All,
First of all, happy new year to all of you!
I wondered if anybody has noticed that, when using -prais-, sometimes the
output model contains t-values that clearly exceed 1.96, but yet show up
as statistically insignificant, even at p<.05 (I don't regard p<.10 as a
particularly useful benchmark for significance testing). Here's an
example, with <enp> the 'offending' variable here:
Cochrane-Orcutt AR(1) regression -- iterated estimates
Regression with robust standard errors Number of obs = 101
F( 5, 20) = 157.58
Prob > F = 0.0000
R-squared = 0.4406
Number of clusters (region) = 21 Root MSE = 12.567
----------------------------------------------------------------------------
| Semi-robust
conpc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------+----------------------------------------------------------------
tuout | .6917606 .172949 4.00 0.001 .3309954 1.052526
incumb | -6.130695 3.487898 -1.76 0.094 -13.40632 1.144932
enp | 8.906969 4.36405 2.04 0.055 -.1962795 18.01022
celtic | -18.91596 2.608885 -7.25 0.000 -24.358 -13.47392
_cons | -27.41839 16.46073 -1.67 0.111 -61.75488 6.91809
-----------+----------------------------------------------------------------
rho | -.0054647
----------------------------------------------------------------------------
Durbin-Watson statistic (original) 2.008198
Durbin-Watson statistic (transformed) 1.996219
Now being a bit thick, I cannot explain this; so is anybody on the list
willing and able to explain why this happens?
Thanks.
CLIVE NICHOLAS |t: 0(44)191 222 5969
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