You are right. It does not matter which year you leave out. If you don't
include a common intercept, you need to include all the year dummies.
Kosuke
On Fri, 4 Apr 2003, Anna Lorien Nelson wrote:
I think (but somebody correct me if I'm wrong!)
that it doesn't really
matter which year you leave out -- that year just becomes the baseline,
and then the dummies tell you how different the observed data is in every
other year compared to the baseline year. On generalized least squares
(which is basically OLS, I think) with panel specific process, see Beck
and Katz 1995. (I don't remember the rest of the citation, but it's an
article you can find on JStor in the poli sci journals).
Anna
On Fri, 4 Apr 2003 efrat(a)fas.harvard.edu wrote:
Hi all,
In the article I'm replicating the data were analyzed in Stata
using "generalized least squares corrected for first order autocorrelation
using panel specific process". What does it mean and how is it done in R?
The author although inclues "a set of 26 dummy variables, one for each year
covered by the data (1971-1997) *less one* to mitigate autocorrelation". So
which dummy should not be included when correcting autocorrelation? The one
for 1997?
Thanks,
Asif
_______________________________________________
gov2001-l mailing list
gov2001-l(a)fas.harvard.edu
http://www.fas.harvard.edu/mailman/listinfo/gov2001-l
_______________________________________________
gov2001-l mailing list
gov2001-l(a)fas.harvard.edu
http://www.fas.harvard.edu/mailman/listinfo/gov2001-l