Why should augmented Dickey-Fuller tests always be used when performing econometric analysis?
A)the augmented tests allow for more degrees of freedom
B)so we can test hypotheses using a t-distribution
C)since no assumptions about the sign of $\rho$ are needed to perform a one-tailed test
D)to confirm that error terms are not autocorrelated

Question

Quizplus · Accepted Answer

Augmented Dickey-Fuller tests are used to test for stationarity in time series data. Stationarity is an important assumption for many econometric analyses, as it ensures that the error terms are not autocorrelated. Therefore, it is important to use augmented Dickey-Fuller tests to confirm stationarity and avoid biased and inaccurate results.

Why Should Augmented Dickey-Fuller Tests Always Be Used When Performing ρ\rhoρ

Why Should Augmented Dickey-Fuller Tests Always Be Used When Performing $\rho$