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Nelineārais ARDL (NARDL) modelis×Vektora kļūdu labojuma modelis (VECM)×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads20141987
AutorsShin, Yu & Greenwood-NimmoRobert F. Engle and Clive W. J. Granger
TipsNonlinear cointegration modelMultivariate time-series 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. link ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Citi nosaukumiNARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration modelVECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Saistītās55
KopsavilkumsThe 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 Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.
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ScholarGateSalīdzināt metodes: Nonlinear ARDL · Vector Error Correction Model. Izgūts 2026-06-15 no https://scholargate.app/lv/compare