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From |
fabio.sigismondi@ulg.ac.be |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Marginal effects with an Heckman selection model |

Date |
Mon, 16 Apr 2012 20:41:58 +0200 (CEST) |

Thanks a lot for your reply. I try to apply your suggestions but it only works when you estimate the heckman selection model by ML. In my case, I estimated my model by the 2 step procedure because the ML estimation does not work. margins, dydx(*) predict(psel) works with the two step procedure but the 2 other predictions does not work // marginal effects on expected // wage (not working is 0 wage) margins, dydx(*) predict(yexpected) // marginal effects on expected // wage (excluding not working women) margins, dydx(*) predict(ycond) ----- Mail original ----- De: "Maarten Buis" <maartenlbuis@gmail.com> À: statalist@hsphsun2.harvard.edu Envoyé: Lundi 16 Avril 2012 09:45:40 Objet: Re: st: Marginal effects with an Heckman selection model On Sun, Apr 15, 2012 at 8:30 PM, <fabio.sigismondi@ulg.ac.be> wrote: > I'm estimating the charitable giving of households thanks to > administrative data's. To do so I'm estimating an exponential Heckman > selection model (Wooldridge, 2nd edition, chapter 17) with the two > step procedure. Notice that this is a multidisciplinary list. This has consequences, one of those is that an article or book that is "world famous" in your (sub-(sub-))discipline is likely to be completely unknown outside that micro cosmos. So even if it is enough within your discipline to a use a name/year or name/edition reference, this is completely uninformative on this list. This is why the Statalist FAQ asks you to give full references. You can find a link to the Statalist FAQ at the bottom of this post (and any other post on this list). It is well worth studying as it contains many tricks on how to ask answerable questions on this list. > I want to estimate the marginal impacts of my variables on the > probability of giving to charities and on the amount given. You do this by specifying the -predict()- option. You can see what you can specify in that option by typing -help heckman postestimation- and going to the entry on -predict-. *----------- begin example -------------- webuse womenwk heckman wage educ age, /// select(married children educ age) // marginal effects on // the probability of working margins, dydx(*) predict(psel) // marginal effects on expected // wage (not working is 0 wage) margins, dydx(*) predict(yexpected) // marginal effects on expected // wage (excluding not working women) margins, dydx(*) predict(ycond) *----------- end example -------------- I leave it up to you how you are going to deal with the problem that you get marginal effects on the log(donations) rather than donations. 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/ * * 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/

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