Semiparametric Detection of Changes in Long Range Dependence
提出一种半参数方法检测时间序列长记忆性的变化，使用局部Whittle估计避免模型误设，蒙特卡洛模拟显示有限样本表现良好，并应用于德国通胀率分析。
We consider changes in the degree of persistence of a process when the degree of persistence is characterized as the order of integration of a strongly dependent process. To avoid the risk of incorrectly specifying the data generating process we employ local Whittle estimates which uses only frequencies local to zero. The limit distribution of the test statistic under the null is not standard but it is well known in the literature. A Monte Carlo study shows that this inference procedure performs well in finite samples. We demonstrate the practical utility of these results with an empirical example, where we analyze the inflation rate in Germany for the period 1986–2017.