IDEAS home Printed from https://ideas.repec.org/p/boc/usug20/03.html
   My bibliography  Save this paper

Agent based models in Mata: Modelling aggregate processes, like the spread of a disease

Author

Listed:
  • Maarten Buis

    (University of Konstanz)

Abstract

An Agent Based Model (ABM) is a simulation in which agents that each follow simple rules interact with one another and thus produce an often surprising outcome at the macro level. The purpose of an ABM is to explore mechanisms through which actions of the individual agents add up to a macro outcome by varying the rules that agents have to follow or varying with whom the agent can interact (for example, varying the network). These models have many applications, like the study of segregation of neighborhoods or the adoption of new technologies. However, the application that is currently most topical is the spread of a disease. In this talk, I will give introduction on how to implement an ABM in Mata, by going through the simple models I (a sociologist, not an epidemiologist) used to make sense of what is happening with the COVID-19 pandemic.Creation-Date: 20200911

Suggested Citation

  • Maarten Buis, 2020. "Agent based models in Mata: Modelling aggregate processes, like the spread of a disease," London Stata Conference 2020 03, Stata Users Group.
    • Handle: RePEc:boc:usug20:03
    as

    Download full text from publisher

    File URL: http://repec.org/usug2020/Buis_u20.zip
    Download Restriction: no
    ---><---

    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:boc:usug20:03. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/stataea.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.