Robust Bayesian Choice

Lorenzo Stanca ()
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Lorenzo Stanca: Department of Economics, Social Studies, Applied Mathematics and Statistics (ESOMAS) and Collegio Carlo Alberto, University of Torino, Italy;

No 79, Working papers from Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino

Abstract: A major concern with Bayesian decision making under uncertainty is the use of a single probability measure to quantify all relevant uncertainty. This paper studies prior robustness as a form of continuity of the value of a decision problem. It is shown that this notion of robustness is characterized by a form of stable choice over a sequence of perturbed decision problems, in which the available acts are perturbed in a precise fashion. Subsequently, a choice-based measure of prior robustness is introduced and applied to portfolio choice and climate mitigation.

Keywords: Risk; Uncertainty; Robustness; Ambiguity; Robust Statistics; Prior Selection. (search for similar items in EconPapers)
JEL-codes: C52 C61 D81 (search for similar items in EconPapers)
Pages: 54 pages
Date: 2023-01
New Economics Papers: this item is included in nep-dcm, nep-mic and nep-upt
References: View references in EconPapers View complete reference list from CitEc
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https://www.bemservizi.unito.it/repec/tur/wpapnw/m79.pdf First version, 2023 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:tur:wpapnw:079

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