Abstract
Policymakers increasingly draw on scientific methods, including simulation modeling, to justify their decisions. For these purposes, scientist and policymakers face an extensive choice of modeling strategies. This paper distinguishes two types of strategies: Massive Simulation Models (MSMs) and Abstract Simulation Models (ASMs), and discusses how to justify strategy choice with reference to the core characteristics of the respective strategies. In particular, I argue that MSMs might have more severe problems than ASMs in determining the accuracy of the model; that MSMs might have more severe problems than ASMs in dealing with inevitable uncertainty; and that MSMs might have more severe problems than ASMs with misinterpretation and misapplication due to their format. While this in no way excludes the prospect that some MSMs provide good justifications for policy decisions, my arguments caution against a general preference for MSM over ASMs for policy decision purposes.
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Notes
- 1.
“We view the social networks created by TRANSIMS as a single instance of a stochastic process defined in an enormous space of possibilities” (Eubank et al. 2004, Supplement, 3).
- 2.
This issue further compounds the problem of particular model targets when policy targets are more abstract, discussed in Sect. 4.1. A close fit to the particular model target—even without the problem of overfitting—might not improve the model’s usefulness for questions about the abstract policy target.
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Grüne-Yanoff, T. (2017). Seven Problems with Massive Simulation Models for Policy Decision-Making. In: Resch, M., Kaminski, A., Gehring, P. (eds) The Science and Art of Simulation I . Springer, Cham. https://doi.org/10.1007/978-3-319-55762-5_7
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