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| ARDL Bounds Test× | Нелинеен авторегресивен модел с разпределени лагове (NARDL)× | Регресия с праг× | |
|---|---|---|---|
| Област | Иконометрия | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model | Regression model |
| Година на възникване≠ | 2001 | 2014 | 2000 |
| Създател≠ | Pesaran, Shin & Smith | Shin, Yu & Greenwood-Nimmo | Bruce E. Hansen |
| Тип≠ | Cointegration test / Autoregressive distributed lag model | Asymmetric cointegration / error-correction model | Nonlinear regime-switching regression |
| Основополагащ източник≠ | 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 ↗ | Shin, Y., Yu, B. & Greenwood-Nimmo, M. (2014). Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In: Sickles, R. & Horrace, W. (Eds.), Festschrift in Honor of Peter Schmidt. Springer. DOI ↗ | Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603. DOI ↗ |
| Други названия≠ | Pesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test) | nonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL) | threshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression) |
| Свързани≠ | 4 | 4 | 5 |
| Резюме≠ | 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 NARDL model, introduced by Shin, Yu and Greenwood-Nimmo in 2014, extends the ARDL framework to capture asymmetric long-run and short-run relationships, testing whether positive and negative changes in a regressor affect the dependent variable differently. | Threshold regression is a nonlinear, regime-switching model in which the regression parameters take different values above and below an estimated threshold value of a threshold variable. The sample-splitting and threshold-estimation framework was developed by Bruce E. Hansen (2000) and is widely used for time-series and panel data with structural breaks and regime-dependent relationships. |
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