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JAS-mine: A new platform for microsimulation and agent-based modelling

Author

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  • Matteo Richiardi

    (Institute for New Economic Thinking at the Oxford Martin School Nuffield College, Oxford, UK)

  • Ross E Richardson

    (Institute for New Economic Thinking at the Oxford Martin School Nuffield College, Oxford, UK)

Abstract

We introduce JAS-mine, a new Java-based computational platform that features tools to support the development of large-scale, data-driven, discrete-event simulations. JAS-mine is specifically designed for both agent-based and microsimulation modelling, anticipating a convergence between the two approaches. An embedded relational database management system provides tools for sophisticated input-output communications and data storage, allowing the power of relational databases to be used within an object-oriented framework. The JAS-mine philosophy encourages the separation of distinct concepts, objects and functionalities of the simulation model, and advocates and supports transparency, flexibility and modularity in model design. For instance, JAS-mine allows to store the list of regressors and the estimated coefficients externally to code, making it easy to change the specification of the regression models used in the simulation and achieving a complete parallelisation between the tasks of the econometricians and those of the programmers. Moreover, tools for uncertainty analysis and search over the parameter space are also built in.

Suggested Citation

  • Matteo Richiardi & Ross E Richardson, 2016. "JAS-mine: A new platform for microsimulation and agent-based modelling," Economics Papers 2016-W04, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:1604
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    References listed on IDEAS

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    Cited by:

    1. Melanie N Tomintz & Bernhard Kosar & Victor M García-Barrios, 2017. "simSALUD: Design and Implementation of an Open-source Wizard based Spatial Microsimulation Framework," International Journal of Microsimulation, International Microsimulation Association, vol. 10(2), pages 118-143.
    2. 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.
    3. Luzius Meisser, 2017. "The Code is the Model," International Journal of Microsimulation, International Microsimulation Association, vol. 10(3), pages 184-201.
    4. 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.
    5. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    6. Martin Spielauer & Thomas Horvath & Marian Fink, 2020. "microWELT: A Dynamic Microsimulation Model for the Study of Welfare Transfer Flows in Ageing Societies from a Comparative Welfare State Perspective," WIFO Working Papers 609, WIFO.
    7. Richiardi, Matteo & Bronka, Patryk, 2022. "LABSim: a dynamic life course model of individual life course trajectories for Italy," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA5/22, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    8. Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin & Kopasker, Daniel & Vittal Katikireddi, Srinivasa, 2023. "SimPaths: an open-source microsimulation model for life course analysis," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA6/23, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    9. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    10. Giovanni Dosi & Andrea Roventini, 2017. "Agent-Based Macroeconomics and Classical Political Economy: Some Italian Roots," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 261-283, November.
    11. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org, revised Nov 2023.
    12. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2020. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," LEM Papers Series 2020/31, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    13. Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin, 2024. "Attenuation and reinforcement mechanisms over the life course," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA2/24, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    14. Matteo G. Richiardi, 2017. "The Future of Agent-Based Modeling," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 271-287, March.
    15. van de Ven, Justin, 2017. "SIDD: An adaptable framework for analysing the distributional implications of policy alternatives where savings and employment decisions matter," Economic Modelling, Elsevier, vol. 63(C), pages 161-174.
    16. repec:ijm:journl:v109:y:2017:i:1:p:106-134 is not listed on IDEAS
    17. 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.

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    More about this item

    Keywords

    Simulation platform; Microsimulation; Agent-based; Software; Open-source.;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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