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Lauren Graham, Leila Patel,
Gina Chowa, Rain Masa de Vera,
Zoheb Khan, Leilanie Williams
and Senzelwe Mthembu
Youth assets for employability:
An evaluation of youth
employability interventions
BASELINE REPORT
SIYAKHA
YOUTH
ASSETS
Copyright © 2016: The authors, the Centre for Social Development in Africa, University of
Johannesburg, and the School of Social Work, University of North Carolina Chapel Hill.
Published by the Centre for Social Development in Africa, University of Johannesburg
Johannesburg, South Africa.
Short extracts from this publication may be produced unaltered without authorisation on
condition that the source is indicated. For rights of reproduction or translation, application
should be made either to the Centre for Social Development in Africa, University of
Johannesburg or the School of Social Work, University of North Carolina Chapel Hill.
The Centre for Social Development in Africa (CSDA), at the University of Johannesburg,
was established in 2003 and is dedicated to basic, applied and strategic research in
social development and developmental welfare. The CSDA aims to positively inuence
development issues in the Southern African region through contributing to debates
on social policy, improvements in service delivery, and the expansion of knowledge
through cutting-edge research.
CSDA, University of Johannesburg, P. O. Box 524, Auckland Park, 2006
Csdainfo@uj.ac.za | www.uj.ac.za/csda
Editing: Ellen Joubert
Layout: Ebrahim Karim, University of Johannesburg Graphics Department
Printing: 4ColourPrint
Photographs: • Jan Potgieter • Media Club South Africa
ISBN: 978-0-86970-797-5 (Print)
ISBN: 978-0-86970-797-5 (Digital)
Contents
Acknowledgements .......................................................................................................... 5
Acronyms ............................................................................................................................... 7
1. Introduction ................................................................................................................8
1.1. Finding solutions to the challenge ........................................................ 8
1.2. Study description ..........................................................................................9
1.3. Conclusion .......................................................................................................10
2. Youth pathways to the labour market ........................................................... 11
2.1. The global youth unemployment landscape ....................................11
2.2. The South African youth unemployment landscape....................11
2.3. Responses to youth unemployment –
a review of interventions ...........................................................................17
2.4. A youth development approach to understanding
pathways to the labour market .............................................................23
2.5. Conceptualising pathways to the labour market for youth –
a theory of change ..................................................................................... 24
2.6. Conclusion ...................................................................................................... 26
3. Methodology ............................................................................................................27
3.1. Introduction ....................................................................................................27
3.2. Implementing partners .............................................................................27
3.3. Research Design .......................................................................................... 28
3.4. Sample ............................................................................................................. 30
3.5. Data collection ...............................................................................................31
3.6. Questionnaire development and pilot testing ...............................32
3.7. Reliability and validity ................................................................................32
3.8. Analysis ............................................................................................................ 33
3.9. Ethics ................................................................................................................ 33
4. Participant background and characteristics ............................................ 34
4.1. Demographic overview ............................................................................ 34
4.2. Living arrangements and care responsibilities ............................. 34
4.3. Household prole.........................................................................................35
4.4. Future orientation and self-ecacy .................................................. 38
4.5. Health and risk behaviour ....................................................................... 39
4.6. Conclusion ...................................................................................................... 40
5. Education ....................................................................................................................41
5.1. Secondary education ..................................................................................41
5.2. Post-secondary education .......................................................................41
5.3. Conclusion ......................................................................................................42
6. Experiences of employment, unemployment,
and work-seeking.................................................................................................. 43
6.1. Employment and work experience .................................................... 43
6.2. Unemployment and work-seeking ..................................................... 46
6.3. Resources for work-seeking ..................................................................50
6.4. Conclusion .......................................................................................................52
7. Financial capability ...............................................................................................53
7.1. Financial behaviours ...................................................................................53
7.2. Financial literacy.......................................................................................... 56
7.3. Conclusion ...................................................................................................... 56
8. Discussion, implications and conclusion ...................................................................................................................................57
8.1 Discussion of key ndings ..................................................................................................................................................... 57
8.2 Implications of the ndings ..................................................................................................................................................59
References ..........................................................................................................................................................................................................61
APPENDIX 1: Methodological details ....................................................................................................................................................68
