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

Efstathios Paparoditis and Dimitris N. Politis

Econometric Reviews, 2018, vol. 37, issue 9, 955-973

Abstract: 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.

Date: 2018
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DOI: 10.1080/00927872.2016.1178887

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