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Linganisha mbinu

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Kipimo cha Granger Causality×Kipimo cha Vikomo vya ARDL (Kipimo cha Vikomo cha Pesaran)×Kipimo cha ushirikiano (Johansen / Engle-Granger)×Muundo wa Uhusiano wa Kiotomatiki wa Vecta (VAR)×
NyanjaEkonometrikiEkonometrikiEkonometrikiEkonometriki
FamiliaRegression modelRegression modelRegression modelRegression model
Mwaka wa asili1969200119882005
MwanzilishiClive W. J. GrangerPesaran, Shin & SmithEngle & Granger (1987); Johansen (1988)Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
AinaTime-series predictive causality testCointegration test / Autoregressive distributed lag modelTime-series cointegration testMultivariate time-series model
Chanzo asiliaGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. 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 ↗Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Majina mbadalaGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik TestiPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)Johansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger)vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Zinazohusiana5454
MuhtasariThe Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.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.The 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).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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ScholarGateLinganisha mbinu: Granger Causality · ARDL Bounds Test · Cointegration Test · VAR Model. Imepatikana 2026-06-19 kutoka https://scholargate.app/sw/compare