Title:      Problematic Choices: Testing for Correlated Unit
Specific Effects in Panel Data

Authors:    Vera Troeger

Entrydate:  2008-07-07 21:29:33

Keywords:   

Abstract:   The (generalized) Hausman specification test
(Hausman 1978) is the gold-standard for political scientists
using time-series cross-section data to check whether unit
specific effects are correlated with right-hand-side variables.
More than 500 articles (published in SSCI journals) over the
last 20 years in Economics and Political Science used the
Hausman test to justify the model choice, e.g. whether to employ
a fixed effects or random effects/ pooled OLS specification. The
asymptotic properties of the Hausman test and its variants are
well known and formal power analyses have shown that the Hausman
test performs reasonably well. Yet, the differences in the
estimates of fixed effects and random effects models in finite
samples can originate from two different sources: On the one
hand, the Hausman test might rightly pick up differences that
are caused by the inconsistency of the random effects estimator
if unit specific effects are correlated with any of the
explanatory variables and the random effects model therefore
produces biased coefficients. On the other hand, differences
might also stem from the inefficiency of the fixed effects
estimator if explanatory variables are rarely changing and
therefore only have a very small within variation. This
inefficiency does not only lead to large standard errors but
also to very unreliable point estimates that might be far away
from the true relationship. While the Hausman test (and
especially more recent variants and augmentations of the
specification test) acknowledge the inefficiency of the fixed
effects model and control for the differences in the asymptotic
variances of the two estimators, this inefficiency in
combination with correlated unit effects might still lead to
unreliable test results. In International Relations and
International and Comparative Political Economy where many of
our explanatory variables measure institutions which do not
change much over time this result might be especially harmful
since the fixed effects model in this case produces very
unreliable point estimates. 
This paper analyses the finite sample properties and power of
the Hausman specification test by using Monte Carlo experiments.
It shows under what conditions, e.g. the size of the correlation
between unit specific effects and explanatory variables, and the
between-within variance ratio of right-hand-side variables, the
Hausman test generates misleading results. 


http://polmeth.wustl.edu/retrieve.php?id=795

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