Hi Le,
Concerning your heteroskedasticity test, it doesn't matter whether you
estimate your fixed effects model with model standard error or panel
robust standard errors. The residuals are the same in both
estimations, it's just the covariance matrix estimator (for the
coefficient estimates) that is different.
As Mark already said, you should not rely on
heteroscedasticity-consistent SEs but rather on panel robust SEs as
the former are typically inconsistent. Moreover, I am quite sure that
your panel will exhibit considerable cross-sectional dependence.
Therefore, without performing a test for cross-sectional dependence
with the -xtcsd- command, you can be quite sure that -xtscc , fe-
would produce more appropriate standard error estimates. In fact, you
can check this by estimating both a model with cluster-robust standard
errors and one with Driscoll-Kraay standard errors. If the t-stats
from the latter model are significantly smaller than those of the
former model, then it is very likely that cross-sectional dependence
is present in your dataset. From my experience with similar-sized
microeconometric panel datasets, I would expect that t-stats from
Driscoll-Kraay standard errors are less than half the size of
cluster-robust t-stats.
Unfortunately, the -xtcsd- command depends on Stata's matsize (at
least the version of the command I know). Therefore, you will not be
able to test for cross-sectional dependence in your large-scale
microeconometric panel. However, what you could do is to perform a CD
test on a subset of, say, 1,000 randomly sampled firms (ideally with a
full history of 12 years).
To summarize: I would recommend to base statistical inference on a
fixed effects regression with Driscoll-Kraay standard errors. [Please
apologize for advertising my own program...]
I hope this helps.
Best,
Daniel
--
*******************************************
Daniel Hoechle
Department of Finance
WWZ of the University of Basel
Holbeinstrasse 12
CH-4051 Basel
phone +41 61 267 32 43
email [email protected]
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