Ghislain Dutheil replied:
> the two model give results quite different : in one case (FGLS) an
> explonary variable is significative in the other, PCSE, it is not, and i
> have only two explonary variables... so the difference is sensible . So
> excuse me but why cross-sectional GLS estimates is pretty unreliable
> compare to OLS-PCSE ?
Since you neither show us any output from your models nor explain what
these models seek to explain theoretically, there really is no way of
judging how 'sensible' your results are. Only you will know.
Much depends on how much contemporaneous correlation of the errors
there is in your data. If you have lots, and T > N by a factor of 3 or
more (which you have), then FGLS estimates should be okay. If you
don't have much by way of CCEs, then OLS-PCSE is to be preferred; see
the whole of Beck and Katz (1995). In most panel data (T > 50 is not
typical), the paramter estimates are inefficient under FGLS: "The FGLS
standard errors underestimate sampling variability because FGLS
assumes that \sigma [the N x N matrix of contemporaneous covariances]
is known, not estimated. Our conclusion is that the Parks-Kmenta
[FGLS] estimator simply should not be used" (Beck, 2001).
However, you _still_ haven't really told us about your data. We're
still left to assume that your units are countries (which would rule
out -bootstrap-ping or -simulate-ing your way out of any
difficulties), that your Ts are equidistantly spaced, and that your
response variable is normally distributed. If your RV isn't, then none
of the modelling approaches mentioned in this thread may be useful for
fitting to your data.
--
Clive Nicholas
[Please DO NOT mail me personally here, but at
<[email protected]>. Please respond to contributions I make in
a list thread here. Thanks!]
Beck N (2001) "Time-Series Cross-Section Data: What Have We Learned in
the Past Few Years", _Annual Review of Political Science_ 4: 271-93.
Beck N and Katz JN (1995) "What To Do (and Not To Do) With Time-Series
Cross-Section Data", _American Political Science Review_ 89 (3):
634-47.
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