Re: st: Selection with an endogenous ordinal variable

[Filipe Silva <filipeourico@googlemail.com>]

Slides were very helpful
Thank you very much for the remark and suggestion

2011/2/9 Austin Nichols <austinnichols@gmail.com>:
> 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?
>
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