Heteroskedasticity of unknown form in spatial autoregressive models with a moving average disturbance term
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.
Year of publication: |
2015
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Authors: | Doğan, Osman |
Published in: |
Econometrics. - Basel : MDPI, ISSN 2225-1146. - Vol. 3.2015, 1, p. 101-127
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Publisher: |
Basel : MDPI |
Subject: | spatial dependence | spatial moving average | spatial autoregressive | maximum likelihood estimator | MLE | asymptotics | heteroskedasticity | SARMA(1,1) |
Saved in:
freely available
Type of publication: | Article |
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Type of publication (narrower categories): | Article |
Language: | English |
Other identifiers: | 10.3390/econometrics3010101 [DOI] 829331468 [GVK] hdl:10419/171819 [Handle] |
Classification: | C13 - Estimation ; C21 - Cross-Sectional Models; Spatial Models ; C31 - Cross-Sectional Models; Spatial Models |
Source: |
Persistent link: https://www.econbiz.de/10011755273