CoChat
Sign Up
Cited by 199Labor market dynamics and wage inequalityLabor Market and EducationDigital literacy in education

The DOI matches its Crossref record; 73 of the 74 references it cites were found in a registry or an index.

What is the price of a skill? The value of complementarity

Open access
Stephany, Fabian, Teutloff, Ole·2024·Research Policy
DOI 10.1016/j.respol.2023.104898
Open this paper in CoChat — free account

Abstract

The global workforce is urged to constantly reskill, as technological change favours particular new skills while making others redundant. But which skills are a good investment for workers and firms? As skills are seldomly applied in isolation, we propose that complementarity strongly determines a skill's economic value. For 962 skills, we demonstrate that their value is determined by complementarity – that is, how many different skills, ideally of high value, a competency can be combined with. We show that the value of a skill is relative, as it depends on the skill background of the worker. For most skills, their value is highest when used in combination with skills of a different type. We put our model to the test with a set of skills related to Artificial Intelligence (AI). We find that AI skills are particularly valuable – increasing worker wages by 21 % on average – because of their strong complementarities and their rising demand in recent years. The model and metrics of our work can inform the policy and practice of digital re-skilling to reduce labour market mismatches. In cooperation with data and education providers, researchers and policy makers should consider using this blueprint to provide learners with personalised skill recommendations that complement their existing capacities and fit their occupational background.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.respol.2023.104898

Cites

73 of 74 references verified0 citation errors · 1 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Citations

Cites

Show all 66 references

Research works printed but not linked: 2

  1. Grundke, 2018, Which skills for the digital era?: returns to skills analysis, OECD.
  2. Squicciarini, 2021, Demand for AI skills in jobs: evidence from online job postings, OECD.

Cited by

Sorted by citations

Items 101–199 of 199

Related

See all

Metadata

Authors
Stephany, F., & Teutloff, O.
Affiliations
  • Bruegel (BE)
  • University of Copenhagen (DK)
Corresponding author
Stephany, Fabian
ORCID
Venue
Research Policy
Publisher
Elsevier BV
Published
2024-01
Volume
53
Issue
1
Pages
104898
ISSN
0048-7333 (ISSN-L)
DOI
10.1016/j.respol.2023.104898
OpenAlex
W4387794313
Semantic Scholar
3751f50d9b59a9804e271572fcd47c100ceae93d
Cited by
199
References
66
Citations by year
2026: 37 · 2025: 42 · 2024: 118
FWCI
37.80
Type
journal article
Language
en
Open access
Licence
Locations
  • Research Policy (publishedVersion, cc-by)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
Funders
Economic and Social Research Council (G2781-15)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor Market and Education
  • Social Sciences › Education › Digital literacy in education
Keywords
skill complementarity, retraining, digital skills, AI competencies, labor market mismatch, skill combination

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review