Showing 1 - 10 of 378
The likelihood functions for spatial autoregressive models with normal but heteroskedastic disturbances have been derived [Anselin (1988, ch.6)], but there is no implementation of maximum likelihood estimation for these likelihood functions in general cases with heteroskedastic disturbances....
Persistent link: https://www.econbiz.de/10014194202
We consider a spatial econometric model containing a spatial lag in the dependent variable and the disturbance term with an unknown form of heteroskedasticity in innovations. We first prove that the maximum likelihood (ML) estimator for spatial autoregressive models is generally inconsistent...
Persistent link: https://www.econbiz.de/10014160295
This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and...
Persistent link: https://www.econbiz.de/10013051285
Persistent link: https://www.econbiz.de/10008661869
Persistent link: https://www.econbiz.de/10011478986
Persistent link: https://www.econbiz.de/10011669077
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...
Persistent link: https://www.econbiz.de/10011290741
Persistent link: https://www.econbiz.de/10012131981
Likelihood functions of spatial autoregressive models with normal but heteroskedastic disturbances have been already derived [Anselin (1988, ch.6)]. But there is no implementation for maximum likelihood estimation of these likelihood functions in general (heteroskedastic disturbances) cases....
Persistent link: https://www.econbiz.de/10012171653
Persistent link: https://www.econbiz.de/10012108383