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Augmented Mean Group (AMG) 推定量の概要×Common Correlated Effects Mean Group (CCEMG) 推定手法×最小二乗法 (OLS) 回帰×
分野計量経済学計量経済学計量経済学
系統Regression modelRegression modelRegression model
提唱年201020062019
提唱者Eberhardt & Teal; Bond & EberhardtM. Hashem PesaranWooldridge (textbook treatment); classical least squares
種類Heterogeneous panel data estimatorHeterogeneous panel estimatorLinear regression
原典Eberhardt, M. & Teal, F. (2010). Productivity Analysis in Global Manufacturing Production. Economics Series Working Papers, No. 515, University of Oxford. link ↗Pesaran, M. H. (2006). Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure. Econometrica, 74(4), 967-1012. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
別名AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)common correlated effects, CCE, CCEMG, Pesaran CCE estimatorordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
関連445
概要The 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 Common Correlated Effects Mean Group estimator, introduced by Pesaran in 2006, is a heterogeneous panel-data estimator that controls for cross-sectional dependence by approximating unobserved common factors with the cross-section averages of the variables. It remains consistent when the slope coefficients differ across units.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGate手法を比較: Augmented Mean Group Estimator · CCEMG Estimator · OLS Regression. 2026-06-19に以下より取得 https://scholargate.app/ja/compare