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

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Re: st: Re: st: Re: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection |

Date |
Fri, 5 Oct 2012 13:28:24 -0400 |

Ebru Ozturk <ebru_0512@hotmail.com>: Start with "Inference for partial effects in nonlinear panel-data models using Stata" by Jeffrey Wooldridge, linked from http://www.stata.com/meeting/snasug08/abstracts.html On Fri, Oct 5, 2012 at 12:51 PM, Nick Cox <njcoxstata@gmail.com> wrote: > Much of the point of this thread is that those answering you > _disagree_ on certain key things and are at least in part_unclear_ on > your situation. > > I already said "If you are expecting that Statalist can act as a > collective oracle that can tell you the _correct_ thing to do in your > project, that is I suggest more than the list can deliver." > > So, you still think you can get definitive advice out of us? > > 0. What do your advisors/supervisors/colleagues say who know more > about your dataset and objectives? > > 1. I think that's overstating it. It just sounds like a natural model > but no-one has access to your data or awareness of your full > objectives to be able to say how well it will work. > > 2. That's overstating it too. Whether you _need_ to do Heckman is your > decision. > > 3. I don't know what this means. See #0. > > 4. You need to try it. Answering this question would mean going back > to Stata 10 and looking at the documentation and I can't answer off > the top of my head. (As you didn't say, contrary to advice, that you > are using an old version of Stata, no-one will have been thinking > about that.) > > 5. I don't see why not in principle, but you may need to write a > program in practice. All depends on how the panel aspect is handled. > > Nick > > On Fri, Oct 5, 2012 at 5:38 PM, Ebru Ozturk <ebru_0512@hotmail.com> wrote: >> >> Thank you very much for your help. I just would like to make sure that I understand you correctly. Also I am here to learn so please forgive me for asking many questions. >> >> 1. I restrict sample to innovating firms and the dependent variables that I am interested in are percentages therefore, you agree on that I should use fractional logit model. >> >> 2. I do not need to do Heckman sample selection even though I restrict my sample. I also want to mention that yes I do not have some Xs but I still do have other Xs for non-innovators which I use them as control variables. >> >> 3. Do you think using a different model puts me trouble? >> >> 4. I use Stata 10 so can I use fractional logit model? >> >> 5. What about if I have a panel data? Is fractional logit model still applicable? >> >> Ebru >> >> ---------------------------------------- >>> Date: Fri, 5 Oct 2012 16:21:40 +0100 >>> Subject: st: Re: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection >>> From: njcoxstata@gmail.com >>> To: statalist@hsphsun2.harvard.edu >>> >>> Isn't this the same question? >>> >>> It seems to me that you have two issues, which are independent of each other. >>> >>> 1. Your response is bounded [0,1] or [0,100], dependent on units. >>> >>> Joerg, Maarten and I all seem to agree that this is not censoring in >>> any strong sense, as values outside the bounds are impossible in >>> principle. Thus we don't think that tobit makes sense here. >>> >>> Daniel's argument appears to be that there is a important sense in >>> which this can be considered as censoring. Thus he seems more open to >>> the idea that tobit makes sense. >>> >>> This is not an election and what is right is not determined by >>> counting votes. As I don't understand Daniel's argument I certainly >>> can't refute it. >>> >>> Personally I pay little attention to what's popular in the literature >>> if I think it's wrong. It's good news for me: I have a chance to try >>> to improve practice. >>> >>> 2. There is a question of what determines which firms do and which do >>> not innovate. This is interesting and important and you should model >>> it _if you have data to do so_. In your earliest posts in this thread, >>> you seemed (to me at least) to imply that you have no other data on >>> non-innovating firms with which to model selection, but you should >>> know. >>> >>> This is just my summary. The others who have contributed to the thread >>> may want to correct or complement it. Other people of course may have >>> other views. >>> >>> If you are expecting that Statalist can act as a collective oracle >>> that can tell you the _correct_ thing to do in your project, that is I >>> suggest more than the list can deliver. >>> >>> Nick >>> >>> On Fri, Oct 5, 2012 at 3:29 PM, Ebru Ozturk <ebru_0512@hotmail.com> wrote: >>> > My question was whether I should use Heckman sample selection as I restricted my sample to innovating firms only. >>> > >>> > After discussing with you, I also confused as I said before many papers used tobit regression and did Heckman correction and never seen fractional logit model in these papers such as Grimpe & Kaiser, (2010); Cassiman & Veugelers, (2006). >>> > >>> > These papers are saying that, the data is left censored as it includes many zeros. Also when I search for fractional logit model it says it is bounded between 0 and 1 but my dependent variable includes for instance, 0, 11, 13, 15, 25 values and so on. >>> > >>> > Maybe I am not very good at statistics but when I read papers they use tobit regression. Whey then? >>> > >>> > Ebru >>> > >>> > ---------------------------------------- >>> >> Date: Fri, 5 Oct 2012 15:02:22 +0200 >>> >> Subject: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection >>> >> From: maartenlbuis@gmail.com >>> >> To: statalist@hsphsun2.harvard.edu >>> >> >>> >> On Fri, Oct 5, 2012 at 1:53 PM, Ebru Ozturk <ebru_0512@hotmail.com> wrote: >>> >> > I think there is a misunderstanding here. Yes, I have valid and meaningful values on my explanatory variables but when I restrict the sample to innovating firms. By restricting the sample I just exclude the firms that no activity toward innovation at all which I am not interested in them. So, in the restricted sample I can also observe Xs for 0s as my dependent variables are radical and incremental innovation. >>> >> > >>> >> > I hope it is clear now. >>> >> >>> >> Now I really don't understand your problem: Is it that you have a >>> >> dependent variable that is a proportion and some of these proportions >>> >> are 0? Than just use a fractional logit model (just -glm- with the >>> >> -link(logit)- and the -vce(robust)- options). For such problems >>> >> neither -tobit- nor -heckman- are appropriate nor is there any >>> >> truncation going on. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Truncated sample or Heckman selection***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**st: RE: Truncated sample or Heckman selection***From:*"Millimet, Daniel" <millimet@mail.smu.edu>

**st: Re: st: RE: Truncated sample or Heckman selection***From:*Nick Cox <njcoxstata@gmail.com>

**RE: st: Re: st: RE: Truncated sample or Heckman selection***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Joerg Luedicke <joerg.luedicke@gmail.com>

**RE: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**RE: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*"Millimet, Daniel" <millimet@mail.smu.edu>

**RE: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Maarten Buis <maartenlbuis@gmail.com>

**RE: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Maarten Buis <maartenlbuis@gmail.com>

**RE: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**st: Re: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Nick Cox <njcoxstata@gmail.com>

**RE: st: Re: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**st: Re: st: Re: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection***From:*Nick Cox <njcoxstata@gmail.com>

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