[Limdep Nlogit List] Comparing two models

Thu Jan 25 07:28:21 EST 2007

Hello Everyone,

On a similiar subject, does anyone have advice about
testing whether a count variable is endogenous (my
count variable ranges from 1 to 50) in an equation
that has a linear dependent variable. I am assuming it
is not as simple as testing if a linear variable is
endogenous.

And what about testing if a binary variable is
endogenous.  I read about a test by Rivers and Vuong,
but looks it is for the case of a binary dependent
variable. Can same test be used if the dependent
variable is linear?

Michael

--- William Greene <wgreene at stern.nyu.edu> wrote:

> those interested.
> Richard is correct about the LIMDEP application of
> the Vuong test for the ZIP and hurdle
> models in LIMDEP.  I'm slightly ambivalent about the
> applications, however, because
> in every application, the zero inflation or hurdle
> model has more parameters than the Poisson
> model, which seems to give it an advantage.  In
> fact, I have never seen the Poisson
> model win the contest, though I have seen it come
> out a draw.  For those interested,
> I have posted a very clean application of the Vuong
> test to a pair of competing models
> for count data that are essentially identically
> parameterized, but differ in the underlying
> distribution, and, therefore, in the shape of the
> probability distribution.  (The example
> will appear in the 6th edition of my text,
> Econometric Analysis, which will be published
> in July.)
> 
>
http://www.stern.nyu.edu/~wgreene/Vuong-Test-For-Count-Models.doc
> 
> Regards,
> Bill Greene
> 
> ************************************************
> Professor William Greene
> Department of Economics
> Stern School of Business
> New York University
> 44 West 4th St., Rm. 7-78
> New York, NY   10012
> Ph. 212.998.0876
> Fax. 212.995.4218
> URL. http://www.stern.nyu.edu/~wgreene
> Email. wgreene at stern.nyu.edu
> ************************************************
> 
> 
> 
> ************************************************
> Professor William Greene
> Department of Economics
> Stern School of Business
> New York University
> 44 West 4th St., Rm. 7-78
> New York, NY   10012
> Ph. 212.998.0876
> Fax. 212.995.4218
> URL. http://www.stern.nyu.edu/~wgreene
> Email. wgreene at stern.nyu.edu
> ************************************************
> 
> ----- Original Message -----
> From: Richard Hofler <rhofler at bus.ucf.edu>
> Date: Wednesday, January 24, 2007 8:46 am
> Subject: RE: [Limdep Nlogit List] Comparing two
> models
> 
> > Andy,
> > 
> > Bill is, of course, correct. I might extend what
> he recommends by
> > referring you to Vuong's paper (cited below.) It
> is quite good and
> > includes a section on testing overlapping models,
> which appears to be
> > the case that you describe below. Note, however,
> that the null is that
> > the two models are equivalent, so don't expect
> that every test will
> > yield a clear choice of one model over the other.
> > 
> > Bill has also included some LIMDEP code for a
> Vuong test (hurdle vs.
> > Poisson) on p. E20-89 of the LIMDEP 8.0 guide. 
> > 
> > Q.H. Vuong, "Likelihood Ratio Tests for Model
> Selection and Non-nested
> > Hypotheses," Econometrica, Vol. 57, No. 2 (March
> 1989), 307-333. 
> > 
> > Richard
> > 
> > 
> > Richard A. Hofler
> > Professor 
> > Office: BA2 302F
> > Voice: (407) 823-2606
> > 
> > 
> > 
> > -----Original Message-----
> > From: limdep-bounces at limdep.itls.usyd.edu.au
> > [limdep-bounces at limdep.itls.usyd.edu.au] On Behalf
> Of William
> > Greene
> > Sent: Wednesday, January 24, 2007 7:47 AM
> > To: Limdep and Nlogit Mailing List
> > Subject: Re: [Limdep Nlogit List] Comparing two
> models
> > 
> > Andy.  You cannot use the LR test for this pair of
> models.  They are
> > nonnested, so the LR test
> > does not apply.  There is a huge literature on
> testing procedures for
> > nonnested models and
> > nonnested hypotheses.  This includes, for example,
> tests by Cox 
> > and by
> > Vuong.  There was also
> > a special issue of the Journal of Econometrics
> about 10 or 15 
> > years ago
> > on the subject.
> > Regards,
> > Bill Greene
> > 
> > ************************************************
> > Professor William Greene
> > Department of Economics
> > Stern School of Business
> > New York University
> > 44 West 4th St., Rm. 7-78
> > New York, NY   10012
> > Ph. 212.998.0876
> > Fax. 212.995.4218
> > URL. http://www.stern.nyu.edu/~wgreene
> > Email. wgreene at stern.nyu.edu
> > ************************************************
> > 
> > ----- Original Message -----
> > From: Andy Sungnok Choi <Andy.Choi at anu.edu.au>
> > Date: Wednesday, January 24, 2007 6:29 am
> > Subject: [Limdep Nlogit List] Comparing two models
> > 
> > > Dear All,
> > > 
> > > I am still at the learning stage in Limdep.
> Regarding 
> > > loglikelihood ratio 
> > > (LR) tests (Hensher et. al 2005: 335), I am not
> clear when two 
> > > models being 
> > > compared are overlapping (i.e., not extended
> from one model). 
> > When 
> > > two 
> > > models have both common variables and uncommon
> variables with 
> > the 
> > > same 
> > > number, and when I want to compare the model
> significance of 
> > > different set 
> > > of uncommon variables, how can I do this?
> > > 
> > > Assuming a generic model form for simplicity,
> > > 
> > > Variables for Model 1 = A + B
> > > Variables for Model 2 = A + C
> > > 
> > > where A, B, and C are matrixes of variables, and
> the number of 
> > > elements for 
> > > B and C are the same. Then, the degree of
> freedom for the LR 
> > test 
> > > is 0. 
> > > Right? ... Even when the number of elements for
> B and C are 
> > > different, can 
> > > I use LR tests?
> > > 
> > > Point is whether I can use LR tests for this
> kind of model 
> > comparison.> 
> > > Any sharing of experience, references, and tips
> will be greatly 
> > > appreciated.
> > > Thanks.
> > > 
> > > Andy S. Choi
> > > 
> > > _______________________________________________
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> > > Limdep at limdep.itls.usyd.edu.au
> > > http://limdep.itls.usyd.edu.au
> > > 
> > 
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> > 
> 
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