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An instrumental variable approach for tests of unit roots and seasonal unit roots in asymmetric time series models

机译:一种工具变量方法,用于测试非对称时间序列模型中的单位根和季节单位根

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摘要

The unit root tests of Caner and Hansen (Econometrica 69 (2001) 1555) for asymmetric time series models based on the ordinary least squares estimator (OLSE) have asymptotic null distributions that depend on parameters of asymmetry. We resolve this parameter dependency by adopting the instrumental variable estimation of Shin and Lee (J. Business & Economic Statist. 19 (2001) 233) and the recursive mean adjustment of Shin and So (J. Time Series Anal. 22 (2001b) 595). If the threshold parameter is known, the limiting null distribution of the proposed Wald test does not depend on any nuisance parameter and is chi-squared. If the threshold parameter is unknown and is estimated from data, then under threshold effect, the limiting null distributions of the proposed Wald tests are chi-squared as those for model with known threshold parameter whereas, under no threshold effect, they are chi-squared only conditionally on the weak limit of the estimated threshold parameter. Our Wald tests extend to seasonalmodels retaining the chi-square asymptotics regardless of the parameter of seasonality, which is not the case of the OLSE-based tests. Moreover, the proposed tests can be modified into one-sided Wald tests which are significantly more powerful than thetests of Caner and Hansen (2001). We apply our method to the monthly US unemployment rate and find some evidences of seasonal unit roots, suggesting nonstationarity rather than the strong stationariry of Caner and Hansen (2001).
机译:基于普通最小二乘估计器(OLSE)的非对称时间序列模型的Caner和Hansen(Econometrica 69(2001)1555)的单位根检验具有取决于不对称参数的渐近零分布。我们通过采用Shin和Lee(J. Business&Economic Statist。19(2001)233)和Shin and So(J. Time Series Anal。22(2001b)595)的递归均值调整来解决此参数依赖性。 )。如果阈值参数已知,则提出的Wald检验的极限零分布不依赖于任何令人讨厌的参数,而是卡方。如果阈值参数是未知的并且是从数据中估计的,则在阈值作用下,拟议的Wald检验的极限零分布与具有已知阈值参数的模型的极限零分布是卡方的,而在没有阈值影响的情况下,它们是卡方的仅在条件上取决于估计的阈值参数的弱极限。我们的Wald检验扩展到保留卡方渐近性的季节性模型,而与季节性参数无关,这不是基于OLSE的检验的情况。此外,建议的测试可以修改为单面Wald测试,其功能比Caner和Hansen(2001)的测试强大得多。我们将我们的方法应用于美国每月的失业率,并找到一些季节性单位根源的证据,这表明非平稳性而非Caner和Hansen(2001)的强劲平稳性。

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