Порівняння методів

	Оцінювач динамічних звичайних найменших квадратів (DOLS)	Оцінювач загальних корельованих ефектів групи середніх (CCEMG)	Регресія звичайно найменших квадратів (ЗНК)	Тести на коінтеграцію в панельних даних (Pedroni, Kao, Westerlund)
Галузь	Економетрика	Економетрика	Економетрика	Економетрика
Родина	Regression model	Regression model	Regression model	Regression model
Рік появи	1993	2006	2019	2004
Автор методу	Stock & Watson (1993); panel extension Kao & Chiang (2001)	M. Hashem Pesaran	Wooldridge (textbook treatment); classical least squares	Pedroni; Kao; Westerlund
Тип	Cointegrating regression estimator	Heterogeneous panel estimator	Linear regression	Panel cointegration test
Основоположне джерело	Stock, J. H. & Watson, M. W. (1993). A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems. Econometrica, 61(4), 783–820.	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.
Інші назви	DOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS)	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
Пов'язані	5	4	5	3
Підсумок	Dynamic 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 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.