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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
来源:
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.
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页码:101 / 127
页数:27
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