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Global Spatial Durbin Model (SDM)×Spatial Error Model (SEM)×
ÄmnesområdeRumslig analysRumslig analys
FamiljRegression modelRegression model
Ursprungsår20091988
UpphovspersonDurbin (1960); adapted to spatial context by LeSage & Pace (2009)Anselin
TypSpatial regression modelSpatial regression (spatially autocorrelated errors)
UrsprungskällaLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗
AliasSDM, Spatial Durbin Model, global SDM, spatially lagged X model with spatial lagSEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
Närliggande55
SammanfattningThe Global Spatial Durbin Model extends the spatial lag model by including not only a spatially lagged dependent variable but also spatially lagged independent variables (WX). A single set of global coefficients applies uniformly across all locations, making it suitable for estimating average spillover effects when spatial dependence is pervasive throughout the study region.The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares.
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ScholarGateJämför metoder: Global Spatial Durbin Model · Spatial Error Model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare