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What's in the News? A New Economic Indicator

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Abstract

Newspaper articles and editorials about the economy do more than just report on official data releases. They also often convey how the journalist and those interviewed feel about the economy. Researchers have recently developed ways to extract data on sentiment from news articles using text analysis and machine learning techniques. These measures of news sentiment track current economic conditions quite well. In fact, they often do a better job than standard consumer sentiment surveys at forecasting future economic conditions.

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  • Adam Hale Shapiro & Daniel J. Wilson, 2017. "What's in the News? A New Economic Indicator," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
  • Handle: RePEc:fip:fedfel:00125
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    1. Carroll, Christopher D & Fuhrer, Jeffrey C & Wilcox, David W, 1994. "Does Consumer Sentiment Forecast Household Spending? If So, Why?," American Economic Review, American Economic Association, vol. 84(5), pages 1397-1408, December.
    2. Sylvain Leduc & Zheng Liu, 2013. "Uncertainty and the slow labor market recovery," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue july22.
    3. Jason Bram & Sydney C. Ludvigson, 1998. "Does consumer confidence forecast household expenditure? a sentiment index horse race," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Jun), pages 59-78.
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