women’s job opportunities in eastern europe: effects of education and migration
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Women’s Job Opportunities in Eastern Europe: Effects of Education and Migration. Outi Kärkkäinen 24 January 2008, World Bank, Washington D.C. Workshop on Sharing Growth Dividend: Women in the ECA Region. What is the ETF?. - PowerPoint PPT PresentationTRANSCRIPT
Women’s Job Opportunities in Eastern Europe: Effects of Education and Migration
Outi Kärkkäinen
24 January 2008, World Bank, Washington D.C.
Workshop on Sharing Growth Dividend: Women in the ECA Region
What is the ETF?
A specialised agency of the European Union financed by the European Commission
EU’s centre of expertise supporting education and training reform in the context of the EU’s external relations programmes
Mission: we assist the EU’s neighbouring countriesin developing and modernisation of HRD policies and putting them into practice
Specific field: vocational education and training and its links to the labour market/employment
We also assist the Commission in implementing the Tempus programme for the development of higher education systems in partner countries
Some facts and figures Established 1990 (Council Reg. 1360)
Operational from 1994
Based in Turin, Italy
Director Muriel Dunbar
Staff 104 +
Budget €19,7 million (2007)
Partner countries +/- 30
ETF’s partner countries
Other countries from Central Asia: Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan
Potential candidate countries: Albania, Bosnia and Herzegovina, Kosovo, Montenegro, Serbia
Acceding and Candidate countries:Croatia, Macedonia FYR, Turkey
European Neighbourhood Countries: Algeria, Armenia, Azerbaijan, Belarus, Egypt, Georgia, Jordan, Israel, Lebanon, Morocco, Moldova, Russia, Syria, Tunisia, Ukraine, West Bank and Gaza Strip
Education and Labor Market Outcomes for Women
Education: An asset that pays off equally for men and women in the transition
countries for accessing the labor market? Do women and men have equal possibility and capacity to benefit of
their educational asset in integrating the home country labor market? In a situation where migration is an opportunity or the only possibility to find employment?
Case pilot studies:1. Transition from Education to Work in Ukraine and Serbia: assessing
both the quantity and quality of the jobs taken up by young people2. Migration Patterns and HRD Albania and Moldova (Egypt and
Tunisia): links between migration, education and training systems and labor market
Transition from School to Work in Ukraine and Serbia Methods and Data
Target group: individuals aged 15-34 who had left education for the first time in the previous 5 years in Serbia and 6 years in Ukraine
Samples: 1,504 respondents out of 8,593 households contacted (17.5%) in Serbia and 2,015 respondents out of 25,081 (8.0%) in Ukraine – Actual response rates 67.5% in Serbia and 68.3% in Ukraine
Monthly data on the labor status of individuals between leaving education and the time of the survey with a distinction between two major types of jobs1. First ever job2. First significant job = lasting a minimum of 6 months and having a
minimum timetable of 20 hours a week
Transition from School to Work in Ukraine and Serbia Methods and Data
The questionnaire used during the survey was structured to cover:
Situation before leaving continuous education for the first timeMonthly calendar of activities since leaving educationFirst job and first significant job after leaving educationCurrent labour market situationEducation and training since leaving educationSociodemographic characteristics.
