摘要翻译：
本文提出了非参数工具回归中约束规范的几种检验方法。基于级数估计量，建立了检验统计量，允许对参数或非参数规范的一般模型进行检验，以及对回归向量的外源性进行检验。在正确规范下，导出了试验的渐近分布，并证明了它们对任何替代模型的一致性。在一系列局部交替假设下，导出了检验的渐近分布。此外，在一类备选方案上建立了一致一致性，这些备选方案到零假设的距离随着样本量的增加而适当地缩小。蒙特卡罗研究检验了检验统计量的有限样本性能。
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英文标题：
《Goodness-of-Fit Tests based on Series Estimators in Nonparametric
  Instrumental Regression》
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作者：
Christoph Breunig
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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：
  This paper proposes several tests of restricted specification in nonparametric instrumental regression. Based on series estimators, test statistics are established that allow for tests of the general model against a parametric or nonparametric specification as well as a test of exogeneity of the vector of regressors. The tests' asymptotic distributions under correct specification are derived and their consistency against any alternative model is shown. Under a sequence of local alternative hypotheses, the asymptotic distributions of the tests is derived. Moreover, uniform consistency is established over a class of alternatives whose distance to the null hypothesis shrinks appropriately as the sample size increases. A Monte Carlo study examines finite sample performance of the test statistics.
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PDF链接：
https://arxiv.org/pdf/1909.10133