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Re: st: goodness of fit measure fir ivtobit


From   Yuval Arbel <yuval.arbel@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: goodness of fit measure fir ivtobit
Date   Mon, 24 Sep 2012 18:47:30 +0200

regarding my last quote: we are talking about annual data between 1897
and 1958. I guess the authors' objective was to demonstrate that high
correlation could be spurious

On Mon, Sep 24, 2012 at 6:43 PM, Yuval Arbel <yuval.arbel@gmail.com> wrote:
> Nick, if we are aware of the many limitations of the R-Squares that's
> O.K. to report it. My fear is that during a presentation somebody will
> see the low R-Squared and say that given that 88 percent of the
> variance cannot be explained  Anat's work is worthless, where this is
> obviously not the case (and believe me, these things happened before).
>
> Finally, a nice anecdote from Johnston and Dinardo's textbook
> (Econometric Methods fourth edition (1997) page 10): they quote
> Plosser and Schwert, who found a +0.91 correlation between the log of
> U.S. nominal income and the log of accumulated sunspots!!!
>
> On Mon, Sep 24, 2012 at 6:26 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>> That is a puzzling argument, if indeed it's an argument at all.
>>
>> I don't think anything much in statistics ensures a _causal_
>> relationship  (presumably what Yuval means here), short of independent
>> evidence on mechanism or process.
>>
>> If a model is not that great, readers need to know. Sometimes a low
>> R-squared makes that vivid.
>>
>> (People who want to remind me how limited R-squared is should please
>> note that I wrote the FAQ cited below, which comes decorated with
>> multiple warnings.)
>>
>> Nick
>>
>> On Mon, Sep 24, 2012 at 5:12 PM, Yuval Arbel <yuval.arbel@gmail.com> wrote:
>>> Anat, note that the possibility to calculate the log likelihood is
>>> there regardless of the method of estimation you are employing.
>>>
>>> In addition, I would personally rather avoid presenting an R-Squared
>>> of 0.12, particularly in these kinds of models. As is well known, high
>>> R-Squared does not ensure casual relationship and low R-Squared does
>>> not ensure lack of casual relationship
>>>
>>> On Mon, Sep 24, 2012 at 4:54 PM, Anat (Manes) Tchetchik
>>> <anatmanes@gmail.com> wrote:
>>>> I haven't thought about the count model, I will definitely try to run
>>>> it! thanks much!
>>>>
>>>> On Mon, Sep 24, 2012 at 5:38 PM, Maarten Buis <maartenlbuis@gmail.com> wrote:
>>>>> That does not sound like censoring at all. I would think of this as a
>>>>> regular count model. There are examples on how to deal with such an
>>>>> iv-model in -help gmm-.
>>>>>
>>>>> Hope this helps,
>>>>> Maarten
>>>>>
>>>>> On Mon, Sep 24, 2012 at 4:11 PM, Anat (Manes) Tchetchik
>>>>> <anatmanes@gmail.com> wrote:
>>>>>> Austin Hi,
>>>>>> Thank you very much for your reply!
>>>>>> What I have as a dependent var. are 500 respondents' reports of the
>>>>>> number of times they travelled abroad to visit their friends and
>>>>>> relatives over the course of their adult lives.  Some respondents yet,
>>>>>> who have relatives abroad, did not travel at all.
>>>>>> So the observations are censored at zero, with mean =2.2, max =50 and
>>>>>> stdev= 3.8.
>>>>>> Do you think in that case that the general methods of moments will be better?
>>>>>> Thanks much!!!
>>>>>> Anat
>>>>>>
>>>>>> On Sun, Sep 23, 2012 at 5:49 AM, Austin Nichols <austinnichols@gmail.com> wrote:
>>>>>>>
>>>>>>> Anat (Manes) Tchetchik <anatmanes@gmail.com>:
>>>>>>> You can always -predict- and compute the squared correlation of
>>>>>>> predictions with observed values:
>>>>>>> http://www.stata.com/support/faqs/statistics/r-squared/
>>>>>>> but are you sure your -ivtobit- model is justified?  What is the
>>>>>>> process that results in observations being censored?  I suspect you
>>>>>>> have a lower limit at zero which is actually a very low conditional
>>>>>>> mean rounded down to zero--am I right?  You may be better off with a
>>>>>>> -gmm- model.
>>>>>>>
>>>>>>> On Sat, Sep 22, 2012 at 5:33 PM, Anat (Manes) Tchetchik
>>>>>>> <anatmanes@gmail.com> wrote:
>>>>>>> > Dear statalisters,
>>>>>>> >
>>>>>>> > I wonder if anyone knows any goodness of fit that is appropriate for
>>>>>>> > tobit with endogenous
>>>>>>> > variables (ivtobit). Not as in "regular" tobit, stata does not report any
>>>>>>> > goodness of fit measure, any idea how to estimate such a measure?
>>>>>>> > Any response will be greatly appreciated..
>> *
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>
>
>
> --
> Dr. Yuval Arbel
> School of Business
> Carmel Academic Center
> 4 Shaar Palmer Street,
> Haifa 33031, Israel
> e-mail1: yuval.arbel@carmel.ac.il
> e-mail2: yuval.arbel@gmail.com



-- 
Dr. Yuval Arbel
School of Business
Carmel Academic Center
4 Shaar Palmer Street,
Haifa 33031, Israel
e-mail1: yuval.arbel@carmel.ac.il
e-mail2: yuval.arbel@gmail.com
*
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