> Have you already thought about incorporating a 'collapse'
switch?
Which would do what, exactly?
The 'collapse' switch is, as far as I know, a clever invention by the
Stata-oriented guys (I believe Roodman himself). In a nutshell, it's a way
to reduce the number of over-identifying restrictions without sacrificing
the main idea, so to speak.
For example, imagine you have a DIF-GMM estimator with T=4: you could use
3 orthogonality conditions
a. \Delta e_{3,i} y_{1,i}
b. \Delta e_{4,i} y_{1,i}
c. \Delta e_{4,i} y_{2,i}
or you could put together a. and c. as
\Delta e_{t,i} y_{t-2,i}
and go down to 2. This means, in practice, that certain matrices get
'compressed' by squeezing out zeros.
From a statistical point of view, this amounts to making some extra
assumptions on the variance of disturbances, compared to ordinary GMM.
From a practical point of view, this is often innocuous, although it
leads
to different results in practice, where the differences should be small
for very large N if the model is well specified. From the regression
monkey's point of view, this is a great invention, because it multiplies
the number of legitimate ways in which you can run the same model, thus
giving you a few more chances to have the little stars in the output
appear exactly where you want them.
-------------------------------------------------------
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
-------------------------------------------------------