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From |
Partha Deb <partha.deb@hunter.cuny.edu> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 20 May 2009 21:09:59 -0400 |

cheers, Partha Martin Weiss wrote:

<>Sam privately asked for more details on my post. I think that theuser-written package -cmp- could be of use to him, so I recommend heinstall it by typing -ssc install cmp- within Stata (while beingconnected to the internet) and subsequently take a look at the helpfile by typing - help cmp- . The file is quite comprehensive, withclickable examples for most constellations of data -cmp- is designedto handle. I hope that Sam succeeds and that other listers can giveadditional 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" <sunghanl@uic.edu> To: <statalist@hsphsun2.harvard.edu> Sent: Wednesday, May 20, 2009 11:15 PM Subject: st: selection bias with bivariate probitHello all,I'm looking for a procedure to control selection bias, but a bitspecial case that I don't know whether STATA supports this.Outcome regression: dichotomous dependent variable (high earnings ornot) y = beta * x + gamma * z (college or not)Selection regression: dichotomous choice dependent variable (collegedegree or not) z = alpha * wClassic Heckman procedure deals with the situation where a selectionmodel with a dummy dependent variable (work or not) and an outcomemodel with a continuous dependent variable (wage) with truncated(only observed if chosen).My challenges to use a Heckman procedure are two folds: (1) a dummyvariable (high wage or not instead of continuous wage) in an outcomemodel (2) outcome observations not truncated (we observe earningsfor both college degree and non-college degree) - so this is more ofa 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 anystata function or ado file dealing with both extensions.As far as I know, we can include both mills ratio of selected andnot-selected in the outcome model from the selection model.Then I'll have a consistent coefficient estimate for gamma. But Idon't know how to correct std dev of gamma in the outcome probitmodel (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 * * 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/* * 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/

-- Partha Deb Professor of Economics Hunter College ph: (212) 772-5435 fax: (212) 772-5398 http://urban.hunter.cuny.edu/~deb/ Emancipate yourselves from mental slavery None but ourselves can free our minds. - Bob Marley * * 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/

**References**:**st: selection bias with bivariate probit***From:*Sam Lee <sunghanl@uic.edu>

**st: Re: selection bias with bivariate probit***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**st: Re: Re: selection bias with bivariate probit***From:*"Martin Weiss" <martin.weiss1@gmx.de>

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