Template-type: ReDif-Paper 1.0
Author-Name: Rony, Sidharth
Author-workplace-name: RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn
Title: LLM Meets Job Advertisements: Unmasking Skill Premia in the UK
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
Classification-JEL: j24,c45,o33
Series: UNU-MERIT Working Papers
Creation-Date: 20260820
Number: 010
File-URL: https://cris.maastrichtuniversity.nl/ws/files/321210553/wp2026-010.pdf
File-Format: application/pdf
File-Size: 5085830
Handle: Repec:unm:unumer:2026010
DOI: 10.53330/QGGU3545