Published online by Cambridge University Press: 18 August 2009
This paper establishes asymptotic properties of
quasi-maximum likelihood estimators for spatial
dynamic panel data with both time and individual
fixed effects when the number of individuals
n and the number of time periods
T can be large. We propose a data
transformation approach to eliminate the time
effects. When n / T → 0, the
estimators are consistent and
asymptotically centered normal; when
n is asymptotically proportional
to T, they are
consistent and
asymptotically normal, but the limit distribution is
not centered around 0; when n / T →
∞, the estimators are consistent with rate
T and have a degenerate limit
distribution. We also propose a bias correction for
our estimators. When n1/3 /
T → 0, the correction will
asymptotically eliminate the bias and yield a
centered confidence interval. The estimates from the
transformation approach can be consistent when
n is a fixed finite number.
We thank two anonymous referees and the co-editor Jinyong Hahn for their comments and suggestions for improving this paper. Lee acknowledges financial support from NSF under grant SES-0519204.