Regression model
Spatial Lag Model (SAR / Spatial Autoregressive)
The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts.
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Sources
- Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI: 10.1007/978-94-015-7799-1 ↗
- LeSage, J. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. DOI: 10.1201/9781420064254 ↗
Related methods
Referenced by
Bayesian Geographically Weighted RegressionBayesian Multiscale Geographically Weighted RegressionBayesian Spatial Durbin ModelBayesian Spatial Lag ModelBayesian Spatial Panel ModelBayesian Spatial RegressionGeary's CGeographically Weighted Random ForestGeographically Weighted RegressionGetis-Ord Gi*Global Spatial Durbin ModelGlobal Spatial Panel ModelLISALocal Geographically Weighted RegressionLocal Spatial Lag ModelLocal Spatial RegressionMGWRMoran's IMultiscale Geographically Weighted RegressionNetwork EconometricsPanel Spatial Durbin ModelPanel Spatial Error ModelPanel Spatial RegressionRobust Universal KrigingSpace-Time Spatial AutocorrelationSpace-Time Spatial Durbin ModelSpace-Time Spatial Lag ModelSpace-Time Spatial Panel ModelSpace-Time Spatial RegressionSpatial Difference-in-DifferencesSpatial Error ModelSpatial SAC ModelSpatial Sensitivity Analysis for Causality