Compară metode

	Modelul SAC spațial	Modelul de decalaj spațial (SAR / Autoregresiv spațial)
Domeniu	Analiză spațială	Analiză spațială
Familie	Regression model	Regression model
Anul apariției	2009	1988
Autorul original	James LeSage & R. Kelley Pace	Anselin (textbook formalisation); LeSage & Pace
Tip	Combined spatial dependence regression model	Spatial autoregressive regression
Sursa seminală	LeSage, J., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. ISBN: 978-1-4200-6424-7	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
Denumiri alternative	SARAR Model, Spatial Autoregressive Model with Autoregressive Disturbances, Cliff-Ord Combined Model, Uzamsal Otoregresif Birleşik Model	SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
Înrudite	3	5
Rezumat	The Spatial Autoregressive Combined (SAC) model, also known as the SARAR model, simultaneously accounts for spatial dependence in both the dependent variable and the error term. Formalized by LeSage and Pace (2009), the SAC model combines the spatial lag model and the spatial error model into a single framework, estimating two distinct spatial autoregressive parameters — one capturing substantive spatial interaction among outcomes and another capturing residual spatial correlation among disturbances.	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.