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NEET) in the Mediterranean EU South Young people not in employment, education or training (NEET) in the Mediterranean EU South: a study of the phenomenon for the recent crisis University of the Aegean, Greece Effie Emmanouil | Michalis Poulimas Οι Κοινωνικές Επιστήμες Σήμερα. Διλήμματα Ioannis Papageorgiou | Stelios Gialis και Προοπτικές πέρα από την Κρίση Λέσβος, 06-09.06.2019 Introduction • the new socioeconomic era - deep recession, followed by an anemic/ weak growth • problems of entering into new jobs or maintaining working placements • precariousness • youth unemployment & early school leaving… NEET: concerns persons who are involved in the two conditions below (Eurostat 2019) • -“they are not employed” (i.e. unemployed or inactive) • -“they have not received any formal or non-formal education or training in the four weeks preceding the survey” “a basic tool for understanding the magnitude of youth vulnerability in relation to the risk of social exclusion and labor market” • Heterogeneity Introduction Aim of the Research – Case Study In order effective policies to be established … Explore / Research: “Low levels of aspiration and little •which age group/ gender is more vulnerable motivation?” •which country/ region is more is more affected •reveal the uneven geographical growth (degree of urbanisation) •the NEETs composition in the study countries •reveal if the problem is unemployment or inactivity and how it is formed Methodological approach: study regions: •geographical / cultural political economy (GR): Attica, Central Macedonia, North & South •secondary data analysis Aegean •use of LQ index to reveal potential concentrations (CY): Cyprus (ES): Madrid, Andalucía, Baleares, Communita Valenciana, Cataluña, Murcia Case study: (IT): Lazio, Lombardia, Campagnia, Basilicata, Sicily, focus on NUTS 2 level: Sardegna •study countries: Greece, Cyprus, Spain and Italy Source: Data from the Labor Force Surveys of Eurostat & the national statistical offices Comparing countries… in rates NEET rates (15-19) NEET rates (20-24) Italy: the highest rates in 15-24 Greece & Italy: the highest rates in 25-29 NEET rates (25-29) Comparing countries… in numbers (2008=100) NEET numbers 2008=100 (15-19) NEET numbers 2008=100 (20-24) For 20-24 and 25-29: the maximum point was in 2013 -2014 For 15-19: more stable rate progress over time Tendency of reduction and return to the initial levels (mainly in Spain – Greece) NEET numbers 2008=100 (25-29) Comparing regions… in rates Sicily, Campagna, Basilicata & Central Macedonia: the highest rates Cyprus, Madrid, Cataluna & Lombardia: the lowest rates NEET rates of the study regions (25-29) Comparing regions… in numbers (2008=100) Lazio, Lombardia, & Cyprus have the highest increase since 2008 In all the Spanish study regions, the NEET numbers are lower in 2018 than in 2008 NEET numbers 2008=100 of the study countries (25-29) Greece NEETs male/female population in rates (25-29) NEETs’ composition (25-29) Unemployed – Inactive (25-29) at the large study regions *unemployment’s denominator is the labour force *inactivity’s denominator is the total population Cyprus NEETs male/female population in rates (25-29) NEETs’ composition (25-29) Unemployed – Inactive (25-29) at the large study regions *unemployment’s denominator is the labour force *inactivity’s denominator is the total population Italy NEETs male/female population in rates (25-29) NEETs’ composition (25-29) Unemployed – Inactive (25-29) at the large study regions *unemployment’s denominator is the labour force *inactivity’s denominator is the total population Spain NEETs male/female population NEETs’ composition (25-29) in rates (25-29) Unemployed – Inactive (25-29) at the large study regions *unemployment’s