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摘要翻译：
关于随机规划的文献通常限制对满足约束条件的问题的关注。关于部分识别下的估计和推理的文献经常限制具有不同高级假设的识别集的几何形状。这些表面上看起来是对密切相关的问题的不同方法。我们广泛地分析了它们之间的关系。除其他外，我们通过纯矩不等式证明了对于部分辨识，文献中的许多假设基本上与Mangasarian-Fromowitz约束条件一致。这澄清了包括计量经济学在内的著名贡献之间的关系，并阐明了开创性论文中一些高级假设的严格性和验证的便利性。
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英文标题：
《Constraint Qualifications in Partial Identification》
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作者：
Hiroaki Kaido, Francesca Molinari, and J\"org Stoye
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最新提交年份：
2021
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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。
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英文摘要：
The literature on stochastic programming typically restricts attention to problems that fulfill constraint qualifications. The literature on estimation and inference under partial identification frequently restricts the geometry of identified sets with diverse high-level assumptions. These superficially appear to be different approaches to closely related problems. We extensively analyze their relation. Among other things, we show that for partial identification through pure moment inequalities, numerous assumptions from the literature essentially coincide with the Mangasarian-Fromowitz constraint qualification. This clarifies the relation between well-known contributions, including within econometrics, and elucidates stringency, as well as ease of verification, of some high-level assumptions in seminal papers.
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PDF链接：
https://arxiv.org/pdf/1908.09103
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