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The Challenge
Employment and active inclusion are among the most
critical challenges for countries across the Western
Balkans
Framework for the analysis
• Target Groups?
• Inactive
• Unemployed
• SSN Beneficiaries
• Barriers to Work?
• Employability
barriers (skills,
experience, etc.)
• Participation
constraints
Activation for Who?
PROFILING
• Incentives in the tax
and benefit systems
• Benefit formula/
generosity
• Mutual obligations
• Earned income
disregards
(Dis)Incentives in
Benefit Design
• Coordination between
welfare and
employment services
• Specific activation
policies and ALMPs
• Implementation
capacity (financing,
staffing, etc.)
Institutional Readiness
for Activation Policies
Analytical Framework: constraints to employment for
safety nets beneficiaries
Employability barriers
Participation constraints
Tax and Benefit
Disincentives
4
Labor demand
• Education / credentials
• Basic skills (literacy, etc)
• Job specific skills
• Behavioral skills
• Care-taking duties
• Lack of empowerment
• Distance from markets
• Information deficit
• Disincentives to formal work from the interaction of
taxation and benefit rules
Objective of “Profiling” of Social Safety Net beneficiaries: provide
tailored activation strategies for diverse clients
5
Client segments
What are the employability barriers (skills, experience, etc) ?
Are there constraints to labor force participation (caretaking duties, disincentives, mobility)?
Who can be activated among SSN beneficiaries?
Who can be activated in the population?
?
Activation Strategies
Client
segments What are their
employability
barriers? Are there
constraints to LF
participation? Who can be
activated among
SSN beneficiaries? Who can be
activated in the
population?
Basic Profiling –SERBIA
Summary Findings
About half of SSN beneficiaries in Serbia are work-able (potentially “activable”)
Worse labor market outcomes for activable SSN beneficiaries (based on HBS data) Lower employment rate (57% vs 63%) Higher unemployment rate (21% vs 16%)
Due to multiple barriers
Employability barriers (more than half has basic or no education)
Participation constraints (higher caretaking duties: 30% with young children; 15% with disabled)
Who can be “activated”?
Of working age (15-64)
Able bodied
Not in education or training
7
Activables: Individuals who can be presumed
to be able to work
• Who can be activated among the population?
• Who can be activated among the SSN beneficiaries?
• Are these groups coinciding?
More than half of population in Serbia are “work-able”
and more than ¾ participate in the labor force
8 Source: Serbia HBS data 2010.
Note: “Work-able” includes all individuals of working age (15–64) who are neither disabled nor in education or training.
12.6
27.1
11.3
26.4
22.1
9.6
32.1
11.0
8.0
8.6
6.1
4.7
56.8
52.9
50.0
54.8
0 20 40 60 80 100
Whole population
SSN all
FSA+CA beneficiaries
FSA beneficiary
Percent
Age Composition of SSN Beneficiaries Relative to General Population in Serbia, 2010
Child Old
Working age (disabled) Working age (in education)
Working age (work-able)
Unemployed 16.42%
Out of labor force,
20.58%
Salaried employee, 75.52%
Employer, 2.72%
Zero Income 6.46%
Employed, 63.01%
Labor Market Status of Work-Able Population in Serbia, 2010
Self-employed,
15.31%
79.0
83.3
72.8
13.0
8.5
13.5
6
6
9 5.
0 20 40 60 80 100
Employed
Unemployed
Outof labor force
Percent
Safety Net Coverage of the Work-Able Population in Serbia, 2010
Nonbeneficiaries in Q2-Q5 Nonbeneficiaries in Q1 Beneficiaries of other SSN FSA beneficiaries
SSN beneficiaries represent a small fraction of the work-
able population
9 Source: Serbia HBS data 2010.
Note: “Work-able” includes all individuals of working age (15–64) who are neither disabled nor in education or training.
