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From |
"de la Garza, Adrian" <ADelagarza@imf.org> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: Heckman or Heckman-twostep? (was: Things to consider when regressions don't converge) |

Date |
Tue, 18 May 2004 16:10:44 -0400 |

Thank you, David. My rho is far from 1, it is 0.18 if I run the model using the two-step procedure. But if I run it without it, it doesn't converge! Two questions: 1/ Is 0.18 "far" from 1, so that you would recommend that I don't use Heckman's two-step procedure? 2/ Do you know why the method using the ML function would not converge? I read somewhere that Heckman's two-step method yielded more efficient estimators... so I was more inclined to use the two-step procedure until you told me this. Do you know of a book or other source that might talk about this (ML vs two-step)? Thanks a lot. Adrian > -----Original Message----- > From: David Greenberg [mailto:dg4@nyu.edu] > Sent: Tuesday, May 18, 2004 3:49 PM > To: statalist@hsphsun2.harvard.edu > Subject: Re: Heckman or Heckman-twostep? (was: Things to > consider when regressions don't converge) > > > When the estimated rho is close to 1, the two-step procedure > may handle the estimation better. Otherwise, I think it is > now considered preferable not to use it. David Greenberg, > Sociology Department, New York University > > ----- Original Message ----- > From: "de la Garza, Adrian" <ADelagarza@imf.org> > Date: Tuesday, May 18, 2004 2:24 pm > Subject: st: Heckman or Heckman-twostep? (was: Things to > consider when regressions don't converge) > > > Since neither I nor anybody else have found an answer to my problem, > > here is another rather technical question: > > > > In which cases would I prefer to use the Heckman model without the > > twostep option and in which cases would I rather run it with the > > twostepoption? > > > > Thank you, all. > > > > Adrian > > > > > -----Original Message----- > > > From: de la Garza, Adrian > > > Sent: Tuesday, May 18, 2004 11:38 AM > > > To: statalist@hsphsun2.harvard.edu > > > Subject: st: Things to consider when regressions don't converge > > > > > > > > > Jean, thanks a lot. But perhaps I should have explained myself > > better.> It is my -R- that I want, that is, the number of bonds > > issued by a > > > particular borrower SO FAR at each different point in time. Your > > -R- > > > would give me the FINAL total of bonds that a particular > > > borrowed issue > > > throughout the whole sample and that number would be repeated > > for each > > > observation within the same borrower. This is not what I want. > > > > > > And yes, I tried the twostep option and it does run my > > regression more > > > smoothly but I am not sure why it doesn't work without the twostep > > > option. > > > > > > Thank you. > > > Adrian > > > > > > > -----Original Message----- > > > > From: jean ries [ries@ires.ucl.ac.be] > > > > Sent: Tuesday, May 18, 2004 11:26 AM > > > > To: statalist@hsphsun2.harvard.edu > > > > Subject: Re: Things to consider when regressions don't converge > > > > > > > > > > > > At 16:29 18/05/2004, you wrote: > > > > >I am running a Heckman selection model (shown below) and > > after this > > > > >non-converging story I started playing around with my > > equation and > > > > >noticed that my -lR- variable might be the one that's giving > > > > me trouble. > > > > >-lR- is ln(R), and -R- is generated as follows: > > > > > > > > > >sort borrower indic signdate mtydate amount > > > > >by borrower: g R = _n > > > > > > > > > >so -R- is the number of bonds issued by a particular > > > borrower at each > > > > >different point in time. > > > > > > > > I don't think that R represents what you expect it to > > > > represent. The way > > > > you define it, R contains the current observation number for > > > > each borrower. > > > > Try the following to obtain the number of bonds issued by a > > > > particular > > > > borrower : > > > > > > > > bysort borrower: g R = _N > > > > > > > > and: > > > > > > > > help _variables > > > > > > > > In any case, have a look at the Stata reference manual. It > > > > contains a nice > > > > discussion on problems related to Heckman selection models. > > > > As suggested > > > > there, you should try to fit your model using the > two-step method. > > > > > > > > Hope this helps, > > > > > > > > jean > > > > > > > > * > > > > * For searches and help try: > > > > * http://www.stata.com/support/faqs/res/findit.html > > > > * http://www.stata.com/support/statalist/faq > > > > * http://www.ats.ucla.edu/stat/stata/ > > > > > > > > > > * > > > * For searches and help try: > > > * http://www.stata.com/support/faqs/res/findit.html > > > * http://www.stata.com/support/statalist/faq > > > * http://www.ats.ucla.edu/stat/stata/ > > > > > > > * > > * For searches and help try: > > * http://www.stata.com/support/faqs/res/findit.html > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: defining svyheckman***From:*"R.E. De Hoyos" <redeho2@hotmail.com>

**Re: st: RE: Heckman or Heckman-twostep? (was: Things to consider when regressions don't converge)***From:*"jean ries" <ries@ires.ucl.ac.be>

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