A generalized moments estimator for the autoregressive parameter in a spatial model

被引:808
作者
Kelejian, HH [1 ]
Prucha, IR [1 ]
机构
[1] Univ Maryland, College Pk, MD 20742 USA
关键词
D O I
10.1111/1468-2354.00027
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
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页码:509 / 533
页数:25
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