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Long-term dynamics of institutions: Using ABM as a complementary tool to support theory development in historical studies
Delft University of Technology, Netherlands.
Delft University of Technology, Netherlands.
Linnaeus University, Faculty of Social Sciences, Department of Social Studies. Linnaeus University, Linnaeus Knowledge Environments, Water. (DISA;CSS)ORCID iD: 0000-0003-2837-0137
Lund University, Sweden.ORCID iD: 0000-0002-0882-4851
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2021 (English)In: JASSS: Journal of Artificial Societies and Social Simulation, E-ISSN 1460-7425, Vol. 24, no 4, article id 7Article in journal (Refereed) Published
Sustainable development
SDG 16: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
Abstract [en]

Historical data are valuable resources for providing insights into social patterns in the past. However, these data often inform us at the macro-level of analysis but not about the role of individuals’ behaviours in the emergence of long-term patterns. Therefore, it is difficult to infer ‘how’ and ‘why’ certain patterns emerged in the past. Historians use various methods to draw hypotheses about the underlying reasons for emerging patterns and trends, but since the patterns are the results of hundreds if not thousands of years of human behaviour, these hypotheses can never be tested in reality. Our proposition is that simulation models and specifically, agent-based models (ABMs) can be used as complementary tools in historical studies to support hypothesis building. The approach that we propose and test in this paper is to design and configure models in such a way as to generate historical patterns, consequently aiming to find individual-level explanations for the emerging pattern. In this work, we use an existing, empirically validated, agent-based model of common pool resource management to test hypotheses formulated based on a historical dataset. We first investigate whether the model can replicate various patterns observed in the dataset, and second, whether it can contribute to a better understanding of the underlying mechanism that led to the observed empirical trends. We showcase how ABM can be used as a complementary tool to support theory development in historical studies. Finally, we provide some guidelines for using ABM as a tool to test historical hypotheses.

Place, publisher, year, edition, pages
Journal of Artificial Societies and Social Simulation , 2021. Vol. 24, no 4, article id 7
Keywords [en]
Institutional Modelling, Historical Data, CPRs, Institutional Evolution
National Category
Social Sciences Interdisciplinary
Research subject
Social Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-107791DOI: 10.18564/jasss.4706ISI: 000714983900006Scopus ID: 2-s2.0-85128062165OAI: oai:DiVA.org:lnu-107791DiVA, id: diva2:1608141
Available from: 2021-11-03 Created: 2021-11-03 Last updated: 2023-02-01Bibliographically approved

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Bravo, GiangiacomoFarjam, MikeForsman, Anders

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Department of Social StudiesWaterDepartment of Biology and Environmental Science
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