Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Оцінювач Fully Modified OLS (FMOLS)× | Тест меж ARDL (Тест меж Pesaran)× | Оцінювач загальних корельованих ефектів групи середніх (CCEMG)× | |
|---|---|---|---|
| Галузь | Економетрика | Економетрика | Економетрика |
| Родина | Regression model | Regression model | Regression model |
| Рік появи≠ | 1990 | 2001 | 2006 |
| Автор методу≠ | Phillips & Hansen (time series); Pedroni (heterogeneous panels) | Pesaran, Shin & Smith | M. Hashem Pesaran |
| Тип≠ | Cointegrating regression estimator | Cointegration test / Autoregressive distributed lag model | Heterogeneous panel estimator |
| Основоположне джерело≠ | Phillips, P. C. B. & Hansen, B. E. (1990). Statistical Inference in Instrumental Variables Regression with I(1) Processes. Review of Economic Studies, 57(1), 99–125. DOI ↗ | 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 ↗ |
| Інші назви≠ | fully modified OLS, Phillips-Hansen FMOLS, Tam Düzeltilmiş OLS (FMOLS) | Pesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test) | common correlated effects, CCE, CCEMG, Pesaran CCE estimator |
| Пов'язані≠ | 5 | 4 | 4 |
| Підсумок≠ | Fully Modified OLS, introduced by Phillips and Hansen (1990), estimates the long-run coefficients of a cointegrating relationship among I(1) variables. It applies a semi-parametric correction to ordinary least squares to remove the bias that endogeneity and serial correlation otherwise induce in cointegrated time series or panel data. | 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. |
| ScholarGateНабір даних ↗ |
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