Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Testul ARDL Bounds (Testul Pesaran Bounds)× | Testul de Cointegrare (Johansen / Engle-Granger)× | Regresia prin metoda celor mai mici pătrate ordinare (OLS)× | |
|---|---|---|---|
| Domeniu | Econometrie | Econometrie | Econometrie |
| Familie | Regression model | Regression model | Regression model |
| Anul apariției≠ | 2001 | 1988 | 2019 |
| Autorul original≠ | Pesaran, Shin & Smith | Engle & Granger (1987); Johansen (1988) | Wooldridge (textbook treatment); classical least squares |
| Tip≠ | Cointegration test / Autoregressive distributed lag model | Time-series cointegration test | Linear regression |
| Sursa seminală≠ | 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 ↗ | Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Denumiri alternative | Pesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test) | Johansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Înrudite≠ | 4 | 5 | 5 |
| Rezumat≠ | 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 cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988). | 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). |
| ScholarGateSet de date ↗ |
|
|
|