Asymptotic Distributions of Quasi-Maximum Likelihood Estimators

Asymptotic properties of MLEs and QMLEs of mixed regressive, spatial autoregressive models are investigated. The stochastic rates of convergence of the MLE and QMLE for such models may be less than the √ n-rate under some circumstances even though its limiting distribution is asymptotically normal. When spatially varying regressors are relevant, the MLE and QMLE of the mixed regressive, autoregressive model may not have this problem and they can converge at the √ n-rate. If the spatially varying regressors are irrelevant, estimates of various components of unknown parameters may possess different rates of convergence.