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Semiparametric error-correction models for cointegration with trends: Pseudo-Gaussian and optimal rank-based tests of the cointegration rank

机译:具有趋势的协整的半参数误差校正模型:伪高斯和协整等级的基于最优等级的检验

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摘要

This paper provides pseudo-Gaussian and locally optimal rank-based tests for the cointegration rank in linear cointegrated error-correction models with common trends and i.i.d. elliptical innovations. The proposed tests are asymptotically distribution-free, hence their validity does not depend on the actual distribution of the innovations. The proposed rank-based tests depend on the choice of scores, associated with a reference density that can freely be chosen. Under appropriate choices they are achieving the semiparametric efficiency bounds; when based on Gaussian scores, they moreover uniformly dominate their pseudo-Gaussian counterparts. Simulations show that the asymptotic analysis provides an accurate approximation to finite-sample behavior. The theoretical results are based on a complete picture of the asymptotic statistical structure of the model under consideration. (C) 2015 Elsevier B.V. All rights reserved.
机译:本文为具有共同趋势和i.d.的线性协整误差校正模型中的协整秩提供了基于伪高斯和局部最优秩的检验。椭圆创新。所提出的测试是渐近无分布的,因此其有效性不取决于创新的实际分布。提议的基于等级的测试取决于分数的选择,以及与可以自由选择的参考密度相关的分数。在适当的选择下,它们达到了半参数效率范围;当基于高斯分数时,它们还统一地支配其伪高斯对应物。仿真表明,渐近分析为有限样本行为提供了准确的近似值。理论结果是基于所考虑模型的渐近统计结构的完整图片。 (C)2015 Elsevier B.V.保留所有权利。

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