Croatias Lost Generation? Youth unemployment, education and training - PowerPoint PPT Presentation

Croatia’s Lost Generation? Youth unemployment, education and training in Croatia since the crisis* Iva Tomić The Institute of Economics, Zagreb Visiting Speaker Programme LSEE Research on SEE, European Institute, LSE 12 October 2016 *in collaboration with Vassilis Monastiriotis, European Institute, LSE

Outline  Motivation  Related literature  Data  Model  Results  Policy initiatives 2

Motivation  2014 ended as a sixth consecutive year with negative real GDP growth in Croatia, with a cumulative drop of 13% as of 2009.  The unemployment rate almost doubled in the period between 2008 and 2014.  Youth unemployment rate is growing much more rapidly than the overall rate:  for conventional youth population (15-24) it increased by 25 pp between 2009 and 2013 (from 25% to 50%),  more than double the total unemployment rate,  considerably higher than the average rate of youth unemployment in the EU;  for the population aged 15-29 it increased by more than 15 pp in the same period.  the NEET rate for youths aged 15-29 was 21.8% in 2014; more than 6 pp higher than in the EU-28 (15.4%), with an increase of almost 9 pp between 2008 and 2014. 3

Source: Eurostat. 10 20 30 40 50 60 70 80 90 In % 0 2007Q1 Unemployment rates for different age-groups in Croatia 2007Q2 2007Q3 2007Q4 2008Q1 2008Q2 2008Q3 2008Q4 15-19 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 20-24 2010Q2 2010Q3 2010Q4 2011Q1 2011Q2 25-29 2011Q3 2011Q4 2012Q1 2012Q2 15-29 2012Q3 2012Q4 2013Q1 2013Q2 2013Q3 15-64 2013Q4 2014Q1 2014Q2 2014Q3 2014Q4 Motivation 2015Q1 2015Q2 2015Q3 2015Q4 4

Motivation Unemployment rates for age-group 15-29 in selected EU countries In % 50 45 40 35 30 25 20 15 10 5 0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 EU-28 Croatia Germany Greece Spain Slovenia Source: Eurostat. 5

Motivation Different indicators of youth (15-29) unemployment in Croatia In % 35 30 25 20 15 10 5 0 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Unemployment rate NEET rate Unemployment ratio Source: Eurostat. 6

Motivation  The issue of labour market exclusion has been more pressing over a longer period of time in countries of the European periphery, including Croatia. o In the (Western) Balkans in particular, levels of inactivity/non-participation are abysmally high compared to EU standards not only for the youth but for much larger segments of the working-age population.  Average youth unemployment and NEET rates, for example, are more than twice as high in these countries as those in the EU. o The literature suggests that the poor situation on the labour market in these countries has structural roots, including delayed transition, high share of informal sector, poor investment climate, skill mismatches, as well as significant dependence on remittances (Gligorov et. al., 2008; Kolev and Saget, 2005; Kovtun et al., 2014). 7

Motivation Youth (15- 24) unemployment and NEET rates in ‘extended’ Europe - 2015 In % 70 60 50 40 30 20 10 0 B&H Kosovo* Greece Spain Macedonia Serbia Croatia Italy Albania Montenegro** Cyprus Portugal Slovakia France Finland Belgium Romania Bulgaria Ireland Poland Sweden Luxembourg Hungary Latvia Lithuania Slovenia United Kingdom Estonia Czech Republic Malta Netherlands Denmark Austria Germany unemployment rate NEET rate *-2014 for NEET rate; **-NEET rate n.a. Source: ILO, ILOSTAT database. 8

Motivation  Despite the policy and social importance of the issue, studies examining empirically the individual and environmental factors contributing to non- participation of youth in the labour market or training (NEET) are rather limited and in the case of the countries in the European periphery virtually non-existent. o High and increasing youth unemployment in Croatia has received a lot of attention from both the public and the policy makers; however, academic contribution, especially empirical economics, is still missing.  Goal: to partially fill the literature gap by examining closely the determinants of youth unemployment and non-participation in ‘employment, education or training’ (NEET) for the newest EU -member state - Croatia. 9

