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Spurious Relationship of Long Memory Sequences in Presence of Trends Breaks

机译:存在趋势中断时长记忆序列的虚假关系

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This article extends the theoretical analysis of spurious relationship and considers the situation where the deterministic components of the processes generating the individual series are long memory sequences with structural changes. Show it by using the ordinary least squares estimator, the t-statistics become divergent and pseudo correlation. However, two long memory time series having change points can produce spurious regression. In the presence of structural change points, confirm the rate of t-statistic tends to infinity increased with the increase in sample size. Numerical simulation results show that when structural changes are a feature of the data, the presence of spurious relationship is unambiguous. And the spurious regression not only depends on long memory indexes, but also for trend of model is also very sensitive.
机译:本文扩展了对虚假关系的理论分析,并考虑了产生单个序列的过程的确定性成分是具有结构变化的长记忆序列的情况。通过使用普通最小二乘估计器进行显示,t统计量将趋于发散和伪相关。但是,两个具有变化点的长存储时间序列会产生虚假回归。在存在结构变化点的情况下,确认t统计量的趋势倾向于随样本数量的增加而无限增大。数值模拟结果表明,当结构变化是数据的特征时,假性关系的存在是明确的。而虚假回归不仅取决于长存储指标,而且对于模型的趋势也非常敏感。

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