Transition from School to Work in Ukraine and Serbia General Findings
Transition process relatively more quick in Ukraine: 3/5 of Ukrainian and 1/3 of Serbian school leavers had a significant job 6 months after leaving education
Difference in quality of jobs and use of skills: Serbian young people remained unemployed longer or took up
different kinds of informal jobs Relatively more Ukrainian young people were employed in the formal
sector but often in jobs of low wages and low qualification level Education played a major role in both countries in order of priority:
1. Post-secondary education (including university graduates) 2. Secondary vocational education3. Secondary general education
Transition from School to Work in Ukraine and Serbia
Gender Differences: Activity Rates
1
Transition from School to Work in Ukraine and Serbia
Gender Differences: Unemployment Rates
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59
Months since leaving education
Un
em
plo
ym
en
t ra
te
Men Ukraine
Women Ukraine
Men Serbia
Women Serbia
Transition from School to Work in Ukraine and Serbia
Gender Differences: Length of the Transition PeriodSerbia
Time to first ever job by gender (%)
7.3
25.3
8.2
12.3
19.2
27.7
7
22
8.410.6
15
37
0
5
10
15
20
25
30
35
40
No search 1-3 mths 4-6 mths 7-12 mths 1-2 yrs > 2 yrs
Men
Women
UkraineTime to first ever job by gender (%)
14.3
49.1
8.6 7 813
15.2
40.5
8.3 6.4 6.7
22.8
0
10
20
30
40
50
60
No search 1-3 mths 4-6 mths 7-12 mths 1-2 yrs > 2 yrs
Men
Women
Transition from School to Work in Ukraine and Serbia
Gender Differences: Length of the Transition Period
SerbiaTime to first significant job by gender (%)
6.8
19.3
6.2
10.814.6
42.3
6.5
18.6
8.3 9.4
14
43.2
0
5
10
15
20
25
30
35
40
45
50
No search 1-3 mths 4-6 mths 7-12 mths 1-2 yrs > 2 yrs
Men
Women
UkraineTime to first significant job by gender (%)
13.6
41
8.66.4
9.9
20.5
14.2
34.8
7.6 6.4 6.3
30.7
0
5
10
15
20
25
30
35
40
45
No search 1-3 mths 4-6 mths 7-12 mths 1-2 yrs > 2 yrs
Men
Women
Transition from School to Work in Ukraine and Serbia
Gender Differences: Status of the JobSerbia
First Ever Job employment by Gender (%)
46.7
38.4
6.3 7.21.2
51.7
39.6
2.7 3.3 2.7
0
10
20
30
40
50
60
Registered job /official employee
Unregistered job /unofficialemployee
Self-employed Family businesshelper
Other
Men
Women
Ukraine First Ever Job employment by Gender (%)
63
29.9
5.71.1 0.3
66.9
28.7
3 1.2 0.10
10
20
30
40
50
60
70
80
Registered job/ official
employee
Unregisteredjob / unofficial
employee
Self-employed Familybusiness
helper
Other
Men
Women
Transition from School to Work in Ukraine and Serbia
Gender Differences: Status of the JobSerbia
First Significant Job employment by Gender (%)
58.5
25.1
7.1 8.4
0.9
57.9
33.8
2.8 3 2.5
0
10
20
30
40
50
60
70
Registered job /official employee
Unregistered job/ unofficialemployee
Self-employed Family businesshelper
Other
Men
Women
UkraineFirst Significant Job employment by Gender (%)
68.5
25.5
4.70.9 0.3
73.2
23.9
2.2 0.6 0.20
10
20
30
40
50
60
70
80
Registered job/ official
employee
Unregisteredjob / unofficial
employee
Self-employed Familybusiness
helper
Other
Men
Women
Transition from School to Work in Ukraine and Serbia
Gender Differences: Job Characteristics
Private/public sector Overall young Serbians much more likely to be employed in the
private sector than Ukrainians + gender gap: slightly fewer women get the first job in the private sector
No gender differences in Ukraine Part-time/Full-time:
Ukraine: Part-time employment more usual (12% and 9.5%) (compare Serbia 9.4% and 5.3%) + gender gap was higher
Transition from School to Work in Ukraine and Serbia
Gender Differences: Mobility
UkraineOccupational status mobility between first ever and current
employment among job changers (%)
23.5
64.8
11.7
19.1
69.5
11.4
0
10
20
30
40
50
60
70
80
Upward Lateral Downward
Men
Women
Serbia Occupational status mobility between first ever and current employment
among job changers (%)
46.51
30.23
23.2623.58
55.66
20.75
0
10
20
30
40
50
60
Upward Lateral Downward
Men
Women
Migration Patterns and HRD in Albania and Moldova
Background
Return migration seen as a resource for the socioeconomic development of the country through financial capital (savings), human capital (skills and experience acquired abroad) and social capital.
