论文标题
单位根测试以趋势缓慢变化
Unit Root Testing with Slowly Varying Trends
论文作者
论文摘要
为时间序列提出了单位根测试，具有一般的非线性确定性趋势分量。结果表明，重叠块的合并OLS估计器渐近地滤除了满足某些Lipschitz条件的任何趋势成分。在固定$ b $和小$ b $块的渐近学下，得出了单位根假设的t统计量的限制分布。滋扰参数校正提供了异方差式测试，并通过预先构成序列相关性。与常规的单位根测试相比，一项蒙特卡洛研究认为缓慢变化的趋势既可以产生良好的尺寸和提高的功率结果。
A unit root test is proposed for time series with a general nonlinear deterministic trend component. It is shown that asymptotically the pooled OLS estimator of overlapping blocks filters out any trend component that satisfies some Lipschitz condition. Under both fixed-$b$ and small-$b$ block asymptotics, the limiting distribution of the t-statistic for the unit root hypothesis is derived. Nuisance parameter corrections provide heteroskedasticity-robust tests, and serial correlation is accounted for by pre-whitening. A Monte Carlo study that considers slowly varying trends yields both good size and improved power results for the proposed tests when compared to conventional unit root tests.
