Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Тест меж ARDL (Тест меж Pesaran)× | Оцінювач загальних корельованих ефектів групи середніх (CCEMG)× | Оцінювач динамічних звичайних найменших квадратів (DOLS)× | |
|---|---|---|---|
| Галузь | Економетрика | Економетрика | Економетрика |
| Родина | Regression model | Regression model | Regression model |
| Рік появи≠ | 2001 | 2006 | 1993 |
| Автор методу≠ | Pesaran, Shin & Smith | M. Hashem Pesaran | Stock & Watson (1993); panel extension Kao & Chiang (2001) |
| Тип≠ | Cointegration test / Autoregressive distributed lag model | Heterogeneous panel estimator | Cointegrating regression estimator |
| Основоположне джерело≠ | Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗ | Pesaran, M. H. (2006). Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure. Econometrica, 74(4), 967-1012. DOI ↗ | Stock, J. H. & Watson, M. W. (1993). A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems. Econometrica, 61(4), 783–820. DOI ↗ |
| Інші назви≠ | Pesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test) | common correlated effects, CCE, CCEMG, Pesaran CCE estimator | DOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS) |
| Пов'язані≠ | 4 | 4 | 5 |
| Підсумок≠ | The ARDL bounds test is an autoregressive distributed lag method that tests for a cointegrating (long-run level) relationship between time series, introduced by Pesaran, Shin and Smith in 2001. Unlike the Johansen procedure, it remains valid whether the variables are I(0), I(1) or a mix of the two, and it is more reliable than Johansen in small samples of roughly 30 to 80 observations. | 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. | 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. |
| ScholarGateНабір даних ↗ |
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