Ilker
As a very crude solution, you could try something like
* do-file begins here
set more off
* Load the data
sysuse grunfeld, clear
matrix tval=J(2,2,.)
matrix colnames tval = tvalue modNr
* Loop over all models (neglected here) and store the
* results of interest (e.g. tval):
tsset fn yr, yearly
xtreg I F, fe
matrix tval[1,1] = _b[F]/_se[F]
matrix tval[1,2] = 1
xtreg I F C, fe
matrix tval[2,1] = _b[F]/_se[F]
matrix tval[2,2] = 2
* create a variable from the matrix and drop the
drop _all
set obs 2 // number of rows in J
svmat tval, names(col)
* only keep the models which are of interest
drop if tval<10
* do-file ends here
Like this you get a list with all interesting models.
If your main interest lays in obtaining the relevant variables in the
model you should probably be better off using -stepwise- together with
-regress- after having manually performed the within transformation.
I hope this helps.
Kind regards,
Ingo
On 4/24/06, Marcello Pagano <[email protected]> wrote:
> For Ilker:
>
> Dear Statalist
>
> I am currently running thousands of fixed effect regressions with panel
> data time series but the independent variable I am interested in is same
> across all regressions. Right now I am manually reviewing all results
> and trying to get the significant ones at alpha= 0.05 level. This
> process is taking a lot of time so is there any way to report only the
> results that satisfy this significance level only for that variable? For
> example I have 20 independent variables (1 to 20) and I am running all
> possible combinations but I only care about variable 4. How can I only
> see the results that variable 4 are significant in? I would really
> appreciate any help on this problem. Thanks in advance....
>
> Ilker Kaya
>
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