鲁棒贝叶斯选择

IF 0.5 4区经济学 Q4 ECONOMICS

Mathematical Social Sciences Pub Date : 2023-11-01 DOI:10.1016/j.mathsocsci.2023.10.002

Lorenzo Stanca

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引用次数: 0

摘要

不确定性下贝叶斯决策的一个主要问题是使用单一概率度量来量化所有相关的不确定性。本文将先验鲁棒性作为决策问题值的一种连续性形式进行研究。我表明，这种鲁棒性概念的特点是对一系列摄动决策问题的稳定选择形式，其中可用的行为以精确的方式被摄动。然后，我引入了一种基于选择的先验稳健性度量，并将其应用于气候缓解和投资组合选择模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Robust Bayesian choice

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. I show 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. I then introduce a choice-based measure of prior robustness and apply it to models of climate mitigation and portfolio choice.

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来源期刊

Mathematical Social Sciences 数学-数学跨学科应用

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

59 days

期刊介绍： The international, interdisciplinary journal Mathematical Social Sciences publishes original research articles, survey papers, short notes and book reviews. The journal emphasizes the unity of mathematical modelling in economics, psychology, political sciences, sociology and other social sciences. Topics of particular interest include the fundamental aspects of choice, information, and preferences (decision science) and of interaction (game theory and economic theory), the measurement of utility, welfare and inequality, the formal theories of justice and implementation, voting rules, cooperative games, fair division, cost allocation, bargaining, matching, social networks, and evolutionary and other dynamics models. Papers published by the journal are mathematically rigorous but no bounds, from above or from below, limits their technical level. All mathematical techniques may be used. The articles should be self-contained and readable by social scientists trained in mathematics.