Economic Surveillance using Corporate Text

Tarek Hassan, Stephan Hollander, Aakash Kalyani, Laurence van Lent, Markus Schwedeler and Ahmed Tahoun

No 33158, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This article applies simple methods from computational linguistics to analyze unstructured corporate texts for economic surveillance. We apply text-as-data approaches to earnings conference call transcripts, patent texts, and job postings to uncover unique insights into how markets and firms respond to economic shocks, such as a nuclear disaster or a geopolitical event—insights that often elude traditional data sources. This method enhances our ability to extract actionable intelligence from textual data, thereby aiding policy-making and strategic corporate decisions. By integrating computational linguistics into the analysis of economic shocks, our study opens new possibilities for real-time economic surveillance and offers a more nuanced understanding of firm-level reactions in volatile economic environments.

JEL-codes: E3 E5 E6 F01 F3 G12 G32 (search for similar items in EconPapers)
Date: 2024-11
New Economics Papers: this item is included in nep-big and nep-cmp
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