- Data, Statistics and AI for Well-Being of People and Organisations
- Edited by Luigi Fabbris, Alberto Franci, Pietro Renzi
Sectoral employment changes: A multi-source analysis
- Annalisa Lucarelli
- Alessandra Righi
- Roberta Rizzi
- © 2026 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-1062-1.47
This work aims to enhance the understanding of labour demand changes at the sectoral level on the basis of a multi-source approach. Among the statistical official sources available, the Compulsory Communication system (Italian Ministry of Labour and Social Policies), the Excelsior Information System (Unioncamere), the Istat quarterly survey on job vacancies and hours worked and the Labour Force survey are taken into account. The study outlines a framework of the characteristics and limitations of the different sources in order to ensure their comparability. It examines whether these sources are consistent with each other in indicating employment trends and clarifies any discrepancies. While using these sources raises questions of consistency, it also allows for a deeper analysis, particularly with regard to introducing the sectoral dimension. Hence, the study attempts to highlight the occupational needs emerging from the different economic activity sectors by using indicators derived from the different sources.
- Keywords:
- labour demand,
- multi-source approach,
- economic activity sector,
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0000-0001-7764-2261
ISTAT, Italian National Institute of Statistics, Italy
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Chapter Information
Chapter Title
Sectoral employment changes: A multi-source analysis
Authors
Annalisa Lucarelli, Alessandra Righi, Roberta Rizzi
Language
English
DOI
10.36253/979-12-215-1062-1.47
Peer Reviewed
Publication Year
2026
Copyright Information
© 2026 Author(s)
Content License
Metadata License
Bibliographic Information
Book Title
Data, Statistics and AI for Well-Being of People and Organisations
Editors
Luigi Fabbris, Alberto Franci, Pietro Renzi
Peer Reviewed
Number of Pages
420
Publication Year
2026
Copyright Information
© 2026 Author(s)
Content License
Metadata License
Publisher Name
Firenze University Press
DOI
10.36253/979-12-215-1062-1
ISBN Print
979-12-215-1061-4
eISBN (pdf)
979-12-215-1062-1
eISBN (xml)
979-12-215-1063-8
Series Title
Applied Statistics Series