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Prošireni procjenitelj srednje skupine (AMG)×Model slučajnih efekata za panelne podatke×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20102021
TvoracEberhardt & Teal; Bond & EberhardtBaltagi (textbook treatment); classical random-effects panel estimator
VrstaHeterogeneous panel data estimatorPanel data regression
Temeljni izvorEberhardt, M. & Teal, F. (2010). Productivity Analysis in Global Manufacturing Production. Economics Series Working Papers, No. 515, University of Oxford. link ↗Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. DOI ↗
Drugi naziviAMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)random effects panel model, RE estimator, GLS random effects, Panel Veri — Rassal Etkiler Modeli
Srodne45
SažetakThe Augmented Mean Group estimator, developed by Eberhardt and Teal (2010), is a panel data method for estimating heterogeneous slope coefficients in the presence of cross-sectional dependence. It approximates the unobserved common dynamic process driving all units and folds it into unit-by-unit regressions, then averages the results.The Random Effects model is a panel-data regression that treats unobserved individual heterogeneity as a random component drawn from a common distribution, rather than a separate parameter for each unit. It is a standard estimator in panel econometrics, developed in textbook treatments such as Baltagi's Econometric Analysis of Panel Data (2021).
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ScholarGateUsporedite metode: Augmented Mean Group Estimator · Random Effects Model. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare