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2018-2020
ETF Assessment of BelarusMinsk, 3 December 2019
Pirita Vuorinen, ETF
FOCUS ON POLICY RESPONSES AND LEARNING
• That obstruct human capital development• That can be addressed through policy• That can be addressed through learning
Image source: https://mindfulambition.net/big-rocks-first/
Torino Process in Belarus
Image source: https://mindfulambition.net/big-rocks-first/
Torino Process 2018-20 5
Demography: progressive increase in pension age since 2017 is working but not fast enough
Source: Belstat, 2019
-
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
1 2 3 4 5 6 7 8
Main age groups in the total population (at the beginning of the year)
Under working age Working age Over working age
Torino Process 2018-20 6
-
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
2015 2016 2017 2018
Migration
Emigration Immigration
Migration is negatively impacting demographics: qualified migration, negative net migration rate is growing
Source: Belstat
Professional training of workers in absolute values
Source: Adult and Continuing Education in Belarus, German Institute for Adult Education (2017)
Only formal adult education financed by the government or region, for public employees, is monitored.
Professional training of workers in percentage
to the total number of employed people
Torino Process 2018-20 8
Respondent's education level From the number of respondents with an appropriate level of
education
From the number of those who received
additional education
Incomplete secondary education 2,5% 1,0%
Incomplete secondary education 3,3% 7,9%
General secondary education 9,8% 14,1%Vocational education 10,4% 7,7%
Secondary special education 11,8% 16,1%
Incomplete higher education 16,4% 6,4%Higher education 19,3% 44,1%Master, postgraduate, doctoral 28,2% 2,7%
Adult education is significantly
more used by higher education
graduates (44.1%) than VET
(7.7%) or secondary
specialised education (16.1%).
Source: Novak, analysis funded by the European Commission, 2019
State program ‘Education and
youth policies’ 2016–2020 aim
is that in 2020 15% of the
population benefits from adult
education (up 5% from 2017,
advanced training and
retraining).
Adult education is significantly more used by higher education graduates
Torino Process 2018-20 9
12.8%
9.0%10.5%
11.5%12.8%
13.7%
29.7%
0%
5%
10%
15%
20%
25%
30%
16-24 25-29 30-34 35-39 40-44 45-49 50 and over
Share of registered unemployed, % of total
Registered unemployment increases with age
Source: Belstat
Adult education: non-formal learning services provided by CSOs are insufficient (cover 1.2% of population over 5 years)
Source: Adult and Continuing Education in Belarus, German Institute for Adult Education (2017)
The government does not provide financial support for entrepreneurship training for silver entrepreneurs (aged 50+) for their active involvement in the economy.
Opportunities
• Attention could move from focus on young people’s education - to lifelong learning and adult education.
• The need in trainers for adult education will increase.
• Strengthening cooperation among providers (including non-formal).
• Guidance for adult learners through the provision of information.
• Validation of informal and non-formal learning for prospective adult education students who wish to further their studies.
• Reintegration through active labour market measures including business initiative and silver entrepreneurship training.
3.5 3.44.1
5.26.0
6.5
2013 2014 2015 2016 2017 2018
ICT gross value added of the economy, %
Agriculture sector value added (2007-2016)
Gross Value Added (GVA) by small and micro enterprises representsabout 28 % of total GVA in Belarus.
Source: World Bank, 2019 Source: EY, 2017
MSME value added sectors
Job growth in MSME value sectors
Source: Belstat, 2019
-
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
2012 2013 2014 2015 2016 2017 2018
Micro, small and medium sized businesses, private capital
micro small medium
Private sector employment is growing primarily in micro enterprises, low value-added services industry
Source: Belstat, 2019
Source: Belstat, 2019
Opportunities (ETF, SBA 2019)
• There’s a need to develop a systematic approach to optimising limited resources and connecting them to a broader innovation drive through SME training and coaching.
• Establishing formal career guidance would foster in a more systematic way students with entrepreneurial aspirations.
• The Ministry of Economy could take the lead in strengthen data on enterprise skills for evidence-based planning, monitoring and evaluation (e.g. under the new Agency for SME Support). This could also serve as a means to establish a co-ordination mechanism for SME support organisations.
