A recent study by economists at the Federal Reserve Bank of San Francisco indicates that consumer sentiment and the tone of news can predict recessions as effectively as traditional economic data. The working paper, titled "Do Vibes Predict Recessions?" was released on July 17 and highlights the importance of soft data in forecasting economic downturns.
The researchers, Nicolas Petrosky-Nadeau, Yeji Sung, and Daniel J. Wilson, found that a sentiment-based model was more accurate than one relying solely on hard economic statistics when looking one month ahead. This sentiment model was quicker to identify rising recession risks, although it also generated more false alarms.
The findings suggest that soft data serves as a complement to hard data, providing unique insights into recession risks.
The study analyzed data from August 1999 through May 2026, covering three recessions. Inputs included consumer surveys, an economic-policy uncertainty index, and sentiment readings from the Fed's Beige Book.
While the results provide some reassurance for households and businesses in Allen, Texas, the authors caution that the paper reflects their views and not the Fed's official stance, emphasizing that it measures predictive capability rather than indicating an imminent recession.
