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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/

**References**:**re: st: loop***From:*Christopher Baum <[email protected]>

**Re: st: loop***From:*Chiara Mussida <[email protected]>

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