Sampling details ...................................................................................................................................................................................68
Cluster level data ..................................................................................................................................................................................68
Recruitment and training of eldworkers ................................................................................................................................69
Data management ...............................................................................................................................................................................70
List of Figures
Figure 1: Employment status by education status for youth 15-34 years ............................................................................ 13
Figure 2: Unemployment rate by province and gender, youth 15 – 34 years. ....................................................................16
Figure 3: Conceptualising pathways to youth employability and employment ..............................................................25
Figure 4: Diagram of longitudinal design ...........................................................................................................................................28
Figure 5: Child Support Grant beneciaries (n=1933) ..................................................................................................................36
Figure 6: Food insecurity (n=1874) ........................................................................................................................................................ 37
Figure 7: Experience of scarcity in ve essential items in the last year (n=1921) ............................................................38
Figure 8: Summary of Positive Responses to Sexual Behaviour Questions ......................................................................39
Figure 9: Highest level of primary or secondary education (n=1954) ...................................................................................41
Figure 10: Highest level of post- secondary education (n=694) ............................................................................................42
Figure 11: Occupation type of most important job (n=1002) ................................................................................................... 44
Figure 12: Occupation type of most important job (n=758) .....................................................................................................45
Figure 13: Source of information about most important job (n=1045) ................................................................................45
Figure 14: Sources of information about recent job applications (multiple response) ................................................47
Figure 15: Types of job search costs in the past 3 months (multiple response) ............................................................ 48
Figure 16: Total median and mean monthly work-seeking costs ........................................................................................... 48
Figure 17: Social capital sources (n=1975) ......................................................................................................................................... 49
Figure 18: Person with most signicant impact (n=1802) ......................................................................................................... 49
Figure 19: Uses of money left over after purchasing necessary items ................................................................................. 53
Figure 20: Reasons for running short of money for necessary items ..................................................................................54
Figure 21: Agreement with statement “I try to save money for the future” (by percent) ..........................................55
Figure 22: Goals for which youth are currently saving and would like to save for in the future (by percent,
multiple response) .........................................................................................................................................................................................55
List of Tables
Table 1: Site level characteristics of the sample by treatment/control .................................................................................29
Table 2: Individual level characteristics of the sample by treatment/control .................................................................. 30
Table 3: Sample by implementing partner ..........................................................................................................................................31
Table 4: Living arrangements – cohabitation with parents .......................................................................................................34
Table 5: Individual and household asset ownership ......................................................................................................................36
Table 6: Employability attribute mean scores ................................................................................................................................... 51
Table 7: Fieldwork teams per province ................................................................................................................................................69
4
ACKNOWLEDGEMENTS
A project of this nature can only be successful with the involvement of a range of role players, from those
who rst planted the idea of the project, to those at the coalface of supporting young people to reach their
dreams of that rst job.
This study was born out of a discussion at a Round Table initiated by the Brookings Institute’s Africa Growth
Initiative and hosted by the Development Policy Research Unit at the University of Cape Town and the National
Youth Development Agency (NYDA). At the time, the conversation about youth unemployment was very
much focused on problems. This Round Table began to shift that outlook to one of solutions and brought
together role players who were later able to conceptualise this study. Thanks must go to these organisations
for laying the soil in which the seeds of this study were ultimately planted.
Through those early contacts and discussions Prof Leila Patel (the principal investigator) came to conceptualise
a study on the role of youth employability programmes in addressing youth unemployment. To date, this is
the rst comprehensive study assessing the eect that this sector has on addressing youth unemployment.
Her ideas were rened and consolidated through interactions with Prof Gina Chowa and Prof Lauren Graham
(co-principal investigators). Thanks to Prof Michael Sherraden and Prof Margaret Sherraden who assisted with
the conceptualisation. Patrick Mpahle, then of the NYDA, was critical in bringing key role players who could
participate in the study together.
The NYDA and the University of Johannesburg’s University and Faculty Research Committees provided
initial seed-funding for the study. It was Paula Nimpuno of the Ford Foundation who understood the research
vision and could appreciate the signicance of the study for South Africa and other developing contexts.
Our grateful thanks to her and to the Ford Foundation for their continued nancial support of this project.
