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The asymptotic size and power of the augmented Dickey-Fuller test for a unit root

机译:单位根的增强Dickey-Fuller检验的渐近大小和幂

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It is shown that the limiting distribution of the augmented Dickey-Fuller (ADF) test under the null hypothesis of a unit root is valid under a very general set of assumptions that goes far beyond the linear AR() process assumption typically imposed. In essence, all that is required is that the error process driving the random walk possesses a continuous spectral density that is strictly positive. Furthermore, under the same weak assumptions, the limiting distribution of the ADF test is derived under the alternative of stationarity, and a theoretical explanation is given for the well-known empirical fact that the test's power is a decreasing function of the chosen autoregressive order p. The intuitive reason for the reduced power of the ADF test is that, as p tends to infinity, the p regressors become asymptotically collinear.
机译:结果表明,在单位根零假设下的增强迪基-富勒(ADF)检验的极限分布在一组非常通用的假设下有效,该假设远远超出了通常采用的线性AR()过程假设。本质上,所需要做的只是驱动随机游走的误差过程具有严格为正的连续光谱密度。此外,在相同的弱假设下,ADF检验的极限分布是在平稳性的替代下得出的,并对众所周知的经验事实进行了理论解释,即检验的功效是所选自回归阶数p的递减函数。 。 ADF测试功率降低的直观原因是,随着p趋于无穷大,p回归变量渐近地共线。

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