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| Ước lượng FMOLS (Fully Modified OLS)× | Kiểm định giới hạn ARDL (Kiểm định giới hạn Pesaran)× | Ước lượng Bình phương Tối thiểu Thông thường Động (DOLS)× | |
|---|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model | Regression model |
| Năm ra đời≠ | 1990 | 2001 | 1993 |
| Người khởi xướng≠ | Phillips & Hansen (time series); Pedroni (heterogeneous panels) | Pesaran, Shin & Smith | Stock & Watson (1993); panel extension Kao & Chiang (2001) |
| Loại≠ | Cointegrating regression estimator | Cointegration test / Autoregressive distributed lag model | Cointegrating regression estimator |
| Công trình gốc≠ | 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 ↗ | Stock, J. H. & Watson, M. W. (1993). A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems. Econometrica, 61(4), 783–820. DOI ↗ |
| Tên gọi khác≠ | 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) | DOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS) |
| Liên quan≠ | 5 | 4 | 5 |
| Tóm tắt≠ | 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. | 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. |
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