Siyka Kovacheva and Gergana DimitrovaPaisii Hilendarski University of Plovdiv

Department of Applied and Institutional Sociology 

Social inequalities in the educational transitions of

Bulgarian youth

Research question

What social inequalities shape young people’s pathways through the levels of the educational system and from there to the labour market?

Previous studies of youth transitions

• ECE_Youth: An Evaluation of Programmes to Assist the Young Unemployed in East-Central Europe, ACE Program, EC (1996-98): four East European countries, survey focusing on young people’s strategies for finding a way out of unemployment

• Fate: Families and Transitions in Europe, Fifth FP, EC (2001-4): eight European countries, survey with graduates and in-depth interviews with parents

• Up2Youth: Youth – Actor of Social Change, 6th FP, EC (2006-9): twelve European countries, secondary data and interviews-in-depth

• SAHWA: Empowering the young generation: towards a new social contract in South and East Mediterranean countries, 7th FP, EC (2014-16), five MENA countries, combined methodology

Theoretical perspective

• Youth as a social group, embedded in a web of social relations which place the young both in and out of the life domains of education, work, family, politics and leisure ( Jones, 2009; Cote, 2014).

• Youth transitions as influenced by the interplay of social structures and individual agency (Roberts, 2009; Furlong, 2013).

• Youth culture as a system of general (social) and specific (youth) values, attitudes and modes of behaviour which lies at the basis of the process of ‘juventization’ of society (Mitev, 1982; Mahler, 1983).

Sources of data for this study2014 study ‘Portrait of Bulgarian youth’ 

• funded by the Friedrich Ebert Foundation• following the model of the German Schell Studies • relying on a representative survey with a probability sample of 1030

young people aged 14-27 and • 10 interviews-in-depth with young people stratified by gender, age

group, ethnicity and type of settlement• focusing on young people’s values and practices in different life

domains.

Official statistical data about the economic context in the country, young people’s participation in education and employment

The social situation of BG youth

• Slow economic recovery in 2013-14, 22% youth unemployment

• Continuing expansion of education, still only 30% (of those aged 30-34) are with tertiary education and 12% early school leavers

• Low flexibility of the labour market in terms of part-time work and atypical contracts (although high informal flexibility)

• Highest share of youth at risk of poverty in the EU, based on Eurostat data and highest score on the Social Exclusion Index, calculated by the European Foundation for the Improvement of Living and Working Conditions

Trends shaping youth transitions from school to work

• Rising educational aspirations (in comparison with previous surveys)

• High satisfaction with the quality of education and school life in general (in comparison with other Balkan countries)

• More active job search strategies, preference for private sector employment and high (declared) readiness to start their own business

• Growing individualization in life (educational and work) projects

• Growing individualization in self-defined values

Educational Aspirations

Current occupational status

Regression models

What explains the inequalities in the educational aspirations of young people and then their integration into the labour market?

Dependent variables: - educational aspirations (higher education)- occupational status (employed+selfemployed)

Independent variables• socio-demographic factors: gender, ethnicity,

type of settlement, parents’ education, social strata, household expenditures, financial difficulties

• educational factors: grades, desired specialty, satisfaction with education, keen to go to school, practical training, private lessons

• values: being independent, having a career, and beliefs about the ways for success at school and in finding a job

Logit model of the likelihood of ‘aspirations for higher 

Pseudo R-Square

Cox and Snell ,501

Nagelkerke ,700

McFadden ,553

Likelihood Ratio Tests

Effect Model Fitting

Criteria

Likelihood Ratio Tests

-2 Log Likelihood

of Reduced Model

Chi-Square df Sig.

