Cognitive and socio-emotional skills of the Bulgarian workforce

Cognitive and socio-emotional
skills of the Bulgarian workforce
A snapshot of initial findings from the Bulgarian
Longitudinal Inclusive Society Survey (BLISS)
Victoria Levin
“Labor Market Challenges in Bulgaria:
The Role of Skills and Competencies”
April 14, 2015
Structure of the presentation

Background: Why do skills matter in Bulgaria?

Definitions: What do we mean by skills?

Data: How do we measure skills?

Emerging findings

Conclusions
2
Structure of the presentation

Background: Why do skills matter in Bulgaria?

Definitions: What do we mean by skills?

Data: How do we measure skills?

Emerging findings

Conclusions
3
Percent
-10
Bulgaria
Latvia
Romania
Croatia
Lithuania
Estonia
Poland
10
Hungary
Slovakia
Slovenia
Czech
Republic
Bulgaria’s population is aging and shrinking
Population dynamics, 2010-2050
0
-20
-30
-40
4
There was a recent shift in labor demand from
low-skill to higher-skill intensive sectors
Cumulative employment growth, 2008-2013
18.3
17
13.2
8.9
5.3
-4.2
-5.9
-10.9
-20.1
Construction
Manufacturing
Agriculture
Public administration
Trade, transport, hotels
Arts, entertainment
Business services
Real estate
Financial services
-39.8
ICT
30
20
10
0
-10
-20
-30
-40
-50
Source: WB calculations based on NSI data
5
There are concerns about the preparedness of
Bulgaria’s current workforce…
Worker education ranked as the
fourth-most important concern of
Bulgaria’s employers in 2008
This concern was especially
severe in IT sector and some subsectors of manufacturing
6
… and future workforce to address the
demographic challenge
Distribution of students by proficiency level in
math, 2012
Bulgaria has the highest rate of
functional innumeracy in Europe…
Index of School Social Stratification
…and the highest
level of school social
stratification
Source: PISA 2012 data.
7
Objectives of the analysis
•
Examine the skills profile of Bulgaria’s current workforce
•
Assess the relationship between skills and labor market
outcomes

Labor force participation

Employability

Earnings

Crisis impacts and coping strategies
8
Structure of the presentation

Background: Why do skills matter in Bulgaria?

Definitions: What do we mean by skills?

Data: How do we measure skills?

Emerging findings

Conclusions
9
The three dimensions of skills
Cognitive
Socioemotional
Technical
Involving the use of
logical, intuitive and
creative thinking
“Soft” skills, social skills,
life-skills, personality
traits
Involving manual
dexterity and / or the use
of methods, materials,
tools and instruments
Problem solving ability
(as opposed to having
knowledge to solve a
specific problem)
Openness to experience,
conscientiousness,
extraversion,
agreeability, emotional
stability
Technical skills
developed through
vocational schooling or
acquired on the job
Verbal ability, numeracy,
problem solving, memory
(working and long-term)
and mental speed
Self-regulation,
perseverance, decision
making, interpersonal
skills
Skills related to a
specific occupation (e.g.
engineer, economist, IT
specialist, etc)
10
Skill formation benefits from earlier investments
and is cumulative
11
Socio-emotional skills are important to employers
Asia-Pacific
Bulgaria
Global
Americas
EMEA
0%
5%
10%
15%
20%
25%
30%
% of employers citing workplace competencies (soft skills) as
reason for difficulty in filling a vacancy
Source: Manpower 2012 data.
12
Structure of the presentation

Background: Why do skills matter in Bulgaria?

Definitions: What do we mean by skills?

Data: How do we measure skills?

Emerging findings

Conclusions
13
The Bulgarian Longitudinal Inclusive Society
Survey (BLISS)
 Implemented by the World Bank in partnership with
Open Society Institute – Sofia
 Builds on the data collected in three rounds of
Bulgaria’s Crisis Monitoring Survey (CMS) in 20102011

Sample: nationally-representative with 2,400 + 300
households in segregated (mostly Roma)
neighborhoods

Questionnaire: Changes focus from crisis impacts to
more structural issues on activation & skills
 Innovative module on cognitive and socio-emotional
skills for a nationally-representative sample of the
adult (18-65) population
Cognitive skills assessment in BLISS
•
Memory: short-term recall of increasingly longer number sequences, starting with two
numbers and ending with 9 numbers (12 items)
•
Semantics: familiarity with synonyms, antonyms, idioms, complex sentence structure (7
multiple-choice items)
•
Reading comprehension: ability to respond to questions about a short non-technical text
(5 multiple-choice items)
•
Comprehension of tables and charts: ability to understand written instructions and ability
to read a timetable (4 multiple-choice items)
•
Numeracy: ability to perform simple calculations (6 multiple-choice items)
What is the promotional price of
one bottle in the package?
Before the sale, how much did
three packages cost?
In cents, what is the reduction in
package price during the sale?
Socio-emotional skills assessment in BLISS (1/2)

Work and learning style factor: captures the individual’s attitude towards work and his
willingness to learn new things. It’s a combination of the following skills:

Conscientiousness: tendency to be organized, responsible, and hardworking (i.e.
When doing a task, are you very careful?).

