摘要翻译：
本文研究的是利用从有限的风险方案集合中观察到的选择数据来学习决策者的偏好。我们提出了一个在考虑集和标准风险厌恶中具有未观察到的异质性的离散选择模型。我们得到了模型半非参数点辨识的充分条件，包括考虑依赖于偏好和一些外生变量的情况。我们的方法得到了一个易于计算的估计量，并适用于具有大选择集的市场。我们用一个财产保险购买数据集来说明它的性质。
---
英文标题：
《Discrete Choice under Risk with Limited Consideration》
---
作者：
Levon Barseghyan, Francesca Molinari, Matthew Thirkettle
---
最新提交年份：
2021
---
分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
--

---
英文摘要：
  This paper is concerned with learning decision makers' preferences using data on observed choices from a finite set of risky alternatives. We propose a discrete choice model with unobserved heterogeneity in consideration sets and in standard risk aversion. We obtain sufficient conditions for the model's semi-nonparametric point identification, including in cases where consideration depends on preferences and on some of the exogenous variables. Our method yields an estimator that is easy to compute and is applicable in markets with large choice sets. We illustrate its properties using a dataset on property insurance purchases.
---
PDF链接：
https://arxiv.org/pdf/1902.06629