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

Abstract

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 individualsnand the number of time periodsTcan be large. We propose a data transformation approach to eliminate the time effects. Whenn / T→ 0, the estimators are$\root \of {nT}$consistent and asymptotically centered normal; whennis asymptotically proportional toT, they are$\root \of {nT}$consistent and asymptotically normal, but the limit distribution is not centered around 0; whenn / T→ ∞, the estimators are consistent with rateTand 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 whennis a fixed finite number.