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st: matsize & single exogeneity & autocorrel. in panel again


From   "vukasinm" <vukasinm@drenik.net>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: matsize & single exogeneity & autocorrel. in panel again
Date   Thu, 26 Aug 2004 00:00:03 +0200

Dear Statalisters,
I would be very grateful if someone could answer following questions.

First, I was trying to estimate panel data model in Intercooled Stata 7.0,
with N=930 and T=6, i.e. total 5580 observations and 12 variables, but
without any success. Could Stata/SE 8.0 solve my problem?

Second, since I suspect autocorrelation and single exogeneity  problem in
the model (some regressors are correlated with individual effects), my
question is: what should I apply first - test for single exogeneity (Hausman
test: fixed effect (FE) v.s. random effect (RE)model) or test for
autocorrelation in RE model? I thought to apply Hausman test first, because
if there is
singly exogeneity problem in RE model, then AR(1) test will be based on
biased
and inconsistent estimates and residuals. But, on the other hand, if
the remainder disturbances u_it  follow an AR(1) process, and I test single
exogeneity first, Hausman test and Hausman-Taylor (HT) over-identification
test are in fact not valid. Any suggestions?

Third,  I am not sure if I made mistake in defining HT set of instruments
A=[QX_1, PX_1, QX_2, Z_1], since I got strange result of HT
over-identification
test (FE AR(1) v.s HT AR(1)):

.xtreg lexAR ldistAR combordAR v97AR v98AR v01AR euAR ceftaAR croAR bjrAR
lpopexAR lpopimAR lgdpimAR lgdpexAR, fe
.hausman,save
. xtivreg lexAR v97AR v98AR v01AR euAR ceftaAR croAR bjrAR (ldistAR lpopexAR
lpopimAR lgdpimAR lgdpexAR = combordAR QlpopiAR1 QlpopeAR1 QlgdpimAR1
QlgdpexAR1), re
.hausman
 Test:  Ho:  difference in coefficients not systematic

                chi2( 12) = (b-B)'[(V_b-V_B)^(-1)](b-B)
                          =    -2.74    chi2<0 ==> model estimated on these
                                        data fails to meet the asymptotic
                                        assumptions of the Hausman test.

Thanks a lot for all  suggestions.
Best regards,
Radmila

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