Making Decisions under Model Misspecification
Fabio Maccheroni and
No 668, Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University
We use decision theory to confront uncertainty that is sufficiently broad to incorporate "models as approximations".We presume the existence of a featured collection of what we call "structured models" that have explicit substantive motivations. The decision maker confronts uncertainty through the lens of these models, but also views these models as simplifications, and hence, as misspecified. We extend min-max analysis under model ambiguity to incorporate the uncertainty induced by acknowledging that the models used in decision-making are simplified approximations. Formally, we provide an axiomatic rationale for a decision criterion that incorporates model misspecification concerns.
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Working Paper: Making Decisions under Model Misspecification (2022)
Working Paper: Making Decisions under Model Misspecification (2020)
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