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Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities

机译:满足有限数量的矩不等式的部分识别参数的置信集

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摘要

This paper proposes a computationally simple way to construct confidence sets for a parameter of interest in models comprised of moment inequalities. Building on results from the literature on multivariate onesided tests, I show how to test the hypothesis that any particular parameter value is logically consistent with the maintained moment inequalities. The associated test statistic has an asymptotic chi-bar-square distribution, and can be inverted to construct an asymptotic confidence set for the parameter of interest, even if that parameter is only partially identified. Critical values for the test are easily computed, and a Monte Carlo study demonstrates implementation and finite sample performance.
机译:本文提出了一种计算简单的方法来构造由矩不等式组成的模型中感兴趣参数的置信集。基于多元单边检验文献的结果,我展示了如何检验以下假设:任何特定参数值在逻辑上都与维持的力矩不等式保持一致。关联的测试统计量具有渐近的卡方分布,即使该参数仅被部分识别,也可以对其进行反转以构造感兴趣参数的渐进置信度集。测试的临界值很容易计算,Monte Carlo研究证明了实现方法和有限的样品性能。

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