Granger Causality Test

The Granger Causality Test MATLAB program serves as an excellent econometric statistical tool designed to detect causal relationships between time series datasets. This implementation employs vector autoregression (VAR) models to accurately assess causal directions between input and output variables, yielding statistically significant conclusions. Through proper model specification and lag selection algorithms, users can better understand variable interdependencies and improve future trend predictions. The program includes key functions for hypothesis testing with F-statistics and p-value calculations to validate causality significance. Additionally, it incorporates data visualization modules that graphically represent temporal patterns and distribution characteristics, enabling users to intuitively comprehend data dynamics through plotted impulse responses and variance decompositions. The code structure supports customizable parameters for optimal model fitting, including AIC/BIC criteria for lag length determination and robustness checks for stationarity requirements.