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From |
Chiara Mussida <cmussida@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: meanonly |

Date |
Wed, 11 Apr 2012 14:56:57 +0200 |

i have to use these means, together with the betas of a reg. More precisely, b are betas by occupation, whilst x are the mean of the variables in my dataset. To compute the total gender wage gap i have to compute this for each occupation: pf (xm-xf)bm + xmbm(pm-pf)+pfxf(bm-bf)+xmbm(pf -pm) m and f is for male and female. P are the predicted probability from a mlogit.b as said and asked yesterday are coef from wage reg. Thanks On 11/04/2012, Maarten Buis <maartenlbuis@gmail.com> wrote: > Haven't we been there before? I suggest you give us the complete story > as what is efficient depends on what you want to do with those means. > > On Wed, Apr 11, 2012 at 12:21 PM, Chiara Mussida <cmussida@gmail.com> wrote: >> ok. What is the most efficient way to store the mean as scalars? >> Thanks >> >> On 10/04/2012, Maarten Buis <maartenlbuis@gmail.com> wrote: >>> On Tue, Apr 10, 2012 at 4:23 PM, Chiara Mussida wrote: >>>> su south, meanonly >>>> scalar variable = r(mean) >>>> gives me a scalar for the mean of variable south. Is there a way to >>>> gen scalars for the mean of the variable south by gender and >>>> occupation? I have 7 occupations. For gender i might simplx add if >>>> fem==0 to the above command. For occupation is there a loop? >>> >>> I think you asked that question before. >>> >>> Here are two ways: >>> >>> *------------ begin example ------------- >>> sysuse nlsw88, clear >>> gen byte black = race == 2 if race < 3 >>> >>> reg wage ibn.black#ibn.occupation, nocons >>> table occupation black, c(mean wage) >>> *------------- end example --------------- >>> >>> Hope this helps, >>> Maarten >>> >>> >>> >>> >>> -- >>> -------------------------- >>> Maarten L. Buis >>> Institut fuer Soziologie >>> Universitaet Tuebingen >>> Wilhelmstrasse 36 >>> 72074 Tuebingen >>> Germany >>> >>> >>> http://www.maartenbuis.nl >>> -------------------------- >>> * >>> * 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/ > > > > -- > -------------------------- > Maarten L. Buis > Institut fuer Soziologie > Universitaet Tuebingen > Wilhelmstrasse 36 > 72074 Tuebingen > Germany > > > http://www.maartenbuis.nl > -------------------------- > > * > * 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: meanonly***From:*Maarten Buis <maartenlbuis@gmail.com>

**References**:**st: meanonly***From:*Chiara Mussida <cmussida@gmail.com>

**Re: st: meanonly***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: meanonly***From:*Chiara Mussida <cmussida@gmail.com>

**Re: st: meanonly***From:*Maarten Buis <maartenlbuis@gmail.com>

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