In this paper we report results from an economic experiment where we investigate the predictive performance of dynamic ambiguity models in the gains domain. Representing ambiguity with the aid of a transparent and non-manipulable device (a Bingo Blower) and using two-stage allocation questions, we gather data that allow us to estimate particular parametric forms of the various functionals and compare their relative performance in terms of out-of-sample fit. Our data show that a dynamic specification of Prospect Theory has the best predictive capacity, closely followed by Choquet Expected Utility, while multiple-prior theories can predict choice only for a very restricted subset of our subjects.

中文翻译：

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动态歧义模型的预测能力的实验测试

在本文中，我们报告了一项经济实验的结果，在该实验中，我们研究了收益域中动态歧义模型的预测性能。在透明且不可操作的设备（宾果鼓风机）的帮助下表达歧义，并使用两阶段分配问题，我们收集了数据，这些数据使我们能够估算各种功能的特定参数形式，并比较它们的相对性能。样本拟合。我们的数据表明，对前景理论的动态规范具有最佳的预测能力，紧随其后的是Choquet预期效用，而多个优先理论只能预测我们学科中非常有限的子集的选择。