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Modelul ARDL neliniar (NARDL)×Testul de cauzalitate Granger×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției20141969
Autorul originalShin, Yu & Greenwood-NimmoClive W. J. Granger
TipNonlinear cointegration modelCausality test (F-test on VAR)
Sursa seminalăShin, 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. link ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗
Denumiri alternativeNARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration modelGranger test, GC test, predictive causality test, Granger non-causality test
Înrudite55
RezumatThe Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically.The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.
ScholarGateSet de date
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  2. 2 Surse
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  1. v1
  2. 2 Surse
  3. PUBLISHED

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ScholarGateCompară metode: Nonlinear ARDL · Granger Causality Test. Preluat la 2026-06-17 de pe https://scholargate.app/ro/compare