A SPATIAL CLIFF-ORD-TYPE MODEL WITH HETEROSKEDASTIC INNOVATIONS: SMALL AND LARGE SAMPLE RESULTS*
提出一个允许因变量、外生变量和扰动项存在空间滞后的线性Cliff-Ord型模型，并假设扰动项具有未知形式的异方差。通过多步GMM/IV方法估计参数，推导了估计量的渐近分布和一致协方差矩阵估计，蒙特卡洛模拟表明大样本分布能很好近似小样本分布。
ABSTRACT In this paper, we specify a linear Cliff-and-Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate multistep GMM/IV-type estimation procedures for the parameters of the model. We also give the limiting distributions for our suggested estimators and consistent estimators for their asymptotic variance-covariance matrices. We conduct a Monte Carlo study to show that the derived large-sample distribution provides a good approximation to the actual small-sample distribution of our estimators.