Subnational Level Data to Measure Gender (in)Equality in the EU: Opportunities and Limitations of Official Datasets

Publication typeBook Chapter
Publication date2023-12-30
SJR
CiteScore0.9
Impact factor
ISSN13876570
Abstract

Over the past decades, the detail used to describe the socio-economic context through statistical indicators has evolved in several directions, one of which is the increasing territorial detail that has gone down to the sub-national level. Ongoing trends in gender equality measurement confirm the interest in a more geographically detailed analysis. Recent studies presented by the JRC or commissioned by the European Union’s DG-REGIO have gone precisely in this direction. The use of national indicators may in fact result in a ‘compensation’ effect that may hide very important differences within a single national territory. this is more true in those realities where historical/cultural events have led to known internal differences. This chapter discusses the importance of developing subnational level analyses for gender equality and at the same time assesses the availability of regional-level data within the Eurostat system.

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Socio-Economic Planning Sciences
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Elsevier
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Di Bella E., Culotta F. Subnational Level Data to Measure Gender (in)Equality in the EU: Opportunities and Limitations of Official Datasets // Subjective Well-Being and Security. 2023. pp. 119-134.
GOST all authors (up to 50) Copy
Di Bella E., Culotta F. Subnational Level Data to Measure Gender (in)Equality in the EU: Opportunities and Limitations of Official Datasets // Subjective Well-Being and Security. 2023. pp. 119-134.
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RIS Copy
TY - GENERIC
DO - 10.1007/978-3-031-41486-2_5
UR - https://doi.org/10.1007/978-3-031-41486-2_5
TI - Subnational Level Data to Measure Gender (in)Equality in the EU: Opportunities and Limitations of Official Datasets
T2 - Subjective Well-Being and Security
AU - Di Bella, Enrico
AU - Culotta, Fabrizio
PY - 2023
DA - 2023/12/30
PB - Springer Nature
SP - 119-134
SN - 1387-6570
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@incollection{2023_Di Bella,
author = {Enrico Di Bella and Fabrizio Culotta},
title = {Subnational Level Data to Measure Gender (in)Equality in the EU: Opportunities and Limitations of Official Datasets},
publisher = {Springer Nature},
year = {2023},
pages = {119--134},
month = {dec}
}