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.

社会科学中的许多经验工作都致力于从有限的替代品（通常称为“可行集合”）中观察自己选择的产品来学习个人的偏好。然而，涵盖微观经济学，行为经济学，市场营销和心理学的理论和应用文献大量，这表明人们通常在做出选择之前实际上并不考虑可行设置中的每一个替代方案。还有广泛的文献记录，即使在一组具有相似特征的个体中，个人的偏好 - 对不同产品的口味也表现出很大的异质性。研究人员提出了两种广泛的经验模型的离散选择模型，这些模型允许在个人认为的替代方案中，即“考虑集合”，以及每个人所拥有的偏好。在一类模型中，偏好中的异质性和考虑集合集合的异质性可以互相依赖。这项研究开发了一种估计偏好和/或考虑集的分布并对估计分布进行推断的方法。它还开发了一种估计（并推断）政策干预措施的福利效应的方法，例如那些使消费者更加了解特定产品或产品属性的人，或那些更改市场中产品集的产品。这项研究的主要输出是实施方法论的便携式计算机程序的集合，这些程序将与社区公开，无需指控或限制。这项研究将带有未经观察的异型性异质化的新经验性选择。在这项研究中考虑的模型中，决策者在他们考虑的产品和偏好方面都是异质的。第一类模型对考虑设置的形成过程没有任何限制，尤其是允许依赖于决策者的随机考虑的不受限制形式，并具有她的偏好以及可观察到的可用替代方案的可观察到的特征。由于其灵活性，该模型是部分但未确定的。第二类模型假定特定的分布（已知参数）作为随机对价集，这是基于微观经济理论文献中最新的理论进步，以有限的考虑/注意力。然后，它旨在提供弱条件，以实现偏好中未观察到的异质性的非参数点鉴定，并识别考虑集合的分布。这项研究旨在为点或设置已确定的分布提出特定的估计器/推理方法。这项研究进一步开发了经验研究人员可以用来实施这些方法的计算机包，并将与社区公开，无需指控或限制与社区共享。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准来评估的。