Explaining U.S. consumer behavior with news sentiment

Matthias W. Uhl
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引用次数: 21

Abstract

We introduce a novel dataset with a news sentiment index that was constructed from a selection of over 300,000 newspaper articles from five of the top ten U.S. newspapers by circulation. By constructing ARMA models, we show that news and consumer sentiment, when combined with other macroeconomic variables, achieve statistically significant results to explain changes in private consumption. We make three distinct findings with respect to sentiment in consumption behavior models: first, both consumer and news sentiment add explanatory power and statistical significance to conventional consumer behavior models. Second, consumer sentiment, measured by the University of Michigan Index of Consumer Sentiment, adds more explanatory power and statistical significance than news sentiment when tested individually. Third, news sentiment is able to determine the signs of all coefficients in the model correctly, whereas consumer sentiment does not. In general, we conclude that news sentiment is a useful variable to add in consumer behavior models, especially when coupled with consumer sentiment and other macroeconomic variables. Tested individually, news sentiment is as good a proxy as personal income for explaining private consumption growth when tested individually.
用新闻情绪解释美国消费者行为
我们引入了一个具有新闻情绪指数的新数据集,该数据集是从美国发行量排名前十的报纸中的五家报纸中选出的30多万篇报纸文章中构建的。通过构建ARMA模型,我们表明,当与其他宏观经济变量相结合时,新闻和消费者情绪在解释私人消费变化方面取得了统计上显著的结果。关于消费行为模型中的情绪,我们有三个明显的发现:首先,消费者情绪和新闻情绪都为传统的消费者行为模型增加了解释力和统计意义。其次,由密歇根大学消费者信心指数衡量的消费者信心,在单独测试时比新闻情绪增加了更多的解释力和统计意义。第三,新闻情绪能够正确地确定模型中所有系数的符号,而消费者情绪则不能。总的来说,我们得出的结论是,新闻情绪是一个有用的变量,可以添加到消费者行为模型中,特别是当与消费者情绪和其他宏观经济变量相结合时。单独测试时,新闻情绪和个人收入一样,都能很好地解释私人消费增长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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