I did not do much in programming. I found that the following approach also
works.
After I demean the variables, run a pooled OLS regression including group
dummies. The code is similar to the following:
xi: i.head
xi: regress newmpg newlen i.head
Thanks again, May and Mark.
Alice
-----Original Message-----
From: [email protected]
[mailto:[email protected]]On Behalf Of Alice(Libo)
Sun
Sent: Tuesday, September 20, 2005 10:41 AM
To: [email protected]
Subject: RE: st: Panel FE vs. pooled OLS with demeaned variables
Thank you so much!
I was wondering how I am going to program with the degree of freedom
adjustment as Mark just pointed out too.
Very much appreciate your help!
Alice
-----Original Message-----
From: [email protected]
[mailto:[email protected]]On Behalf Of May Boggess
Sent: Tuesday, September 20, 2005 10:24 AM
To: [email protected]
Subject: Re: st: Panel FE vs. pooled OLS with demeaned variables
On Tuesday morning, Alice Sun wrote:
>
> I need to run a two-step regression similar to the fixed effect model.
> (Xtreg, fe).
>
> I first replicate the fixed effect results by running pooled OLS with
> demeaned variables (demean by groups). Yet, I got same coefficients, but
> relative larger t statistics.
>
There is a degrees-of-freedom adjustment to be made. Here is an example
that shows how that is done. Here I am primarily interested in the
coefficient, and the standard error of that coefficient, of the
independent variable "length":
clear
sysuse auto
replace length=length/10
tab head
local df = r(r) - 1
sort head
by head: egen mean = mean(mpg)
by head: gen newmpg = mpg-mean
drop mean
by head: egen mean = mean(len)
by head: gen newlen = len-mean
drop mean
regress newmpg newlen
mat b=e(b)
scalar vadj = e(df_r)/(e(N)-1-(e(df_m) + `df'))
matrix V = vadj*e(V)
cap program drop change
program change, eclass
eret post b V
end
change
eret display
xtreg mpg len, i(head) fe
You should find that the last two sets of results show the same
coefficient and standard error for "length".
--May
[email protected]
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