Testing linearity against threshold effects: uniform inference in quantile regression
Testing linearity against threshold effects: uniform inference in quantile regression
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DOI：
10.1007/s10463-013-0418-9
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发表时间：
2014-04-01
影响因子：
1
通讯作者：
Olmo, Jose
中科院分区：
文献类型：
--
作者：
Galvao, Antonio F.;Kato, Kengo;Olmo, Jose
本文在分位数回归框架中对阈值效应的线性进行了统一检验。该测试基于Wald过程在分位数和阈值参数空间上的最大值。建立了平稳弱相关过程检验统计量的极限零分布，并提出了一种近似临界值的模拟方法。所提出的仿真方法使测试易于实现。蒙特卡罗实验表明，该方法对非线性阈值模型具有良好的规模和合理的能力。
This paper develops a uniform test of linearity against threshold effects in the quantile regression framework. The test is based on the supremum of the Wald process over the space of quantile and threshold parameters. We establish the limiting null distribution of the test statistic for stationary weakly dependent processes, and propose a simulation method to approximate the critical values. The proposed simulation method makes the test easy to implement. Monte Carlo experiments show that the proposed test has good size and reasonable power against non-linear threshold models.