摘要翻译：
实验者试图了解受试者的偏好关系。实验者产生成对的替代方案。对于每一对，受试者被要求选择。我们争辩说，一般而言，大而有限的数据不能给出主体偏好的密切近似值，即使有限的（可数无限的）数据足以完美地推断出偏好。我们在备选方案、偏好和对序列的集合上提供了充分的条件，以便观察有限多个选择使实验者能够以任意精度了解受试者的偏好。当偏好在我们的充分条件下可以被识别时，我们证明了效用函数的识别是困难的。我们用几个例子来说明我们的结果，包括Anscombe-Aumann模型中的消费者选择、期望效用和偏好。
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英文标题：
《Preference Identification》
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作者：
Christopher P. Chambers and Federico Echenique and Nicolas S. Lambert
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：Theoretical Economics        理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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英文摘要：
  An experimenter seeks to learn a subject's preference relation. The experimenter produces pairs of alternatives. For each pair, the subject is asked to choose. We argue that, in general, large but finite data do not give close approximations of the subject's preference, even when the limiting (countably infinite) data are enough to infer the preference perfectly. We provide sufficient conditions on the set of alternatives, preferences, and sequences of pairs so that the observation of finitely many choices allows the experimenter to learn the subject's preference with arbitrary precision. While preferences can be identified under our sufficient conditions, we show that it is harder to identify utility functions. We illustrate our results with several examples, including consumer choice, expected utility, and preferences in the Anscombe-Aumann model.
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PDF链接：
https://arxiv.org/pdf/1807.11585