A Nonparametric Test for I(0)
提出一种非参数检验方法，用于判断时间序列是否为I(0)（即平稳或差分平稳），无需对频谱行为做假设，并通过蒙特卡洛模拟和实证数据验证其有效性。
There is frequently interest in testing that a scalar or vector time series is I(0), possibly after first-differencing or other detrending, while the I(0) assumption is also taken for granted in autocorrelation-consistent variance estimation. We propose a test for I(0) against fractional alternatives. The test is nonparametric, and indeed makes no assumptions on spectral behaviour away from zero frequency. It seems likely to have good efficiency against fractional alternatives, relative to other nonparametric tests. The test is given large sample justification, subjected to a Monte Carlo analysis of finite sample behaviour, and applied to various empirical data series.