Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications
Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications
复制标题
使 Anscombe-Aumann 歧义方法适合描述性应用
DOI：
10.1007/s11166-018-9273-7
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发表时间：
2018
影响因子：
4.7
通讯作者：
P. Wakker
中科院分区：
文献类型：
--
作者：
S. Trautmann;P. Wakker
如今，Anscombe-Aumann（AA）模型最初是为了给预期实用程序提供正常基础的，主要用于另一个目的：分析由于歧义而与预期的效用分析（未知的可能性）。不要参考歧义：即使通常适当地描述，这些假设的预期效用也是如此。测试和所有基于AA的歧义理论，同时由于违反辅助假设而避免了混淆，因此，最终的测试仅使用简单的刺激，避免了由于复杂性而避免了噪音。违反了AA理论：参考独立性，普遍的歧义性厌恶和弱确定性独立性。并使参考依赖性概括是，我们将AA歧义模型扩展到了前景理论。
The Anscombe-Aumann (AA) model, originally introduced to give a normative basis to expected utility, is nowadays mostly used for another purpose: to analyze deviations from expected utility due to ambiguity (unknown probabilities). The AA model makes two ancillary assumptions that do not refer to ambiguity: expected utility for risk and backward induction. These assumptions, even if normatively appropriate, fail descriptively. This paper relaxes these ancillary assumptions to avoid the descriptive violations, while maintaining AA’s convenient mixture operation. Thus, it becomes possible to test and apply all AA-based ambiguity theories descriptively while avoiding confounds due to violated ancillary assumptions. The resulting tests use only simple stimuli, avoiding noise due to complexity. We demonstrate the latter in a simple experiment where we find that three assumptions about ambiguity, commonly made in AA theories, are violated: reference independence, universal ambiguity aversion, and weak certainty independence. The second, theoretical, part of the paper accommodates the violations found for the first ambiguity theory in the AA model—Schmeidler’s CEU theory—by introducing and axiomatizing a reference dependent generalization. That is, we extend the AA ambiguity model to prospect theory.
影响因子：
4.7
作者：
M. Abdellaoui;H. Bleichrodt;Olivier L’Haridon;D. Dolder
通讯作者：
M. Abdellaoui;H. Bleichrodt;Olivier L’Haridon;D. Dolder
影响因子：
2.8
作者：
Kocher, Martin G.;Lahno, Amrei Marie;Trautmann, Stefan T.
通讯作者：
Trautmann, Stefan T.
影响因子：
5.4
作者：
Baucells, Manel;Weber, Martin;Welfens, Frank
通讯作者：
Welfens, Frank