Business News and Business Cycles

Leland Bybee, B. Kelly, Asaf Manela, D. Xiu
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引用次数: 24

Abstract

We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984–2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and explains 25% of aggregate stock market returns. A text-augmented VAR demonstrates the large incremental role of news text in modeling macroeconomic dynamics. We use this model to retrieve the narratives that underlie business cycle fluctuations.
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商业新闻和商业周期
我们提出了一种通过对商业新闻的文本分析来衡量经济状况的方法。从1984-2017年的80万篇《华尔街日报》文章全文中,我们估计了一个主题模型,该模型将商业新闻总结为可解释的主题,并量化每个主题随时间分配的新闻关注比例。新闻关注密切追踪着广泛的经济活动,并解释了25%的股市总回报率。文本增强VAR显示了新闻文本在宏观经济动态建模中的巨大增量作用。我们使用这个模型来检索商业周期波动背后的叙述。
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