On Mon, 16 Jun 2014, Mārtiņš Liberts wrote:
Could you please explain briefly what has been changed for intreg at
the gretl version 1.9.13?
In brief: we introduced the concept of a "pseudo-point" observation, to
deal with cases when the interval between the high and low bounds is so
narrow, and so away from 0, that the relevant loglikelihood cannot be
computed reliably. In that case, the observation is treated as if it was a
point observation, with value equal to the midpoint. According to your
output files, this happens for 1 observation out of 6170, but is enough to
alter substantially the shape of the log-likelihood, so the algorithm
converges to a slightly different maximum.
It's difficult to be more specific without looking at the data, but I
can't help noticing that the normality test strongly rejects the null in
both output files; therefore, I'm inclined to think that the normal-based
interval model is not particularly appropriate for your data, and the
issue you're experiencing is just a by-product of an unfortunate choice
for the measurement of the dependent variable. In other terms, the
assumption that you have a latent variable y* which is normally
distributed (conditional on your explanatory variable) is quite difficult
to justify. In these cases, you should either re-define your dependent
variable (are logs an option, for example?), or re-define your model, by
using other densities than the normal (the gamma density, maybe, if your
dependent variable is non-negative?). If you choose the latter option,
you'll have to code your estimator via mle, or use some other
non-parametric alternative.
Hope this helps!
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Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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