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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).
agent-based models; epistemology; equation-based models; economic; methodology; social simulation