63.0
55.2
56.8
58.1
56.5
16.4
25.9
20.7
21.9
20.7
20.6
18.8
22.4
20.1
22.8
0 20 40 60 80 100
Whole population
Non-beneficiaries, poor
SSN beneficiaries
FSA + CAbeneficiaries
FSA beneficiaries
Percent
Employment and Unemployment rates among the work-able population in Serbia, 2010
Employed Unemployed Out of labor force
However, they are more likely to be unemployed or
inactive or have low-quality jobs
10
34.4
17.2
13
28.6
27.8
30.3
11.2
14.7
12.7
25.7
40.3
44.1
56.1
0 20 40 60 80 100
Wholepopulation
Nonbeneficiaries, poor
SSN beneficiaries
FSA beneficiaries
Percent
Sector of Employment for work-able Population in Serbia, 2010
Public and professions Retail, trade, crafts
Constr., industry, transport Agriculture and manual jobs
Not identified*
Source: Serbia HBS data 2010.
Note: “Work-able” includes all individuals of working age (15–64) who are neither disabled nor in education or training
* Because of the sample size, conclusions cannot be drawn about the sectors other than “Agriculture and manual jobs.” .
5.4
11.0
9.0
12.1
17.3
19.0
28.0
29.2
28.5
33.5
59.3
53.0
56.4
52.5
40.8
0 20 40 60 80 100
Activablepopulation
SSN beneficiaries
Nonbeneficiaries, poor
SA + CA beneficiaries
FSA beneficiaries
Percent
Education Distribution of SSN Beneficiaries in Serbia, 2010
Never attended No education completed
Elementary school Secondary/Vocational
Higher education (college or higher)
Which could be largely explained by lower educational
attainment
11 Source: Serbia HBS data 2010.
Note: “Work-able” includes all individuals of working age (15–64) who are neither disabled nor in education or training.
58.2
49.5
60.0
58.4
55.2
54.7
58.6
53.0
60.4
57.8
54.0
65.7
61.2
14.6
18.1
23.4
8.1
18.5
32.5
15.0
17.7
25.8
8.1
12.7
18.0
15.5
0 20 40 60 80 100
< Prim
Prim
Sec +
< Prim
Prim
Sec +
< Prim
Prim
Sec +
< Prim
Prim
Sec +
All
FSA
ben
efic
iari
esT
arge
ted S
SN
No
nb
enef
icia
rie
s, p
oo
rA
ctiv
able
po
pula
tion
Percent
Employment Status of SSN Beneficiaries in Serbia, by Education Level, 2010
Employed Unemployed
Work-able SSN beneficiaries display greater caretaking
needs than the work-ready population as a whole
12
5.3
20.4
4.9
23.7
9.4
31.5
8.2
29.8
2.6
9.5
2.4
15.4
0 10 20 30 40
General population
SSN all
FSA+CA beneficiaries
FSA beneficiaries
Percent
Share of work-able population living with at least one person in need of care in Serbia, 2010
% hh with disabled % hh with child ≤5 % hh with child ≤2
Source: Serbia HBS data 2010.
Note: “Work-able” includes all individuals of working age (15–64) who are neither disabled nor in education or training.
Putting various traits into a multi-dimensional analysis of
vulnerability using Latent Class Analysis
Objective: to define sub-groups of SSN clients with similar
labor market vulnerability
Non parametric method to identify similar “latent classes” of
the population through a number of ‘indicator’ variables
Uses socio/economic/demographic characteristics that we
believe are relevant for targeting policies
age, gender, family situation, location
education, experience, past/present occupation
employment status, work restrictions, type of vulnerability
-> Statistical method that “searches” for distinct groups using
all these characteristics (minimizes heterogeneity within each
group and maximize differences across groups 13
Latent Class Analysis
SERBIA
Elder experienced unemployed, 35%
Inactive uneducated women, 21%
Elder experienced inactive, 16%
Inexperienced unemployed women,, 12% Chronic
unemployed, 8%
Educated unemployed
youth, 8%
Latent Class Analysis
SERBIA Elder experienced
unemployed
Inactive
uneducated
women
Elder
experienced
inactive
Inexperienced
unemployed
women
Chronic
unemployed
Educated
unemployed
youth
Class size 35% 21% 16% 12% 8% 8%
Ind
ica
tors
Worked before 100% 19% 95% 24% 20% 21%
Willing to retrain 54% 23% 5% 45% 66% 73%
Inactive 22% 100% 100% 16% 0% 19%
Long-term unemployed 66% 0% 0% 63% 99% 6%
Short-term unemployed 12% 0% 0% 21% 0% 75%
Act
ive
cov
ari
ate
s
Uneducated 6% 31% 21% 31% 20% 6%
Elementary education 34% 54% 36% 38% 37% 21%
Secondary+ education 61% 16% 43% 31% 43% 73%
Young (15–29) 4% 41% 8% 26% 39% 92%
Adult (30–54) 54% 52% 45% 59% 61% 4%
Prime age (55–64) 42% 7% 47% 15% 0% 4%
Female 41% 82% 34% 92% 28% 26%
Caretaker 0% 33% 32% 0% 0% 0%
Sta
tist
ics
Married 62% 65% 64% 48% 55% 9%
Discouraged inactive
(% of total)
20% 56% 78% 8% 0% 14%
Willing inactive
(% of total)
2% 44% 22% 8% 0% 5%
Mean age 46 32 47 36 31 23
Source: Calculations from MOP/FSA Beneficiaries Survey 2011.
