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Model NARDL ze zmiennymi w czasie parametrami (TVP-NARDL)×Regresja progowa×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2019 (TVP extension); 2014 (NARDL base)2000
TwórcaBagnai & Ospina-Rojas (TVP extension); NARDL base by Shin, Yu & Greenwood-NimmoBruce E. Hansen
TypNonlinear time-series model with time-varying coefficientsNonlinear regime-switching regression
Źródło pierwotneShin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. Horrace & R. Sickles (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer. link ↗Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603. DOI ↗
Inne nazwyTVP-NARDL, time-varying NARDL, rolling NARDL, dynamic asymmetric ARDLthreshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression)
Pokrewne35
PodsumowanieThe Time-Varying Parameter NARDL (TVP-NARDL) model extends the Nonlinear ARDL framework by allowing the coefficients on positive and negative partial sums of a regressor to change over time. This combination captures both asymmetric responses and structural instability in long-run and short-run relationships within a single cointegrating specification.Threshold regression is a nonlinear, regime-switching model in which the regression parameters take different values above and below an estimated threshold value of a threshold variable. The sample-splitting and threshold-estimation framework was developed by Bruce E. Hansen (2000) and is widely used for time-series and panel data with structural breaks and regime-dependent relationships.
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ScholarGatePorównaj metody: Time-varying parameter NARDL · Threshold Regression. Pobrano 2026-06-17 z https://scholargate.app/pl/compare