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Re: st: Using dwstat after regress and dfuller


From   Robert A Yaffee <[email protected]>
To   [email protected]
Subject   Re: st: Using dwstat after regress and dfuller
Date   Fri, 17 Feb 2006 21:05:43 -0500

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
> 
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