Najwah Allie-Edries is another visionary who could understand the signicance of the study for analysing
what mechanisms might work to streamline more young people into the labour market. Her support and
that of the National Treasury through the Government Technical Advisory Committee have been invaluable
in supporting the continuation of the study. Grateful thanks also to the British Academy Newton Advanced
Fellowship, of which Prof Lauren Graham was a fellow, for their contribution to the qualitative component of
the study.
Each implementing partner in this project must be acknowledged. They have spent a great deal of time
providing the research team with information about their programmes, facilitating site visits, smoothing
the pathways for data collection and programme roll out at the sites, and assisting with contacting alumni
of their programmes. This project would not have been possible without the commitments of EOH Proserv,
NYDA YouthBuild, loveLife groundBREAKERS, Afrika Tikkun Services, Fit for Life Fit for Work, Raymond
Ackerman Academy, Thabiso Skills Institute, and Harambee. Grateful thanks to Standard Bank South Africa
5
SIYAKHA YOUTH ASSETS REPORT
(SBSA), and particularly to Wendy Orr and Simon Dagut, for understanding the vision of the study and the
importance of it for inclusive growth in South Africa, and for agreeing to be our nancial partner. Grounded
Media assisted us with the development of the nancial capability curriculum and ably trained the trainers
from the partner programmes.
Various individuals have contributed to this project at certain points. Thanks to Helene Perold, Dr Kingstone
Mutsonziwa and Abel Motsomi of FinMark Trust, and Prof Zitha Mokomane for their expert feedback on our
questionnaires. Our eldwork managers and supervisors and team of eldworkers were always willing to go
to sites, sometimes at the last minute, and never once provided us with any reason to doubt the authenticity
of the data collected. We thank them for their commitment to the research and its integrity. Researchers at
the CSDA, UNC and beyond, aside from those named as authors, have been involved in this study since its
inception and have all contributed to its development. Thanks must go to Jacqueline Moodley, Kim Baldry,
Tessa Hochfeld Aislinn Delany, Oluwafemi Adeagbo, Thapelo Mqehe, Innocentia Kgaphola, Ben Lough, David
Ansong, Sara Mitra Harwood, and Deborah Hughes for their inputs into the development and progress of
this project.
Finally, our most grateful thanks must go to the participants of this study. They spent a great deal of time
answering questions, sometimes dicult ones, about their personal lives and that of their households. They
did so for no direct benet, which is testament to their nature. We hope that the story we have presented on
these pages reects your lives; that it speaks to the realities of your struggles but that it also highlights the
incredible agency and resilience that you demonstrate. Ultimately this study is for you in the hopes that you,
and many like you, will nd that foot in the door and that this project will have in some way strengthened the
pathways to get there.
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6
ACRONYMS
ATS Afrika Tikkun Training Services
CDE Centre for Development and Enterprise
CSDA Centre for Social Development in Africa
CSG Child Support Grant
CBPWP Community-Based Public Works Programme
DOL Department of Labour
DPME Department of Planning, Monitoring and Evaluation
DPRU Development Policy Research Unit
DTI Department of Trade and Industry
EPWP Expanded Public Works Programmes
ETI Employment Tax Incentive (also known as the Youth Wage Subsidy)
FFLFFW Fit for Life For for Work
GDP Gross Domestic Product
HFIAS Household Food Insecurity Access Scale
IEC Independent Electoral Commission
ILO International Labour Organisation
J-PAL The Abdul Latif Jameel Poverty Action Lab
LEED Local Economic and Employment Development
LMIP Labour Market Intelligence Project
LPI Lived Poverty Index
NDP National Development Plan
NEET Not in Employment, Education or Training
NGO Non-Governmental Organisation
NIDS National Income Dynamics Study
NMW National Minimum Wage
NYDA National Youth Development Agency
NYP National Youth Policy
NYS National Youth Service
OECD Organization for Economic Cooperation and Development
PAY E Pay As You Earn
PEP Public Employment Programme(s)
PII Poverty and Inequality Initiative
QLFS Quarterly Labour Force Survey
RAA Raymond Ackerman Academy
RIE Realist Impact Evaluation
SADC Southern African Development Community
SALDRU Southern Africa Labour and Development Research Unit
SARS South African Revenue Service
SASSA South African Social Security Agency
SBSA Standard Bank South Africa
SDL Skills Development Levy
SETA Sector Education and Training Authority
SSA Sub-Saharan Africa
TSI Thabiso Skills Insitute
TVET Technical and Vocational Education and Training
UCT University of Cape Town
UJ University of Johannesburg
YEP Youth Employability Programme
7
SIYAKHA YOUTH ASSETS REPORT
1. INTRODUCTION
Each year a new cohort of young people exit the schooling
system and begin their journey to education and into the labour
market. Some, mostly those who have come from middle-class and
privileged backgrounds, make the transition from school to higher
education and on to employment relatively seamlessly. The majority
of South Africa’s youth, however, are trapped in a protracted
struggle to access post-secondary education or training or to get
their rst job. The pathway to employability and to work is uneven,
dicult, and is often marked by numerous unsuccessful attempts by
disadvantaged young people to nd work or to obtain skills. Many
become discouraged work seekers and end up in long-term chronic
unemployment which perpetuates the intergenerational cycle of
poverty in poor families and inequality in society.
