 The Behavioral Foundations of Model MisspecificationAislinn Bohren and Daniel Hauser No 17884, CEPR Discussion Papers from Centre for Economic Policy Research Abstract: We link two approaches to biased belief formation: non-Bayesian updating and misspecified models. The former parameterizes a bias with an updating rule mapping signals to posterior beliefs or a belief forecast describing anticipated beliefs; the latter is an incorrect model of the signal generating process. Our main result derives necessary and sufficient conditions for an updating rule and belief forecast to have a misspecified model representation, shows that these two components uniquely pin down a representation, and constructs it. This clarifies the belief restrictions implicit in the misspecified model approach. It also allows leveraging of the distinct advantages of each approach by decomposing a model into empirically identifiable components, showing these components isolate the two forms of bias that the model encodes---the retrospective bias after information arrives and the prospective bias beforehand, and rendering off-the-shelf tools to characterize asymptotic learning and equilibrium predictions in misspecified models applicable to non-Bayesian updating. Keywords: Model; misspecification (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:17884 Ordering information: This working paper can be ordered from Access Statistics for this paper More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK. |
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