Young NEETs in the EU South: socio-spatial and gender divisions in between the Great Recession and the Covid-19 pandemic

ABSTRACT

The 2008/2009 global economic recession and the Covid-19 pandemic fuelled a heap of social and economic problems, including growing youth unemployment and inactivity. Amidst this pressing conjuncture, female youngsters living in economically deprived regions have been affected the most. The paper in hand studies the changing analogies between young women that are “Not in Employment, Education or Training” (the so-called NEETs) and young men of the same status, between 2008 and 2020, across the regions of four EU South countries. By employing a mixed-methods approach, namely analysing quantitative indices and semi-structured interviews, we put the gender divisions and the geographically uneven distribution of NEETs under thorough scrutiny. Furthermore, by adopting a spatially-sensitive perspective, the paper elucidates key underlying factors behind NEETs’ persistence in some of the EU’s least-prosperous regions. Along with several structural and institutional factors, peripherality, regional specialization and gender divisions are indicated as crucial, though commonly neglected, dimensions of contemporary youth disengagement.

KEYWORDS:

• Youth unemployment
• inactivity
• regional resilience
• 2008/2009 crisis
• impact of the pandemic
• youthspaces

Acknowledgements

The corresponding author (Athina Avagianou) received funding for this paper from the ‘ESPON (2020) Cooperation Programme within the framework of the initiative to support young researchers and dissemination of ESPON results among the scientific community.’

The authors of this paper are researchers of the project YOUTHShare - ‘A Place for Youth in Mediterranean EEA: Resilient and Sharing Economies for NEETs’ (www.youthshare-project.org), which is funded by Iceland, Liechtenstein and Norway through the EEA and Norway Grants Fund for Youth Employment (2018-2022). The third author (Stelios Gialis) acknowledges the contribution of a DAAD - ‘Research Stays for Academics 2022’ scholarship in the finalization of the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed here

Notes

1. The RRYI composite indicator includes 9 variables: i) Youth Unemployment Rate (15–24 years old); ii) Youth ratio of young unemployed (15–24) to working-age 25–64; iii) NEETs rate; iv) Youth economic activity; v) Youth employment per education attainment (Level 0–2); vi) Youth employment per education attainment (Level 5–8); vii) Youth average weekly hours of work in the main job; viii) GDP per capita in PPP; ix) GDP Growth rate (2-year lag).

2. All secondary data are available upon request.

3. Eurostat is the coordinator agency of all national statistical agencies of the EU Member states. For Greece: HELSTAT_Hellenic Statistical Authority (https://www.statistics.gr/en/home); for Cyprus: CYSTAT Cypriot Statistical Service (https://www.cystat.gov.cy/en); for Italy: ISTAT Istituto Nazionale di Statistica (https://www.istat.it/en); for Spain: INE_ Instituto Nacional de Estadistica (ttps://www.ine.es)

4. The LQ is calculated by dividing the regional share of NEETs with the share of NEETs in all four study countries. When LQ values are lower than 0.75, NEETs are considered as under-concentrated in the region in relation to the whole study area; respectively, NEETs are over-concentrated in a region when that region’s LQ value is higher than 1.25.

5. For Greece: North Aegean, South Aegean, Ionian Islands, Crete; Spain: the Balearic Islands, Canary Islands; Italy: Sicily, Sardinia; Cyprus

6. 23 interviewees are actively seeking employment; 7 interviewees are not seeking employment

7. We conducted 9 interviews in Italy and 7 in each of the other three southern European countries (Spain, Greece and Cyprus).

8. 9 interviewees: Higher secondary school certificate; 5 interviewees: Vocational post-secondary certificate; 9 interviewees: Bachelor’s degree; 4 interviewees: Master’s degree; 2 interviewees: Lower secondary school certificate; 1 interviewee: Non-formal/post-secondary vocational certificate.

9. 9 interviewees: Bottom 25%: 0–10.000€; 10 interviewees: Low/median 25%: 10.000–20.000€; 6 interviewees: Median 25%: 20.000–30.000€; 0 interviewees: High 25%: >30.000€

Additional information

Funding

This work was supported by the ESPON (2020) Programme (2014TC16RFIR004) [ESPON 2020 Programme (2014TC16RFIR004) EE/SO4/133/2021].