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Re: st: goodness of fit measure fir ivtobit


From   "Anat (Manes) Tchetchik" <anatmanes@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: goodness of fit measure fir ivtobit
Date   Tue, 25 Sep 2012 15:36:22 +0200

Great, Thanks!

On Tue, Sep 25, 2012 at 3:32 PM, Austin Nichols <austinnichols@gmail.com> wrote:
> Anat (Manes) Tchetchik <anatmanes@gmail.com>:
> 1. You can specify that max as exposure, but it sounds a bit odd to
> me--why not just include ln(number_of_years_rel_abroad) and ln(age-17)
> as predictors and let the regression estimate the coefs?  If one coef
> turns out to be close to one, then it looks like an exposure variable:
> an exposure X just means that ln(X) enters with a coef of one
> (elasticity of one). An offset X just means that X enters with a coef
> of one (semi-elasticity of one).
> 3. Yes, predict yhat and calculate squared corr of y and yhat as a
> pseudo-R-squared.
>
> On Tue, Sep 25, 2012 at 7:49 AM, Anat (Manes) Tchetchik
> <anatmanes@gmail.com> wrote:
>> Austin hi,
>> I have read the material regarding the ivpois model you have referred
>> me to and ran it on my data set. The results look pretty plausible .
>> Just before sticking to this model I have few last questions:
>>
>> 1. Can I use the exposure variable (in my case the maximum of the two
>> values: respondent's adulthood years and and the no. of years his/her
>> relative is staying abroad) also as an independent var.? (or given
>> that I do it- I should not use the exposure option)
>>
>> 2. I'm not sure i understand when I should use the exposure option and
>> when the offset one
>>
>> 3. Do I calculate goodness of fit measure using the same procedure you
>> recommended earlier
>> (http://www.stata.com/support/faqs/statistics/r-squared/) ?
>>
>> Thank you very much!
>> Anat
>>
>> On Mon, Sep 24, 2012 at 6:38 PM, Austin Nichols <austinnichols@gmail.com> wrote:
>>>
>>> Anat (Manes) Tchetchik <anatmanes@gmail.com> :
>>> Indeed, no censoring in your model. You have exactly the case I
>>> referred to when I wrote "I suspect you have a lower limit at zero
>>> which is actually a very low conditional mean rounded down to zero."
>>> Unless you believe that the Tobit model somehow correctly captures
>>> bunching at zero due to utility functions which would imply a negative
>>> demand for travel abroad, if such a thing were possible, which is
>>> implausible at best, you are much better off assuming that people with
>>> zero travel abroad simply have very low demand, and a group that has a
>>> conditional mean of 1/100000 trips will indeed have a lot of zeros
>>> observed.  The -ivpois- package on SSC, and the -gmm- specifications
>>> that supersede it, are designed to allow instrumental variables in a
>>> count model, or a regression with nonnegative outcomes more generally:
>>> http://www.stata.com/meeting/boston10/boston10_nichols.pdf
>>> http://fmwww.bc.edu/repec/bocode/i/ivpois.html
>>>
>>> On Mon, Sep 24, 2012 at 10:54 AM, 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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-- 
Anat Tchetchik, PhD
Department of Hotel and Tourism Management
Guilford Glazer Faculty of Business and Management
Ben-Gurion University of the Negev
P.O.Box: 653
Beer-Sheva, Israel, 84105

E-mail:       anat@som.bgu.ac.il
Phone         972-(0)8-6479735
Fax:           972-(0)8-6472920
Web:          http://cmsprod.bgu.ac.il/Eng/som/hotelmanage/Staff/Academic/ChechikA.htm
*
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