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Re: Re: st: Re: Re: selection bias with bivariate probit


From   nicola.baldini2@unibo.it
To   statalist@hsphsun2.harvard.edu
Subject   Re: Re: st: Re: Re: selection bias with bivariate probit
Date   Sun, 24 May 2009 12:43:14 +0200

Belated suggestion: you may also download -ssm- from SSC (use with the switch option).
Nicola
 
P.S. I'll NOT receive/read any email but the Digest.

At 02.33 21/05/2009 -0400, you wrote:
>Unless I've understood the specification incorrectly, there are at least 
>2 ways to do it in Stata.
>
>1. Ignore the binary nature of both outcome and treatment and use linear 
>IV (-ivregress-, -ivreg2-).
>
>2. Assume bivariate normality (which -cmp- does as well) and use the 
>bivariate probit model (-biprobit- ).
>
>cheers,
>
>Partha
>
>Martin Weiss wrote:
>> <>
>>
>> Sam privately asked for more details on my post. I think that the 
>> user-written package -cmp- could be of use to him, so I recommend he 
>> install it by typing -ssc install cmp- within Stata (while being 
>> connected to the internet) and subsequently take a look at the help 
>> file by typing - help cmp- . The file is quite comprehensive, with 
>> clickable examples for most constellations of data -cmp- is designed 
>> to handle. I hope that Sam succeeds and that other listers can give 
>> additional guidance to him...
>>
>> HTH
>> Martin
>> _______________________
>> ----- Original Message ----- From: "Martin Weiss" <martin.weiss1@gmx.de>
>> To: <statalist@hsphsun2.harvard.edu>
>> Sent: Wednesday, May 20, 2009 11:18 PM
>> Subject: st: Re: selection bias with bivariate probit
>>
>>
>>> <>
>>>
>>> Try -ssc d cmp-
>>>
>>> HTH
>>> Martin
>>> _______________________
>>> ----- Original Message ----- From: "Sam Lee" 
>>> To: <statalist@hsphsun2.harvard.edu>
>>> Sent: Wednesday, May 20, 2009 11:15 PM
>>> Subject: st: selection bias with bivariate probit
>>>
>>>
>>>> Hello all,
>>>>
>>>> I'm looking for a procedure to control selection bias, but a bit 
>>>> special case that I don't know whether STATA supports this.
>>>> Outcome regression: dichotomous dependent variable (high earnings or 
>>>> not) y = beta * x + gamma * z (college or not)
>>>> Selection regression: dichotomous choice dependent variable (college 
>>>> degree or not) z = alpha * w
>>>>
>>>> Classic Heckman procedure deals with the situation where a selection 
>>>> model with a dummy dependent variable (work or not) and an outcome 
>>>> model with a continuous dependent variable (wage) with truncated 
>>>> (only observed if chosen).
>>>> My challenges to use a Heckman procedure are two folds: (1) a dummy 
>>>> variable (high wage or not instead of continuous wage) in an outcome 
>>>> model (2) outcome observations not truncated (we observe earnings 
>>>> for both college degree and non-college degree) - so this is more of 
>>>> a treatment model instead of a selection model.
>>>> STATA has "heckprob" dealing with the first problem and "treatreg" 
>>>> dealing with the second problem. But so far I couldn't find any 
>>>> stata function or ado file dealing with both extensions.
>>>>
>>>> As far as I know, we can include both mills ratio of selected and 
>>>> not-selected in the outcome model from the selection model.
>>>> Then I'll have a consistent coefficient estimate for gamma. But I 
>>>> don't know how to correct std dev of gamma in the outcome probit 
>>>> model (I guess since it is difficult to deal with covariance matrix, 
>>>> I prefer a standard procedure supporting this correction).
>>>>
>>>> Your help will be greatly appreciated.
>>>>
>>>> Sincerely,
>>>>
>>>> Sam Lee
>>>>
>>>>
>>>> Sam Lee
>>>>
>>>> Department of Accounting
>>>>
>>>> College of Business Administration
>>>> University of Illinois (RM# 2302)
>>>> 601 S. Morgan St, Chicago Il 60607
>>>>
>>>> Ph:312.413.2131 Fax:312.996.4520
>>>>
>>>> *

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