ScholarGate
Asystent

Porównaj metody

Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.

Test ko-integracji (Johansen / Engle-Granger)×Test granic ARDL (Pesaran Bounds Test)×Model Autoregresji Wektorowej (VAR)×
DziedzinaEkonometriaEkonometriaEkonometria
RodzinaRegression modelRegression modelRegression model
Rok powstania198820012005
TwórcaEngle & Granger (1987); Johansen (1988)Pesaran, Shin & SmithLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TypTime-series cointegration testCointegration test / Autoregressive distributed lag modelMultivariate time-series model
Źródło pierwotneJohansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. DOI ↗Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Inne nazwyJohansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger)Pesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Pokrewne544
PodsumowanieThe cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988).The ARDL bounds test is an autoregressive distributed lag method that tests for a cointegrating (long-run level) relationship between time series, introduced by Pesaran, Shin and Smith in 2001. Unlike the Johansen procedure, it remains valid whether the variables are I(0), I(1) or a mix of the two, and it is more reliable than Johansen in small samples of roughly 30 to 80 observations.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
ScholarGateZbiór danych
  1. v1
  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 1 Źródła
  3. PUBLISHED

Przejdź do wyszukiwania Pobierz slajdy

ScholarGatePorównaj metody: Cointegration Test · ARDL Bounds Test · VAR Model. Pobrano 2026-06-18 z https://scholargate.app/pl/compare