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News-Driven Uncertainty Fluctuations
被引:1
|作者:
Song, Dongho
[1
]
Tang, Jenny
[2
]
机构:
[1] Johns Hopkins Univ, Carey Business Sch, Baltimore, MD USA
[2] Fed Reserve Bank Boston, Res Dept, Boston, MA 02210 USA
关键词:
Bayesian learning;
Discrete environment;
News shocks;
Survey forecasts;
Uncertainty;
BUSINESS;
EXPECTATIONS;
SHOCKS;
D O I:
10.1080/07350015.2022.2097912
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
We investigate the channels through which news influences the subjective beliefs of economic agents, with a particular focus on their subjective uncertainty. The main insight of the article is that news that is more at odds with agents' prior beliefs generates an increase in uncertainty; news that is more consistent with their prior beliefs generates a decrease in uncertainty. We illustrate this insight theoretically and then estimate the model empirically using data on U.S. output and professional forecasts to provide novel measures of news shocks and uncertainty. We then estimate impulse responses from the identified shocks to show that news shocks can affect macroeconomic variables in ways that resemble the effects of uncertainty shocks. Our results suggest that controlling for news can potentially diminish the estimated effects of uncertainty shocks on real variables, particularly at longer horizons.
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页码:968 / 982
页数:15
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