Youth unemployment has reached crisis proportions. The 2016
Quarterly Labour Force Survey: Quarter One (Statistics South
Africa 2016a) put the unemployment rate for young people 15 – 24
years old at 55% - up from 50% in the previous year. The situation
has worsened since 2008 both in terms of unemployment rates and
disengagement of young people from the labour market (Statistics
South Africa 2015a). Further, high numbers of young people are
not only unemployed but are also not in education or training. In
2015 almost one third of young people between 15 and 24 years
were in this position. These young people are at high risk of chronic
unemployment and poverty with young women and African and
Coloured youth being most vulnerable to unemployment and
poverty (Graham and Mlatsheni 2015).
South Africa’s youth unemployment rate is markedly high in relation
to most other countries. Globally, youth unemployment is typically
higher than the general unemployment rate (owing to lags in
getting into the labour market for youth). In 2014, the global youth
unemployment rate was 13% with signicant variations between
regions and countries (International Labour Organisation (ILO) 2015). Youth unemployment is declining
especially in developed economies with the exception of Spain, Greece and Italy that were most severely
aected by the global economic crisis of 2008. Similar declines have been noted in the Sub-Saharan Africa
region while in the Middle East and North Africa, rates have increased (ILO 2015).
The growing problem of youth unemployment in South Africa is indicative of the structural problems of the
economy, the dynamics of the labour market itself and the education system. Low economic and employment
growth and low labour absorption rates of people with less skills compared to those who are better qualied
are cited as some of the reasons for the unusually high rates of unemployment among young people. Ongoing
inequalities in access to the labour market due to a range of factors such as gender inequality, geographic
location, time and costs of travel due to distances between home and work, inadequate access to quality
primary, secondary and further education, have contributed to young people being ill prepared to create and
take up jobs in a labour market that increasingly demands high levels of skills (Seekings and Nattrass 2005;
Banerjee et al. 2007; Spaull 2015). Shifts in youth unemployment will therefore require signicant changes
in both the education system and the labour market itself coupled with economic growth strategies that
prioritise jobs and that can absorb the increasing numbers of unemployed people, not just youth.
Despite these challenges, some young people nd their way into various public, private and the non-prot
organisations that provide learning and employment support. What might we learn from young people and
the organisations that have taken up the challenge of nding solutions to youth unemployment in South
Africa? Can these solutions provide pointers for collective action? These are urgent questions that need
a thoughtful response. Reliance on untested solutions can only lead to further delays, mounting frustration
among young people, loss of human capital and social and political instability.