Matching Beneficiary Profiles and Activation
Services in Serbia, by Client Group
Elder experienced unemployed
Inactive uneducated
women Inexperienced unemployed
women
Experienced inactive elder
Chronic unemployed
Educated unemployed
youth
0
0.5
1
1.5
2
2.5
3
3.5
4
0 0.5 1 1.5 2 2.5 3 3.5
Em
plo
yab
ilit
y o
bst
acle
s
Other barriers to participation
Market Ready
(job info, matching, search
assistance)
Intensified Activation
(TVET, Skills)
Hard-to-serve
(skills, special support)
Special Support
(care for dependents,
transport, social, health)
(Dis)Incentives in Benefit Design—
KOSOVO
Activation for Who?
PROFILING
• Benefit formula/
generosity
• Mutual obligations
• Incentives in the tax
and benefit systems
• Earned income
disregards
(Dis)Incentives in
Benefit Design
Institutional Readiness
for Activation Policies
Main characteristics of the Asistenca
Sociale
Asistenca Sociale‘s (AS) main features - type of
program
• AS combines elements of (i) last-resort social assistance; (ii) non-contributory unemployment benefit and (iii) child allowance
• AS is granted based on multiple criteria: (i) income and asset test; (ii) workability / dependence; (iii) family demographics; (iv) unemployment status
Design, financing and implementation
• Centrally designed: by the Ministry of Labor and Social Welfare
• Centrally financed
• Implementation is at local level: by Centers for Social Work which belong to the municipal administration
Basic administrative and survey data
• Average monthly spending in 2012 – 2.33 million EUR; 28.26 million EUR in 2011
• Number of beneficiary families – 17,570 (Category I) and 13,541 (Category II)
• Spending - 0.7% of GDP (2012)
• Increasing share of able-bodied (Category II) among AS recipient families
18
Asistenca Sociale’s design implies more
disincentives than incentives to be active
19
Disincentives Incentives
Disincentives for work stem from the
Asistenca Sociale benefit formula
The due benefit is calculated as ‘difference’ between the AS threshold applicable to a family of that size and its monthly income
Each additional euro of income will be 100% taken away from the benefit
amount due: Earned income loss of
benefit completely
…Complete loss of benefit only for
formal / legal income
Income from informal employment, household
agriculture, remittances not measured : ‘assessed
through assets’ (either as exclusionary filters or ‘
fully overlooked’/ not considered) bias in both
cases
20
(Dis)incentives due to AS generosity
21
• AS contributes a significant share to consumption of the poor (over 40%), due to low consumption level but also relatively high nominal transfers
Core AS benefit is generous
• AS beneficiary status provides automatic eligibility for electricity subsidy and some other financial benefits
‘Packaging’ of AS with other benefits
Going Forward: Activation agenda much broader than
just focusing on addressing welfare dependency
Social assistance beneficiaries are only a fraction of the inactive, and
activation measures that only target them will not bring significant impact
Room for improvement in the design of LRSA programs – e.g. introduction of gradual income disregard, in-work benefits etc.
Closer institutional cooperation between EAs and SWCs is needed for effective activation of vulnerable.
The capacity and effectiveness of the EA work need to be strengthened for broader activation–e.g. staffing realignment, non-state providers etc.
Improved cost-effectiveness of the ALMPs– e.g. increased competition, advanced (statistical) profiling etc.
22