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동적 최소제곱추정량 (Dynamic Ordinary Least Squares (DOLS) Estimator)×증강 평균 그룹 (Augmented Mean Group, AMG) 추정량×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도19932010
창시자Stock & Watson (1993); panel extension Kao & Chiang (2001)Eberhardt & Teal; Bond & Eberhardt
유형Cointegrating regression estimatorHeterogeneous panel data estimator
원전Stock, 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 ↗
별칭DOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS)AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)
관련54
요약Dynamic 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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ScholarGate방법 비교: Dynamic OLS · Augmented Mean Group Estimator. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare