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Re: st: loop
From
Chiara Mussida <[email protected]>
To
[email protected]
Subject
Re: st: loop
Date
Fri, 30 Mar 2012 11:05:28 +0200
margins, by(fem occupation)
gives me all the values of the interactions between fem#occupation,
therefore a total of 14 interactions (2 genders*7 occupations):
--------------------------------------------------------------------------------
| Delta-method
| Margin Std. Err. z P>|z| [95% Conf. Interval]
---------------+----------------------------------------------------------------
fem#occupation |
0 1 | 2.398703 .0055137 435.04 0.000 2.387896 2.40951
0 2 | 2.122676 .0037042 573.04 0.000 2.115416 2.129936
0 3 | 1.991713 .0042913 464.13 0.000 1.983303 2.000124
0 4 | 1.870097 .0044309 422.06 0.000 1.861413 1.878781
0 5 | 1.84829 .003824 483.34 0.000 1.840795 1.855785
0 6 | 1.906402 .0049577 384.53 0.000 1.896685 1.916119
0 7 | 1.729511 .0051132 338.24 0.000 1.719489 1.739532
1 1 | 2.416612 .0055682 434.00 0.000 2.405698 2.427525
1 2 | 2.176147 .0036372 598.31 0.000 2.169018 2.183276
1 3 | 2.007075 .0042586 471.30 0.000 1.998728 2.015422
1 4 | 1.838439 .0044087 417.00 0.000 1.829798 1.84708
1 5 | 1.862418 .0039549 470.92 0.000 1.854666 1.870169
1 6 | 1.921239 .0050201 382.71 0.000 1.9114 1.931078
1 7 | 1.750215 .0051475 340.01 0.000 1.740127 1.760304
--------------------------------------------------------------------------------
is it possible to gen a new variable for each of the listet interaction?
For example, a variable taking the value 2.398703, etc. This is useful
for me, since therafter I have to compute calculations by using these
interactions.
thanks
Chiara
On 30/03/2012, Chiara Mussida <[email protected]> wrote:
> Thanks Kit,
>
> margins, by(married occupation)
> gives me the product between the Betas of the estimated wage reg and
> the mean value of characteristics for each occupation, for married and
> unmarried. Right?
>
> Chiara
>
> On 29/03/2012, Christopher Baum <[email protected]> wrote:
>> <>
>> Chiara said
>> I wrote a loop for wage regressions to obtain the predicted wages if
>> men are paid as men at each occupation:
>>
>> reg lwage $x if fem==0
>> predict pip if fem==0, xb
>> forvalues k = 1 2 to 7 {
>> predict pip`k' if fem==0 & occ`k'==1, xb
>> }
>> summarize pip, meanonly
>> scalar xMbM=r(mean) /*Predicted wages if men are paid as men*/
>> forvalues k = 1 2 to 7 {
>> summarize pip`k', meanonly
>> scalar xMbM`k'=r(mean) /*Predicted wages if men are paid as men at
>> each occupation*/
>> }
>>
>> I now want to get the xMbM (and also xFbF for females) by occupation.
>> For each occupation I want the product between ythe mean individual
>> charachteristics (xM) and the coefficients (bM). I tried with this
>> loop, but i'm not sure it's the correct one:
>>
>> reg lwage $x if fem==0
>> predict pip if occupation==1, xb
>> forvalues k = 1 {
>> predict pip`k' if fem==0 & occ`k'==1, xb
>> }
>> summarize pip, meanonly
>> scalar xMbM=r(mean) /*Predicted wages if men are paid as men*/
>> forvalues k = 1 {
>> summarize pip`k', meanonly
>> scalar xMbM`k'=r(mean) /*Predicted wages if men are paid as men at
>> each occupation*/
>> }
>>
>> More precisely, i'm not sure this wille give me each product between
>> mean values of characteristics (x, for M or F) and estomated wage
>> equation coefficients (b, for M or F) at each 1...7 occupation.
>>
>>
>>
>>
>> No need for all this manual labor...
>>
>> --------------------
>> webuse nlsw88,clear
>> // lets treat marital status as equivalent of gender, since all people
>> here
>> are women
>> // run regression over all cases so can generate pred wage by mar.stat.
>> and
>> occup.
>> reg wage age collgrad south i.occupation
>> margins, by(married occupation)
>> marginsplot,graph(married) xlab(,angle(90))
>> ---------------------
>>
>> Kit
>>
>>
>> Kit Baum | Boston College Economics & DIW Berlin |
>> http://ideas.repec.org/e/pba1.html
>> An Introduction to Stata Programming |
>> http://www.stata-press.com/books/isp.html
>> An Introduction to Modern Econometrics Using Stata |
>> http://www.stata-press.com/books/imeus.html
>>
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
>>
>
>
> --
> Chiara Mussida
> PhD candidate
> Doctoral school of Economic Policy
> Catholic University, Piacenza (Italy)
>
--
Chiara Mussida
PhD candidate
Doctoral school of Economic Policy
Catholic University, Piacenza (Italy)
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/