High-Frequency Cross-Sectional Identification of Military News Shocks

Francesco Amodeo and Edoardo Briganti

Staff Working Papers from Bank of Canada

Abstract: This study develops a two-step procedure to identify and quantify fiscal news shocks. First, we augment a narrative identification strategy using large language model searches to compile events (2001–2023) that altered the expected path of U.S. defense expenditure. Second, for each event, we estimate market-implied shifts in expected defense spending with cross-sectional regressions of contractors’ stock returns on their reliance on military revenues. We show that this approach statistically validates each event; quantifies each shock in an intuitive, model-consistent fashion; and readily generalizes to other macroeconomic contexts. Employing the estimated shocks in a shift-share analysis yields a two-year, metropolitan statistical area–level GDP multiplier of approximately 1 for U.S. military build-ups.

Keywords: Fiscal Policy; Business Fluctuations and Cycles; Econometric and Statistical Methods (search for similar items in EconPapers)
JEL-codes: E20 E30 E32 E60 E62 E65 (search for similar items in EconPapers)
Pages: 60 pages
Date: 2025-10
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.34989/swp-2025-27 Abstract (text/html)
https://www.bankofcanada.ca/wp-content/uploads/2025/10/swp2025-27.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bca:bocawp:25-27

Access Statistics for this paper

More papers in Staff Working Papers from Bank of Canada 234 Wellington Street, Ottawa, Ontario, K1A 0G9, Canada. Contact information at EDIRC.
Bibliographic data for series maintained by ().