Openness to experience: tendency to be open to new aesthetic, cultural, or
intellectual experiences (i.e. Are you very interested in learning new things?).

Grit: perseverance and passion for long-term goals (i.e. Do you finish whatever you
begin?).

Achievement-striving: facet of conscientiousness: need for personal achievement
and sense of direction (i.e. Do you do more than what's expected of you?).

Decision making: process of generating solutions and considering future
consequences (i.e. Do you think about how the things you do will affect you in the
future?).
Socio-emotional skills assessment in BLISS (2/2)

Relational factor: captures how the individual socializes. It’s a combination of the following
skills:


Extraversion: orientation of one’s interests and energies toward the outer world of
people and things rather than the inner world of subjective experience;
characterized by positive affect and sociability. (i.e. Are you talkative?).

Agreeableness: tendency to act in a cooperative, unselfish manner (i.e. Are you
generous to other people with your time or money?).

A facet of openness to experience: Do you enjoy beautiful things, like nature, art,
and music?

A facet of decision making: Do you ask for help when you don't understand
something?
Growth vs fixed mindset: belief that one’s personality is malleable or fixed (i.e. As
much as I hate to admit it, you can’t teach an old dog new tricks. You can’t really
change their deepest attributes).
Structure of the presentation

Background: Why do skills matter in Bulgaria?

Definitions: What do we mean by skills?

Data: How do we measure skills?

Emerging findings

Conclusions
18
Skills profile: Significant but not perfect
correlation with educational attainment
Average skills in Bulgaria's WAP, by Education
***
1
0.5
***
***
**
***
***
***
***
**
0
-0.5
Primary or below
***
***
Secondary (base)
Bachelor
***
***
***
***
***
***
***
MA/PhD
-1
Fixed mindset factor
Working/learning style factor
Numeracy
Reading of other
Reading of texts
Semantics
Memory
Cognitive skills
Relational factor
***
-1.5
Overall cognitive
Standardized score
1.5
Socio-emotional skills
Notes: Significant differences from base category: * 10%, ** 5%, ***1%. Students aged less than 25 years old have been removed from the sample
Skills profile: Almost no gender differences in
skills
Average skills in Bulgaria's WAP, by Gender
Standardized score
0.15
***
0.1
Men (base)
0.05
Women
*
0
-0.05
-0.1
Cognitive skills
Fixed mindset factor
Working/learning style factor
Relational factor
Overall cognitive
Numeracy
Reading of other
Reading of texts
Semantics
Memory
-0.15
Socio-emotional skills
Notes: Significant differences from base category: * 10%, ** 5%, ***1%. Students aged less than 25 years old have been removed from the sample
Skills profile: Older adults have lower cognitive
but higher socio-emotional skills related to
socializing with others
**
*
18-29
30-49 (base)
50-65
Cognitive skills
Fixed mindset factor
Working/learning style factor
Relational factor
***
Overall cognitive
**
Numeracy
Reading of other
*
***
Reading of texts
**
Semantics
0.25
0.2
0.15
0.1
0.05
0
-0.05
-0.1
-0.15
-0.2
Memory
Standardized score
Average skills in Bulgaria's WAP, by Age
Socio-emotional skills
Notes: Significant differences from base category, controlling for education: * 10%, ** 5%, ***1%.
Students aged less than 25 years old have been removed from the sample
Skills profile: Almost no significant differences
in skills between urban and rural residents
Average skills in Bulgaria's WAP, by Settlement Type
0.25
Standardized score
0.2
0.15
Metropolitan (base)
0.1
Urban
0.05
Rural
0
-0.05
-0.1
**
Cognitive skills
Fixed mindset factor
Working/learning style factor
Relational factor
Overall cognitive
Numeracy
Reading of other
Reading of texts
Semantics
Memory
-0.15
Socio-emotional skills
Notes: Significant differences from base category, controlling for education: * 10%, ** 5%, ***1%.
Students aged less than 25 years old have been removed from the sample
Skills and LM outcomes: The employed have
higher cognitive and better working/learning
socio-emotional skills
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
-0.7
Employed (base)
**
***
***
**
***
***
***
***
***
Unemployed
***
*
Inactive
***
***
***
Cognitive skills
Fixed mindset factor
Working/learning style factor
Relational factor
Overall cognitive
Numeracy
Reading of other
Reading of texts
Semantics
***
Memory
Standardized score
Average skills in Bulgaria's WAP, by Labor Market Status
Socio-emotional skills
Notes: Significant differences from base category: * 10%, ** 5%, ***1%. Students aged less than 25 years old have been removed from the sample
Skills and LM outcomes: Labor force
participation
•
Probability of being active
Cognitive skills
•
Relational factor
Work/learning style factor
Growth mindset dummy
At least secondary education
*
Aged 30-49
•
***
**
***
***
Aged 50-65
**
Married or cohabiting
•
•
Women
Roma
Men
•
Other ethnicity
Urban
•
South
***
At least one child 0-5
*
**
At least one child 6-14
At least one member 15-65 working
At least one member 15-65 not working
•
***
***
**
At least one adult 65+
-0.3
-0.2
-0.1
0
0.1
0.2
Cognitive and socio-emotional
skills appear not to matter for
LFP
Education is positively
associated with activity, esp. for
women
Middle-aged women are more
likely to be active compared to
youth
LFP is lower for older adults (50+)
Married women are less likely to
be active
Roma individuals are as likely as
non-Roma to be in the labor force
Small children are associated
with lower LFP of women and
higher LFP of men
Presence of other working adults
is positively correlated with
women’s LFP
0.3
Notes: Significant differences from base category: * 10%, ** 5%, ***1%. Students aged less than 25 years old have been removed from the sample
Skills and LM outcomes: Employability
Probability of being
Probability
of being active
employed
Cognitive skills
*
Relational factor
**
Work/learning style factor
•
**
Growth mindset dummy
*
***
***
*
* **
At least secondary education
Aged 30-49
•
***
***
Aged 50-65
**
Married or cohabiting
Roma
•
*
**
Other ethnicity
Women
*
Men
Urban
South
**
***
At least one child 0-5
*
**
At least one child 6-14
At least one member 15-65 working
**
***
At least one adult 65+
-0.3-0.3
-0.2
-0.2
-0.1
-0.1
00
•
•
***
**
At least one member 15-65 not working
•
0.10.1
•
•
For men, skills seem to matter more
than diplomas for finding a job, while
for women educational attainment
plays a more prominent role
Men with higher cognitive skills are
more likely to be employed
The working/learning style factor
(incl. conscientiousness) is positively
correlated with the probability of being
employed for men
Men with a higher relational factor
appear less likely to be employed
Women with a growth mindset are
less likely to be employed
Women with secondary or higher
education and middle-aged women
are more likely to be employed
Roma are less likely to be employed
Men in the South are more likely to be
employed
0.2 0.2 0.3 0.3
Notes: Significant differences from base category: * 10%, ** 5%, ***1%. Students aged less than 25 years old have been removed from the sample
Structure of the presentation

