Dear Ben:
It worked and I am very close to the end result. There is still a little problem. In the utput, under each column of coefficients, for each model, I get the general stats (N, F...). Surprisingly, in the column "predicted signs", instead of getting blanks on the ligns corresponding to the general stats, I obtain the general stats of the last model.
I provide the last version of my command:
use measures_all6
regress absence1 common ownership, cluster(name) robust, if name!="MEX" & name!="PER"
est store m1, title(Model 1)
regress absence1 common ownership finance_aggregate, cluster(name) robust, if name!="MEX" & name!="PER"
est store m2, title(Model 2)
tempname b
matrix `b' = e(b)
matrix `b'[1,1] = -999 //neg. sign for common
matrix `b'[1,2] = +999 //pos. sign for ownership
matrix `b'[1,3] = .z //no sign for finance_aggregate
matrix `b'[1,4] = 998 //? for _cons
eret2 matrix signs = `b'
estimates store pred
estout pred m1 m2 using estout_signs, replace substitute(-999.000 - 999.000 + 998.000 ?) cells ("signs(pat (1 0 0)) b(fmt(%9.3f) pat(0)) p(fmt(%9.3f) pattern(0))") stats (N F p r2 r2_a, fmt(%9.0f %9.3f %9.3f %9.3f %9.3f) labels ("Number of observations" "F" "Prob>F" "R-square" "Adjusted R-square")) label varlabels(_cons Constant)
Best regards
Herv�
***********************************************************
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HEC Paris
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>>> [email protected] 03/04/05 8:42 AM >>>
Herv� wrote:
> I refer to a problem I mentioned earlier and which was solved
> by the second solution you proposed originally (the one with
> the program prsign, eclass): in my estout output, I want to
> have the results of two regressions:
>
> regress y var1 var2
> regress y var1 var2 var3.
>
> In the predicted signs column, I need to have the three
> variables var1, var2 and var3, although >the first model only
> uses var1 and var2.
>
> It seems to me that your latest solution (with tempname b) is
> related to only one model.
No, not necessarily. Consider:
sysuse auto
regress price mpg weight
est sto model0
regress price mpg weight foreign
estimates store model1
tempname b
matrix `b' = e(b)
matrix `b'[1,1] = -999 //neg. sign for mpg
matrix `b'[1,2] = +999 //pos. sign for weight
matrix `b'[1,3] = .z //no sign for foreign
matrix `b'[1,4] = 998 //? for _cons
eret2 matrix signs = `b'
estimates store pred
estout pred model0 model1, cells("signs(pat(1 0 0)) b(pat(0))") ///
substitute(-999 - 999 + 998 ?)
ben
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