1.1. Finding solutions to the challenge
Youth unemployment is rmly on the national agenda (The Presidency, Republic of South Africa 2015). A
great deal of public policy and programmatic attention has been and continues to be paid to the issue,
albeit with limited positive impact at this stage. These initiatives include public employment programmes such
as the Expanded Public Works Programme (EPWP) and the Community-Based Public Works Programme
(CBPWP) that have had a long-standing youth target intended to draw more young people into public sector
temporary employment. The National Treasury’s Jobs Fund and The Employment Tax Incentive (ETI) are
further attempts to encourage employers to create work opportunities for young work seekers (South African
8
Revenue Service (SARS) 2016; National Treasury 2011). Leading edge research is under way that could provide
insight into policy and programmatic interventions. Examples include experimental research into the eects
of the introduction of a transport subsidy for young work seekers (The Abdul Latif Jameel Poverty Action
Lab (J-PAL) 2016); the development of skills to improve job applications by youth (R Burger 2016) while the
Department of Labour (DOL) is assessing the potential eects of a National Minimum Wage (NMW) for South
Africa on the employment prospects of youth (Patel et al. 2016). There is also a growing interest in evidence
based youth employment interventions to facilitate youth labour market transitions and scale up of such
interventions (Department of Planning Monitoring and Evaluation 2016). These responses are aligned to the
call of the National Development Plan (NDP) for high level social policy and programmatic interventions to
create employment opportunities for young people. The NDP cautions against the potential instability that
may arise from a failure to act (National Planning Commission 2012, 16).
The youth unemployment challenge has prompted a range of innovative labour market interventions by civil
society, the private sector and government. These initiatives can be broadly categorised into four forms and
are aimed at:
• Enhancing the employability of young work seekers by means of developing their human capabilities
through technical and social skills, strengthening their social capital, and entrepreneurship or small business
development such as small business incubators. These programmes are often described as supply side
interventions and attempt to overcome the skills gaps and a lack of work experience of young work seekers.
• Job creation, and the enhancement of the demand for young workers, such as impact sourcing1, the
ETI, public works programmes, youth service and volunteering including labour market regulation and
activation policies.
• Decreasing the barriers to accessing the labour market and to educational opportunities at strategic
points, which can serve to smooth the pathway of young people as they exit the school system. Examples
of employment support services provided by some organisations include improving information ows
about labour market opportunities and connecting unemployed youth to work opportunities (Graham
2014; Dieltiens 2015). Particular types of interventions aim to decrease the cost of the job search by means
of, for example, transport subsidies; by increasing access to the labour market and to post-secondary
training opportunities; and improve work-readiness through gaining work experience.
• Developing knowledge of nancial literacy and access to saving for further education and training, which is
a signicant constraint for unemployed youth. Many lack competencies in nancial literacy which limits the
building of their nancial capabilities and assets. Although fewer youth employability programmes (YEPs)
oer nancial education programmes, this is an innovation which has been tested in other developing
countries to promote nancial inclusion and a culture of savings among youth to mitigate risk, smooth
consumption and support job search activities.
Initiatives of this kind are indicative of the commitment of a diversity of actors, both state and non-state,
in reducing youth unemployment rates. Evidence-based social interventions that could counter past and
continuing patterns of social and economic exclusion that underlie youth unemployment are, however,
sorely needed.
1.2. Study description
The Siyakha Youth Assets study is a longitudinal study that contributes to lling this knowledge gap and could
contribute to evidence-based employment interventions that may prevent long-term chronic unemployment.
The study focuses on youth employability programmes that aim to enhance the employability of young
people. More specically it includes those programmes that rstly, oer human capability skills (that is, social
skills that enable young people to function eectively in the work environment); secondly, technical and or
vocational skills; and nally, opportunities to increase work experience in order to prepare them for the labour
market and smooth their transition to employment.
Youth employability programmes that form part of the study include: loveLife groundBREAKERS, Fit for Life
Fit for Work, Thabiso Skills Institute, Raymond Ackerman Academy, Harambee Youth Employment Accelerator,
the National Youth Development Agency YouthBuild programme, Afrika Tikkun Training Services, and EOH
learnerships programme. Taken together, these organisations and programmes represent a signicant
investment in training provision for the workplace and oer accessible alternatives to formal post-secondary
education for young people. Yet, we know little about their impact. Do they in fact assist young people to
nd work? What elements of their programmes are most eective? And how can lessons be shared across
programmes to strengthen, consolidate and scale up the oerings within the sector?
The study is premised on the assumption that young people have dreams, that they want to study and to
work, and that they have a range of assets that could contribute to programme success such as their own
1 A process of working with employers to shift their perceptions of who they consider to be “employable” in order
to promote more inclusive recruitment and placement processes. Youth are not typically seen as viable employees
because of perceived training costs and lack of work experience. Shifting employers’ perceptions of youth is important
as a strategy for enhancing demand for young workers.
