A SPATIAL DYNAMIC PANEL DATA MODEL WITH BOTH TIME AND INDIVIDUAL FIXED EFFECTS

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 7 can be large. We propose a data transformation approach to eliminate the time effects. When n/T --> 0, the estimators are root nT consistent and asymptotically centered normal; when n is asymptotically proportional to T, they are root nT consistent and asymptotically normal, but the limit distribution is not centered around 0; when n/T --> infinity, the estimators are consistent with rate T and have a degenerate limit distribution. We also propose a bias correction for our estimators. When n(1/3)/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.