A Robust LM Test for Spatial Error Components

This paper presents a modified LM test of spatial error components, which is shown to be robust against distributional misspecifications and spatial layouts. The proposed test differs from the LM test of Anselin (2001) by a term in the denominators of the test statistics. This term disappears when e...

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Main Author: YANG, Zhenlin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/soe_research/1137
https://ink.library.smu.edu.sg/context/soe_research/article/2136/viewcontent/Yang09a.pdf
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spelling sg-smu-ink.soe_research-21362019-04-21T14:58:57Z A Robust LM Test for Spatial Error Components YANG, Zhenlin This paper presents a modified LM test of spatial error components, which is shown to be robust against distributional misspecifications and spatial layouts. The proposed test differs from the LM test of Anselin (2001) by a term in the denominators of the test statistics. This term disappears when either the errors are normal, or the variance of the diagonal elements of the product of spatial weights matrix and its transpose is zero or approaches to zero as sample size goes large. When neither is true, as is often the case in practice, the effect of this term can be significant even when sample size is large. As a result, there can be severe size distortions of the Anselin's LM test, a phenomenon revealed by the Monte Carlo results of Anselin and Moreno (2003) and further confirmed by the Monte Carlo results presented in this paper. Our Monte Carlo results also show that the proposed test performs well in general. 2009-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1137 https://ink.library.smu.edu.sg/context/soe_research/article/2136/viewcontent/Yang09a.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Distributional misspecifications Robustness Spatial layouts Spatial error components LM tests Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Distributional misspecifications
Robustness
Spatial layouts
Spatial error components
LM tests
Econometrics
spellingShingle Distributional misspecifications
Robustness
Spatial layouts
Spatial error components
LM tests
Econometrics
YANG, Zhenlin
A Robust LM Test for Spatial Error Components
description This paper presents a modified LM test of spatial error components, which is shown to be robust against distributional misspecifications and spatial layouts. The proposed test differs from the LM test of Anselin (2001) by a term in the denominators of the test statistics. This term disappears when either the errors are normal, or the variance of the diagonal elements of the product of spatial weights matrix and its transpose is zero or approaches to zero as sample size goes large. When neither is true, as is often the case in practice, the effect of this term can be significant even when sample size is large. As a result, there can be severe size distortions of the Anselin's LM test, a phenomenon revealed by the Monte Carlo results of Anselin and Moreno (2003) and further confirmed by the Monte Carlo results presented in this paper. Our Monte Carlo results also show that the proposed test performs well in general.
format text
author YANG, Zhenlin
author_facet YANG, Zhenlin
author_sort YANG, Zhenlin
title A Robust LM Test for Spatial Error Components
title_short A Robust LM Test for Spatial Error Components
title_full A Robust LM Test for Spatial Error Components
title_fullStr A Robust LM Test for Spatial Error Components
title_full_unstemmed A Robust LM Test for Spatial Error Components
title_sort robust lm test for spatial error components
publisher Institutional Knowledge at Singapore Management University
publishDate 2009
url https://ink.library.smu.edu.sg/soe_research/1137
https://ink.library.smu.edu.sg/context/soe_research/article/2136/viewcontent/Yang09a.pdf
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