Salīdzināt metodes
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| Laika mainīgo parametru NARDL (TVP-NARDL)× | Regresija ar slieksni× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2019 (TVP extension); 2014 (NARDL base) | 2000 |
| Autors≠ | Bagnai & Ospina-Rojas (TVP extension); NARDL base by Shin, Yu & Greenwood-Nimmo | Bruce E. Hansen |
| Tips≠ | Nonlinear time-series model with time-varying coefficients | Nonlinear regime-switching regression |
| Pirmavots≠ | Shin, 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 ↗ |
| Citi nosaukumi | TVP-NARDL, time-varying NARDL, rolling NARDL, dynamic asymmetric ARDL | threshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression) |
| Saistītās≠ | 3 | 5 |
| Kopsavilkums≠ | The 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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