Methodology of the Karfali-VAR-Model
The Karfali-VAR-Model integrates statistical analysis with a nine-year economic cycle to predict crises. It employs Vector AutoRegression (VAR), a technique analyzing interrelationships among variables like GDP growth, inflation, interest rates, unemployment, oil prices, and stock indices (e.g., S&P 500) (Granger, 1969). The nine-year cycle, derived from historical patterns (Juglar, 1862), identifies phases from recovery (Year 1) to potential recession (Year 9). This long-term perspective minimizes short-term noise, while interconnectivity between variables enhances prediction accuracy. For more details, see
https://orcid.org/0009-0002-9626-7289
2. Historical Applications
The model’s effectiveness is tested through historical crises. The 1973–1974 oil crisis saw oil prices rise from $4.75 to $9.35 per barrel, inflation from 8.71% to 12.34%, and GDP growth fall from 5.6% to -0.5% (BP Statistical Review, 2023; World Bank, 2023; IMF, 2023), signaling a crisis in Year 9 (1975). The 2007–2008 financial crisis was preceded by slowed GDP growth (2.0% in 2007 to 0.12% in 2008) and a falling S&P 500 (1,468.36 to 903.25) (World Bank, 2023; Yahoo Finance, 2023), indicating a bubble in Year 9 (2007). The 2020 COVID-19 crisis, though an external shock, followed a GDP slowdown to 2.47% in 2019 (IMF, 2023), highlighting vulnerabilities exacerbated by the pandemic.
3. Practical Applications for Stakeholders
The model aids proactive planning. Individuals can diversify investments, maintain liquidity (6–12 months of savings), and avoid speculative bubbles. Businesses should plan cyclically, diversify financing, and use data-driven strategies to anticipate downturns. Governments can adjust interest rates, invest in innovation, and implement proactive policies to manage inflation and enhance productivity, ensuring resilience against cyclical crises.
4.Limitations and Enhancements
The model struggles with unpredictable external shocks (e.g., pandemics, wars) and relies on accurate historical data. Structural economic changes may also limit its applicability. However, its strength lies in detecting slowdowns 6–12 months in advance, leveraging past nine-year cycles to provide actionable warnings for decision-makers.
Conclusion
The Karfali-VAR-Model effectively predicts economic crises by analyzing business cycles and economic variables within a nine-year framework. Historical cases like the 1973 oil crisis, 2008 financial crisis, and 2020 COVID-19 recession demonstrate its utility. While limitations exist, the model empowers individuals, businesses, and governments to mitigate crisis impacts through informed planning.