Gräbner, C, Bale, CSE orcid.org/0000-0002-2413-0673, Furtado, BA et al. (4 more authors) (2019) Getting the Best of Both Worlds? Developing Complementary Equation-Based and Agent-Based Models. Computational Economics, 53 (2). pp. 763-782. ISSN 0927-7099
Abstract
We argue that building agent-based and equation-based versions of the same theoretical model is a fruitful way of gaining insights into real-world phenomena. We use the epistemological concept of “models as isolations and surrogate systems” as the philosophical underpinning of this argument. In particular, we show that agent-based and equation-based approaches align well when used simultaneously and, contrary to some common misconceptions, should be considered complements rather than substitutes. We illustrate the usefulness of the approach by examining a model of the long-run relationship between economic development and inequality (i.e., the Kuznets hypothesis).
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2017. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Keywords: | Agent-based models; epistemology; equation-based models; economic methodology; social simulation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/K022288/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Sep 2017 11:34 |
Last Modified: | 23 Jun 2023 22:40 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/s10614-017-9763-8 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:121737 |
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