Regular Consistent Preferences

Maximilian Mihm, Kemal Ozbek
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Abstract

In a dynamic choice environment, an agent's tastes may change over time, leading to a conflict between plans made today and choices made in the future. In response, a consistent planner restricts herself to plans that she will actually follow, by anticipating today how she will rank continuation plans in the future. Since the agent's expected future rankings often play an important role in policy analysis, they need to be elicited from observable choices. In this paper, we provide a method to elicit expected future rankings by considering the agent's preferences today over dynamic decision problems. Our identification strategy exploits that, in many applications of the consistent planning model, future rankings are monotone with respect to a partial order, which provides an unambiguous ranking of some alternatives. Our results are developed in a general framework, and can therefore be used to elicit expected future rankings in many applications of the consistent planning model. To illustrate our findings, we consider a dynamic consumption problem with quasi-hyperbolic discounting, and show how the agent's expectations about her present-bias in the future can be elicited from simple choice experiments today.
定期一致的偏好
在动态选择环境中,代理人的品味可能会随着时间的推移而改变,从而导致今天制定的计划和未来做出的选择之间的冲突。作为回应,一个始终如一的计划者会把自己限制在她实际会执行的计划上,通过预测今天她将如何对未来的延续计划进行排序。由于代理人的预期未来排名在政策分析中经常起着重要作用,因此它们需要从可观察的选择中得出。在本文中,我们提供了一种方法,通过考虑智能体今天对动态决策问题的偏好来引出预期的未来排名。我们的识别策略利用了在一致规划模型的许多应用中,未来的排名相对于偏序是单调的,这提供了一些备选方案的明确排名。我们的结果是在一个一般框架中开发的,因此可以用来在一致规划模型的许多应用中引出预期的未来排名。为了说明我们的发现,我们考虑了一个具有准双曲折现的动态消费问题,并展示了代理人如何从今天的简单选择实验中得出她对未来的现在偏差的期望。
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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