EconPapers    
Economics at your fingertips  
 

LLM Meets Job Advertisements: Unmasking Skill Premia in the UK

Sidharth Rony
Additional contact information
Sidharth Rony: RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn

No 10, MERIT Working Papers from United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT)

Abstract: Rapid advances in technology and events such as COVID-19 have significantly transformed the modern workplace, potentially altering the skills demanded in jobs. This study examines the evolving demand and posted-wage premia for Information and Communication Technology (ICT), interpersonal, and Artificial Intelligence (AI) skills in the UK labour market. Using a comprehensive dataset of online job advertisements (2016 to 2022), skills are extracted and categorised via GPT-4 zero-shot learning. Cross-sectional log-wage regressions, incorporating occupation and regional fixed effects with three-way Cameron-Gelbach-Miller clustered standard errors, reveal divergent trends in skill compensation. While interpersonal skills are ubiquitously demanded (approximately 90% of listings), they yield no significant posted-wage premium, likely reflecting their near-universal baseline requirement across postings. In contrast, ICT skills, demanded in approximately 55% of postings, carry a posted-wage premium of approximately 7%. AI skills, mentioned in approximately 3% of postings, carry a posted-wage premium of approximately 9% within the ICT-mentioning subsample. These findings document robust associational posted-wage premia for technical competencies amidst recent pandemic-induced and technological labour market shifts.

Keywords: Skills; Wage premium; Machine-assisted mixed methods; big data; Large Language Model; LLM; COVID-19; AI; artifical intelligence (search for similar items in EconPapers)
JEL-codes: C45 J24 O33 (search for similar items in EconPapers)
Date: 2026-08-20
References: Add references at CitEc
Citations:

Downloads: (external link)
https://cris.maastrichtuniversity.nl/ws/files/321210553/wp2026-010.pdf (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:unm:unumer:2026010

DOI: 10.53330/QGGU3545

Access Statistics for this paper

More papers in MERIT Working Papers from United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT) Contact information at EDIRC.
Bibliographic data for series maintained by Ad Notten ( this e-mail address is bad, please contact ).

 
Page updated 2026-08-21
Handle: RePEc:unm:unumer:2026010