We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.

Durham Research Online
You are in:

Negotiating a Future that is not like the Past

Elsenbroich, Corinna and Badham, Jennifer (2022) 'Negotiating a Future that is not like the Past.', International Journal of Social Research Methodology .


Agent-based models combine data and theory during both development and use of the model. As models have become increasingly data driven, it is easy to start thinking of agent-based modelling as an empirical method, akin to statistical modelling, and reduce the role of theory. We argue that both types of information are important in modelling dynamic complex systems, where the past is not a reliable blueprint for the future. By balancing theory and data, agent-based modelling is a tool to describe plausible futures, that we call “justified stories”. We conclude that this balance must be maintained if agent-based models are to serve a useful decision support role for policy makers.

Item Type:Article
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial 4.0.
File format - PDF
Full text:(VoR) Version of Record
Available under License - Creative Commons Attribution 4.0.
Download PDF
Publisher Web site:
Publisher statement:© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Date accepted:01 September 2022
Date deposited:14 October 2022
Date of first online publication:04 November 2022
Date first made open access:06 January 2023

Save or Share this output

Look up in GoogleScholar