IDEAS home Printed from https://ideas.repec.org/p/kob/dpaper/dp2026-13.html

The Effects of Training under the Employment Adjustment Subsidy during the COVID-19 Pandemic: Evidence from Japan

Author

Listed:
  • Takashi Kamihigashi

    (Center for Computational Social Science (CCSS) and Research Institute for Economics & Business Administration, Kobe University, JAPAN)

  • Corrado Di Guilimi

    (Economic Discipline Group, University of Technology Sydney, AUSTRALIA, Department of Economics and ManagementUniversity of Florence, ITALY, Center for Computational Social Science, Kobe University, JAPAN and Centre for Applied Macroeconomic Analysis, Australian National University, AUSTRALIA)

Abstract

The paper introduces forward-looking intertemporal optimization in an agent-based model. Optimization is implemented considering, on the one hand that revision of economic behavior do not occur continuosly over time but only when circumstances suggest or impose it, and, on the other hand, that, given the inherent uncertainty and complexity of the economic system, the planning horizon is finite. We propose a macroeco nomic model with a large population of household agents. Each period a random sample of them will reset their propensities to consume and invest by maximizing their intertemporal utility. The study is a primer in considering the joint effect of heterogeneous agents’ interaction and forward-looking behavior, and provides novel insights into the mechanism of transmission of individual choices to the macroeconomy. The heavy computational tasks are managed through the development of new programming tools. The oexistence of interaction and forward looking be havior generates interesting coordination dynamics. The results suggest that even a tiny fraction of optimizing agents over the whole population has a significant effect of aggregate output, but this effect is nonlinear and conditional on the length of the panning horizon.

Suggested Citation

  • Takashi Kamihigashi & Corrado Di Guilimi, 2026. "The Effects of Training under the Employment Adjustment Subsidy during the COVID-19 Pandemic: Evidence from Japan," Discussion Paper Series DP2026-13, Research Institute for Economics & Business Administration, Kobe University.
  • Handle: RePEc:kob:dpaper:dp2026-13
    as

