When Unemployment Signals Recession: Understanding Sahm's Three-Month Rule

The Origin of a Simple Indicator

The Sahm Rule is a recession detection mechanism created by economist Claudia Sahm, which is based on an elegantly simple logic: monitoring the unemployment rate. The original proposal aimed to automate the triggering of economic stimuli during times of crisis, eliminating the need for complex analyses. Currently, platforms like the Federal Reserve Economic Data (FRED) track this indicator in real time.

The central concept is that when the three-month moving average of the unemployment rate exceeds its lowest point of the last twelve months by a margin equal to or greater than 0.50%, there are signs that the economy may be entering a recession.

How It Works in Practice

The calculation follows a direct sequence:

Step 1: Calculate the arithmetic mean of the unemployment rates from the last three consecutive months.

Step 2: Identify what was the lowest three-month moving average recorded in the previous twelve months.

Step 3: Calculate the difference between these two values.

If this difference reaches or exceeds 0.50%, the recession signal is triggered.

A Practical Example

Let's imagine that in the months of April, May, and June the unemployment rates were 3.8%, 3.9%, and 4.0%, respectively. The average would be:

(3,8% + 3,9% + 4,0%) / 3 = 3,9%

If in the previous twelve-month period the lowest three-month average was 3.4%, the difference would result in 0.5%, triggering exactly the threshold of the Sahm Rule.

Effectiveness and Limitations

Historically, this indicator has shown remarkable accuracy without generating many false alarms. However, in August 2024, when the rule was triggered due to the increase in unemployment rates, the creator Claudia Sahm herself expressed skepticism about the confirmation of a real recession. This situation could represent the first significant failure of the model to correctly predict an economic crisis.

Adapting the Concept for Cryptocurrencies

Although the Sahm Rule originates from traditional macroeconomic analyses, its principles can be transposed to the crypto ecosystem. Instead of monitoring unemployment, we could track metrics such as:

• Growth or decline in the number of jobs in the blockchain sector
• Trading volume variations over three-month periods
• Changes in total cryptocurrency market capitalization
• Fluctuations in the number of active addresses on the network

These alternative indicators would operate under the same logic: detecting when there is significant deterioration compared to the recent peak, signaling a possible contraction in the crypto market.

Conclusion

The Sahm Rule represents a pragmatic approach to identifying early stages of economic recessions through a unique and transparent indicator. Although its traditional application is in the general economic market, the conceptual framework offers opportunities for adaptation to monitor the health of the cryptocurrency market. Even tools with a proven track record can face limitations when economic dynamics change, as recently demonstrated, reinforcing the importance of using multiple indicators in complementarity.