{"title":"商业新闻和商业周期","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":"39 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"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\":\"39 1\",\"pages\":\"\"},\"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}","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}
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.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
