测试模糊回归不连续设计中 LATE 的识别条件

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics Pub Date : 2024-04-01 DOI:10.1016/j.jeconom.2024.105738

Yu-Chin Hsu , Ji-Liang Shiu , Yuanyuan Wan

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引用次数: 0

摘要

本文推导了模糊回归不连续设计中局部平均治疗效果识别条件的可检验含义。我们表明，这些识别条件的可检验含义是对观测数据分布的有限数量的不等式限制。然后，我们提出了可检验含义的规范检验，并证明所提出的检验可以控制规模，而且在渐近上是一致的。我们将我们的检验应用于文献中的几种模糊回归不连续设计。

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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Testing identification conditions of LATE in fuzzy regression discontinuity designs

This paper derives testable implications of the identifying conditions for the local average treatment effect in fuzzy regression discontinuity designs. We show that the testable implications of these identifying conditions are a finite number of inequality restrictions on the observed data distribution. We then propose a specification test for the testable implications and show that the proposed test controls the size and is asymptotically consistent. We apply our test to several fuzzy regression discontinuity designs in the literature.

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来源期刊

Journal of Econometrics 社会科学-数学跨学科应用

CiteScore

8.60

自引率

1.60%

发文量

220

审稿时长

3-8 weeks

期刊介绍： The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal''s interests. The Annals of Econometrics is a supplement to the Journal of Econometrics.