Intercept 319,853a ,000 0 .

s4 gender 321,874b 2,022 7 ,959

s5_age 348,733b 28,881 91 1,000

s7 ethnicity 228,755b . 28 .

s2 type of settlement 393,137b 73,285 21 ,000

s6b mother’s education 286,995b . 35 .

s6c father’s education 342,429b 22,576 35 ,948

class1 (social strata) 377,442b 57,589 21 ,000

m10 household expenditures 1224,946b 905,093 91 ,000

e3 having experienced financial difficulties 326,649b 6,796 14 ,942

e7 school grades 4921,728b 4601,875 28 ,000

e11 desired specialty at school 344,740b 24,887 21 ,252

e12 keen to go to school 364,054b 44,201 35 ,137

e5 private lessons ,009b . 35 .

e15 having had practical training 313,406b . 14 .

e19 thinking about own business 312,490b . 21 .

a7_3 being independent 294,967b . 21 .

a7_5 having a career 263,076b . 21 .

b4_2 being discriminated against 342,137b 22,284 49 1,000

e2 personal abilities and efforts at school 215,408b . 28 .

e17 personal abilities and efforts in finding a job 344,048b 24,196 28 ,671

The chi-square statistic is the difference in -2 log-likelihoods between the final model and a reduced model. The reduced

model is formed by omitting an effect from the final model. The null hypothesis is that all parameters of that effect are 0.

a. This reduced model is equivalent to the final model because omitting the effect does not increase the degrees of

freedom.

b. Unexpected singularities in the Hessian matrix are encountered. This indicates that either some predictor variables

should be excluded or some categories should be merged.

Logit model of the likelihood ‘to be employed’ 

Pseudo R-Square

Cox and Snell ,447

Nagelkerke ,660

McFadden ,524

Likelihood Ratio Tests

Effect Model Fitting

Criteria

Likelihood Ratio Tests

-2 Log Likelihood

of Reduced Model

Chi-Square df Sig.

Intercept 304,959a ,000 0 .

s4 gender 306,754 1,795 1 ,180

s5_age 404,672 99,713 13 ,000

s7 ethnicity 313,739 8,780 4 ,067

s2 type of settlement 307,384 2,426 3 ,489

s6b mother’s education 307,112 2,153 5 ,828

s6c father’s education 311,843 6,884 5 ,229

class1 (social strata) 313,478 8,519 3 ,036

m10 household expensditures 343,539 38,581 13 ,000

e3 having experienced financial difficulties 305,008 ,049 2 ,976

e7 school grades 308,583 3,624 4 ,459

e11 desired specialty at school 305,214 ,255 3 ,968

e12 keen to go to school 312,438 7,479 5 ,187

e5 private lessons 310,103 5,144 5 ,399

e15 having had practical training 305,688 ,729 2 ,694

e19 thinking about own business 324,136 19,177 3 ,000

a7_3 being independent 306,037 1,078 3 ,782

a7_5 having a career 308,629 3,670 3 ,299

b4_2 being discriminated against 316,299 11,340 7 ,124

e2_personal abilities and efforts in school 306,225 1,266 4 ,867

e17_ personal abilities and efforts in finding a job 306,572 1,613 4 ,806

The chi-square statistic is the difference in -2 log-likelihoods between the final model and a reduced model. The

reduced model is formed by omitting an effect from the final model. The null hypothesis is that all parameters of that

effect are 0.

a. This reduced model is equivalent to the final model because omitting the effect does not increase the degrees of

freedom.

Factors explaining educational aspirations and labour market integration

Aspirations for higher education:• Living in the capital• Wealthy family• High household expenditures• Having high grades

Employment:• Being older• Bulgarian ethnicity• Wealthy social strata• High household expenditures• Thinking about own business

ConclusionThe analysis showed that both educational aspirations and labour market integration of young people in Bulgaria are strongly dependent upon their family background (ethnicity, place of living, and most importantly the financial resources of the family). While in the study we measured a growing individualization of values and life styles (mainly in leisure), still the school-to-work transition was found to be highly influenced by structural factors. Having higher academic success at school has a positive impact on the wish to go to the university but none of the examined school factors increased the likelihood of being in employment. Among the personal values examined in the study, having an entrepreneurial mind raised the chances of finding a job.

Thank you for your attention!