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Regressão Geograficamente Ponderada Multiescala em Painel (Panel MGWR)×Modelo Espacial de Erros em Painel×
ÁreaAnálise espacialAnálise espacial
FamíliaRegression modelRegression model
Ano de origem2017-20201988 / 2003
Autor originalFotheringham, Yang & Kang (MGWR base); panel extension developed in spatial econometrics literatureAnselin (1988); extended to panels by Elhorst (2003, 2014)
TipoSpatially varying coefficient panel regressionSpatial econometric panel model
Fonte seminalFotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale Geographically Weighted Regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265. DOI ↗Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408
Outros nomesPanel MGWR, MGWR panel data, multiscale GWR panel, panel spatially varying coefficient modelpanel SEM, spatial error panel model, panel spatial autocorrelation error model, SEM panel
Relacionados55
ResumoPanel MGWR extends Multiscale Geographically Weighted Regression to repeated-observations (panel) data, allowing each predictor to operate at its own spatial bandwidth while controlling for unit-specific or time-specific fixed effects. It is used when both spatial heterogeneity and temporal structure matter simultaneously.The Panel Spatial Error Model (panel SEM) extends the classical spatial error model to panel data, allowing spatial dependence to enter through the error term across cross-sectional units over multiple time periods. It accounts for spatially correlated omitted variables without imposing a substantive spatial spillover in the outcome itself.
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ScholarGateComparar métodos: Panel Multiscale Geographically Weighted Regression · Panel Spatial Error Model. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare