摘要翻译：
本文探讨了模拟矩对基于矩不等式的推理方法性能的影响。常用的参数置信度集是准则函数的水平集，其边界点可能以不规则的方式依赖于样本矩。由于这一特性，仿真误差可以以非标准的方式影响推理的性能。特别地，由于模拟误差而产生的（一阶）偏差可能保留在置信度集的估计边界中。通过Monte Carlo实验，我们证明了模拟误差会显著降低小样本下置信集的复盖概率。当不等式限制数较多时，尺寸畸变尤为严重。这些结果突出了在矩不等式模型中由于仿真误差而忽略采样变化的危险。当在矩不等式模型中使用预测变量时，也会出现类似的问题。我们提出了一种基于正则化参数空间矩交的方法来正确校正这些变化，并在理论和实践中证明了该方法的有效性。
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英文标题：
《Moment Inequalities in the Context of Simulated and Predicted Variables》
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作者：
Hiroaki Kaido, Jiaxuan Li, Marc Rysman
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最新提交年份：
2018
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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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一级分类：Statistics        统计学
二级分类：Computation        计算
分类描述：Algorithms, Simulation, Visualization
算法、模拟、可视化
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英文摘要：
  This paper explores the effects of simulated moments on the performance of inference methods based on moment inequalities. Commonly used confidence sets for parameters are level sets of criterion functions whose boundary points may depend on sample moments in an irregular manner. Due to this feature, simulation errors can affect the performance of inference in non-standard ways. In particular, a (first-order) bias due to the simulation errors may remain in the estimated boundary of the confidence set. We demonstrate, through Monte Carlo experiments, that simulation errors can significantly reduce the coverage probabilities of confidence sets in small samples. The size distortion is particularly severe when the number of inequality restrictions is large. These results highlight the danger of ignoring the sampling variations due to the simulation errors in moment inequality models. Similar issues arise when using predicted variables in moment inequalities models. We propose a method for properly correcting for these variations based on regularizing the intersection of moments in parameter space, and we show that our proposed method performs well theoretically and in practice.
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PDF链接：
https://arxiv.org/pdf/1804.03674