
From  "Rodrigo A. Alfaro" <raalfaroa@gmail.com> 
To  <statalist@hsphsun2.harvard.edu>, <nicola.baldini2@unibo.it> 
Subject  Re: st: dynamic panel with selection and more endogeneous 
Date  Fri, 23 Mar 2007 01:24:21 0400 
My knowledge of statistics has big gaps. What does "simulate the model (as a reduced model) and see which estimator is better" mean?
Anyway, thanks Rodrigo for your suggestion: I never thought about xthtaylor
It sounds like enjoying the benefits of the FE without actually imposing them.
I knew from the manual of xtabond2 that if T is large, dynamic panel bias can be worked around with FE. First, my T=15 and I was not sure that it is large enough, given that according to the manual T=9 seems not (and, playing on web dataset abdata, I have found that FE actually exhacerbate the problem), but I will have a look at your suggested papers. More important, I thought the problem to be more complicated, given that past y influences not only present y, but also the likelihood that the event "change from regime 1 (z1=0) to 2 (z1>0)" happens. Can FE work this additional complication?
P.S. My exogenous variables are only four. I am not taking care of the possible unobservable in the model; rather, I needed something to use as instruments.
At 02.33 21/03/2007 0400, "Rodrigo A. Alfaro" wrote:
Nicola,
It is crucial to put y(t1) or t (something like that) in your RHS. For a
large T, you can use xtreg, fe, it is known that the bias in the lagged
dependent variable decreases with T. Two papers in Econometrica analyze
this: Hahn and Kuersteiner (2002) and Alvarez and Arellano (2003). If you
are interested in the z's coefficients maybe you can take a look of
HausmanTaylor estimator help xthtaylor, again you could modify to allow
more instruments in the last step. For several exogenous variables, maybe
you are taking care of the possible unobservable in the model then pooled
leastsquare is an option. Anyway, if there is a few number of endogenous
variables, I suggest you to simulate the model (as a reduced model) and see
which estimator is better.
R.
  Original Message I have the following PANEL model:
Regime 1 (observed if z1 = 0): y = y(t1) + exog
Regime 2 (observed if z1 > 0): y = y(t1) + exog + z1 + z2 + endog
At t=0, all observations are in regime 1; changing from 1 to 2 depends on
y(t1) and exog; changing from 2 to 1 not possible.
y is a count variable, y(t1) is past y (I am uncertain about using lagged
y or a depreciated stock up to t1; in regime 2, alternatively, I can use
a "yearssince regime 2" time counter), z1 and z2 are proportions
(endogenous; my key independent variables), endog are additional
endogenous variables, exog are exogenous. To put it differently, in regime
1 all endogenous are 0, while in regime 2 z1 is not 0 (and remaining
endogenous may be 0 or not).
All endogenous variables are almost timeinvariant (e.g.
0/0/0/0/0/0/0/0/50/50/50/50/50/50/50; 0/0/0/0/0/0/0/0/0/0/0/0/0/0/0;
0/0/0/0/0/0/0/0/0/0/0/0/25/25/50; etc...).
I have thought about xtivreg y (z1 z2 endog y(t1) = exog).
Do you have any suggestion or better idea?
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