denominator is the labour force *inactivity’s denominator is the total population Comparing regions… using the LQ index LQ >1,2 – over-concentration LQ <0,8 – de-concentration Attica C. MacedoniaNorth AegeanSouth Aegean Andalucia Baleares Cataluna Madrid C. Valenciana Murcia Lombardia Lazio CampagnaBasilicata Sicilia Sardegna 2008 0.8 1.0 1.0 1.3 1.4 1.0 1.0 0.7 0.9 1.2 0.6 0.7 1.9 1.4 1.9 1.3 2009 0.8 1.0 1.2 1.3 1.3 0.9 1.0 0.7 1.1 1.2 0.6 0.9 1.8 1.3 1.7 1.3 2010 0.8 1.1 1.1 1.1 1.3 1.0 0.9 0.7 1.1 1.1 0.6 0.9 1.7 1.5 1.6 1.2 2011 0.9 1.1 1.1 0.9 1.3 1.1 0.9 0.8 1.0 1.2 0.6 1.0 1.7 1.4 1.7 1.2 2012 0.9 1.0 1.0 0.7 1.3 1.0 0.9 0.8 1.0 1.1 0.6 0.9 1.6 1.4 1.8 1.2 2013 0.9 1.0 0.7 0.9 1.3 0.8 0.9 0.7 1.0 1.1 0.7 0.9 1.5 1.3 1.6 1.3 2014 0.9 1.0 0.9 0.9 1.2 0.9 0.9 0.8 1.0 1.0 0.6 0.9 1.5 1.2 1.6 1.3 2015 0.9 1.1 0.9 0.6 1.2 0.9 0.9 0.8 1.0 1.2 0.6 1.0 1.4 1.2 1.6 1.2 2016 0.8 1.1 1.0 1.1 1.3 0.9 0.8 0.9 0.9 1.0 0.6 0.9 1.5 1.0 1.5 1.3 2017 0.8 1.0 1.0 1.2 1.4 0.9 0.8 0.9 0.8 1.1 0.6 0.9 1.4 1.3 1.6 1.2 2018 0.8 1.0 0.9 1.1 1.4 0.8 0.9 0.8 1.0 0.9 0.6 0.9 1.5 1.2 1.7 1.3 Attica, Madrid, Lazio: de concentration Greece: insignificant uneven concentration 0,8<LQ<1,3 Spain: 0,8<LQ<1,2 in all regions, except Andalucia, LQ=1,4 in 2018 Italy: South regions <1,2<LQ<1,9 over-concentration Comparing regions… using the LQ index LQ >1,2 – over-concentration LQ <0,8 – de-concentration Attica, Madrid, Lazio: de concentration Greece: insignificant uneven concentration 0,8<LQ<1,3 Spain: 0,8<LQ<1,2 in all regions, except Andalucia, LQ=1,4 in 2018 Italy: South regions <1,2<LQ<1,9 over-concentration Comparing regions… using the LQ index - GDP per capita Attica C. Macedonia North Aegean South Aegean Andalucia Baleares Cataluna Madrid C. Valenciana Murcia Lombardia Lazio CampagnaBasilicata Sicilia Sardegna 2008 1,3 0,8 0,8 1,1 0,8 1,1 1,2 1,3 0,9 0,8 1,3 1,2 0,7 0,7 0,7 0,7 2009 1,4 0,8 0,8 1,1 0,8 1,0 1,2 1,3 0,9 0,8 1,3 1,3 0,7 0,7 0,7 0,8 2010 1,4 0,8 0,8 1,1 0,8 1,0 1,2 1,3 0,9 0,8 1,3 1,2 0,7 0,7 0,7 0,7 2011 1,4 0,8 0,8 1,1 0,8 1,0 1,2 1,4 0,9 0,8 1,3 1,2 0,6 0,7 0,6 0,7 2012 1,4 0,8 0,8 1,0 0,7 1,0 1,2 1,4 0,9 0,8 1,3 1,2 0,6 0,7 0,6 0,8 2013 1,4 0,8 0,8 1,1 0,7 1,0 1,2 1,4 0,9 0,8 1,3 1,2 0,6 0,7 0,6 0,7 2014 1,4 0,8 0,8 1,1 0,7 1,1 1,2 1,4 0,9 0,8 1,3 1,2 0,6 0,7 0,6 0,7 2015 1,4 0,8 0,8 1,1 0,7 1,0 1,2 1,4 0,9 0,8 1,3 1,1 0,6 0,8 0,6 0,7 2016 1,4 0,8 0,7 1,1 0,7 1,1 1,2 1,4 0,9 0,8 1,3 1,2 0,6 0,7 0,6 0,7 2017 1,4 0,8 0,7 1,1 0,7 1,0 1,2 1,3 0,9 0,8 1,3 1,1 0,6 0,7 0,6 0,7 Attica, Madrid, Lombadia: over concentration Greece: not significant uneven concentration except Attica Spain: Andalucia – de concentation Italy: South regions - de concentation Results Gender distinction: for all countries: female vulnerability Age vulnerability: •Greece = distinctively 25-29 •Cyprus = 20-24 nowadays •Spain & Italy = 25-29 (slight difference) NEETs composition (unemployed – inactive): •Greece, Cyprus & Spain = youth unemployment •Italy = inactivity Youth unemployment / inactivity •unemployment follows the recession pattern, •inactivity does not follow society’s changes Results Uneveness: Italy: significant uneven concentration (North - South) Urbanisation: Capital cities tend to have lower NEET rates GDP per capita: Tension of over-concentration GDP & de-concentration of NEETs Conclusions •Tendency of reduction but still in high rates…not a recent phenomenon •A matter of unemployment or inactivity? •A matter of agency or structure? •Reconsider the existing policies (Youth Guarantee)? •Proof of stereotypes?…”underdeveloped South” •Periphery and Unevenness – space’s crucial and active role Acknowledgements: A.Kizos, Professor of the Aegean University C. Pesquera – Alonso, PhD Candidate of the Catholic University of Murcia.
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