Heteroskedasticity of unknown form in spatial autoregressive models with a moving average disturbance term

Osman Doğan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)101-127
Number of pages27
JournalEconometrics
Volume3
Issue number1
DOIs
Publication statusPublished - Mar 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 by the author; licensee MDPI, Basel, Switzerland.

Keywords

  • Asymptotics
  • Heteroskedasticity
  • MLE
  • Maximum likelihood estimator
  • SARMA(1, 1)
  • Spatial autoregressive
  • Spatial dependence
  • Spatial moving average

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