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Panelkointegrationstester (Pedroni, Kao, Westerlund)×Augmented Mean Group (AMG) skattare×Vanligaste minsta kvadratmetoden (OLS) Regression×
ÄmnesområdeEkonometriEkonometriEkonometri
FamiljRegression modelRegression modelRegression model
Ursprungsår200420102019
UpphovspersonPedroni; Kao; WesterlundEberhardt & Teal; Bond & EberhardtWooldridge (textbook treatment); classical least squares
TypPanel cointegration testHeterogeneous panel data estimatorLinear regression
UrsprungskällaPedroni, 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 ↗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: 978-1337558860
AliasPedroni cointegration test, Kao cointegration test, Westerlund cointegration test, panel long-run equilibrium testsAMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Närliggande345
SammanfattningPanel 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.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).
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ScholarGateJämför metoder: Panel Cointegration Tests · Augmented Mean Group Estimator · OLS Regression. Hämtad 2026-06-18 från https://scholargate.app/sv/compare