IDEAS home Printed from https://ideas.repec.org/a/ijm/journl/v9y2016i3p1-4.html
   My bibliography  Save this article

Editorial

Author

Listed:
  • Matteo Richiardi

    () (Institute for New Economic Thinking, Oxford Martin School, University of Oxford, Eagle House, Walton Well Road, OX2 6ED Oxford, UK)

Abstract

No abstract is available for this item.

Suggested Citation

  • Matteo Richiardi, 2016. "Editorial," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 1-4.
  • Handle: RePEc:ijm:journl:v:9:y:2016:i:3:p:1-4
    as

    Download full text from publisher

    File URL: http://www.microsimulation.org/IJM/V9_3/0_IJM_9_3_2016_Editorial.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
    2. 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.
    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. 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.
    2. 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.
    3. Nils Bertschinger & Iurii Mozzhorin, 0. "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 0, pages 1-38.
    4. Sylvain Barde & Sander Van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," Sciences Po publications 17/12, Sciences Po.
    5. Platt, Donovan & Gebbie, Tim, 2018. "Can agent-based models probe market microstructure?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1092-1106.
    6. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    7. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    8. Guerini, Mattia & Moneta, Alessio, 2017. "A method for agent-based models validation," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 125-141.
    9. repec:ijm:journl:v109:y:2017:i:1:p:106-134 is not listed on IDEAS
    10. Adam Majewski & Stefano Ciliberti & Jean-Philippe Bouchaud, 2018. "Co-existence of Trend and Value in Financial Markets: Estimating an Extended Chiarella Model," Papers 1807.11751, arXiv.org.
    11. Barry J. Milne & Roy Lay-Yee & Jessica M. Mc Lay & Janet Pearson & Martin von Randow & Peter Davis, 2015. "Modelling the Early life-course (MELC): A Microsimulation Model of Child Development in New Zealand," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 28-60.
    12. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    13. Herbert Dawid & Philipp Harting & Sander Hoog & Michael Neugart, 2019. "Macroeconomics with heterogeneous agent models: fostering transparency, reproducibility and replication," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 467-538, March.
    14. Jan Pablo Burgard & Joscha Krause & Simon Schmaus, 2019. "Estimation of Regional Transition Probabilities for Spatial Dynamic Microsimulations from Survey Data Lacking in Regional Detail," Research Papers in Economics 2019-12, University of Trier, Department of Economics.
    15. Majewski, Adam A. & Ciliberti, Stefano & Bouchaud, Jean-Philippe, 2020. "Co-existence of trend and value in financial markets: Estimating an extended Chiarella model," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    16. Sander Hoog, 2019. "Surrogate Modelling in (and of) Agent-Based Models: A Prospectus," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1245-1263, March.
    17. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    18. Lucas Fievet & Didier Sornette, 2018. "Calibrating emergent phenomena in stock markets with agent based models," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    19. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    20. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    21. Gijs Dekkers & Richard Cumpston, 2012. "On weights in dynamic-ageing microsimulation models," International Journal of Microsimulation, International Microsimulation Association, vol. 5(2), pages 59-65.

    More about this item

    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:ijm:journl:v:9:y:2016:i:3:p:1-4. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jinjing Li). General contact details of provider: http://www.microsimulation.org/ijm/ .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.