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Narrative fragmentation and the business cycle

Christoph Bertsch (), Isaiah Hull () and Xin Zhang

Economics Letters, 2021, vol. 201, issue C

Abstract: According to Shiller (2017), economic and financial narratives often emerge as a consequence of their virality, rather than their veracity, and constitute an important, but understudied driver of aggregate fluctuations. Using a unique dataset of newspaper articles over the 1950–2019 period and state-of-the-art methods from natural language processing, we characterize the properties of business cycle narratives. Our main finding is that narratives tend to consolidate around a dominant explanation during expansions and fragment into competing explanations during contractions. We also show that the existence of past reference events is strongly associated with increased narrative consolidation.

Keywords: Natural language processing; Machine learning; Narrative economics (search for similar items in EconPapers)
JEL-codes: C63 D84 E32 E7 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1016/j.econlet.2021.109783

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