Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects

This paper studies the variable selection of high-dimensional spatial autoregressive panel models with fixed effects in which a matrix transformation method is applied to eliminate the fixed effects. Then, a penalized quasi-maximum likelihood is developed for variable selection and parameter estimat...

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Main Authors: Miaojie Xia, Yuqi Zhang, Ruiqin Tian
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2023/9837117
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author Miaojie Xia
Yuqi Zhang
Ruiqin Tian
author_facet Miaojie Xia
Yuqi Zhang
Ruiqin Tian
author_sort Miaojie Xia
collection DOAJ
description This paper studies the variable selection of high-dimensional spatial autoregressive panel models with fixed effects in which a matrix transformation method is applied to eliminate the fixed effects. Then, a penalized quasi-maximum likelihood is developed for variable selection and parameter estimation in the transformed panel model. Under some regular conditions, the consistency and oracle properties of the proposed estimator are established. Some Monte-Carlo experiments and a real data analysis are conducted to examine the finite sample performance of the proposed variable selection procedure, showing that the proposed variable selection method works satisfactorily.
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institution Kabale University
issn 2314-4785
language English
publishDate 2023-01-01
publisher Wiley
record_format Article
series Journal of Mathematics
spelling doaj-art-e933fa6ea9c2424c9b5909cb55ac13c22025-02-03T06:47:21ZengWileyJournal of Mathematics2314-47852023-01-01202310.1155/2023/9837117Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed EffectsMiaojie Xia0Yuqi Zhang1Ruiqin Tian2School of MathematicsSchool of MathematicsSchool of MathematicsThis paper studies the variable selection of high-dimensional spatial autoregressive panel models with fixed effects in which a matrix transformation method is applied to eliminate the fixed effects. Then, a penalized quasi-maximum likelihood is developed for variable selection and parameter estimation in the transformed panel model. Under some regular conditions, the consistency and oracle properties of the proposed estimator are established. Some Monte-Carlo experiments and a real data analysis are conducted to examine the finite sample performance of the proposed variable selection procedure, showing that the proposed variable selection method works satisfactorily.http://dx.doi.org/10.1155/2023/9837117
spellingShingle Miaojie Xia
Yuqi Zhang
Ruiqin Tian
Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects
Journal of Mathematics
title Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects
title_full Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects
title_fullStr Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects
title_full_unstemmed Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects
title_short Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects
title_sort variable selection of high dimensional spatial autoregressive panel models with fixed effects
url http://dx.doi.org/10.1155/2023/9837117
work_keys_str_mv AT miaojiexia variableselectionofhighdimensionalspatialautoregressivepanelmodelswithfixedeffects
AT yuqizhang variableselectionofhighdimensionalspatialautoregressivepanelmodelswithfixedeffects
AT ruiqintian variableselectionofhighdimensionalspatialautoregressivepanelmodelswithfixedeffects