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Prueba de cointegración (Johansen / Engle-Granger)×Prueba de fronteras ARDL (Prueba de fronteras de Pesaran)×Modelo de Vectores Autorregresivos (VAR)×
CampoEconometríaEconometríaEconometría
FamiliaRegression modelRegression modelRegression model
Año de origen198820012005
Autor originalEngle & Granger (1987); Johansen (1988)Pesaran, Shin & SmithLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TipoTime-series cointegration testCointegration test / Autoregressive distributed lag modelMultivariate time-series model
Fuente seminalJohansen, 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 ↗
AliasJohansen 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
Relacionados544
ResumenThe 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).
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ScholarGateComparar métodos: Cointegration Test · ARDL Bounds Test · VAR Model. Recuperado el 2026-06-18 de https://scholargate.app/es/compare