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

Program in Economics, The Graduate School and University Center, The City University of New York, New York, NY 10016, USA
Academic Editor: Giuseppe Arbia
Econometrics 2015, 3(1), 101-127; https://doi.org/10.3390/econometrics3010101
Received: 14 October 2014 / Accepted: 27 January 2015 / Published: 26 February 2015
(This article belongs to the Special Issue Spatial Econometrics)
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. View Full-Text
Keywords: spatial dependence; spatial moving average; spatial autoregressive; maximum likelihood estimator; MLE; asymptotics; heteroskedasticity; SARMA(1,1) spatial dependence; spatial moving average; spatial autoregressive; maximum likelihood estimator; MLE; asymptotics; heteroskedasticity; SARMA(1,1)
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Doğan, O. Heteroskedasticity of Unknown Form in Spatial Autoregressive Models with a Moving Average Disturbance Term. Econometrics 2015, 3, 101-127.

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