Is AI Trained on Public Money? Evidence from US Data Centers

Adam Feher, Emilia Garcia-Appendini and Roxana Mihet
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Adam Feher: University of Lausanne
Emilia Garcia-Appendini: Norges Bank; University of St. Gallen - School of Finance; Swiss Finance Institute
Roxana Mihet: Swiss Finance Institute - HEC Lausanne

No 25-73, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We leverage a comprehensive dataset on U.S. data center energy loads, utility electricity prices, and establishment-level revenues, employment, and carbon emissions from 2010 to 2023 to examine whether rising data center demand affects local retail energy prices or other spillovers. For identification, we employ an instrumental variables continuous difference-indifferences design, exploiting exogenous variation in data center location attractiveness. We find no detectable local spillover effects from data center energy growth. A regional model calibrated to these null results suggests that shocks larger than those observed through 2023 could still result in noticeable increases in household utility bills if not offset by regulation or external supply.

Keywords: AI; energy prices; spillovers; data centers; energy; electricity (search for similar items in EconPapers)
JEL-codes: D24 L94 O33 O44 Q55 Q58 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2025-09
New Economics Papers: this item is included in nep-ain, nep-ene, nep-env, nep-res and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2573

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