1. Diana Damean OSI Europe Foundation
The Educational Selectivity Effects of European Social Funds in Romania

2. Objectives
seek to investigate the contribution of the European Social Fund (ESF) to the mitigation of educational inequalities in Romania
focus on the distribution of ESF financial resources allocated to the mitigation of educational inequalities among individual contractors, beneficiaries, and NUTS3 regions
explore the correspondence between investments and the level of need of individual NUTS3 regions.

3. Research Questions
Are most projects managed more likely to be from more needy regions? Have the most needy regions had the highest opportunity to develop capacities for mitigating educational inequalities?
Which regions profited most from ESF resources intended for the mitigation of educational inequalities? Did the distribution of money correspond to the needs of the regions? Were the most disadvantaged regions the most frequent beneficiaries? Have they received the highest share of ESF resources?
Who were the main implementers of ESF projects in the area of the mitigation of educational inequalities in participating countries? What was the involvement of NGOs?

4. Data and Method
we collected the projects selected for funding in the SOP HRD priority axes focused on the mitigation of educational inequalities at the ISCED levels 0-4 in the programming period

5. The general objective of SOP HRD
the development  of  human capital  and increasing competitiveness, by  linking education and lifelong learning with the labour  market  and ensuring increased opportunities for future participation on a modern, flexible and inclusive labour market for 1,650,000 people (Ministry of Labour, Family and Equal Opportunities, 2007).

6. Our focus
Priority axis no. 2. Linking lifelong learning and labour market
2.1. Transition from school to active life
2.2 Preventing and correcting early school leaving
These 2 measures of axis 2 encompass all pupils in primary, secondary and vocational schools.
They are focused on the life-long learning perspective, on its contribution to improve the graduates’ insertion on the labour market, respectively on reducing early school leaving.

7. Data and Method Collected variables included: project identification
money allocation
the type of contractor and its residence
the type of beneficiaries
the location of the beneficiaries
project objective
project activities

8. Demographic variables
The money allocation among individual NUT3 regions is compared with the level of need of the regions. This was determined on the basis of EUROSTAT indicators on:
unemployment rate
average salary
proportion of inhabitants with university education

9. Projects included in the analysisOP
Priority axis
Area of intervention
Type
Subgroup
No. of projects
SOP HRD 2
2.1
Strategic projects, Grant projects
All
130
2.2
Children in risk of early school leaving 88
Total
218

10. Results
Our analysis examined the distribution and characteristics of ESF project contractors and beneficiaries in Romania and explored the capacity building potential of these projects.

11. Demographics Average unemployment per region (%)
Rate of unemployed HED graduates
Rate of unemployed SED graduates per region

12. Projects distribution by region

13. Projects distribution by region
Bucharest-Ilfov, the region with the highest number of funded SOP HRD projects, has the highest average salary, while the West region, with the lowest number of SOP HRD projects, has the lowest average salary.
The neediest region benefits less from ESF funds.

14. Funds distribution by region

15. Funds distribution by region
Bucharest-Ilfov is by far the highest funded region, totalling over 50% of the funds distributed in Romania.
The South-East region is the region that attracted the lowest amount of SOP HRD funds.
Again, most funds were directed to the most developed region, while regions with high unemployment rates and low salaries benefited from least funding.

16. Distribution of beneficiary types per region

17. Axis 2.1 Transition from school to active life addressed mostly ISCED 5-6 students and ISCED 2-4 vocational/technical students.
Axis 2.2 Preventing and correcting early school leaving targeted pupils in risk of early school leaving and their families, but also pupils from disadvantaged families, Roma or disabled pupils.

18. Distribution of contractor types per region

19. Distribution of contractor types per region
The contractors that have successfully implemented SOP HRD 2.1 and 2.2 grants are most often:
public universities (17.43%)
NGOs operating in education (15.60%)
ISCED 2 and 3 vocational/technical schools (14.68%)

20. Distribution of contractor types per region
The most successful universities are clustered in the North-East region and in Bucuresti-Ilfov.
The most successful NGOs are located in the South (South-Muntenia and Bucuresti-Ilfov regions).
The most successful ISCED 2 and 3 vocational/technical schools are located in the North-East and South-West Oltenia regions.

21. Distribution of funds per contractor type

22. Distribution of funds per contractor type
The contractors that attracted the highest amount of funds from Priority Axes 2.1 and 2.2 are:
the NGOs operating in education (22.62%)
public universities (15.71%)
school authorities (14.50%)
Although the number of projects they implemented was lower, NGOs were more likely to implement strategic projects (that extend over a longer period of time and require more funds) than public universities.

23. Conclusions
In Romania by far the highest proportion of ESF funds in the area of the mitigation of educational inequalities has been managed by contractors in the region of the capital city.
The most disadvantaged regions have not administered any projects, they took part in SOP HRD projects only as partners.
The data do not show any systematic effort to secure the managerial potential in the most disadvantaged regions.

24. Conclusions
The region that profited most from ESF resources intended for the mitigation of educational inequalities was the most developed region in the country – the region of the capital city.
On the other hand, not only do the most disadvantaged regions not administer any projects, but they also are among those that receive the lowest support.
Here we seem to witness the Matthew effect: the rich get richer and the poor get poorer (Straková et al., 2013).

25. Conclusions
In Romania there is no focus on capacity building regarding the mitigation of educational inequalities in the most disadvantaged regions and there is no systematic effort to make the most disadvantaged regions the biggest beneficiaries of ESF funds.

26. Thank you!