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Modelis Nardl (Nonlinear Autoregressive Distributed Lag Model)×ARDL robežu tests (Pesaran robežu tests)×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads20142001
AutorsShin, Yu, and Greenwood-NimmoPesaran, Shin & Smith
TipsNonlinear cointegration modelCointegration test / Autoregressive distributed lag model
PirmavotsShin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281-314). Springer. 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 ↗
Citi nosaukumiNARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds testPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)
Saistītās44
KopsavilkumsThe Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing an explanatory variable into its positive and negative partial sums, it tests whether increases and decreases in a regressor have different effects on the dependent variable — a feature that linear cointegration methods cannot capture.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.
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ScholarGateSalīdzināt metodes: Nonlinear NARDL · ARDL Bounds Test. Izgūts 2026-06-17 no https://scholargate.app/lv/compare