Could Numerically-Based Economic Cycles Be the Key to Predicting Future Financial Crises?

Question

Introduction: In the world of economics, economic cycles are key to understanding how global markets function. Traditionally, economists rely on indicators like Gross Domestic Product (GDP) and unemployment rates to determine when economic crises begin and end. However, a new and unconventional approach has been introduced by Karfali Jaouad, which uses numbers to define these cycles. But what makes this approach innovative? And how could it help in predicting upcoming financial crises?

What is Karfali Jaouad Methodology?
Karfali Jaouad methodology is based on a simple yet intriguing idea: if you sum the digits of a year, like 1927 (1+9+2+7 = 19 → 1+9 = 10 → 1+0 = 1), you can identify the beginning of an economic cycle marked by the number "1." Similarly, 1935 (1+9+3+5 = 18 → 1+8 = 9) represents the end of the cycle that started in 1927.

Why 9 Years?
The cycle that Karfali Jaouad’s method follows is based on a 9-year pattern. Historical data analysis shows that major financial crises tend to occur approximately every 9 years. For example, the Great Depression of 1929 fits into this pattern, as does the financial crisis of 2008.

Karfali Jaouad’s Method vs. Traditional Forecasting:
What sets Karfali Jaouad’s methodology apart is its predictive accuracy, which stands at 82%—higher than traditional forecasting models like ARIMA (68%) and VAR (72%). Using this approach, economic events can be predicted well in advance, allowing for more effective preparation for potential crises.

Future Applications:
Karfali Jaouad’s model predicts that the year 2025 (2+0+2+5 = 9) marks the end of the economic cycle that began in 2017. This suggests a possible economic contraction, urging policymakers to adjust their strategies and be proactive in response to future shifts in the economy.

A Call for Collaboration:
This methodology represents an exciting new way to understand economic cycles, and it calls for researchers and institutions to collaborate in refining this tool. Together, they can develop better tools for forecasting and responding to financial crises, which could be crucial for global economic stability.

Conclusion:
As economic challenges continue to grow globally, Karfali Jaouad’s numerically-based cycle methodology may offer a more accurate and timely way to predict financial downturns. This approach could potentially replace traditional methods and provide a clearer path toward anticipating future economic changes.

For more details, you can refer to the full study via this link: https://doi.org/10.5281/zenodo.14901679

Answer 1

An economic cycle is caused because consumption y lower than supply. There are two main forces that makes consumption lower, savings and a trade balance deficit. When banks lend money to companies and householders  is closing that gap. Even considering that imports exceeding exports and total credit that is feasible to lend is a higher amount than total savings. So, a share of production is not sold, which makes unemployment hard to fight when there isna recession. There are two main causes of the slump in every economic cycle, the normal one is that savings decrease during a short period of high employment and the trade balance deficit is bigger than the savings of that periods. There isn't enough money and production starts dismissing workers. The second is that in a levereged economy, banks are not going to receive the full amount of their loans and can cut lending, provoking the same situation as before.

Comments

Dear Professor,

I am very pleased to receive your response, and I sincerely thank you for your valuable insights!

The statistical analysis shows that the 2008 crisis was not entirely unexpected. According to the IMF and World Bank databases, U.S. GDP growth slowed in 2007, while the debt-to-GDP ratio increased significantly. This aligns with the end-cycle dynamics identified by the numerical model.

Supporting data:
GDP growth: Declined from 2.5% (2007) to -0.1% (2008).
Debt-to-GDP ratio: Increased from 67.2% (2007) to 76.1% (2008).
Global trade growth: Slowed significantly from 7.2% (2007) to 2.8% (2008).
Retrospective Analysis: The 2008 Financial Crisis
To validate the model, we compare it against historical data from the IMF and World Bank. The pattern aligns closely with major economic events:

1999–2000 Peak: The Dot-com bubble.
2001–2002 Trough: Recession following the bubble burst.
2007–2008 Collapse: The housing and debt crisis—approximately 9 years later.
This suggests that the numerical cycle model could have predicted the downturn, reinforcing its potential as a predictive tool.

My question to you:
Do you think traditional models could benefit from integrating this type of cyclical analysis? And how can we further enhance the accuracy of economic forecasts in the future?

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In my opinion, you must have a deep economic knowledge about the economic patterns and functioning of the economy. It's clear that we don't tamme business cycles as in the decades before, they replicate themselves following a pattern of years that are around 10.