ScholarGate
Asistent

Usporedite metode

Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.

Nelinearni strukturni vektorski autoregresijski (NL-SVAR) model×Vektorski model korekcije pogreške (VECM)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1990s–2010s1987
TvoracExtensions by Koop, Potter, Auerbach, Gorodnichenko and othersRobert F. Engle and Clive W. J. Granger
VrstaMultivariate nonlinear structural time series modelMultivariate time-series model
Temeljni izvorKoop, G., & Korobilis, D. (2010). Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends in Econometrics, 3(4), 267–358. DOI ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Drugi nazivinonlinear structural VAR, NL-SVAR, threshold SVAR, regime-switching SVARVECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Srodne65
SažetakThe 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 Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

ScholarGateUsporedite metode: Nonlinear SVAR Model · Vector Error Correction Model. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare