Artificial intelligence and local debt: Evidence from five OECD bond markets

Sean Dougherty and Christos Makridis

No 51, OECD Working Papers on Fiscal Federalism from OECD Publishing

Abstract: This paper examines whether local investments in artificial intelligence (AI) improve subnational borrowing terms in an international setting. Building on U.S. evidence that AI-intensive countries experience lower municipal bond yields and stronger local fiscal capacity, the analysis is extended to five OECD countries: Belgium, Canada, Germany, Spain and Sweden. Vacancy data from Lightcast are used to measure the AI share of job postings at comparable subnational geographies and to link these measures to municipal and regional bond outcomes. Expansions of the AI share of jobs are found to be associated with increases rather than decreases, in bond yields. These results point to challenges that many OECD economies may face in financing the development of new digital infrastructure in the emerging AI economy.

Keywords: artificial intelligence; job posting data; municipal bonds; regional fiscal risks; subnational public finance (search for similar items in EconPapers)
JEL-codes: G12 H74 H77 O33 R51 (search for similar items in EconPapers)
Date: 2026-01-26
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:oec:ctpaab:51-en

Access Statistics for this paper

More papers in OECD Working Papers on Fiscal Federalism from OECD Publishing Contact information at EDIRC.
Bibliographic data for series maintained by ().