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Динамички Обични Најмањи Квадрати (DOLS) Естиматор×Augmented Mean Group (AMG) estimator×Regresija običnih najmanjih kvadrata (OLS)×Panel Cointegration Tests (Pedroni, Kao, Westerlund)×
OblastEkonometrijaEkonometrijaEkonometrijaEkonometrija
PorodicaRegression modelRegression modelRegression modelRegression model
Godina nastanka1993201020192004
TvoracStock & Watson (1993); panel extension Kao & Chiang (2001)Eberhardt & Teal; Bond & EberhardtWooldridge (textbook treatment); classical least squaresPedroni; Kao; Westerlund
TipCointegrating regression estimatorHeterogeneous panel data estimatorLinear regressionPanel cointegration test
Temeljni izvorStock, 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 ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Pedroni, P. (2004). Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis. Econometric Theory, 20(3), 597–625. DOI ↗
Drugi naziviDOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS)AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuPedroni cointegration test, Kao cointegration test, Westerlund cointegration test, panel long-run equilibrium tests
Srodne5453
SažetakDynamic 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.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).Panel cointegration tests check whether a set of integrated variables share a stable long-run equilibrium relationship across a panel of cross-sectional units. Pedroni (1999, 2004) provides heterogeneous-panel tests with seven statistics, Kao (1999) gives an ADF-based homogeneous-panel test, and Westerlund (2007) adds error-correction-based tests robust to structural breaks and cross-sectional dependence.
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ScholarGateUporedite metode: Dynamic OLS · Augmented Mean Group Estimator · OLS Regression · Panel Cointegration Tests. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare