Is AI Trained on Public Money? Evidence from U.S. Data Centers

Adam Feher, Emilia Garcia-Appendini and Roxana Mihet

No 20758, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: We leverage a novel 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-in-differences 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: Climate change; Technology adoption; Data Centers (search for similar items in EconPapers)
JEL-codes: L94 O44 Q55 Q58 (search for similar items in EconPapers)
Date: 2025-10
References: Add references at CitEc
Citations:

Downloads: (external link)
https://cepr.org/publications/DP20758 (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:cpr:ceprdp:20758

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP20758

Access Statistics for this paper

More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().