Abstract

How is it possible that models from game theory, which are typically highly idealised, can be harnessed for designing institutions through which we interact? I argue that game theory assumes that social interactions have a specific structure, which is uncovered with the help of directed graphs. The graphs make explicit how game theory encodes counterfactual information in natural collections of its models and can therefore be used to track how model-interventions change model-outcomes. For model-interventions to inform real-world design requires the truth of a causal hypothesis, namely that structural relations specified in a model approximate causal relations in the target interaction; or in other words, that the directed graph can be interpreted causally. In order to increase their confidence in this hypothesis, market designers complement their models with natural and laboratory experiments, and computational methods. Throughout the paper, the reform of a matching market for medical residents provides a case study for my proposed view, which hasn't been previously considered in the philosophy of science.