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| Stimatore FMOLS (Fully Modified OLS)× | Il test ai limiti ARDL (ARDL Bounds Test)× | Stimatore di Minimi Quadrati Ordinari Dinamici (DOLS)× | |
|---|---|---|---|
| Campo | Econometria | Econometria | Econometria |
| Famiglia | Regression model | Regression model | Regression model |
| Anno di origine≠ | 1990 | 2001 | 1993 |
| Ideatore≠ | Phillips & Hansen (time series); Pedroni (heterogeneous panels) | Pesaran, Shin & Smith | Stock & Watson (1993); panel extension Kao & Chiang (2001) |
| Tipo≠ | Cointegrating regression estimator | Cointegration test / Autoregressive distributed lag model | Cointegrating regression estimator |
| Fonte seminale≠ | 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 ↗ |
| Alias≠ | 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) |
| Correlati≠ | 5 | 4 | 5 |
| Sintesi≠ | 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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