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摘要翻译：
我们提出了一种新的单位根检验，它利用了单位根模型的局部渐近布朗泛函极限实验中的不变性。不变性结构自然地提出了基于观测增量的等级、它们的平均值和创新的假定参考密度的检验。这些检验是半参数的，因为它们是有效的，即具有正确的（渐近的）大小，而与真正的新息密度无关。对于一个正确指定的参考密度，我们的测试是点最优和几乎有效的。对于任意参考密度，我们建立了一个Chernoff-Savage型结果，即在高斯新息分布下，我们的测试与常用的测试一样好，但在其他新息分布下，如胖尾或倾斜新息分布下，我们的测试的功率有所提高。为了避免非参数估计，我们提出了一个简化版本的检验，除了Chernoff-Savage结果，我们只能通过模拟来证明，它具有相同的渐近性质。
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英文标题：
《Semiparametrically Point-Optimal Hybrid Rank Tests for Unit Roots》
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作者：
Bo Zhou, Ramon van den Akker and Bas J.M. Werker
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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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英文摘要：
We propose a new class of unit root tests that exploits invariance properties in the Locally Asymptotically Brownian Functional limit experiment associated to the unit root model. The invariance structures naturally suggest tests that are based on the ranks of the increments of the observations, their average, and an assumed reference density for the innovations. The tests are semiparametric in the sense that they are valid, i.e., have the correct (asymptotic) size, irrespective of the true innovation density. For a correctly specified reference density, our test is point-optimal and nearly efficient. For arbitrary reference densities, we establish a Chernoff-Savage type result, i.e., our test performs as well as commonly used tests under Gaussian innovations but has improved power under other, e.g., fat-tailed or skewed, innovation distributions. To avoid nonparametric estimation, we propose a simplified version of our test that exhibits the same asymptotic properties, except for the Chernoff-Savage result that we are only able to demonstrate by means of simulations.
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PDF链接：
https://arxiv.org/pdf/1806.09304
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