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Empirical likelihood for spatial dynamic panel data models

Spatial dynamic panel data (SDPD) models have received great attention in economics in recent 10 years. Existing approaches for the estimation and test of SDPD models are quasi-maximum likelihood (QML) approach and generalized method of moments (GMM). In this article, we introduce the empirical like...

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Detalles Bibliográficos
Autores principales: Li, Yinghua, Qin, Yongsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479273/
https://www.ncbi.nlm.nih.gov/pubmed/34602835
http://dx.doi.org/10.1007/s42952-021-00150-4
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author Li, Yinghua
Qin, Yongsong
author_facet Li, Yinghua
Qin, Yongsong
author_sort Li, Yinghua
collection PubMed
description Spatial dynamic panel data (SDPD) models have received great attention in economics in recent 10 years. Existing approaches for the estimation and test of SDPD models are quasi-maximum likelihood (QML) approach and generalized method of moments (GMM). In this article, we introduce the empirical likelihood (EL) method to the statistical inference for SDPD models. The EL ratio statistics are constructed for the parameters of spatial dynamic panel data models. It is shown that the limiting distributions of the empirical likelihood ratio statistics are chi-squared distributions, which are used to construct confidence regions for the parameters of the models. Simulation results show that the EL based confidence regions outperform the normal approximation based confidence regions.
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spelling pubmed-84792732021-09-29 Empirical likelihood for spatial dynamic panel data models Li, Yinghua Qin, Yongsong J Korean Stat Soc Research Article Spatial dynamic panel data (SDPD) models have received great attention in economics in recent 10 years. Existing approaches for the estimation and test of SDPD models are quasi-maximum likelihood (QML) approach and generalized method of moments (GMM). In this article, we introduce the empirical likelihood (EL) method to the statistical inference for SDPD models. The EL ratio statistics are constructed for the parameters of spatial dynamic panel data models. It is shown that the limiting distributions of the empirical likelihood ratio statistics are chi-squared distributions, which are used to construct confidence regions for the parameters of the models. Simulation results show that the EL based confidence regions outperform the normal approximation based confidence regions. Springer Nature Singapore 2021-09-29 2022 /pmc/articles/PMC8479273/ /pubmed/34602835 http://dx.doi.org/10.1007/s42952-021-00150-4 Text en © Korean Statistical Society 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Li, Yinghua
Qin, Yongsong
Empirical likelihood for spatial dynamic panel data models
title Empirical likelihood for spatial dynamic panel data models
title_full Empirical likelihood for spatial dynamic panel data models
title_fullStr Empirical likelihood for spatial dynamic panel data models
title_full_unstemmed Empirical likelihood for spatial dynamic panel data models
title_short Empirical likelihood for spatial dynamic panel data models
title_sort empirical likelihood for spatial dynamic panel data models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479273/
https://www.ncbi.nlm.nih.gov/pubmed/34602835
http://dx.doi.org/10.1007/s42952-021-00150-4
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AT qinyongsong empiricallikelihoodforspatialdynamicpaneldatamodels