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| Modello Vettoriale Autoregressivo Strutturale Non Lineare (NL-SVAR)× | Modello VAR Non Lineare× | |
|---|---|---|
| Campo | Econometria | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1990s–2010s | 1990s–2000s |
| Ideatore≠ | Extensions by Koop, Potter, Auerbach, Gorodnichenko and others | Tsay (1998); Krolzig (1997); Tong (1990) for threshold framework |
| Tipo≠ | Multivariate nonlinear structural time series model | Multivariate nonlinear time series model |
| Fonte seminale≠ | Koop, G., & Korobilis, D. (2010). Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends in Econometrics, 3(4), 267–358. DOI ↗ | Tsay, R. S. (1998). Testing and modeling multivariate threshold models. Journal of the American Statistical Association, 93(443), 1188–1202. DOI ↗ |
| Alias | nonlinear structural VAR, NL-SVAR, threshold SVAR, regime-switching SVAR | NLVAR, nonlinear vector autoregression, threshold VAR, TVAR |
| Correlati≠ | 6 | 4 |
| Sintesi≠ | The Nonlinear Structural VAR model extends the standard SVAR framework to allow structural relationships and dynamic responses to vary across economic regimes or states of the world. By imposing nonlinear transition mechanisms — such as threshold switching or smooth regime change — it captures asymmetric responses to shocks that a linear SVAR cannot detect. | 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. |
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