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Back to the future: Agent-based modelling and dynamic microsimulation

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  • Richiardi, Matteo
  • Bronka, Patryk
  • van de Ven, Justin

Abstract

In this chapter we focus on the commonalities and differences between agent-based and dynamic microsimulation analytical approaches. Starting from a shared history, we discuss how the two literatures quickly diverged. Discussion concludes with evidence of some recent convergence between agent-based and dynamic microsimulation methods, and emerging opportunities for mutual reinforcement of the two methodologies.

Suggested Citation

  • Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin, 2023. "Back to the future: Agent-based modelling and dynamic microsimulation," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA8/23, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    • Handle: RePEc:ese:cempwp:cempa8-23
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    1. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
    2. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.
    3. Gunnar Eliasson, 2018. "Why Complex, Data Demanding and Difficult to Estimate Agent Based Models? Lessons from a Decades Long Research Program," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 4-60.
    4. Anders Klevmarken, 2022. "Microsimulation. A Tool for Economic Analysis," International Journal of Microsimulation, International Microsimulation Association, vol. 15(1), pages 6-14.
    5. Leombruni, Roberto & Richiardi, Matteo, 2005. "Why are economists sceptical about agent-based simulations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 103-109.
    6. Joke Bilcke & Philippe Beutels & Marc Brisson & Mark Jit, 2011. "Accounting for Methodological, Structural, and Parameter Uncertainty in Decision-Analytic Models," Medical Decision Making, , vol. 31(4), pages 675-692, July.
    7. Matteo Richiardi & Ross E. Richardson, 2017. "JAS-mine: A new platform for microsimulation and agent-based modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 10(1), pages 106-134.
    8. Adrian Carro & Marc Hinterschweiger & Arzu Uluc & J Doyne Farmer, 2023. "Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 32(2), pages 386-432.
    9. Deborah J Schofield & Melanie J B Zeppel & Owen Tan & Sharyn Lymer & Michelle M Cunich & Rupendra N Shrestha, 2018. "A Brief, Global History of Microsimulation Models in Health: Past Applications, Lessons Learned and Future Directions," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 97-142.
    10. Cathal O'Donoghue & Gijs Dekkers, 2018. "Increasing the Impact of Dynamic Microsimulation Modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 61-96.
    11. Eliasson, Gunnar, 1977. "Competition and Market Processes in a Simulation Model of the Swedish Economy," American Economic Review, American Economic Association, vol. 67(1), pages 277-281, February.
    12. Farmer, J. Doyne & Axtell, Robert L., 2022. "Agent-Based Modeling in Economics and Finance: Past, Present, and Future," INET Oxford Working Papers 2022-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    13. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    14. Caiani, Alessandro & Godin, Antoine & Caverzasi, Eugenio & Gallegati, Mauro & Kinsella, Stephen & Stiglitz, Joseph E., 2016. "Agent based-stock flow consistent macroeconomics: Towards a benchmark model," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 375-408.
    15. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    16. Jinjing Li & Cathal O'Donoghue, 2014. "Evaluating Binary Alignment Methods in Microsimulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(1), pages 1-15.
    17. Barbara R. Bergmann, 1974. "A Microsimulation of the Macroeconomy with Explicitly Represented Money Flows," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 3, pages 475-489, National Bureau of Economic Research, Inc.
    18. Leif Andreassen & Dennis Fredriksen & Hege M Gjefsen & Elin Halvorsen & Nils M Stølen, 2020. "The dynamic cross-sectional microsimulation model MOSART," International Journal of Microsimulation, International Microsimulation Association, vol. 13(1), pages 92-113.
    19. Peter Stephensen, 2016. "Logit Scaling: A General Method for Alignment in Microsimulation models," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 89-102.
    20. repec:ijm:journl:v109:y:2017:i:1:p:106-134 is not listed on IDEAS
    21. 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.
    22. John Creedy & Guyonne Kalb & Hsein Kew, 2007. "Confidence Intervals For Policy Reforms In Behavioural Tax Microsimulation Modelling," Bulletin of Economic Research, Wiley Blackwell, vol. 59(1), pages 37-65, January.
    23. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    24. Jinjing Li & Cathal O'Donoghue, 2013. "A survey of dynamic microsimulation models: uses, model structure and methodology," International Journal of Microsimulation, International Microsimulation Association, vol. 6(2), pages 3-55.
    25. Bergmann, Barbara R, 1990. "Micro-to-Macro Simulation: A Primer with a Labor Market Example," Journal of Economic Perspectives, American Economic Association, vol. 4(1), pages 99-116, Winter.
    26. Gaëtan de Menten & Gijs Dekkers & Geert Bryon & Philippe Liégeois & Cathal O'Donoghue, 2014. "LIAM2: a New Open Source Development Tool for Discrete-Time Dynamic Microsimulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(3), pages 1-9.
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