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Ikke-lineær Autoregressiv Distribuert Lag-modell (NARDL)×Minste kvadraters metode (OLS)×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår20142019
OpphavspersonShin, Yu, and Greenwood-NimmoWooldridge (textbook treatment); classical least squares
TypeNonlinear cointegration modelLinear regression
Opprinnelig kildeShin, 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 ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
AliasNARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds testordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relaterte45
SammendragThe 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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateSammenlign metoder: Nonlinear NARDL · OLS Regression. Hentet 2026-06-15 fra https://scholargate.app/no/compare