Author
Listed:
- Nicolò Barbieri
(Department of Economics and Management, University of Ferrara, Ferrara, Italy)
- Pietro Casavecchia
(Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy; Applied Computational Logic and Artificial Intelligence (ACLAI) Lab, University of Ferrara, Ferrara, Italy)
- Fabio Landini
(University of Parma)
- Giacomo Roberto Lupi
(Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy)
- Alberto Marzucchi
(Gran Sasso Science Institute)
- Giovanni Pagliarini
(Applied Computational Logic and Artificial Intelligence (ACLAI) Lab, University of Ferrara, Ferrara, Italy)
- Ugo Rizzo
(Department of Economics and Management, University of Ferrara, Ferrara, Italy; Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy)
- Daniele Rotolo
(Department of Mechanics, Mathematics and Management, Polytechnic of Bari, Bari, Italy; SPRU – Science Policy Research Unit, University of Sussex Business School, Brighton, United Kingdom)
- Guido Sciavicco
(Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy; Applied Computational Logic and Artificial Intelligence (ACLAI) Lab, University of Ferrara, Ferrara, Italy)
Abstract
This paper develops a novel empirical framework to measure the skill content of higher education programmes. Using natural language processing techniques, we link the official descriptions of Italian degree programmes to the ESCO taxonomy of labour-market skills, constructing a high-dimensional skill provision matrix covering more than 48,000 programme-year observations over 2013–2022. We exploit this skill-based representation in two applications. First, we map the distribution and evolution of green skills across disciplines and territories. Second, we construct measures of programme-level uniqueness and examine their association with first-year enrolment. While abstract skill-based uniqueness is not significantly related to enrolment, a geographically weighted measure—capturing differentiation relative to proximate alternatives—is positively and robustly associated with student demand. The proposed methodology provides a scalable and flexible tool to open the “black box†of curricular content and can be readily extended to a wide range of applications, including the analysis of skill alignment, institutional adaptation, and the evolving geography of higher education provision.
Suggested Citation
Nicolò Barbieri & Pietro Casavecchia & Fabio Landini & Giacomo Roberto Lupi & Alberto Marzucchi & Giovanni Pagliarini & Ugo Rizzo & Daniele Rotolo & Guido Sciavicco, 2026.
"Course Descriptions and Skill Supply: An Exploration of Green Content and Uniqueness,"
SEEDS Working Papers
0626, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Feb 2026.
Handle:
RePEc:srt:wpaper:0626
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Keywords
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JEL classification:
- I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
- I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development
- J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
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