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Model nelinearnog autoregresivnog distribuiranog zaostatka (NARDL)×Model vektorske autoregresije (VAR)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka20142005
TvoracShin, Yu, and Greenwood-NimmoLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TipNonlinear cointegration modelMultivariate time-series model
Temeljni izvorShin, 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 ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Drugi naziviNARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds testvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Srodne44
SažetakThe 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.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGateUporedite metode: Nonlinear NARDL · VAR Model. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare