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st: AW: RE: AW: RE: F-test Stata reg..., robust


From   "Julian Dragendorf" <[email protected]>
To   <[email protected]>
Subject   st: AW: RE: AW: RE: F-test Stata reg..., robust
Date   Fri, 20 Aug 2010 12:10:00 +0200

Thanks for the quick response! 

Below (1) I show the outputs with "reg,..., robust" STATA and (2) EVIEWs
with white hetero-const- st errors. As u see everything is equal except the
f-test! Why?

(1) STATA
						
F(  3,   182)	=	2.42				
Prob > F	=	0.0676				
R-squared	=	0.0596	adjusted R2=	0.04412889		
Root MSE	=	12.535				
						
						
		Robust				
Y	Coef.	Std. Err.	t	P>t	[95% Conf.	Interval]
						
X1	3.487523	2.421257	1.44	0.151	-1.289821
8.264866
X2	-1.118751	2.103527	-0.53	0.595	-5.269187
3.031685
X3	0.305943	0.1843521	1.66	0.099	-0.0577991
0.6696852
cons	-0.137852	1.45166	-0.09	0.924	-3.0021	2.726396


(2) EVIEWs:

White Heteroskedasticity-Consistent Standard Errors & Covariance

				
	Coefficient	Std. Error	t-Statistic	Prob.  
				
X1	3.487523	2.421257	1.440377	0.1515
X2	-1.118751	2.103527	-0.531845	0.5955
X3	0.305943	0.184352	1.659559	0.0987
C	-0.137852	1.45166	-0.094962	0.9244
				
R-squared			0.05963	
Adjusted R-squared	0.044129	    S.D. dependent var
12.82129
S.E. of regression	12.5352	    Akaike info criterion	7.91623
Sum squared resid		28597.9	    Schwarz criterion
7.985601
Log likelihood		-732.2094	    Hannan-Quinn criter.
7.944341
F-statistic			3.846913	     Durbin-Watson stat
1.868423
Prob(F-statistic)		0.010593			


-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von DE SOUZA Eric
Gesendet: Freitag, 20. August 2010 11:58
An: '[email protected]'
Betreff: st: RE: AW: RE: F-test Stata reg..., robust

Which standard errors don't change?
In the example below, without robust you get the OLS standard errors for the
coefficients, whereas with the robust option you get the robustified
standard errors:
. webuse auto

. reg mpg weight foreign price

      Source |       SS       df       MS              Number of obs =
74
-------------+------------------------------           F(  3,    70) =
45.93
       Model |  1620.30716     3  540.102388           Prob > F      =
0.0000
    Residual |  823.152295    70  11.7593185           R-squared     =
0.6631
-------------+------------------------------           Adj R-squared =
0.6487
       Total |  2443.45946    73  33.4720474           Root MSE      =
3.4292

----------------------------------------------------------------------------
--
         mpg |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
      weight |  -.0067758   .0009048    -7.49   0.000    -.0085805
-.0049712
     foreign |  -1.855891   1.289063    -1.44   0.154    -4.426846
.7150641
       price |   .0000566   .0001922     0.29   0.769    -.0003268
.00044
       _cons |   41.95948   2.377726    17.65   0.000     37.21725
46.7017
----------------------------------------------------------------------------
--

. reg mpg weight foreign price, robust

Linear regression                                      Number of obs =
74
                                                       F(  3,    70) =
62.39
                                                       Prob > F      =
0.0000
                                                       R-squared     =
0.6631
                                                       Root MSE      =
3.4292

----------------------------------------------------------------------------
--
             |               Robust
         mpg |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
      weight |  -.0067758   .0006777   -10.00   0.000    -.0081274
-.0054243
     foreign |  -1.855891   1.419701    -1.31   0.195    -4.687396
.9756145
       price |   .0000566   .0002061     0.27   0.784    -.0003545
.0004677
       _cons |   41.95948   1.733047    24.21   0.000     38.50302
45.41593
----------------------------------------------------------------------------
--

Eric de Souza
Professor, European Economic Studies
Director, Library
College of Europe
Dyver 11
BE-8000 Brugge (Bruges)
Belgium
Tel.: (32.(0)50) 47 72 23
Fax:: (32 (0)50) 47 71 10
http://www.coleurope.eu

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Julian Dragendorf
Sent: 20 August 2010 11:52
To: [email protected]
Subject: st: AW: RE: F-test Stata reg..., robust

Thx! But then the St. Errors should change also! or? But st. errors stay the
same! And MSS and RSS are not displayed automatically but used a command to
get the information "display e(mss)"! 

-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von DE SOUZA Eric
Gesendet: Freitag, 20. August 2010 11:24
An: '[email protected]'
Betreff: st: RE: F-test Stata reg..., robust

Robustification only affects the variances and the covariances.
Coefficients stay the same, which means that Model SS, Residual SS and d.f.
remains the same.
But the F-test should take into account the new variances and covariances
calculated under robustification.

Why don't you post some output using a commonly accessible file such as
auto.dta webuse auto will get you the file

By the way, Stata v10.1 does not produce the model ss, residual ss, under
robustification.  


Eric de Souza
College of Europe
Brugge (Bruges)
Belgium

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Julian Dragendorf
Sent: 20 August 2010 11:13
To: [email protected]
Subject: st: F-test Stata reg..., robust

Hello! 

I have a short question regarding the F-test for STATA 10.0 and EVIEWs 6.0
when using a simple OLS multiple regression model: If I use the Stata
command "reg..., robust" to estimate a multiple regression model I get the
same coef., std. err, t-stat and r2 as if I use Eviews OLS regression with
white heteroskedasticity-const std error & covariance. However, the only
thing which differs is the F-test which is higher for Eviews than for Stata.
When I use the Model SS, Residual SS and the respective d.f. of model
estimated with STATA I can calculate the F-test manually whereby I get out
the same F-test as in Eviews. Does somebody know why there is a difference
in the F-test but everything else is equal when using STATA (reg...,robust)
and Eviews (reg with white hetero. consist. st errors)?

Many thanks!



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