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An Empirical Model of Limited Consideration: Robust Inference for Risk Preferences

有限考虑的经验模型：风险偏好的稳健推论

基本信息

批准号：
1824448
负责人：
Levon Barseghyan
金额：
$ 39.6万
依托单位：
Cornell University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1824448&HistoricalAwards=false
关键词：
Empirical Model Limited Consideration Robust

项目摘要

Much empirical work in the social sciences is devoted to learning individuals' preferences from observing their choice of a product from a finite collection of alternatives (often referred to as "feasible set"). Yet, there is a large body of theoretical and applied literature spanning microeconomics, behavioral economics, marketing, and psychology, suggesting that often individuals do not actually consider every alternative in the feasible set before making their choice. There is also a wide literature documenting that individuals' preferences -- their tastes over different products -- exhibit large heterogeneity even within a group of individuals with similar characteristics. The investigators put forward two broad classes of empirical models of discrete choice that allow both for unobserved heterogeneity in the collection of alternatives that the individual considers, i.e. "consideration set", and in the preferences that each individual holds. In one class of models, heterogeneity in preferences and heterogeneity in consideration sets are allowed to depend on each other. This research develops a method to estimate the distribution of preferences and/or consideration sets, and conduct inference on the estimated distributions. It also develops a method to estimate (and conduct inference on) the welfare effect of policy interventions, e.g. ones that make consumers more aware of specific products or product attributes, or those that change the set of products in the market, etc. A primary output of this research is a collection of portable computer programs implementing the methodology, that will be shared with the community openly and free of charges or restrictions.This research puts forward new empirical models of discrete choice with unobserved heterogeneity in consideration sets. In the models considered in this research, decision makers are heterogeneous both in the products they consider and in their preferences. The first class of models places no restriction on the consideration set formation process and, in particular, allows for unrestricted forms of dependence of the decision maker's random consideration set with her preferences and with the observable characteristics of the available alternatives. Due to its flexibility, this model is partially but not point identified. The second class of models assumes specific distributions (known up to parameters) for the random consideration sets, building on recent theoretical advances in the microeconomic theory literature on limited consideration/attention. It then aims at providing weak conditions to achieve non-parametric point identification of unobserved heterogeneity in preferences, as well as identification of the distribution of consideration sets. This research aims at suggesting specific estimators/inference methods for the point or set identified distributions. This research further develops computer packages that empirical researcher can use to implement the methods, and that will be shared with the community openly and free of charges or restrictions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

社会科学中的许多实证研究都致力于通过观察个人从有限的备选方案集合（通常称为“可行集”）中选择产品来了解个人的偏好。然而，有大量的理论和应用文献，涵盖微观经济学、行为经济学、市场营销学和心理学，表明人们在做出选择之前，通常不会考虑可行集合中的每一种选择。也有大量文献记载，个人的偏好-他们对不同产品的品味-即使在一组具有相似特征的个人中也表现出很大的异质性。研究人员提出了两大类离散选择的经验模型，允许在个人考虑的替代品集合（即“考虑集”）和每个人持有的偏好中存在未观察到的异质性。在一类模型中，允许偏好的异质性和考虑集的异质性相互依赖。本研究发展一种方法来估计偏好和/或考虑集的分布，并对估计的分布进行推断。它还开发了一种方法来估计（并进行推理）政策干预的福利效应，例如，使消费者更多地了解特定产品或产品属性的政策干预，或改变市场上产品组合的政策干预等。本研究的主要成果是实施该方法的便携式计算机程序集，该研究提出了考虑集具有不可观测异质性的离散选择的新的经验模型。在本研究所考虑的模型中，决策者在他们考虑的产品和他们的偏好方面都是异质的。第一类模型的地方没有限制的考虑集的形成过程中，特别是，允许不受限制的形式依赖的决策者的随机考虑集与她的喜好和可用的替代品的可观察到的特征。由于其灵活性，该模型是部分但不是点识别的。第二类模型假设随机考虑集的特定分布（已知参数），建立在微观经济理论文献中关于有限考虑/注意力的最新理论进展之上。然后，它的目的是提供弱条件，以实现非参数点识别未观察到的异质性的偏好，以及识别的考虑集的分布。本研究的目的是提出具体的估计/推断方法的点或集确定的分布。这项研究进一步开发了计算机软件包，实证研究人员可以使用它来实现这些方法，并将与社区公开分享，不收取任何费用或限制。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。