    Download full text from publisher

    File URL: https://www.rieb.kobe-u.ac.jp/academic/ra/dp/English/DP2026-13.pdf
    File Function: First version, 2026
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Salle, Isabelle L., 2015. "Modeling expectations in agent-based models — An application to central bank's communication and monetary policy," Economic Modelling, Elsevier, vol. 46(C), pages 130-141.
    2. Catalano, Michele & Di Guilmi, Corrado, 2019. "Uncertainty, rationality and complexity in a multi-sectoral dynamic model: The dynamic stochastic generalized aggregation approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 117-144.
    3. Michael Woodford, 2019. "Monetary Policy Analysis When Planning Horizons Are Finite," NBER Macroeconomics Annual, University of Chicago Press, vol. 33(1), pages 1-50.
    4. Lengnick, Matthias & Wohltmann, Hans-Werner, 2016. "Optimal monetary policy in a new Keynesian model with animal spirits and financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 64(C), pages 148-165.
    5. Calvert Jump, Robert & Hommes, Cars & Levine, Paul, 2019. "Learning, heterogeneity, and complexity in the New Keynesian model," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 446-470.
    6. Mattia Guerini & Mauro Napoletano & Andrea Roventini, 2018. "No man is an Island: The impact of heterogeneity and local interactions on macroeconomic dynamics," Post-Print halshs-03509084, HAL.
    7. repec:spo:wpmain:info:hdl:2441/2qdhj5485p93jrnf08s1meeap9 is not listed on IDEAS
    8. Gobbi, Alessandro & Grazzini, Jakob, 2019. "A basic New Keynesian DSGE model with dispersed information: An agent-based approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 101-116.
    9. Mauro Napoletano, 2018. "A Short Walk on the Wild Side: Agent-Based Models and their Implications for Macroeconomic Analysis," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(3), pages 257-281.
    10. Arifovic, Jasmina & Dawid, Herbert & Deissenberg, Christophe & Kostyshyna, Olena, 2010. "Learning benevolent leadership in a heterogenous agents economy," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1768-1790, September.
    11. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    12. repec:spo:wpmain:info:hdl:2441/28ldm6et9r9pbak4qpf3imo9bj is not listed on IDEAS
    13. Guerini, Mattia & Napoletano, Mauro & Roventini, Andrea, 2018. "No man is an Island: The impact of heterogeneity and local interactions on macroeconomic dynamics," Economic Modelling, Elsevier, vol. 68(C), pages 82-95.
    14. Duncan Foley, 2017. "Crisis and theoretical methods: equilibrium and disequilibrium once again," Working Papers 1703, New School for Social Research, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mauro Napoletano, 2018. "A Short Walk on the Wild Side: Agent-Based Models and their Implications for Macroeconomic Analysis," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(3), pages 257-281.
    2. Emanuele Russo, 2021. "Harrodian instability in decentralized economies: an agent-based approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 539-567, July.
    3. repec:spo:wpmain:info:hdl:2441/2qdhj5485p93jrnf08s1meeap9 is not listed on IDEAS
    4. Váry, Miklós, 2021. "The long-run real effects of monetary shocks: Lessons from a hybrid post-Keynesian-DSGE-agent-based menu cost model," Economic Modelling, Elsevier, vol. 105(C).
    5. Delli Gatti, Domenico & Grazzini, Jakob, 2020. "Rising to the challenge: Bayesian estimation and forecasting techniques for macroeconomic Agent Based Models," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 875-902.
    6. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    7. Orlando Gomes, 2021. "Growth theory under heterogeneous heuristic behavior," Journal of Evolutionary Economics, Springer, vol. 31(2), pages 533-571, April.
    8. repec:spo:wpmain:info:hdl:2441/dcditnq6282sbu1u151qe5p7f is not listed on IDEAS
    9. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux," Working Papers hal-03459348, HAL.
    10. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    11. Gobbi, Alessandro & Grazzini, Jakob, 2019. "A basic New Keynesian DSGE model with dispersed information: An agent-based approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 101-116.
    12. Schiozer, Nikolas & Lima, Gilberto Tadeu & Alexandre, Michel, 2026. "Heterogeneity in pricing behavior in hybrid DSGE-ABM macrodynamics," Economic Modelling, Elsevier, vol. 155(C).
    13. Jump, Robert Calvert & Levine, Paul, 2019. "Behavioural New Keynesian models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 59-77.
    14. Hommes, Cars & He, Mario & Poledna, Sebastian & Siqueira, Melissa & Zhang, Yang, 2025. "CANVAS: A Canadian behavioral agent-based model for monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    15. Cars Hommes & Mario He & Sebastian Poledna & Melissa Siqueira & Yang Zhang, 2022. "CANVAS: A Canadian Behavioral Agent-Based Model," Staff Working Papers 22-51, Bank of Canada.
    16. Gross, Marco, 2022. "Beautiful cycles: A theory and a model implying a curious role for interest," Economic Modelling, Elsevier, vol. 106(C).
    17. Anufriev, Mikhail & Lamantia, Fabio & Radi, Davide & Tichy, Tomas, 2025. "Leaning against the wind in the New Keynesian model with heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    18. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    19. Emanuele Ciola & Edoardo Gaffeo & Mauro Gallegati, 2021. "Search for Profits and Business Fluctuations: How Banks' Behaviour Explain Cycles?," Working Papers 450, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    20. Masciandaro, Donato, 2022. "Independence, conservatism, and beyond: Monetary policy, central bank governance and central banker preferences (1981–2021)," Journal of International Money and Finance, Elsevier, vol. 122(C).
    21. Proaño, Christian R. & Lojak, Benjamin, 2020. "Animal spirits, risk premia and monetary policy at the zero lower bound," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 221-233.
    22. Orlando Gomes, 2021. "Hand-to-mouth consumers, rule-of-thumb savers, and optimal control," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 229-263, April.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kob:dpaper:dp2026-13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Office of Promoting Research Collaboration, Research Institute for Economics & Business Administration, Kobe University (email available below). General contact details of provider: https://edirc.repec.org/data/rikobjp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.