Regression model
Spatial Error Model (SEM)
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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Sources
- Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI: 10.1007/978-94-015-7799-1 ↗
Related methods
Referenced by
Bayesian Spatial Durbin ModelBayesian Spatial Error ModelBayesian Spatial Panel ModelBayesian Spatial RegressionGeographically Weighted RegressionGlobal Spatial Durbin ModelGlobal Spatial Panel ModelLISALocal Geographically Weighted RegressionLocal Spatial RegressionMGWRMoran's IMultiscale Geographically Weighted RegressionPanel Spatial Error ModelPanel Spatial RegressionSpace-Time Spatial Durbin ModelSpace-Time Spatial Error ModelSpace-Time Spatial Panel ModelSpace-Time Spatial RegressionSpatial Lag ModelSpatial SAC ModelSpatial Sensitivity Analysis for Causality