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摘要翻译：
本文给出了半参数条件均值模型的一致异方差鲁棒拉格朗日乘子(LM)型规格检验。一致性是通过使用级数方法将一个条件矩限制转化为越来越多的无条件矩限制来实现的。所提出的检验统计量计算简单，且在零值下是渐近标准正态。与以往文献中基于级数的参数模型规格检验相比，我依赖于级数估计量的投影性质，得到了不同的检验统计量的归一化。与古普塔最近的测试（2018年）相比，我使用了一种不同的方法来解释异方差性。我用蒙特卡罗研究证明，与现有的测试相比，我的测试具有优越的有限样本性能。我将该测试应用于Yatchew and No(2001)的一个半参数汽油需求规范，并没有发现反对它的证据。
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英文标题：
《A Consistent Heteroskedasticity Robust LM Type Specification Test for
Semiparametric Models》
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作者：
Ivan Korolev
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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 develops a consistent heteroskedasticity robust Lagrange Multiplier (LM) type specification test for semiparametric conditional mean models. Consistency is achieved by turning a conditional moment restriction into a growing number of unconditional moment restrictions using series methods. The proposed test statistic is straightforward to compute and is asymptotically standard normal under the null. Compared with the earlier literature on series-based specification tests in parametric models, I rely on the projection property of series estimators and derive a different normalization of the test statistic. Compared with the recent test in Gupta (2018), I use a different way of accounting for heteroskedasticity. I demonstrate using Monte Carlo studies that my test has superior finite sample performance compared with the existing tests. I apply the test to one of the semiparametric gasoline demand specifications from Yatchew and No (2001) and find no evidence against it.
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PDF链接：
https://arxiv.org/pdf/1810.07620
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