Stationarity and Correlation Insights from VAR Modeling of Gas Base Fees

This article presents a detailed econometric analysis of Ethereum’s blob gas base fee and gas base fee using a VAR (Vector Autoregression) model. It begins with ADF tests confirming the stationarity of both time series, ensuring their suitability for modeling. The study then provides full regression outputs, model diagnostics, and statistical measures such as AIC, BIC, and HQIC to evaluate performance. A correlation matrix of residuals reveals minimal cross-equation correlation, while coefficient estimates show strong predictive power from lagged values, particularly the first lag. Together, these results offer a comprehensive view of the dynamics and interplay between these key gas pricing metrics.