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DOLS (Dynamic Ordinary Least Squares) novērtēšanas rīks×Augmented Mean Group (AMG) novērtētājs×Kopējo saistīto efektu vidējās grupas (CCEMG) novērtētājs×Paneļa kointegrācijas testi (Pedroni, Kao, Westerlund)×
NozareEkonometrijaEkonometrijaEkonometrijaEkonometrija
SaimeRegression modelRegression modelRegression modelRegression model
Izcelsmes gads1993201020062004
AutorsStock & Watson (1993); panel extension Kao & Chiang (2001)Eberhardt & Teal; Bond & EberhardtM. Hashem PesaranPedroni; Kao; Westerlund
TipsCointegrating regression estimatorHeterogeneous panel data estimatorHeterogeneous panel estimatorPanel cointegration test
PirmavotsStock, 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 ↗Pesaran, M. H. (2006). Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure. Econometrica, 74(4), 967-1012. DOI ↗Pedroni, 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 ↗
Citi nosaukumiDOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS)AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)common correlated effects, CCE, CCEMG, Pesaran CCE estimatorPedroni cointegration test, Kao cointegration test, Westerlund cointegration test, panel long-run equilibrium tests
Saistītās5443
KopsavilkumsDynamic 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.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.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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ScholarGateSalīdzināt metodes: Dynamic OLS · Augmented Mean Group Estimator · CCEMG Estimator · Panel Cointegration Tests. Izgūts 2026-06-19 no https://scholargate.app/lv/compare