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Estimador de Mínimos Quadrados Ordinários Dinâmicos (DOLS)×Estimador Augmented Mean Group (AMG)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem19932010
Autor originalStock & Watson (1993); panel extension Kao & Chiang (2001)Eberhardt & Teal; Bond & Eberhardt
TipoCointegrating regression estimatorHeterogeneous panel data estimator
Fonte seminalStock, J. H. & Watson, M. W. (1993). A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems. Econometrica, 61(4), 783–820. DOI ↗Eberhardt, M. & Teal, F. (2010). Productivity Analysis in Global Manufacturing Production. Economics Series Working Papers, No. 515, University of Oxford. link ↗
Outros nomesDOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS)AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)
Relacionados54
ResumoDynamic OLS is a cointegrating-regression estimator introduced by Stock and Watson (1993) that recovers the long-run relationship between I(1) variables. It augments the static regression with leads and lags of the differenced regressors, correcting endogeneity bias parametrically so that the long-run coefficient can be estimated by ordinary least squares.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.
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ScholarGateComparar métodos: Dynamic OLS · Augmented Mean Group Estimator. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare