Comparer des méthodes

	Régression spatiale (modèles de retard spatial et d'erreur spatiale)	Régression à seuil
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1988	2000
Auteur d'origine	Luc Anselin	Bruce E. Hansen
Type	Spatial regression (cross-sectional)	Nonlinear regime-switching regression
Source fondatrice	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers.	Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603.
Alias	spatial econometrics, spatial lag model, spatial error model, SAR / SEM	threshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression)
Apparentées	5	5
Résumé	Spatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term.	Threshold regression is a nonlinear, regime-switching model in which the regression parameters take different values above and below an estimated threshold value of a threshold variable. The sample-splitting and threshold-estimation framework was developed by Bruce E. Hansen (2000) and is widely used for time-series and panel data with structural breaks and regime-dependent relationships.