مقایسهٔ روش‌ها

	رگرسیون فضایی (مدل‌های وقفه فضایی و خطای فضایی)	رگرسیون‌های ظاهراً نامرتبط (SUR)
حوزه	اقتصادسنجی	اقتصادسنجی
خانواده	Regression model	Regression model
سال پیدایش	1988	1962
پدیدآور	Luc Anselin	Arnold Zellner
نوع	Spatial regression (cross-sectional)	System regression (multi-equation)
منبع بنیادین	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers.	Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348-368.
نام‌های دیگر	spatial econometrics, spatial lag model, spatial error model, SAR / SEM	SUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR)
مرتبط	5	5
خلاصه	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.	Seemingly Unrelated Regressions, introduced by Arnold Zellner in 1962, is a system regression method that estimates several linear equations jointly when their error terms are correlated across equations. By exploiting that cross-equation correlation through generalized least squares, it is more efficient than estimating each equation separately by OLS.