Talk:Augmented Dickey–Fuller test

message: Hi! The bottom line of the article says that 
if the test statistic is greater [...] than the critical value, then the null hypothesis of γ = 0 is rejected and no unit root is present.
 
Under Examples, it says 
 
This is more negative than the tabulated critical value of −3.50, so at the 95 per cent level the null hypothesis of a unit root will be rejected.
So, in the main article, the null is rejected if the test statistic is greater than the critical value, in the example it is rejected if it is smaller than the critical value. I think that the example is right...  —Preceding unsigned comment added by 193.103.207.10 (talk) 14:27, 30 September 2009 (UTC)
replies: text: The crucial factor is not whether the numbers are positive or negative but whether they are greater or smaller than the relevant tabulated critical values. Karina.l.k 12:44, 26 April 2007 (UTC)

text: I stuck to Greene but I agree that this formulation is sloppy, since one can also wrongly fail to reject the null or wrongly reject the null (Type I and Type II errors). I've changed it now, hope that it's better. Feel free to edit further as I think this example section could and should be expanded.Karina.l.k 08:05, 27 May 2007 (UTC)

text: Yes you are right, if the model is written with variables in levels, the null hypothese is gamma=1 but if the model is written in difference (as in this article), then the null hypothese becomes gamma=0.EtudiantEco  —Preceding comment was added at 22:38, 17 February 2008 (UTC)

text: This issue (and a few others) now tidied up.  —Preceding unsigned comment added by 203.20.253.5 (talk) 01:52, 23 April 2008 (UTC)

message: Does ADF test regression (whose lag length (that is optimal) obtained via SBC or AIC after performing ADF test when a given max lag length) remove all autcorrelation? 
(Do we really know with 100% certainty that ADF-resulted-regression has no autocorrelation?)
In detail:
The goal of ADF is to test whether we have unit root or not.
DF (Dickey-Fuller) test equation (regression equation) may include autocorrelation, and its result is not so reliable.
In ADF, additional lags of the differenced variable are added to the right of the ADF regression equation. These added lags of the differenced variable reduces autocorrelation.
Now, assume that we are performing ADF test when max lag length (say 14) is given (or assume max lag length (say 14) is the obtained from Schwetz's formula; as in Eviews).
If ADF test results in optimal lag length of 5 (via AIC or SBC criterion) in ADF test regression equation, then do we really know that the ADF equation with optimal lag length of 5  includes no autocorrelation in residuals of the ADF regression (with 5 lengths)?
OR, do we have to check that the ADF test regression equation with optimal lag length of 5 (that we found via SBC or AIC during the execution of ADF test) includes no autocorrelation by the help of some autocorrelation tests?88.226.65.125 (talk) 10:05, 28 December 2014 (UTC)
thread_title:  A missing in the article 

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