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The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar

The dynamic general nesting spatial econometric model for spatial panels with common factors is the most advanced model currently available. It accounts for local spatial dependence by means of an endogenous spatial lag, exogenous spatial lags, and a spatial lag in the error term. It accounts for dy...

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Autor principal: Elhorst, J. Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8631700/
http://dx.doi.org/10.1007/s10037-021-00163-w
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author Elhorst, J. Paul
author_facet Elhorst, J. Paul
author_sort Elhorst, J. Paul
collection PubMed
description The dynamic general nesting spatial econometric model for spatial panels with common factors is the most advanced model currently available. It accounts for local spatial dependence by means of an endogenous spatial lag, exogenous spatial lags, and a spatial lag in the error term. It accounts for dynamic effects by means of the dependent variable lagged in time, and the dependent variable lagged in both space and time. Finally, it accounts for global cross-sectional dependence by means of cross-sectional averages or principal components with heterogeneous coefficients, which generalizes the traditional controls for time-invariant and spatial-invariant variables by unit-specific and time-specific effects. This paper provides an overview of the main arguments in favor of each of these model components, as well as some potential pitfalls.
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spelling pubmed-86317002021-12-01 The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar Elhorst, J. Paul Rev Reg Res Original Paper The dynamic general nesting spatial econometric model for spatial panels with common factors is the most advanced model currently available. It accounts for local spatial dependence by means of an endogenous spatial lag, exogenous spatial lags, and a spatial lag in the error term. It accounts for dynamic effects by means of the dependent variable lagged in time, and the dependent variable lagged in both space and time. Finally, it accounts for global cross-sectional dependence by means of cross-sectional averages or principal components with heterogeneous coefficients, which generalizes the traditional controls for time-invariant and spatial-invariant variables by unit-specific and time-specific effects. This paper provides an overview of the main arguments in favor of each of these model components, as well as some potential pitfalls. Springer Berlin Heidelberg 2021-11-30 2022 /pmc/articles/PMC8631700/ http://dx.doi.org/10.1007/s10037-021-00163-w Text en © Springer-Verlag GmbH Germany, part of Springer Nature 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 Original Paper
Elhorst, J. Paul
The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar
title The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar
title_full The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar
title_fullStr The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar
title_full_unstemmed The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar
title_short The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar
title_sort dynamic general nesting spatial econometric model for spatial panels with common factors: further raising the bar
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8631700/
http://dx.doi.org/10.1007/s10037-021-00163-w
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