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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Kielelezo cha Utegemezi wa Kujirudia kwa Kiasi Kidogo (NARDL)×Muundo wa Uhusiano wa Kiotomatiki wa Vecta (VAR)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili20142005
MwanzilishiShin, Yu, and Greenwood-NimmoLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
AinaNonlinear cointegration modelMultivariate time-series model
Chanzo asiliaShin, 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 ↗
Majina mbadalaNARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds testvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Zinazohusiana44
MuhtasariThe 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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ScholarGateLinganisha mbinu: Nonlinear NARDL · VAR Model. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare