摘要翻译:
具有内生变量的高维线性模型在最近的计量经济学文献中发挥着越来越重要的作用。在这项工作中,我们允许具有多个内生变量和多个工具变量的模型来实现辨识。由于第二阶段的高维性,构造具有渐近正确覆盖的诚实置信域是一个不简单的问题。我们的主要贡献是提出可以实现这一目标的估计量和置信域。该方法依赖于对干扰参数具有附加正交性质的矩条件。此外,高维干扰参数的估计是通过新的关键程序进行的。为了得到同时有效的置信域,我们使用乘数引导程序来计算临界值并确定其有效性。
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英文标题:
《Simultaneous Confidence Intervals for High-dimensional Linear Models
with Many Endogenous Variables》
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作者:
Alexandre Belloni, Christian Hansen and Whitney Newey
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最新提交年份:
2019
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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:
High-dimensional linear models with endogenous variables play an increasingly important role in recent econometric literature. In this work we allow for models with many endogenous variables and many instrument variables to achieve identification. Because of the high-dimensionality in the second stage, constructing honest confidence regions with asymptotically correct coverage is non-trivial. Our main contribution is to propose estimators and confidence regions that would achieve that. The approach relies on moment conditions that have an additional orthogonal property with respect to nuisance parameters. Moreover, estimation of high-dimension nuisance parameters is carried out via new pivotal procedures. In order to achieve simultaneously valid confidence regions we use a multiplier bootstrap procedure to compute critical values and establish its validity.
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PDF链接:
https://arxiv.org/pdf/1712.08102