9
SIYAKHA YOUTH ASSETS REPORT
ideas, motivations and energies to make a dierence in their lives. It is akin to Gidden’s (1984) notion of human
agency dened as the “capacity of the individual to make a dierence to a pre-existing state of aair[s]”
(Giddens 1984, p.14). We take the view that young work seekers are active participants in achieving their goals.
While constrained by systemic barriers in the labour market, educational system and the structural nature
of unemployment in South Africa, they are nevertheless motivated to make constructive decisions, use the
opportunities available to them and their resources and networks to take appropriate action. But, on their
own they are unlikely to overcome these formidable barriers. Appropriate public, private and voluntary sector
employability initiatives have stepped in to meet this challenge.
From a social development perspective, social and human capital investments alone are not enough to promote
positive social development outcomes. The theory of social development promotes the idea that a combination
of social and nancial/economic interventions are needed to enhance human development outcomes. We
therefore hypothesise that a combination of social and economic youth employability interventions are likely
to lead to the best development outcomes for the youth themselves and for their families, with positive long-
term returns for society at large (Patel 2015). Applied to this study, the youth employability programmes on
their own represent investments in human capital development which in and of themselves may lead to better
employability and employment outcomes. But if a nancial capability intervention were to be added, the
outcomes should be even better. We therefore developed a nancial capability intervention to be added to
the existing employability interventions oered by the youth employability programmes. Financial capability
is taken to refer to nancial literacy and the opportunity to use and apply the knowledge required through
gaining access to nancial products and services (Johnson and Sherraden 2007). In this study we developed
a nancial literacy module focused on savings and, in partnership with Standard Bank South Africa, access to
a savings account was provided.
Aims and objectives
The overarching aim of the study is to assess the impact of youth employability and nancial inclusion
interventions to more eectively support young people in the transition to work. We envisage that the results
of the ‘Siyakha project’ may be useful to inform policy and programmatic interventions to enhance youth
employment.
Overview of the methodology
The study is set up as a comparative, longitudinal research design. The eight organisations mentioned
above deliver programmes across 48 sites nationally. In each site we have collected data from a sample of
participants as they enter the programme and as they exit the programme. Data will again be collected nine
and 18 months after completion of the programme from the same participants. The research design will allow
us to test the relative eects of the dierent programme types – whether a short or longer-term programme
is more eective, what combination of practical and classroom based training seems to be most eective, and
whether the sector they are training for has any eect on the outcome.
In addition, 24 of the sites were randomly selected for participants to also receive the nancial capability input
(training and savings account). We will thus be able to assess whether the addition of a nancial capability
component enhances outcomes for young people or not.
The experimental design allows us to test the eect of the treatment (the nancial capability intervention). It
does not allow us to assess the eect of the youth employability programmes on their own, primarily because
a control group of participants not in youth employability programmes is not possible to nd2. For this reason
we will also be engaging in a realist impact evaluation (RIE) with a sample of participants from across the
programmes; the purpose of which is to qualitatively assess the role played by the youth employability
programmes in their pathways to work. It is used to specically assess the outcomes of a programme and
to comment on the programme impact in relation to the context in which it operated, the target group it
intended to reach, and its stated aims and objectives (Kazi 2003).
1.3. Conclusion
In summary, this intervention research study has begun to implement and rigorously test a simple concept
to address youth unemployment in South Africa. It will provide evidence that could guide sustainable social
investments in the development of the human capabilities of young people in collaboration with the private
sector, government and NGO partners. Initial lessons on what is working within the sector, and how to better
integrate, enhance and or improve the programme eects could emerge from the ndings. This report is the
rst in a series that will continue to share knowledge that could inform social policies and practice on the long-
term outcomes of youth employability programmes. The study makes a contribution to evidence-based social
policies and programmes to address youth unemployment in South Africa.
2 Because participants self-select into the programmes an adequate control group of young people not going through
the programmes at all was impossible to locate.
10
2. YOUTH PATHWAYS TO THE LABOUR MARKET
A further interrogation of the challenge, and particularly the nuances of what drives it, is necessary in order
to understand how to better address the problem. So too is an analysis of what we know works globally. For
instance, we need to understand:
• What the global and local structural features of the challenge are
• What the individual and community level explanations of the challenge are
• What lessons can be learned from international evidence on youth employment solutions, and
• What role nancial capability interventions can play in addressing youth employment?
