A Test Against Spurious Long Memory
提出一种频域检验统计量，用于区分平稳长记忆过程与受制度转换或平滑趋势影响的时间序列，适用于非高斯或条件异方差数据，无需指定备择假设下的趋势形式或制度数量。
This paper proposes a test statistic for the null hypothesis that a given time series is a stationary long-memory process against the alternative hypothesis that it is affected by regime change or a smoothly varying trend. The proposed test is in the frequency domain and is based on the derivatives of the profiled local Whittle likelihood function in a degenerating neighborhood of the origin. The assumptions used are mild, allowing for non-Gaussianity or conditional heteroscedasticity. The resulting null limiting distribution is free of nuisance parameters and can be easily simulated. Furthermore, the test is straightforward to implement; in particular, it does not require specifying the form of the trend or the number of different regimes under the alternative hypothesis. Monte Carlo simulation shows that the test has decent size and power properties. The article also considers three empirical applications to illustrate the usefulness of the test. This article has supplementary material online.