A recent study from the Federal Reserve has determined that consumer sentiment, along with the tone of news coverage, can predict recessions with accuracy comparable to traditional economic indicators like jobs and prices. The research was conducted by economists from the Federal Reserve Bank of San Francisco, including Nicolas Petrosky-Nadeau, Yeji Sung, and Daniel J. Wilson.
The paper, titled "Do Vibes Predict Recessions?", was released on July 17 and suggests that soft data, such as measures of consumer sentiment and economic-policy uncertainty, can sometimes provide faster signals of impending recessions than hard statistics. The study found that a sentiment-based model was more accurate in predicting recession risks one month ahead compared to models relying solely on hard data.
While the sentiment model was effective, it also produced a higher number of false alarms. The authors emphasized that soft data serves as both a proxy for information reflected in hard data and as an independent indicator of recession risk. The combination of both types of data is recommended for the best predictive outcomes.
The researchers analyzed data from August 1999 to May 2026, covering three recessions, using various sentiment inputs including consumer surveys and economic-policy uncertainty indices. This finding may provide reassurance for households and businesses in Celina, Texas, as they assess economic trends. However, the authors noted that the paper reflects their views and does not represent the Fed's official stance.