PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects

This article deals with asymmetrical spatial data which can be modeled by a partially linear varying coefficient spatial autoregressive panel model (PLVCSARPM) with random effects. We constructed its profile quasi-maximum likelihood estimators (PQMLE). The consistency and asymptotic normality of the...

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Autores principales: Shuangshuang Li, Jianbao Chen, Danqing Chen
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/24e810e88aba4ba89bc00cb5b7e26ea7
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spelling oai:doaj.org-article:24e810e88aba4ba89bc00cb5b7e26ea72021-11-25T19:06:23ZPQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects10.3390/sym131120572073-8994https://doaj.org/article/24e810e88aba4ba89bc00cb5b7e26ea72021-11-01T00:00:00Zhttps://www.mdpi.com/2073-8994/13/11/2057https://doaj.org/toc/2073-8994This article deals with asymmetrical spatial data which can be modeled by a partially linear varying coefficient spatial autoregressive panel model (PLVCSARPM) with random effects. We constructed its profile quasi-maximum likelihood estimators (PQMLE). The consistency and asymptotic normality of the estimators were proved under some regular conditions. Monte Carlo simulations implied our estimators have good finite sample performance. Finally, a set of asymmetric real data applications was analyzed for illustrating the performance of the provided method.Shuangshuang LiJianbao ChenDanqing ChenMDPI AGarticlePLVCSARPMPQMLEconsistency asymptotic normalityMonte Carlo simulationasymmetric dataMathematicsQA1-939ENSymmetry, Vol 13, Iss 2057, p 2057 (2021)
institution DOAJ
collection DOAJ
language EN
topic PLVCSARPM
PQMLE
consistency asymptotic normality
Monte Carlo simulation
asymmetric data
Mathematics
QA1-939
spellingShingle PLVCSARPM
PQMLE
consistency asymptotic normality
Monte Carlo simulation
asymmetric data
Mathematics
QA1-939
Shuangshuang Li
Jianbao Chen
Danqing Chen
PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects
description This article deals with asymmetrical spatial data which can be modeled by a partially linear varying coefficient spatial autoregressive panel model (PLVCSARPM) with random effects. We constructed its profile quasi-maximum likelihood estimators (PQMLE). The consistency and asymptotic normality of the estimators were proved under some regular conditions. Monte Carlo simulations implied our estimators have good finite sample performance. Finally, a set of asymmetric real data applications was analyzed for illustrating the performance of the provided method.
format article
author Shuangshuang Li
Jianbao Chen
Danqing Chen
author_facet Shuangshuang Li
Jianbao Chen
Danqing Chen
author_sort Shuangshuang Li
title PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects
title_short PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects
title_full PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects
title_fullStr PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects
title_full_unstemmed PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects
title_sort pqmle of a partially linear varying coefficient spatial autoregressive panel model with random effects
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/24e810e88aba4ba89bc00cb5b7e26ea7
work_keys_str_mv AT shuangshuangli pqmleofapartiallylinearvaryingcoefficientspatialautoregressivepanelmodelwithrandomeffects
AT jianbaochen pqmleofapartiallylinearvaryingcoefficientspatialautoregressivepanelmodelwithrandomeffects
AT danqingchen pqmleofapartiallylinearvaryingcoefficientspatialautoregressivepanelmodelwithrandomeffects
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