Methoden vergleichen

	Common Correlated Effects Mean Group (CCEMG) Schätzer	Methode der kleinsten Quadrate (OLS)	Panel-Kointegrationstests (Pedroni, Kao, Westerlund)	Paneldaten-Fixed-Effects-Modell
Fachgebiet	Ökonometrie	Ökonometrie	Ökonometrie	Ökonometrie
Familie	Regression model	Regression model	Regression model	Regression model
Entstehungsjahr	2006	2019	2004	2014
Urheber	M. Hashem Pesaran	Wooldridge (textbook treatment); classical least squares	Pedroni; Kao; Westerlund	Hsiao (textbook treatment); within transformation of panel data
Typ	Heterogeneous panel estimator	Linear regression	Panel cointegration test	Panel data regression
Wegweisende Quelle	Pesaran, M. H. (2006). Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure. Econometrica, 74(4), 967-1012.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	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.	Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press.
Aliasnamen	common correlated effects, CCE, CCEMG, Pesaran CCE estimator	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	Pedroni cointegration test, Kao cointegration test, Westerlund cointegration test, panel long-run equilibrium tests	fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Verwandt	4	5	3	5
Zusammenfassung	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.	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.	The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).