On top of the mechanical problems discussed by Austin and Jeff, I
would like to remind that logit with dummy variables is not the same
as conditional logit (although on most occasions the results that are
quite similar). Conditional logit truly excludes the panel effects out
of estimation, so Stata's bootstrap won't have any problems like
"Oops... I dropped this variable because of multicollinearity... WHAT
HAVE I JUST DONE? I CANNOT ESTIMATE THIS PARAMETER ANYMORE!!!" (shown
as "x" in the -bootstrap- output when a useful option -dots- is
specified). Logit with dummy variables is... well, it is a logit with
dummy variables. It is not a panel data command. -xtlogit-, to my
understanding, is identical to -clogit-. In your context, it only
estimates one parameter (the slope of the January temperature), so it
does not run into identification problems.
Furthermore, there should be little difference of the bootstrap
standard errors from -logit ..., cluster(division)-. If there is a big
difference between the standard errors obtained from
linearization/-cluster- option calculation, on one hand, and
-bootstrap-, on the other, I won't trust either of them. The two types
of standard errors work under pretty much the same assumptions
(whatever warrants the asymptotic normality of the estimates as the
number of clusters goes to infinity), so if they are wildly different,
then those assumptions are likely not met (or you have not set up your
bootstrap right).
On Thu, Aug 27, 2009 at 4:53 PM, L S<[email protected]> wrote:
> I am trying to perform a clustered bootstrap in which I also include
> fixed effects for the variable serving as the cluster identifier. For
> cross-sectional data on individuals in different states, I would like
> to do a bootstrap that clusters by state, but also includes state
> fixed effects.
--
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.
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