Seamus,
Try saving your residuals after each procedure and comparing them.
If they appear to be the same, then examine them with the Durbin
alternative, which should reduce to a DW d. Compare the significance
level of both.
If they are the same, examine the formula in the ado files. See if they
are the same.
- Robert Yaffee
Robert A. Yaffee, Ph.D.
Research Professor
Shirley M. Ehrenkranz
School of Social Work
New York University
home address:
Apt 19-W
2100 Linwood Ave.
Fort Lee, NJ
07024-3171
Phone: 201-242-3824
Fax: 201-242-3825
[email protected]
----- Original Message -----
From: "Coffey, Seamus" <[email protected]>
Date: Friday, February 17, 2006 3:18 pm
Subject: st: Using dwstat after regress and dfuller
> Can someone explain why dwstat returns different values (in Stata
> 8.0) after
> the dfuller and regress commands for what are the equivalent
> regressions?
> The results are shown below and you can see that the d value is
> 1.996121after dfuller and is 1.314681 after regress.
>
> I know the d statistic is not appropriate for an autogregressive
> model but
> surely the computed value should be the same.
>
> Thanks
>
>
> . dfuller gdp, trend regress
>
> Dickey-Fuller test for unit root Number of obs =
> 87
>
> ---------- Interpolated Dickey-Fuller
> ---------
> Test 1% Critical 5% Critical 10%
> Critical
> Statistic Value Value
> Value
> --------------------------------------------------------------------
> --------
> --
> Z(t) -1.625 -4.069 -3.463
> -3.158
> --------------------------------------------------------------------
> --------
> --
> * MacKinnon approximate p-value for Z(t) = 0.7815
> --------------------------------------------------------------------
> --------
> --
> D.gdp | Coef. Std. Err. t P>|t| [95% Conf.
> Interval]
> -------------+------------------------------------------------------
> --------
> --
> gdp |
> L1 | -.0603169 .0371113 -1.63 0.108 -.1341169
> .013483
> _trend | 1.477641 .9172438 1.61 0.111 -.346399
> 3.301681
> _cons | 190.3836 103.5257 1.84 0.069 -15.48857
> 396.2559
> --------------------------------------------------------------------
> --------
> --
> . dwstat
> Durbin-Watson d-statistic( 3, 87) = 1.996121
>
> . regress D.gdp L.gdp n
> Source | SS df MS Number of
> obs =
> 87
> -------------+------------------------------ F( 2,
> 84) =
> 1.32
> Model | 3388.93239 2 1694.4662 Prob > F
> =
> 0.2721
> Residual | 107661.688 84 1281.68677 R-squared
> =
> 0.0305
> -------------+------------------------------ Adj R-
> squared =
> 0.0074
> Total | 111050.621 86 1291.28629 Root MSE
> =
> 35.801
> --------------------------------------------------------------------
> --------
> --
> D.gdp | Coef. Std. Err. t P>|t| [95% Conf.
> Interval]
> -------------+------------------------------------------------------
> --------
> --
> gdp |
> L1 | -.0603169 .0371113 -1.63 0.108 -.1341169
> .013483
> n | 1.477641 .9172438 1.61 0.111 -.346399
> 3.301681
> _cons | 190.3836 103.5257 1.84 0.069 -15.48857
> 396.2559
> --------------------------------------------------------------------
> --------
> --
> . dwstat
> Durbin-Watson d-statistic( 3, 87) = 1.314681
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
