Extended Research: Karfali-VAR-Model Forecasts and Sensitivity Tests 2026-2034

Abstract

The Karfali-VAR-Model, developed by Jaouad Karfali, combines a nine-year cycle methodology with Vector Autoregression (VAR) analysis to forecast economic trends for 2026-2034. Using 27 years of data (1999-2025) from BEA, EIA, and FRED, the model weights numerical cycles at 30% and VAR at 70%, achieving 87% accuracy in predicting historical recessions (1800-2020), outperforming ARIMA (70%) and traditional VAR (74%). Baseline forecasts predict stability: GDP growth at 1.7%, S&P 500 rising to 6054.74 by 2034, with stable oil prices ($70), unemployment dropping to 3.92%, and interest rates declining to 3.12%. A 2026 sensitivity test (oil at $100, interest rate at 6.5%, S&P 500 -20% to 4621.76) indicates a slowdown, not a full crisis, contrasting with the 2008 collapse (GDP -2.58%, S&P -57%). Compared to IMF’s 2025 forecast (3.2%growth), Karfali’s -1.8% GDP prediction for year 9 (2025) signals a downturn, with 2026 marking recovery onset. The model’s early warning potential (6-12 months) emerges from detecting gradual shifts (e.g., oil price rises, S&P declines), enhanced by real-time data and global integration (e.g., UK GDP). Applications include crisis forecasting, policy timing, and scenario testing, with recommendations to expand datasets and simulate stronger shocks (e.g., oil at $150). This self-funded study offers a novel, proactive tool for economic foresight.

JEL Classification: E27, E32, C53