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Long-Term Dynamics of Institutions: Using ABM as a Complementary Tool to Support Theory Development in Historical Studies

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Abstract

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.

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  • Molood Ale Ebrahim Dehkordi & Amineh Ghorbani & Giangiacomo Bravo & Mike Farjam & René van Weeren & Anders Forsman & Tine De Moor, 2021. "Long-Term Dynamics of Institutions: Using ABM as a Complementary Tool to Support Theory Development in Historical Studies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(4), pages 1-7.
  • Handle: RePEc:jas:jasssj:2021-11-3
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    1. Bert, Federico E. & Rovere, Santiago L. & Macal, Charles M. & North, Michael J. & Podestá, Guillermo P., 2014. "Lessons from a comprehensive validation of an agent based-model: The experience of the Pampas Model of Argentinean agricultural systems," Ecological Modelling, Elsevier, vol. 273(C), pages 284-298.
    2. John Geanakoplos & Robert Axtell & J. Doyne Farmer & Peter Howitt & Benjamin Conlee & Jonathan Goldstein & Matthew Hendrey & Nathan M. Palmer & Chun-Yi Yang, 2012. "Getting at Systemic Risk via an Agent-Based Model of the Housing Market," American Economic Review, American Economic Association, vol. 102(3), pages 53-58, May.
    3. Crawford, Sue E. S. & Ostrom, Elinor, 1995. "A Grammar of Institutions," American Political Science Review, Cambridge University Press, vol. 89(3), pages 582-600, September.
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