Bayesian Decision Theory and Stochastic Independence

Philippe Mongin

No 1228, HEC Research Papers Series from HEC Paris

Abstract: Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, we introduce preference axioms that entail not only these definitional properties, but also the stochastic independence of the two sources of uncertainty. This goes some way towards filling a curious lacuna in Bayesian decision theory.

Keywords: Stochastic Independence; Probabilistic Independence; Bayesian Decision Theory; Savage (search for similar items in EconPapers)
JEL-codes: D81 D89 (search for similar items in EconPapers)
Pages: 11 pages
Date: 2017-11-01, Revised 2017-11-28
New Economics Papers: this item is included in nep-mic and nep-upt
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Citations: View citations in EconPapers (1)

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Working Paper: Bayesian Decision Theory and Stochastic Independence (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:ebg:heccah:1228

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