Business News and Business Cycles

Leland Bybee, B. Kelly, Asaf Manela, D. Xiu
{"title":"Business News and Business Cycles","authors":"Leland Bybee, B. Kelly, Asaf Manela, D. Xiu","doi":"10.2139/ssrn.3446225","DOIUrl":null,"url":null,"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.","PeriodicalId":13594,"journal":{"name":"Information Systems & Economics eJournal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems & Economics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3446225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信