Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Nelineārs VAR modelis× | Nelineārais ARDL (NARDL) modelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1990s–2000s | 2014 |
| Autors≠ | Tsay (1998); Krolzig (1997); Tong (1990) for threshold framework | Shin, Yu & Greenwood-Nimmo |
| Tips≠ | Multivariate nonlinear time series model | Nonlinear cointegration model |
| Pirmavots≠ | Tsay, R. S. (1998). Testing and modeling multivariate threshold models. Journal of the American Statistical Association, 93(443), 1188–1202. DOI ↗ | Shin, 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. link ↗ |
| Citi nosaukumi | NLVAR, nonlinear vector autoregression, threshold VAR, TVAR | NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | The Nonlinear VAR (NLVAR) model extends the standard vector autoregression by allowing the dynamic relationships among multiple time series to switch or change smoothly depending on an observed threshold variable, a latent regime state, or a smooth transition function. It is used when economic systems exhibit asymmetric responses, regime shifts, or state-dependent dynamics that a linear VAR cannot capture. | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically. |
| ScholarGateDatu kopa ↗ |
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