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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Selection with an endogenous ordinal variable |

Date |
Tue, 8 Feb 2011 22:37:41 -0500 |

Filipe Silva <filipeourico@googlemail.com>: I don't see any theory motivating a selection model, and correlated residuals in a misspecified -heckman- are not evidence in favor of a selection model. Firms with mean R+D conditional on X vars close to zero will often have realized R+D of zero or so small an amount that it will be measured as zero in your data. Sounds more like -glm- with a log link, or better, given an instrument for FC, a -gmm- model: http://repec.org/bost10/nichols_boston2010.pdf On Tue, Feb 8, 2011 at 9:43 PM, Filipe Silva <filipeourico@googlemail.com> wrote: > Thank you for the suggestion on the -cmp- > > I apologise for not being as clear as I should have been > > I intend to measure the impact of firms' financial constraints (FC) > upon R&D investment: > y: R&D investent, whith 74% of zeroes, €{0}U]0, +00[ > main x: FC, which is ordinal, €{0;1;2;3} > > Since there are so many zeroes, I hypothesized that there is first the > decision to invest or not (RD) followed by the decision on the amounts > invested if RD==1. Accordingly, if these decisions are assumed to be > independent (conditional on observable vars.), I'd estimate a 2part > "hurdle" with no need to jointly specify errors. > However, I tested a -heckman- not accounting for endogeneity and it > appears that there are unobservables affecting both errors. > As a result I thought of a selection model, but please correct me if > wrong (I have just recently started to deal with such kind of data). > > Additionally, there are reasons to believe that FC is endogenous in > the RD_I decision, which further complicates. > > Thank you very much, > Filipe > > > > 2011/2/8 Austin Nichols <austinnichols@gmail.com>: >> Filipe Silva <filipeourico@googlemail.com>: >> I don't understand your problem statement--can you clarify what the outcome and >> endogenous ordinal var are, and what form of selection is hypothesized? >> You may also want to look at -cmp- on SSC for MLE options. >> >> On Tue, Feb 8, 2011 at 5:57 AM, Filipe Silva >> <filipeourico@googlemail.com> wrote: >>> Dear all, >>> >>> I am currently trying to estimate a model of selection, where the main >>> explanatory variable in this model is endogenous (and ordinal!). All >>> of them observed. >>> This should be easily done with -heckman-, if not for the endogenous regressor. >>> >>> I wonder if there is any package that can handle (MLE) estimation of such model? >>> >>> Alternatively I have considered a two-step procedure (probit, obtain >>> mills, use in ivreg2 to account for endogeneity- as far as I've >>> understood this is the procedure described in Wooldridge's textbook, >>> 2002 pp. 567-570 as an extension to "heckit", even though I'm not >>> totally sure it applies to an ordinal endogenous var.) but the the >>> Variance correction in the second step is rather hard to compute. I >>> have considered using the bootstrap for such correction. >>> >>> Could anyone please advise me if this reasoning is correct or if there >>> is an alternative way to do it? * * 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/

**Follow-Ups**:**Re: st: Selection with an endogenous ordinal variable***From:*Filipe Silva <filipeourico@googlemail.com>

**References**:**st: Selection with an endogenous ordinal variable***From:*Filipe Silva <filipeourico@googlemail.com>

**Re: st: Selection with an endogenous ordinal variable***From:*Austin Nichols <austinnichols@gmail.com>

**Re: st: Selection with an endogenous ordinal variable***From:*Filipe Silva <filipeourico@googlemail.com>

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