Labour market shortages
0
10
20
30
40
50
60
70
80
90
100
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Supply and demand for labour (in thousands)
Unemployed job seekers Vacancies
Source: Belstat and Employment Services, 2019
COMPARISON OF LABOR MARKET BY PROFESSION
Rating Employee Positions QuantityAverage salary
1Nurse 2 621 478,52
2 Medical specialist 2 581 633,74
3 Engineer 1 716 732,55
4 Specialist 969 651,01
5 Veterinarian 748 574,10
6 Accountant 557 501,47
7 Director 437 899,20
8Medical Laboratory Assistant 411 479,78
9 Forester 386 549,24
10 Master 361 666,19
11 Paramedic 327 553,27
12 Chief accountant 320 684,98
13 Pre-school teachers 293 428,6514 Veterinary nurses 285 477,05
15 Chief Engineer 276 778,54
The most required positions for employees
Source: Vankevich, 2019
Labour market shortages
Early career, students Art, entertainment, mass mediaHR management, trainingAccounting, management accounting, enterprise finances
Administrative staffScience, educationManufacturingMarketing, advertising, PR Transport, logisticsProcurementSalesMedicine, pharmaceuticalsSports clubs, fitness, beauty salonsIT technologies, Internet, telecomConstruction, real estateBanks, investments, leasingHousehold staffAutomotive businessTourism, hotels, restaurantsWorkforce
Competition in the field of professional areas in Q3 2019
ratio of the number of resumes and vacancies
A strong link between income and transition path from school to work
Source: Novak, analysis funded by the European Commission, 2019
short transition mid transition long transition
more than 1200 rubles
801-1200 rubles
401-800 rubles
less than 400 rubles
Salary (in the second half of 2018), slightly higher only among respondents with higher education
Average wages
by level of
education
Source: Novak, analysis funded by the European Commission, 2019
general secondary education
special secondary education
higher education
full higher education
vocational education
0% 5% 10% 15% 20% 25% 30% 35% 40%
Yes, the work is related to training received in aneducational institution
No, I’m not working in my specialty
I work in a field that is close to my education
To work in the specialty, received additional education
Other
Relevance of obtained skills or education to those required by the job
Source: https://jobs.tut.by/article/13579
Skills mismatches result from both over-qualification and under-qualification
78,400
60,960
16002 134596,698 4,660
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
2017 2025
Education system growth forecast (based on existing trends)
graduates
stem graduates
stem graduates in most sought after specialisation
Emerging labour shortages and skills gapsFrom the supply side perspective (education and training) digital economy entails making better use of digital technology for teaching and learning. However,
• 51% of teachers lack the necessary quantity of computers for training and internet access
• 44% of teachers say that digital technologies are used only occasionally by students in class
• two-thirds of classes have access to reliable and appropriate computer hardware and software
Many employers are concerned key competences i.e. workers lack ‘soft skills’.
Source: EY, 2017
Opportunities
• Stronger partnerships needed between private sector and training.
• Improve access to digital educational resources in VET schools.
• Improve VET teachers’ skills in applying digital educational resources.
• The HTP is an important training and coaching hub for the IT sector. However, it is restricted to ICT companies only. Possible replication of such a model for other value added sectors to benefit from a similar open innovation ecosystem.
• Big data tools offers opportunities for real-time labour market analysis of the demand side. Big data could be used to strengthen skills anticipation.
Efficiency: Image of the education system is positive
Negative, 2.3%
Rather negative,
7.6%
Neutral, 28.7%
Quite positive, 38.5%
Fully positive, 22.9%
Distribution of answers to the
question: “How do you assess the
work of the educational system of
the Republic of Belarus as a
whole?”
Source: Novak, analysis funded by the European Commission, 2019
Efficiency: The level of education is related to the level of employment.
