摘要翻译：
本文提出了一种在弱假设条件下对各种可能的非线性IV模型进行推断的简单方法。该方法是非渐近的，因为它提供了一个关于拒绝正确零假设的真实概率和名义概率之差的有限样本界。该方法是安德森-鲁宾测试的非学生版本，但动机和分析不同。与传统的Anderson-Rubin检验相比，本文提出的方法不需要限制性分布假设、估计模型的线性或联立方程。它也不需要知道仪器是强还是弱。它不需要测试或估计仪器的强度。该方法可应用于可能是非线性的分位数IV模型，并可用于检验参数IV模型与非参数替代方案之间的关系。无论仪器的强度如何，这里给出的结果在有限的样本中都成立。
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英文标题：
《Non-Asymptotic Inference in Instrumental Variables Estimation》
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作者：
Joel L. Horowitz
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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：Mathematics        数学
二级分类：Statistics Theory        统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类：Statistics        统计学
二级分类：Statistics Theory        统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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英文摘要：
  This paper presents a simple method for carrying out inference in a wide variety of possibly nonlinear IV models under weak assumptions. The method is non-asymptotic in the sense that it provides a finite sample bound on the difference between the true and nominal probabilities of rejecting a correct null hypothesis. The method is a non-Studentized version of the Anderson-Rubin test but is motivated and analyzed differently. In contrast to the conventional Anderson-Rubin test, the method proposed here does not require restrictive distributional assumptions, linearity of the estimated model, or simultaneous equations. Nor does it require knowledge of whether the instruments are strong or weak. It does not require testing or estimating the strength of the instruments. The method can be applied to quantile IV models that may be nonlinear and can be used to test a parametric IV model against a nonparametric alternative. The results presented here hold in finite samples, regardless of the strength of the instruments.
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PDF链接：
https://arxiv.org/pdf/1809.03600