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Title: Exact credibility reference Bayesian premiums
Authors: Gómez Déniz, Emilio 
Vázquez Polo, Francisco José 
UNESCO Clasification: 530204 Estadística económica
Keywords: Bayesian
Reference Decision
Robustness, et al
Issue Date: 2022
Project: Aportaciones A la Toma de Decisiones Bayesianas Óptimas: Aplicaciones Al Coste-Efectividad Con Datos Clínicos y Al Análisis de Riestos Con Datos Acturiales. 
Journal: Insurance: Mathematics and Economics 
Abstract: In this paper, reference analysis, the tool provided by Berger et al. (2009), is used to obtain reference Bayesian premiums, which can be helpful when the practitioner has insufficient information to elicit a prior distribution. The Bayesian premiums thus obtained are based exclusively on prior distributions built from the model generated and from the available data. This mechanism produces an objective Bayesian inference, which appears to be the same as the robust Γ-minimax inference. In an informational-theoretical sense, the prior distribution used to make the inference is less informative. These Bayesian premiums are expected to approximate those which would have been obtained using proper priors describing a vague initial state of knowledge. Useful credibility expressions are readily derived by taking classes of priors involving restrictions on moments, i.e., restrictions on the collective or prior premium when the weighted squared-error loss function is used.
ISSN: 0167-6687
DOI: 10.1016/j.insmatheco.2022.04.002
Source: Insurance: Mathematics and Economics [ISSN 0167-6687], v. 105, p. 128-143, (Julio 2022)
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