Source: Novak, analysis funded by the European Commission, 2019
80.50%
77.50%
77.85%
15.67%
0.30%
высшее образование
среднее специальное
профессионально-техническоe
общее среднее
базовое
Employment rate by level of education
basic education
general secondary education
vocational education
secondary specialized education
higher education
Efficiency: VET and specialised secondary education (SSE)
Source: Belstat, 2019
0
5
10
15
20
25
30
35
40
45
Number of students in VET 2010-2018
2010 2018
0
10
20
30
40
50
60
Number of students in SSE 2010-2018
2010 2018
0
100
200
300
400
500
600
700
800
900
2010 2011 2012 2013 2014 2015 2016 2017 2018
Number of students per VET and SSE institution 2010-2018
VET, average number of students per institution
Specialised secondary education, average number ofstudents per institution
Efficiency: resource centers for economic development
To improve the quality of professional education, a network of 47 resource centers has been created, in which the implementation of educational programs in a network form of interaction is possible
Source: https://edu.gov.by/sistema-obrazovaniya/glavnoe-upravlenie-professionalnogo-obrazovaniya/prof-obr/
Vitebsk region
Mogilev region
Gomel regionBrest region
Grodnyregion
Minsk region
Minsk
DOMESTIC SERVICE
TIMBER HARVESTING AND PROCESSING
INFORMATION SYSTEMS AND TECHNOLOGIES
LIGHT INDUSTRY
MACHINERY
CATERING
FOOD PRODUCTION
RADIO- MICRO- AND NANO ELECTRONIC TECHNOLOGY
AGRICULTURECONSTRUCTION AND MUNICIPAL SERVICES
TRANSPORTENERGETICS
Quality: teachers competencies are valued
3.69
3.76
3.97
3.79
3.79
3.54
3.28
3.54
3.90
3.91
4.13
3.92
3.98
3.83
3.48
3.57
Content of training programmes
Organization of the training process
Qualifications and competence of teachers
Management of educational institutions
Level of received knowledge, qualifications
Applicability of acquired knowledge in
practice
Employment potential
Material base (condition of classrooms,
equipment, etc.)
VillageTown
Evaluate the following
components of the
education system as a
whole” (mean
according to locality, to
5-scale)
Source: Novak, analysis funded by the European Commission, 2019
Quality: findings of the ETF study on VET teachers• Over 30% say training did not cover all or any of the subjects that they are
teaching.
• 37% of specialist VET teachers have no working experience in the industry for which they are preparing recruits.
• Principals have some influence over individual appointments and the curriculum offer but little influence over salaries and the school budget.
• Social partners participate in 82% of school boards.
• 86% of principals say their effectiveness is limited by shortage of resources.
• 50% see their effectiveness constrained by: the lack of ‘a career-based teachers’ wage system’; lack of participation and support by parents or guardians and a high workload and level of responsibility for their work.
• Overall, approx. 80% of VET teachers believe CPD offer is relevant.
Opportunities
• Efficiency: ‒ School network restructuring towards a more flexible system able to effectively respond to
the needs of learners and labour market.
• Quality: ‒ Enhance interaction between providers and companies to improve the learning process. ‒ Application of modular provision would facilitate better integration of theory with practice
(e.g. training in company). This could also bring together the most advanced teachers and trainers from VET providers, companies and the private sector to work on reviewing the profiles.
• Training of VET provider managers:‒ Modernise competence requirements of VET managers (e.g. autonomy).
• Teacher training for the implementation of competence-based VET:‒ Improve and streamline standards of VET teachers/trainers taking into account combination
of roles and functions (e.g. counselling mentoring in addition to teaching)‒ Design and test career development scheme for VET teachers/trainers with a special
attention to the needs of trainers/mentors in work-based and adult learning
Источник: Boeing
Youth Education
42.08%
45.92%
46.48%
46.63%
53.05%
61.99%
67.70%
22.62%
33.67%
28.13%
32.12%
33.80%
24.56%
18.76%
35.29%
20.41%
25.39%
21.24%
13.15%
13.45%
13.54%
Higher Specialized secondaryBasic, secondary, general vocational
10.6%
15.2%
20.6%
10.5%
15.3%
19.1%
8.7%
0%
5%
10%
15%
20%
25%
Brest Vitebsk Gomel Grodny MinskCity
Minsk Mogilev
Share of regional industrial output
Regional human capital
31 25 33 18 279 46 23677 625 2,234
442
18,937
3,690
803
0
5000
10000
15000
20000
Brest Vitebsk Gomel Grodny MinskCity
Minsk Mogilev
Concentration of R&D Organisations and personnel
No of research organisations No of persons working on research
Source: Belstat, 2019 Source: Novak, analysis funded by the European Commission, 2019
The most educated young people live in the capital, Minsk.
