Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Chiara Mussida <[email protected]> |

To |
[email protected] |

Subject |
Re: st: loop |

Date |
Fri, 30 Mar 2012 10:08:41 +0200 |

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) * * 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/

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

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

- Prev by Date:
**Re: st: gformula** - Next by Date:
**st: Accessing Google Analytics data from withing Stata** - Previous by thread:
**re: st: loop** - Next by thread:
**Re: st: loop** - Index(es):