The relationship between migration and development is not straightforward nor happens automatically.
Knowledge on the impact of migration on the education/skills and labour markets is limited: the ETF research approach included a review of the existing literature, fact-finding missions and field surveys in five ETF partner countries: Albania, Egypt, Moldova, Tunisia and Ukraine.
Migration Patterns and HRD in Albania and Moldova
Methods and Data
Target groups: 1/ potential migrants aged 18–40 years 2/ returning migrants who left the country aged 18 or over and have
lived and worked abroad continuously for at least six months
Two questionnaires: one for the potential migrants’ survey and one for the returning migrants’ survey
Moldovan sample: 2,020 people (1,010 potential and 1,010 returning) Albanian a sample of 2,029 people (1,027 and 1,002)
Difficulties in obtaining statistically significant data (few potential migrants aged 18–40 years in rural areas, a high number of refusals for the returning migrants’ survey, few female return migrants etc.)
Migration Patterns and HRD in Albania and Moldova
Gender Differences: Who Migrates and Why?
Massive migration flows: 44,6% of the Moldovan and 44,2% of the Albanians interviewed stated they thought of living and working aboard - Men migrate more than women
Largest category of male migrants: aged between 21 and 30 Largest category of female migrants: aged between 31 and 40
migrants
Intention to leave are approximately equal for employed and unemployed
The most stated reason to migrate was to improve standard of living The second most stated was “have no job” for men in both countries
and Moldovan women while for Albanian women the second most stated reason was to accompany spouse or parent
Migration Patterns and HRD in Albania and Moldova
Gender Differences
Albania - MoldovaPotential Migrants: intends to migrate
46.951.6
40.9 38.2
0
10
20
30
40
50
60
Albania Moldova
Male
Female
Migration Patterns and HRD in Albania and Moldova Gender Differences: Education
Both in Albania and Moldova potential and returning female migrants tend to have a slightly higher level of education than men
The biggest difference for university graduate returning migrants: Albania 10.7% male, 26.4% female, Moldova 9.7% male, 18.2% female
The higher the level of education the higher the mismatch of qualifications with the work in the country of destination
Example: 65% of Albanian male and 59% of Albanian female university
graduated returning migrants had worked as unskilled worker 60% of Moldovan male and 78% of Moldovan female university
graduated returning migrants had worked as unskilled worker
Male potential migrants believed slightly less that education could improve living standards while among the returning once gender gap had diminished
Migration Patterns and HRD in Albania and Moldova
Gender Differences: Job Situation in Return
Albania - MoldovaReturning Migrants:
Migration helped getting better jobs at home
63.9
51.654.2
37.9
010203040506070
Albania Moldova
Male
Female
Migration Patterns and HRD in Albania and Moldova
Gender Differences: Does Migration Pay Off?
Albania - MoldovaReturning Migrants: considering being better off of much
better off
68.1
52.9
67.360.4
0
20
40
60
80
Albania Moldova
Male
Female
Migration Patterns and HRD in Albania and Moldova Gender Differences: Remittances
1 Albania - MoldovaReturning Migrants:
Sent home remittances
77.6 82.1
38.2
79.9
0
20
40
60
80
100
Albania Moldova
Male
Female
Migration Patterns and HRD in Albania and Moldova Gender Differences: Savings
Albania - MoldovaReturning Migrants:
returned with savings
89.4
75.4
85.5
78.6
65
70
75
80
85
90
95
Albania Moldova
Male
Female
Further Questions Do women and men acquire further skills and qualifications to the same
extent in the country of immigration? How these skills are used in return? Differences in the use of financial capital (savings) brought back to home?
Does the level of education (primary, secondary, secondary vocational, university) affect differently female and male school leavers in accessing the labor market in the first place and how? Is there a difference between sexes of what pays off to study and qualify for?
Has the education as an asset the same return for females and males in terms of getting the first significant job (matching skills and qualifications)? Whose skills are the most efficiently and appropriately used?
What are the barriers? According to women? According to employers?