The level of education of young people is significantly higher among urban residents
49.00%
67.70%
29.06%
18.76%
21.94%
13.54%Young people living in the capital
Young people living in rural areas
Higher educationSpecialized secondary educationBasic, secondary, general vocational education
Source: Novak, analysis funded by the European Commission, 2019
37.83%
57.21%
30.26%
25.60%
31.91%
17.19%Urban population
Rural population
Internal migration- urbanisation
-1888
-1833
-1828
-513
10254
6754
-1583
-4000 -2000 0 2000 4000 6000 8000 10000 12000
Brest
Vitebsk
Gomel
Grodno
Minsk Сity
Minsk
Mogilev
Net migration
Source: Belstat, 2019
Regional Competitiveness Index
Source: IPM Research Center, analysis funded by the European Commission, 2018.
Fig. 3. connection between RCI and GDP per capita
GDP per capita, thou.$
↘
Notation keys: BR – Brest region, VT-Vitebsk region,HM-Gomel region,HR-Grodny region,MC-Minsk,MS-Minsk region,MH-Mogilev region,BY-Belarus in general,’17 and ‘18 RCI-2017 (GDP-2016) and RCI-2018 (GDP-2017) accordingly.Sourses: own calculations based on data from the IPM Belstat and National Bank
Regional Competitiveness Index: Subindex “Innovation and Business Development Status”
Source: IPM Research Center, analysis funded by the European Commission, 2018.
Mogilev region
Minsk region
Minsk
Grodny region
Gomel region
Vitebsk region
Brest region
Belarus
RCI-2018 RCI-2017 changes
Research organisations are concentrated in Minsk and too small to leverage on proximity at regional level
31 25 33 18 279 46 23677 625
2,234
442
18,937
3,690
803
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
Brest Vitebsk Gomel Grodny Minsk City Minsk Mogilev
Concentration of R&D Organisations and personnel
No of research organisations No of persons working on research
10%8% 9% 8%
40%
19%
8%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Brest Vitebsk Gomel Grodny MinskCity
Minsk Mogilev
Share of micro and small enterprises
15%12%
15%11%
21%
15%
11%10%10% 9%
11%
29%
19%
11%
0%
5%
10%
15%
20%
25%
30%
Brest Vitebsk Gomel Grodno Minsk Сity
Minsk Mogilev
Number of SMEs in regions, per 1000 people (%)
Share of the total population SMEs per 1,000 population, %
Private sector growth is concentrated in Minsk
Source: Belstat, 2019
In Vitebsk, the average number
of students shrank by 57%
9.3%7.4%
9.9% 10.5%
27.7%
14.4%
6.8%
0%
5%
10%
15%
20%
25%
30%
Brest Vitebsk Gomel Grodny MinskCity
Minsk Mogilev
GRP of GDP
19,141 18,419 20,434 21,358
31,524.6
25,541.8
18,463.9
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Brest Vitebsk Gomel Grodny Minsk City Minsk Mogilev
Labour productivity (in thousands) (RUB)
256.4 75.9 203.6 149.8
6,640.0
1,036.6
174.9 0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
Brest Vitebsk Gomel Grodny Minsk City Minsk Mogilev
FDI ($US in thousands)
828.4 814.4 853.3 831.9
1329.6
956.8802
0
500
1000
1500
Brest Vitebsk Gomel Grodny MinskCity
Minsk Mogilev
Nominal accrued average monthly wages of employees, rubles, 2011-2015 - thousand
roubles.
Possible spillovers of private sector growth is also concentrated
Source: Belstat, 2019
Regional Competitiveness Index: factors that increase efficiency, the education component
Source: IPM Research Center, analysis funded by the European Commission, 2018.
Mogilev region
Minsk region
Minsk
Grodny region
Gomel region
Vitebsk region
Brest region
Belarus
changesRCI-2017RCI-2018
Opportunities
• Make use of resource centres to develop competences of regional workforce and MSME training.
• Focus skills development to support growth centres and competitive niches (e.g. clusters, centres of excellence).
Thank you !