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首页> 外文期刊>Journal of Forecasting >Testing for (Common) Stochastic Trends in the Presence of Structural Breaks
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Testing for (Common) Stochastic Trends in the Presence of Structural Breaks

机译:在存在结构性断裂的情况下测试(共同)随机趋势

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摘要

This paper considers the problem of testing for the presence of stochastic trends in multivariate time series with structural beaks. The breakpoints are assumed to be known. The testing framework is the multivariate locally best invariant test and the common trend test of Nyblom and Harvey (2000). The asymptotic distributions of the test statistics are derived under a specification of the deterministic component which allows for structural breaks. Asymptotic critical values are provided for the case of a single breakpoint. A modified statistic is then proposed, the asymptotic distribution of which is independent of the breakpoint location and belongs to the Cramer-von Mises family. This modification is particularly advantageous in the case of multiple breakpoints. It is also shown that the asymptotic distributions of the test statistics are unchanged when seasonal dummy variables and/or weakly dependent exogenous regressors are included. Finally, as an example, the tests are applied to UK macroeconomic data and to data on road casualties in Great Britain.
机译:本文考虑了在带有结构喙的多元时间序列中检验随机趋势的存在性的问题。假定断点是已知的。检验框架是多元局部最佳不变检验和Nyblom和Harvey(2000)的共同趋势检验。检验统计量的渐近分布是在确定性成分的规范下得出的,该成分允许结构性破坏。对于单个断点,提供了渐近临界值。然后提出了一种改进的统计量,其渐近分布与断点位置无关,属于Cramer-von Mises家族。在多个断点的情况下,这种修改是特别有利的。还表明,当包括季节性虚拟变量和/或弱相关外生回归变量时,检验统计量的渐近分布不变。最后,例如,将测试应用于英国宏观经济数据和英国道路伤亡数据。

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