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

From   Nick Cox <>
Subject   st: Re: st: Re: st: Re: st: Re: st: Re: st: RE: Truncated sample or Heckman selection‏
Date   Fri, 5 Oct 2012 16:21:40 +0100

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

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.


On Fri, Oct 5, 2012 at 3:29 PM, Ebru Ozturk <> 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:
>> To:
>> On Fri, Oct 5, 2012 at 1:53 PM, Ebru Ozturk <> 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.

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