The sharp drop in the fiscal impulse represents a direct, dollar-for-dollar hit to nominal GDP that has already occurred. This indicates a recession is underway, not forthcoming. The National Bureau of Economic Analysis (NBER) will likely backdate the start of this recession to the third quarter of 2025.

Economists are confronting a paradoxical scenario where the labor market could enter a recession (job losses, rising unemployment) while the broader economy, measured by GDP, continues to expand. This potential disconnect challenges traditional definitions of an economic downturn and complicates forecasting.

The podcast's economists assess the probability of a recession in the next year at 40-45%, significantly higher than the consensus view of 25-30%. This heightened risk is based on deteriorating labor market trends and is corroborated by Moody's own machine learning models.

Multiple indicators, including a modified Sahm rule and hiring rates, point to a recession in the labor market. However, GDP is forecast to grow 2.5-3%. This divergence suggests a potential structural shift where economic output decouples from job creation, posing a unique challenge for policymakers.

The Sahm Rule provides a clear signal that a recession has begun: when the three-month moving average unemployment rate rises by more than 0.5 percentage points above its low from the previous year. This metric is useful for cutting through noise and identifying when a slowly weakening job market has definitively tipped into a downturn.

An analysis modeling the NBER's recession dating methodology at the state level reveals a fractured economic landscape. As of September, states representing one-third of the nation's GDP were in or near recessionary conditions. This contrasts with the strong national headline numbers and highlights significant underlying weakness in specific regions.

A Moody's machine learning model, which analyzes leading economic indicators, had already calculated a 48.6% probability of recession *before* the Iran conflict began. The primary driver for this high reading was a deteriorating labor market, indicating underlying economic weakness.

The primary risk to the economy is a deteriorating labor market. A further increase of just a few tenths of a percentage point in the unemployment rate would trigger the "Sahm Rule," a historical regularity that reliably predicts recessions. This could spark a negative feedback loop in consumer confidence and spending.

To navigate conflicting economic signals, Moody's built a model that uses a machine learning technique called a random forest. It aggregates 'votes' from numerous decision trees based on economic data, with labor markets carrying the most weight, to produce a single 12-month recession probability.