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Negotiating a Future that is not like the Past

Elsenbroich, Corinna; Badham, Jennifer

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Corinna Elsenbroich


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.


Elsenbroich, C., & Badham, J. (2023). Negotiating a Future that is not like the Past. International Journal of Social Research Methodology, 26(2), 207-213.

Journal Article Type Article
Acceptance Date Sep 1, 2022
Online Publication Date Nov 4, 2022
Publication Date 2023
Deposit Date Oct 14, 2022
Publicly Available Date Mar 22, 2023
Journal International Journal of Social Research Methodology
Print ISSN 1364-5579
Electronic ISSN 1464-5300
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 26
Issue 2
Pages 207-213


Published Journal Article (624 Kb)

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Copyright Statement
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.<br /> 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.

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