Spatial panel data models with common shocks

Spatial effects and common-shocks effects are of increasing empirical importance. Each type of effect has been analyzed separately in a growing literature. This paper considers a joint modeling of both types. Joint modeling allows one to determine whether one or both of these effects are present. A large number of incidental parameters exist under the joint modeling. The quasi maximum likelihood method (MLE) is proposed to estimate the model. Heteroskedasticity is explicitly estimated. This paper demonstrates that the quasi-MLE is effective in dealing with the incidental parameters problem. An inferential theory including consistency, rate of convergence and limiting distributions is developed. The quasi-MLE can be easily implemented via the EM algorithm, as confirmed by the Monte Carlo simulations. The simulations further reveal the excellent finite sample properties of the quasi-MLE. Some extensions are discussed.