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RE: st: sample selection with bivariate probit


From   "David Moore" <davem@hartman-group.com>
To   statalist@hsphsun2.harvard.edu
Subject   RE: st: sample selection with bivariate probit
Date   Thu, 26 Sep 2002 14:08:57 -0700

I've been thinking about this problem a little.  I first thought you could
estimate each version of the wage equation separately (i.e., with z=1 and
z=0).  Now, I think you have an even more complicated situation in that you
should estimate both equations simultaneously as a form of switching or
mover/stayer model with sample selection.  I'm not suggesting how you'd use
Stata for this purpose (though it would entail writing your own ml
routines), however, it seems to me that if you're going to take a stab at
it, you may as well go all the way.  Otherwise, I believe separate
estimation will provide consistent, if not fully efficient, estimates.


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of
Abdurrahman.Aydemir@statcan.ca
Sent: Thursday, September 26, 2002 11:49 AM
To: statalist@hsphsun2.harvard.edu
Subject: RE: st: sample selection with bivariate probit


Dan, and fellow Stata users,

Thanks for the reply. I checked the heckman procedure from the Stata manual
( - I am a new Stata user). It clearly allows for one selection, which
implies one inverse Mill's ratio. Does it also allow for two selections? I
am interested in estimating the coefficients of the two selectivity terms
(referring to y1 and y2 where z=y1*y2) in earnings equations.

Ab

>-----Original Message-----
>From: DL Millimet [mailto:millimet@post.cis.smu.edu]
>Sent: Thursday, September 26, 2002 2:22 PM
>To: statalist@hsphsun2.harvard.edu
>Subject: RE: st: sample selection with bivariate probit
>
>
>this sounds like simply 2 seperate standard (univariate)
>heckman selection
>problems.
>
>dann
>
>-----Original Message-----
>From: owner-statalist@hsphsun2.harvard.edu
>[mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of
>Abdurrahman.Aydemir@statcan.ca
>Sent: Thursday, September 26, 2002 1:06 PM
>To: statalist@hsphsun2.harvard.edu
>Cc: sameos@mac.com
>Subject: RE: st: sample selection with bivariate probit
>
>
>Erik, thanks for you reply. Here the parameters of interest are the
>parameters of the earnings equation. The context is
>international migration.
>z=1 refers to migrants, z=0 refers to non-migrants. What I
>need is sample
>selectivity corrected returns to characteristics in the lnw
>equation. In the
>data I observe lnw for a given individual either for z=1 or
>z=0, but not for
>both (previous message is misleading - sorry ). I.e. for those
>who migrate I
>only observe lnw|z=1 and for non-migrants I only observe
>lnw|z=0. I want to
>predict the earnings of a migrant had that individual not
>migrated ( and
>vice versa for non-migrants). Given returns to characteristics
>of the same
>individual can be different in the host country and in the
>source country I
>want to estimate the model separately for z=1 and z=0, and use
>the estimated
>coefficients for my prediction.
>
>
>
>>-----Original Message-----
>>From: Erik Ø. Sørensen [mailto:sameos@mac.com]
>>Sent: Thursday, September 26, 2002 1:32 PM
>>To: Abdurrahman.Aydemir@statcan.ca
>>Subject: Re: st: sample selection with bivariate probit
>>
>>
>>On torsdag, sep 26, 2002, at 13:07 America/Montreal,
>>Abdurrahman.Aydemir@statcan.ca wrote:
>>
>>> Dear Users,
>>>
>>> I am estimating a log earnings equation controlling for
>>selection. The
>>> selection involves two stages that leads to a bivariate probit with
>>> partial
>>> observability.
>>>
>>> lnw=x3b3+e3 observed for z=1 and z=0
>>>
>>> where z=y1 x y2; z=1 iff y1=y2=1; z=0 if y1=0 or y2=0
>>
>>I think you need to explain more carefully what is observed, what is
>>not observed and what is the parameters of interest. If you get to
>>observe lnw=x3b3+e3 no matter what is the value of z, why do you want
>>to estimate it seperately for the values of z? Why would this make a
>>difference?
>>
>>Erik
>>--
>>Erik Ø. Sørensen,  <http://www.geocities.com/erik_oiolf/>
>>
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