A Yale University study found that an increase in Wall Street Journal news stories about a recession could predict lower production and higher unemployment in the economy, reports Ray Schultz of Publishers Daily.
Schultz reports, “The authors gathered roughly 763,000 WSJ articles, published from 1984 to 2017. The software counted the number of times that spe
cific one- or two-word terms were used in each article, then a machine-learning algorithm identified broad topics—i.e., clusters of terms that often appeared together, the article continues. They then did a manual review.
“One set of words that popped up included ‘Greenspan,’ ‘Yellen,’ ‘federal-funds rate’ and ‘raise rate,’ etc. The software identified the topic as the Federal Reserve.
“The result of this exercise? The team found that ‘an increase in the ‘recession’ attention measure, from the 5th to the 95th percentile, was correlated to a 1.99% drop in industrial production 17 months later and a 0.92% drop in employment 20 months later.’
“In other words, the recession attention metric appeared to provide additional forecasting ability.”
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