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Simulation for labor market using a multi-agent model toward validation of the Amended Labor Contract Act

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Abstract

In 2012, Japan amended its Labor Contract Act (LCA) to ameliorate the employment conditions for fixed-term workers. Unfortunately, the amended law still has a problem, which is known as the refusal to renew employment contracts. This paper argues that the law’s amendment fails to reflect its initial motivation due to a gap between its predicted and its actual effects. We employ a multi-agent system, in which agents autonomously behave as employers and employees. We simulated the amendment’s effect with a multi-agent system that consists of company agents with Q-learning and worker agents. Our experiments clarified that since the LCA was enforced in advance, companies are more likely to hire permanent workers without being swayed by economic trends. We achieved a small economic society through which we examined the source of the economic disparity post-LCA. Our study supports legislation for amendment of such employment laws.

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References

  1. J. Lee (2010) Labour policy on fixed-term employment contracts in Korea. In: Nakakubo H, Araki T (eds) Regulation of fixed-term employment contracts, chapter 7. Kluwer Law International

  2. Matoba R, Komai K, Nanba T, Hagiwara S, Nakamura M (2020), Simulation of employment environment using multi-agent model. In: Proceedings of the 25th international symposium on artificial life and robotics 2020 (AROB 25th 2020), pp 408–413

  3. Ministry of Health, Labor and Welfare (2014) Actual condition survey of employment structure

  4. Watanabe Y (2018) New rules of conversion from fixed-term to open-ended contracts: companies' approaches to compliance and the subsequent policy developments. In: Japan labor issues, vol 2, no 7. Japan Institute for Labour Policy and Training, pp 13–19

  5. Ikezoe H (2018) Termination of employment relationships in Japan (Part II): dismissal and refusal to renew a fixed-term contract. In: Japan labor issues, vol 2, no 7. Japan Institute for Labour Policy and Training, pp 25–28

  6. WatkinsCJCH (1989) Learning from delayed rewards. PhD thesis. Cambridge University, Cambridge

  7. C. J. C. H. Watkins, P. Dayan (1992), Q-learning. Machine Learning, Vol. 8, pp 279–292, Kluwer Academic Publishers, Boston.

  8. HagiwaraS, Tojo S (2006) Discordance detection in regional ordinance: Ontology-based validation. In: van Engers TM (eds) Legal knowledge and information systems—JURIX 2006: the nineteenth annual conference on legal knowledge and information systems, Paris, France, 7–9 December 2006, vol 152, frontiers in artificial intelligence and applications. IOS Press, pp 111–120

  9. Nakamura M, Nobuoka S, Shimazu A (2008) Towards translation of legal sentences into logical forms. In: New frontiers in artificial intelligence, LNCS, vol 4914. Springer, pp 349–362

  10. Takano K, Nakamura M, Oyama Y, Shimazu A (2010) Semantic analysis of paragraphs consisting of multiple sentences—towards development of a logical formulation system. In: Legal knowledge and information systems—JURIX 2010. IOS Press, pp 117–126

  11. Bergmann BR (1974) A microsimulation of the macroeconomy with explicitly represented money flows. Ann Econ Soc Meas 3(3):475–489

    Google Scholar 

  12. Eliasson G (1976) Competition and market processes in a simulation model of the Swedish economy. Am Econ Rev 67:277–281

    Google Scholar 

  13. NeugartM, Richiardi MG (2014) Agent-based models of the labor market. In: The oxford handbook of computational economics and finance. Oxford University Press

  14. BaruffiniM (2015) An agent-based simulation of the Swiss labour market: an alternative for policy evaluation. In: J. policy and complex systems, vol 2, no 1. Policy Studies Organization, pp 15–30

  15. LewkoviczZ, Kant J (2008) A multiagent simulation of a stylized French Labor market: emergences at the micro level. In: Advances in complex systems, vol 11, no 2. World Scientific, pp 217–230

  16. Gemkow S, Neugart M (2011) Referral hiring, endogenous social networks, and inequality: an agent-based analysis. J Evolut Econ 21:703–719

    Article  Google Scholar 

  17. Deissenberg C, van der Hoog S, Dawid H (2008) Eurace: a massively parallel agent-based model of the European economy. Appl Math Comput 204:541–552

    Article  MathSciNet  Google Scholar 

  18. Dawid H, Gemkow S, Harting P, Neugart M (2012) Labor market integration policies and the convergence of regions: the role of skills and technology diffusion. J Evolut Econ 22(3):543–562

    Article  Google Scholar 

  19. Boudreau JW (2010) Stratification and growth in agent-based matching markets. J Econ Behav Organ 75:168–179

    Article  Google Scholar 

  20. Sutton RS, Barto AG (1998) Reinforcement Learning: An Introduction. MIT Press, Cambridge

    MATH  Google Scholar 

  21. ShirakawaH (2009) An empirical analysis of worker age, productivity, and real wages (in Japanese) In: Is the aging of society a threat?—the key to productivity growth in the next decade. National Institute for Research Advancement, pp 34–53

  22. JinnoM (2009) Nenrei kubun de mita roudou seisansei no suikei. In: Koureika wa kyoui ka?—Kagi nigiru mukou 10 nen no seisansei koujou (in Japanese) (Estimation of Labor Productivity by Age Group. In: Is the aging of society a threat? - The Key to Productivity Growth in the Next Decade), National Institute for Research Advancement, pp 54–65

  23. Ministry of Health, Labor and Welfare (2010) White Paper on the Labor Economy

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Acknowledgements

This research was partly supported by JSPS KAKENHI Grant numbers JP19K22899 and JP19H04427.

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Authors and Affiliations

  1. Niigata Institute of Technology, Niigata, Japan

    Makoto Nakamura

  2. National Institute of Technology, Toyama College, Toyama, Japan

    Shingo Hagiwara & Ryuichi Matoba

Authors
  1. Makoto Nakamura
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  2. Shingo Hagiwara
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  3. Ryuichi Matoba
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Correspondence to Makoto Nakamura.

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Nakamura, M., Hagiwara, S. & Matoba, R. Simulation for labor market using a multi-agent model toward validation of the Amended Labor Contract Act. Artif Life Robotics 27, 472–479 (2022). https://doi.org/10.1007/s10015-022-00764-9

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  • DOI: https://doi.org/10.1007/s10015-022-00764-9

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