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# Re: st: playing with coefficients

 From Joerg Luedicke To statalist@hsphsun2.harvard.edu Subject Re: st: playing with coefficients Date Fri, 23 Mar 2012 08:27:06 -0700

-c.- is for continuous, see -help fvvarlist-

J.

On Fri, Mar 23, 2012 at 8:08 AM, Chiara Mussida <cmussida@gmail.com> wrote:
> I got it: for categorical variable c.namevariable, and for dummy
> variables? or continuous variable?
>
>
>
>
>
> On 23/03/2012, Chiara Mussida <cmussida@gmail.com> wrote:
>> Occupation takes the values from 1 to 7, therefore by using
>> i.occupation I get 7 coefs. i.fem is instead a dummy variable (fem==1
>> if female, 0 otherwise). The use of both i.occupation and i.fem
>> therefore gives me the coefs for female. How do I get the one for male
>> (fem==0)?
>>
>> Thanks
>> chiara
>>
>> On 23/03/2012, Christopher Baum <kit.baum@bc.edu> wrote:
>>> <>
>>> Chiara said
>>>
>>> I totally agree: is there a way to cast this as a single regression:
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==0 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==1
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==1 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==1
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==0 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==2
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==1 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==2
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==0 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==3
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==1 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==3
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==0 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==4
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==1 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==4
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==0 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==5
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==1 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==5
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==0 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==6
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==1 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==6
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==0 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==7
>>> reg lwage pexper pexpersq edu2 edu3 child12 married northe centre
>>> south ftc partime d09 if fem==1 & cond3==1 & age>=15 & age<=64 &
>>> dipind==1 & hours>20 & hours<55 & occupation==7
>>>
>>> preserve
>>> keep if cond3==1 & age>=15 & age<=64 & dipind==1 & hours>20 & hours<55
>>> reg lwage i.fem##i.occupation##c.(pexper pexpersq edu2 edu3 child12
>>> married
>>> northe centre south ftc partime d09)
>>> restore
>>>
>>> If some of the parenthesized variables are categorical, rewrite the
>>> latter
>>> as
>>>
>>> (c.pexper c.pexpersq i.edu2 i.edu3 c.child12 ... )
>>>
>>> You can then use margins to produce coefficients or conditional means for
>>> any combinations of gender and occupation.
>>>
>>> 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
>>>
>>>
>>> *
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>>>
>>
>>
>> --
>> 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)
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