[Limdep Nlogit List] Comparing two models

[William Greene]

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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