Heteroskedasticity of Unknown Form in Spatial Autoregressive Models with a Moving Average Disturbance Term

被引:4
|
作者
Dogan, Osman [1 ]
机构
[1] CUNY, Program Econ, Grad Sch & Univ Ctr, New York, NY 10016 USA
关键词
spatial dependence; spatial moving average; spatial autoregressive; maximum likelihood estimator; MLE; asymptotics; heteroskedasticity; SARMA(1,1);
D O I
10.3390/econometrics3010101
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this study, I investigate the necessary condition for the consistency of the maximum likelihood estimator (MLE) of spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive and spatial moving average parameters is generally inconsistent when heteroskedasticity is not considered in the estimation. I also show that the MLE of parameters of exogenous variables is inconsistent and determine its asymptotic bias. I provide simulation results to evaluate the performance of the MLE. The simulation results indicate that the MLE imposes a substantial amount of bias on both autoregressive and moving average parameters.
引用
收藏
页码:101 / 127
页数:27
相关论文
共 50 条