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Re: st: RE: RE: Dependent variable is a proportion

From   joachim Wagner <>
Subject   Re: st: RE: RE: Dependent variable is a proportion
Date   Thu, 13 May 2004 13:36:56 +0200

Nick (and others):

No, the paper deals with the (0,1) case. A solution for the [0,1] case with many zeros is the fractional logit estimator introduced by Leslie Papke and Jeff Wooldridge in their Journal of Applied Econometrics paper in 1996; see also Jeff Wooldridge 's textbook " Econometric Analysis of Cross Section and Panel Data ", MIT Press 2002, p. 661ff. This can easily done in Stata by using glm with the binomial family and a logit link.


At 12:11 13.05.04 +0100, you wrote:

This looks like a valuable reference. From the abstract,
which is in the public domain, I note recommendation
of (among others) beta-distribution-based models for which -betafit-
on SSC may be of some use.

Note, however, the subtle but crucial notation point that
observations are on (0,1). The problem
which started this thread (see bottom) has observations
on [0,1). i.e. some values are 0. Does the
paper address this complication to anyone's knowledge?


Moran, John

> A good review of this problem (the authors used various
> packages, including
> Stata 7) is given in: R. Kieschnick and B. D. McCullough. Regression
> analysis of variates observed on (0,1): percentages, proportions and
> fractions. Statistical modelling 3:193-213, 2003.

TELHAJ Shqiponje

> The dependent variable I have is a proportion (percentage of 16 year
> olds enrolled in a particular subject) which is between 0 and 86
> percent. I am not sure about the linear form. My dependent
> variable is 0
> only in 3,980 cases out of 112,412 sample obs. Here a zero is a
> structural one, because the school does not offer history (which is
> choice subject).
> Would somebody suggest to me whether it would be better to perform a
> logit transformation, or estimate -glm- with family(gaussian) and
> link(logit). Any suggestion would be greatly appreciated!

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