A matrix exponential spatial specification

被引:97
作者
LeSage, James P. [1 ]
Pace, R. Kelley
机构
[1] Texas State Univ, McCoy Coll Business Adm, Dept Finance & Econ, San Marcos, TX 78666 USA
[2] Louisiana State Univ, EJ Ourso Coll Business Adm, Dept Finance, Baton Rouge, LA 70803 USA
基金
美国国家科学基金会;
关键词
spatial autoregression; bayesian; maximum likelihood; log-determinants; matrix exponentials; model comparison;
D O I
10.1016/j.jeconom.2006.09.007
中图分类号
F [经济];
学科分类号
02 ;
摘要
We introduce the matrix exponential as a way of modelling spatially dependent data. The matrix exponential spatial specification (MESS) simplifies the log-likelihood allowing a closed form solution to the problem of maximum-likelihood estimation, and greatly simplifies the Bayesian estimation of the model. The MESS can produce estimates and inferences similar to those from conventional spatial autoregressive models, but has analytical, computational, and interpretive advantages. We present maximum likelihood and Bayesian approaches to the estimation of this spatial model specification along with methods of model comparisons over different explanatory variables and spatial specifications. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:190 / 214
页数:25
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