We study stochastic choice from lists. All lists present the same set of alternatives albeit in different orders. Faced with a list, the decision maker makes her choice in two stages. In the first stage she searches through the list till she sees $k$ alternatives. In the second stage she chooses from the alternatives she has seen. Both $k$ and the choice rule governing her second stage behavior are random. We show that the underlying primitives of our model are revealed by the decision maker’s choice frequencies from lists. We characterize the model and two of its special cases. In the first special case the decision maker deterministically chooses the best observed alternative according to a given preference. In the second, the decision maker maximizes random preferences.

我们研究列表中的随机选择。尽管顺序不同，但所有列表都提供了相同的备选方案集。面对一份清单，决策者分两个阶段做出选择。在第一阶段她搜索列表直到她看到$克$备择方案。在第二阶段，她从她看到的备选方案中进行选择。两个都$克$并且控制她第二阶段行为的选择规则是随机的。我们表明，决策者从列表中的选择频率揭示了我们模型的基本原语。我们描述了模型及其两个特殊情况。在第一个特殊情况下，决策者根据给定的偏好确定性地选择最佳观察替代方案。第二，决策者最大化随机偏好。