Methoden vergleichen

	Global Spatial Durbin Model (SDM)	Global Spatial Error Model
Fachgebiet	Räumliche Analyse	Räumliche Analyse
Familie	Regression model	Regression model
Entstehungsjahr	2009	1988
Urheber	Durbin (1960); adapted to spatial context by LeSage & Pace (2009)	Luc Anselin
Typ	Spatial regression model	Spatial regression model
Wegweisende Quelle	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737322
Aliasnamen	SDM, Spatial Durbin Model, global SDM, spatially lagged X model with spatial lag	SEM, spatial error model, spatial error regression, global SEM
Verwandt	5	5
Zusammenfassung	The 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 Global Spatial Error Model (SEM) is a spatial regression technique that accounts for spatially autocorrelated error terms using a single, globally constant spatial parameter. It separates genuine predictor effects from spatial nuisance dependence in the residuals, yielding unbiased and efficient coefficient estimates when spatial error correlation is present across all observations.