Bubbles and Crashes with Near-Zero-Intelligence Traders: Towards an Understanding of Laboratory Findings," Computational Economics 0307001, University Library of Munich, Germany, revised 17 Mar 2004.
    4. 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.
    5. Richard B. Freeman, 2007. "Labor Market Institutions Around the World," NBER Working Papers 13242, National Bureau of Economic Research, Inc.
    6. 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.
    7. Sandra Silva & Jorge Valente & Aurora Teixeira, 2012. "An evolutionary model of industry dynamics and firms’ institutional behavior with job search, bargaining and matching," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(1), pages 23-61, May.
    8. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
    9. Clemens Kühn & Katja Hillmann, 2016. "Rule-based modeling of labor market dynamics: an introduction," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 11(1), pages 57-76, April.
    10. Boudreau, James W., 2010. "Stratification and growth in agent-based matching markets," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 168-179, August.
    11. 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.
    12. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.

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    More about this item

    Keywords

    Simulation; Agent-Based; Computational Economics; Labor; Industrial Dynamics; Innovation; Cluster; Firm Behavior;
    All these keywords.

    JEL classification:

    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory

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