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Re: st: RE: Adj-R2 becomes too low with XTIVREG2?


From   Erasmo Giambona <e.giambona@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Adj-R2 becomes too low with XTIVREG2?
Date   Fri, 27 Mar 2009 10:39:05 +0100

Dear Statalist,

I posted a message a few days ago about the Adj-R2 with xtivreg2.
Following a suggestion of Nick Cox, I posted a code (and data) that
exactly replicates my commands.

I will try to reformulate my question with the hope that somebody can
provide some suggestions on how to interpret my output. Here it is: I
fit exactly the same model with xtreg and xtivreg2. R2 and Adj-R2 are
about 0.20 with xtreg. R2 and Adj-R2 are respectively about 0.20 and
0.02 with xtreg and xtivreg2. I am puzzled by the drop in the Adj-R2
in this latter case. My question is: could this drop by explained by
the poor properties of the Adj-R2 with IV regressions?

I would also be happy to pass my data and code to anybody who can
provide further insights.

Thanks and regards,

Erasmo




On Wed, Mar 25, 2009 at 6:19 PM, Erasmo Giambona <e.giambona@gmail.com> wrote:
> Here is the exact code I am using based on data (also attached) from
> help q_cross.
>
> Thanks,
>
> Erasmo
>
> On Wed, Mar 25, 2009 at 5:46 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
>> I am just asking for more information on behalf of those who might
>> answer this question.
>>
>> I understand that your dataset is too big to post here, but that's all
>> the more reason to strain to reproduce the behaviour you report in
>> something mutually accessible, say one of the datasets downloadable via
>>
>> . help q_cross
>>
>> I can't see anywhere in your reply the precise commands you used. That
>> means a do file, or equivalent. It means exact code. It means something
>> reproducible. You don't need more "hints": just do what I say!
>>
>> Nick
>> n.j.cox@durham.ac.uk
>>
>> Erasmo Giambona
>>
>> Thanks Nick.
>>
>> It is a very large dataset, but I would still be happy to pass it to
>> Mark Scaffer.
>>
>> In any case, I will also try to provide more details about the
>> commands and the data.
>>
>> I am using an unbalanced panel dataset of firms over a period of about
>> 10 years. For both xtreg and xtivreg2 I am fitting exactly the same
>> model. In both cases, I cluster the standard errors at the firm level
>> and I use fe i(firm). In the iv-model, three of the independent
>> variables are assumed endogenous.
>>
>> I hope I have not missed anything else.
>>
>> Any hints would be appreciated,
>>
>> Erasmo
>>
>>
>> On Wed, Mar 25, 2009 at 5:06 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
>>> -xtivreg2- is a user-written command from SSC (Mark Schaffer).
>>>
>>> For Mark, or anybody else, to have anything much to work with here,
>> tell
>>> us about the data and the precise commands you used.
>>>
>>> Ideally, reproduce your results on a dataset accessible to all, or let
>>> Mark privately have a copy of your data _and_ your commands.
>>>
>>> Otherwise there is little to go on here. It's not even clear that you
>>> are fitting precisely the same model, or equivalent models.
>>>
>>> More attention to age-old advice in the FAQ, often repeated on the
>> list,
>>> would have yielded a question easier to answer.
>>>
>>> Nick
>>> n.j.cox@durham.ac.uk
>>>
>>> P.S. no SHOUTING of command names please.
>>>
>>> Erasmo Giambona
>>>
>>> I am estimating the panel regression model with XTREG and XTIVREG2.
>>> When I use XTREG, I obtain an adj-R2 of around 0.21. The within and
>>> between R2's have a similar size. Similarly, when I use XTIVREG2, the
>>> centered and uncentered R2 are around 0.20. However, if I do: . di
>>> "R2-adj: " e(r2_a), I get: R2-adj: .02060245. This sems a huge drop
>>> compared to the centered/uncentered R2 or the adj-R2 from XTREG.
>>>
>>> I have explored the statalist archive finding a lot of very useful
>>> information about the nuances with the R2 with IV regressions, but I
>>> didn't find a good answer to my question.
>>>
>>> I would appreciate any hints on this issue.
>>
>> *
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>>
>

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