Related literature  The literature suggests that females, less educated, and those coming from deprivileged backgrounds, including immigrants, are more exposed to being unemployed at a younger age.  Unlike in Croatia, there are some empirical studies on the youth exclusion from the labour market in different (south) European countries:  Bell and Blanchflower (2015) analyse various dimensions of historically high level of youth unemployment in Greece.  Dolado et al. (2013) examine youth labour market performance in Spain from the microperspective.  Marelli and Vakulenko (2014) estimate the unemployment risk of young people for Italy and Russia.  Kelly and McGuinness (2015) examine the impact of the recent recession on youth unemployment and youth NEET rate in Ireland. 10

Related literature  Several comparative studies focusing more specifically on the NEET population:  Bruno et al. (2014) study the impact of the recent crisis on the NEET rate and the youth unemployment rate in different EU regions.  Carcillo et al. (2015) review a situation for the NEET population since the onset of the financial crisis in the OECD countries.  Eichhorst and Neder (2014) examine youth unemployment situation in Mediterranean Countries, precisely in France, Greece, Italy, Portugal, and Spain.  Eurofound (2012) analyses characteristics, costs and policy responses in Europe of young NEET population.  Mauro and Mitra (2015) focus on the NEET youth in the Europe and Central Asia region. 11

Data  Individual Labour Force Survey (LFS) microdata obtained from the Croatian Bureau of Statistics (CBS) in the period 2007-2014  Youth population between 15 and 29 years with respect to the labour market status: excluded (NEETs) vs employed and excluded vs in education (mutually exclusive statuses)  Demographic characteristics  those usually exogenous to the individual (age, gender, ethnicity) &  more marketable characteristics, i.e. education or experience  years of education of the household head in this case (+ control variable if a youth person is actually a head of the household)  Household characteristics (socio-economic background)  marriage, household composition and household size  Area characteristics  urbanization and regional affiliation 12

Data Structure of the Croatian youth (15-29) population by their labour market status 2008 2013 work train NEET total work train NEET total Age: 15-19 6% 61% 21% 30% 3% 59% 17% 32% Age: 20-24 34% 33% 38% 34% 27% 32% 41% 33% Age: 25-29 61% 7% 41% 36% 70% 8% 43% 36% Female 41% 54% 60% 49% 45% 52% 48% 49% Married/cohabiting 26% 1% 31% 16% 21% 1% 21% 12% Foreign-born 7% 6% 8% 7% 7% 3% 10% 6% Low education 6% 51% 19% 27% 4% 51% 13% 27% Medium education 78% 47% 70% 64% 71% 43% 71% 58% High education 16% 1% 11% 9% 26% 6% 17% 15% Household size 4.2 4.5 4.9 4.4 4.1 4.4 4.3 4.3 Youth head of the household 7% 1% 3% 4% 9% 2% 4% 4% Years of education of the household head 10.8 11.8 10.1 11.1 11.2 11.9 10.8 11.5 Urban area of living 49% 58% 44% 52% 56% 62% 51% 58% Northwest Croatia 41% 40% 27% 39% 43% 39% 32% 38% Central & Eastern Croatia 27% 27% 46% 29% 25% 28% 37% 29% Adriatic Croatia 32% 34% 27% 32% 32% 33% 31% 32% No. of observations 3317 3526 902 7745 1823 3072 1362 6257 Source: Labor Force Survey (LFS) data obtained from the Croatian Bureau of Statistics. 13

Data  Employed youths are older than both NEET and those in education (70% of 25+ year-olds in 2013).  Male workers experienced stronger unemployment growth in the crisis (female share among NEETs decreased by more than 10 pp).  Share of married youth decreased in all groups in the observed period.  More ‘foreigners’ among NEETs than within other two groups, especially in 2013.  Visible increase of those with finished higher education (Bologna process?).  NEETs generally come from larger households, but this has almost ceased in the crisis.  Lowest levels of education of the household head for NEET youths and highest for those in education.  Increased share of urban population during the crisis in all groups.  Disproportionately high share of youth NEETs in Central and Eastern Croatia; during the crisis Northwestern Croatia has gained a lot of youth unemployed/NEETs. 14

Model  The risk of youth unemployment (non-participation) o What is the alternative to unemployment/NEET status:  employment or  education? Youths (15-29) search search (NEETs) (NEETs) vs. vs. work train (employed) (in education) 15