摘要翻译：
这项研究比较了ARCH检验的统计特性，这些检验对存在错误规定的条件均值是稳健的。本研究采用的方法是基于条件均值的两个非参数回归。首先是使用Nadayara-Watson核回归的ARCH测试。二是采用多项式逼近回归的ARCH检验。这两种方法不需要条件均值的规定，可以适应各种先验未知的非线性模型。因此，它们对错误指定的条件均值模型具有鲁棒性。仿真结果表明，对于各种非线性模型，基于多项式逼近回归方法的ARCH检验比基于Nadayara-Watson核回归方法的ARCH检验具有更好的统计特性。
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英文标题：
《Robust tests for ARCH in the presence of the misspecified conditional
  mean: A comparison of nonparametric approches》
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作者：
Daiki Maki and Yasushi Ota
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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 study compares statistical properties of ARCH tests that are robust to the presence of the misspecified conditional mean. The approaches employed in this study are based on two nonparametric regressions for the conditional mean. First is the ARCH test using Nadayara-Watson kernel regression. Second is the ARCH test using the polynomial approximation regression. The two approaches do not require specification of the conditional mean and can adapt to various nonlinear models, which are unknown a priori. Accordingly, they are robust to misspecified conditional mean models. Simulation results show that ARCH tests based on the polynomial approximation regression approach have better statistical properties than ARCH tests using Nadayara-Watson kernel regression approach for various nonlinear models.
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PDF链接：
https://arxiv.org/pdf/1907.12752