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Regressioni Apparentemente Non Correlate (SUR)×GMM Sistematico (Arellano-Bover / Blundell-Bond)×
CampoEconometriaEconometria
FamigliaRegression modelRegression model
Anno di origine19621998
IdeatoreArnold ZellnerArellano & Bover (1995); Blundell & Bond (1998)
TipoSystem regression (multi-equation)Dynamic panel data estimator
Fonte seminaleZellner, 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. DOI ↗Arellano, M. & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297. DOI ↗
AliasSUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR)Arellano-Bover estimator, Blundell-Bond estimator, dynamic panel GMM, Sistem GMM (Arellano-Bover / Blundell-Bond)
Correlati54
SintesiSeemingly 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.System GMM is a generalized method of moments estimator for dynamic panel models that contain a lagged dependent variable. Introduced by Blundell and Bond (1998), building on Arellano and Bover, it augments the differenced equation of the earlier difference GMM (Arellano-Bond) with the equation in levels to deliver consistent estimates when N is large and T is small.
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ScholarGateConfronta i metodi: Seemingly Unrelated Regression · System GMM. Consultato il 2026-06-18 da https://scholargate.app/it/compare