For me, such as big valué in the chi2 reject the null, whatever which one. You should write Roodman in order to assess p-valúes.


El domingo, 19 de mayo de 2013, Pindar escribió:

I'm still trying to get a feeling for the dpanel gmm estimators.
When estimating this xtabond2 statement from Roodman (2006/2008) for abdata.gdt
"xtabond2 n L.n L(0/1).(w k) yr*, gmmstyle(L.(n w k)) ivstyle(yr*, equation(level)) robust small"
open abdata.gdt
dpanel 1; n const w w(-1) k k(-1) ; \
  GMM(n,2,8) GMM(w,2,8) GMM(k,2,8) \
  GMMlevel(w,1,1) GMMlevel(k,1,1) --time --sys

I came across a question concerning the Sargan/Hansen test of overid. restrictions.
In the gretl-guide on p.152 it is stated that "Specifically, xtabond2 computes both a “Sargan
test” and a “Hansen test” for overidentification, but what it calls the Hansen test is what DPD and
gretl call the Sargan test."

The Hansen test in this example does not reject the validity of the instruments while the Sargan does.

"Sargan test of overid. restrictions: chi2(100) = 186.90 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(100) = 110.70 Prob > chi2 = 0.218
(Robust, but can be weakened by many instruments.)"

In gretl output however the result of the Sargan test is and not the Hansen test :
"Sargan over-identification test: Chi-square(100) = 154.808 [0.0004]"

That's was quite a surprise for me.
Perhaps it's because the test statistic is not the same and it's really the Hansen test (cos I believe in what u documented :-)), but why then such drastic differences?