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分类依据与纠错

AI 根据所提供的论文材料归类:摘要以 LATE、工具变量独立性、无违背者及排除限制为主要识别问题。

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关注这篇论文的作者
Moyu Liao

以可检验假设扩展经济模型:理论与应用

研究问题
当经济模型的假设被观测分布否证时,如何放宽假设并保留识别内容,同时在原假设未被否证时维持原有识别结果?
方法与思路
作者从 LATE 模型出发,分别放宽无违背者和工具变量独立性假设,再利用偏离原假设的度量构造一般化的放宽方法。
材料陈述的贡献
摘要称,两种放宽在原假设未被否证时保留经典 Wald 表达式,并提供估计及极限理论,以及一般识别集保持一致的条件。
阅读关注点
应核对两种放宽的形式、排除限制如何处理、偏离度量的选择,以及识别集与 Wald 表达式一致的确切条件。
阅读边界
所给 Crossref 摘要未说明放宽假设的完整内容或选择准则;不可否证不代表假设真实,原假设未被否证也不等于得到验证。

原文摘要

This article studies the identification of complete economic models with testable assumptions. We start with a local average treatment effect ( L A T E $LATE$ upper L upper A upper T upper E ) model where the “No Defiers,” the independent IV assumption, and the exclusion restrictions can be jointly refuted by some data distributions. We propose two relaxed assumptions that are not refutable, with one assumption focusing on relaxing the “No Defiers” assumption while the other relaxes the independent IV assumption. The identified set of L A T E $LATE$ upper L upper A upper T upper E under either of the two relaxed assumptions coincides with the classical L A T E $LATE$ upper L upper A upper T upper E Wald ratio expression whenever the original assumption is not refuted by the observed data distribution. We propose an estimator for the identified L A T E $LATE$ upper L upper A upper T upper E and derive the estimator’s limit distribution. We then develop a general method to relax a refutable assumption A . This relaxation method requires finding a function that measures the deviation of an econometric structure from the original assumption A , and a relaxed assumption A ~ $\tilde {A}$ upper A overtilde is constructed using this measure of deviation. We characterize a condition to ensure the identified sets under A ~ $\tilde {A}$ upper A overtilde and A coincide whenever A is not refuted by the observed data distribution and discuss the criteria to choose among different relaxed assumptions.

笔记与分组