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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: meanonly |

Date |
Thu, 12 Apr 2012 10:59:06 +0200 |

Marteen, you're perfectly right! Programming is the solution and I'm working on this. the predict command after reg, like: reg lwage educ2 educ3 north centre predict pip if fem==0, xb predicts the betas from the above reg * the mean of the independent variables in my data, which do not necessarily correspond to the ones used to fit my reg. Right? Thanks Chiara On 11/04/2012, Maarten Buis <maartenlbuis@gmail.com> wrote: > I would probably rephrase the entire problem in terms of various > -predict-s after each model (the wage regression, the regress to get > the means, the -mlogit-). My guess would be that that is easiest to > program / debug, but you'll just have to find out if that is true by > trying it. That is programing: you use your intuition to guess what > would be easiest and than you try it (and find out you were wrong...). > > If you insist on using matrices, than you can, but you need to worry > about not mixing up the column numbers > > If you insist on using scalars, than you can, but you need to use > -tempname-s in order to avoid conflicts with variable names. > > -- Maarten > > On Wed, Apr 11, 2012 at 2:56 PM, Chiara Mussida <cmussida@gmail.com> wrote: >> 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/ > > > > -- > -------------------------- > 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>

**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>

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

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

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