A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model
针对空间自相关模型中的自回归参数，提出一种计算简单的广义矩估计量，并给出其大样本和小样本性质，适用于中等或大样本数据。
This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed in this paper, the (quasi) maximum likelihood estimator may not be computationally feasible in many cases involving moderate‐ or large‐sized samples. In this paper we suggest a generalized moments estimator that is computationally simple irrespective of the sample size. We provide results concerning the large and small sample properties of this estimator.