RE: st: RE: Different results for Fixed and Random Effects models Using STATA and SAS

["Nick Cox" <n.j.cox@durham.ac.uk>]

Thanks for this. Those with expert knowledge of knowledge of fixed and random effects models (not me) should be in a better position to comment or to ask for specific extras.  

You should probably be using an extra dummy for North-East England.... 

Nick 
n.j.cox@durham.ac.uk 

Talal

Dear Nick,

Thanks for your comment and sorry for my shallow explanations of the problem. Below is the command and result comparison between SAS and STATA.
I have slightly unbalaced data for 4 regional areas of GB.


a-	For Fixed Effect:

SAS:

proc reg data=chapter3.all_area;
Model Ln_qdt = Ln_qdt2 Ln_vkm Ln_income Ln_F deregulation_dummy Time_Trend London_dummy Mets_ dummy Scotland_ dummy Wales_ dummy;
test  London_dv = Mets_dv = Scotland_dv = Wales_dv = 0 ;
run;


STATA:

regress   Ln_qdt Ln_qdt2 Ln_vkm Ln_income Ln_F deregulation_dummy Time_Trend London_dummy Mets_ dummy Scotland_ dummy Wales_ dummy




b-	For Random Effect:

SAS:

proc panel data=chapter3.all_area;
ID area year;
Model Ln_qdt = Ln_qdt2 Ln_vkm Ln_income Ln_F deregulation_dummy Time_Trend / RANONE BP VCOMP=WK
;
run;
                        

STATA:

iis area
 xtreg qdt Ln_qdt2 Ln_vkm Ln_income Ln_F deregulation_dummy Time_Trend, re theta

	SAS		
Model	FE	RE		FE (STATA) RE(STATA)
 	Coeff.	Coeff.		Coeff.	Coeff.
 					
Ln F	-.108	-0.09892		-.108	-0.06321
Ln VKM	.114	0.135992		.115	0.082707
Ln Income	-.560	-0.52503		-.566	-0.297
Ln Qdt-1	.695	0.747298		.692	0.924061
Der. DV	-.046	-0.04975		-.047	-0.05055
TT	.011	0.010877		.011	0.00887
 					
Mets	.196			0.198	
Scot	.153			0.154	
Wales	-.023			-0.023	
constant	5.999	 	 	5.908	 
 					
F	        3624.282		3618.020	
R2 (Adj.)	.997	0.973		0.9969	0.9967
Durbin-Watson	1.703	 	 	 	 
 					
(Incremental) F	5.57 (0.0015)	5.57 (0.0015)	
Breusch Pagan Test	0.00 (0.9781)	0.00 (0.9779)	
Hausman Test	2.34 (0.8859)	20.16 (0.0026)	


--- On Mon, 10/5/10, Nick Cox <n.j.cox@durham.ac.uk> wrote:

> From: Nick Cox <n.j.cox@durham.ac.uk>
> Subject: st: RE: Different results for Fixed and Random Effects models Using STATA and SAS
> To: statalist@hsphsun2.harvard.edu
> Date: Monday, 10 May, 2010, 10:34
> This is only a small distance away
> from "I got different results from different programs and
> don't understand why". People who know about these commands
> need to see exactly what you typed in both programs so that
> they can be sure that the commands are exactly equivalent.
> They also would find it difficult to comment unless your
> results are phrased in terms of datasets that everyone can
> access. 
> 
> Nick 
> n.j.cox@durham.ac.uk
> 
> 
> Talal
> 
> I have estimated Fixed and Random Effects models for panal
> data which are slightly unbalanced using SAS and STATA
> 
> the two softwa estimated totally different parametres for
> Ranndom Effects Model, and slightly different one for Fixed
> Effects one res.
> 
> Is this due to diffrent estimation approches? What are
> these since I have to report them on my study?
> 
> For Hausman test: I also got major differences between the
> two softwares.
> 
> Is this due to diffrent estimation approches too? What are
> these?
> 
> Is the 2 software deals with unbalanced data in different
> ways?
> 
> I am very thankful for any answers.
> 
> *
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> *   http://www.ats.ucla.edu/stat/stata/
> 


      

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