2017-01 | March 2018
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Measuring News Sentiment
We develop and assess new time series measures of economic sentiment based on computational text analysis of economic and financial newspaper articles from January 1980 to April 2015. The text analysis is based on predictive models estimated using machine learning techniques. We analyze four alternative news sentiment indexes. The news sentiment indexes correlate strongly with contemporaneous business cycle indicators and improve forecasting performance. A positive news sentiment shock appears consistent with an aggregate demand shock, increasing future employment, prices, and the federal funds rate. However, we find muted effects of news sentiment on future consumption. While news sentiment affects overall consumer sentiment, it has no effect on the components of consumer sentiment that drive consumption.
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Shapiro, Adam Hale, Moritz Sudhof, and Daniel Wilson. 2017. "Measuring News Sentiment," Federal Reserve Bank of San Francisco Working Paper 2017-01. Available at https://doi.org/10.24148/wp2017-01