Background: Why do skills matter in Bulgaria?

Definitions: What do we mean by skills?

Data: How do we measure skills?

Emerging findings

Conclusions
26
Some potential policy implications
•
•
•
•
•
•
Strengthen cognitive and socio-emotional skills formation
in early childhood and general education
Expand access to preschool and early years programs
Adapt school curriculum and teaching methods for
disadvantaged communities
Delay vocationalization/early tracking
Incorporate promising international examples of socioemotional skills interventions in vocational/dual system
training for youth (Youth Guarantee)
Increase participation in Active Labor Market Programs
*http://documents.worldbank.org/curated/en/2014/11/20426330/developing-social-emotional-skills-labor-market-practice-model
27
Although participation in ALMPs is low, there is a
latent demand for this service
•
In 2013, only 7% of Bulgarians aged 18-65
participated in any training to improve their skills in
100%
the previous 12 months
•
Reasons for non-participation varied significantly
with the LM status:
80%

Employed cited time constraints
60%

Unemployed lacked awareness of any suitable
training
40%

Inactive were not interested in training programs
20%
•
There appears to be potential untapped demand
for training


One third of Bulgarians are likely or rather likely to
use PES vouchers to obtain training to improve their
employability
More than half (57.7%) of the unemployed would
be willing to use this service
Reason to use the PES voucher
0%
18-29
30-49
50-65
Total
Other
Get skills in another specialization to get additional job
Personal interest
Get skills in another specialization to get a new job
Increase skills in own specialization to get a new job
Increase skills in own specialization to advance current job
Source: World Bank staff calculations and assessment
based on BLISS (2013)
28
Thank you
For questions and comments please contact
Ulrich Hoerning
uhoerning@worldbank.org, Tel: +1 202 473 4972
Victoria Levin
vlevin@worldbank.org, Tel: +1 202 473 5392
Plamen Danchev
pdanchev@worldbank.org, Tel: +359 2 9697253
Christian Bodewig
cbodewig@worldbank.org, Tel: +32 2 552 0023