Quotes / The Models Are Misspecified

The consequences of a decision may depend on exogenous contingencies and uncertain outcomes that are outside the control of a decision maker. This uncertainty takes on many forms. Economic applications typically feature risk, where the decision maker knows the correct probabilistic model governing the contingencies but not necessarily the decision outcomes. Yet, this is a demanding assumption. As a result, statisticians and econometricians have long wrestled with how to confront ambiguity over models or unknown parameters within a model. Each model is itself a simplification or an approximation designed to guide or enhance our understanding of some underlying phenomenon of interest. Thus, the model, by its very nature, is misspecified, but in typically uncertain ways. How should a decision maker acknowledge model misspecification in a way that guides the use of purposefully simplified models sensibly? This concern has certainly been on the radar screen of statisticians and control theorists, but it has been largely absent in formal approaches to decision theory.