This chapter of the report considers the above in more detail and the evidence of what drives the youth
unemployment challenge. It also outlines the theoretical approach that was adopted including the conceptual
framework that guided the study.
2.1. The global youth unemployment landscape
A key challenge driving high levels of unemployment has been the recessionary economic environment around
the world since 2008, and accompanying policies of austerity, which have led to increasingly scally constrained
governments who spend less on higher education and employment creation (African Economic Outlook 2014;
World Economic Forum 2014; Branson and Zuze 2012; Mlatsheni 2012). The result was that between 2009 and
2012 youth unemployment rates in most regions steadily rose (International Labour Organisation (ILO) 2012b).
Explanations for this include a general loss of employment over this period; but also that young people were
particularly badly aected by the downturn given that they usually join the labour market queue last and with
the least work experience. Since then both employment rates and youth employment rates have started to
recover, albeit with dierences across regions. However, youth employment rates are yet to return to their pre-
2008 levels (International Labour Organisation (ILO) 2015).
The global trends in employment for youth also point to the precarity of work for youth. The ILO notes the
reduction in the numbers of permanent, stable jobs occupied by youth, coupled with an increase in temporary
work, informal work and other forms of vulnerable work. In part this is led by increased technological
advancements that shrink the numbers of available jobs (International Labour Organisation (ILO) 2015).
These features of the changing nature of employment for youth no doubt also inuence South Africa. We did
for instance see signicant job losses in the period following the 2008 nancial crisis. Similarly, a sustained
period of low to no job growth has been evident (Mahadea 2003; Altman 2007; Darma Mahadea and Simson
2010), which has meant that there are fewer jobs available to be taken by young employees.
2.2. The South African youth unemployment landscape
In the rst quarter of 2015, Stats SA estimated that the unemployment rate for youth aged 15 to 34 was just
under 37%, compared to 17% among adults aged 35 to 64 (Statistics South Africa 2015a). Incorporating the
numbers of young people who are unemployed but who have given up looking for work, would place the
unemployment rate among young people over 44% (Graham and Mlatsheni 2015). And in the rst quarter of
2016, the unemployment rate (including only active job-seekers) for 15- to 24-year-olds was about 55% – up
5% on the previous year (Statistics South Africa 2016a). What is of most concern is that these gures have
increased since 2008 owing in part to an increase in discouraged work seekers in this cohort (Statistics South
Africa 2015a).
Of even greater concern than youth unemployment is the issue of young people who are neither in employment,
nor education or training – commonly referred to as NEET (Not in Employment, Education or Training). Of the
almost 10.2 million young people between the ages of 15 and 24 years, 33% are NEET (Graham and Mlatsheni, 2015)
and therefore fall into a particularly vulnerable group as they are “neither improving their future employability
through investment in skills nor gaining experience through employment” (Statistics South Africa 2015a). They
are arguably the most vulnerable to chronic unemployment and poverty as well as social exclusion.
Although ocially the NEET rate is measured for youth between the ages of 15 and 24, it is worth considering
how the NEET rate changes across the extended age range of 15 – 34 years to assess patterns of vulnerability.
The proportions of youth who are NEET remains low for 15 – 17-year olds, many of whom are still at secondary
school, but rises quite dramatically for 18 – 25-year-olds, peaking at 51% for 21 – 25-year-olds. Thereafter the
proportion of NEETs declines somewhat. However, for 30 – 34-year-olds the rate is still 42% (Graham and
Mlatsheni 2015). This suggests that over time some young people are nding their way into employment,
however a 42% NEET rate for 30 – 34-year-olds is still alarmingly high, and these are likely to be people who
end up in chronic unemployment throughout their lives.
As can be expected – youth with less education are more likely to be NEET (Statistics South Africa 2015a). For
example, 58% of young people aged 21 – 25 years who have not completed secondary education are NEET,
while for those with some post-secondary education only 36% are NEET. In the same way that young women
are more vulnerable to unemployment than young men, they are also more likely to be both unemployed and
not in education or training: 36% of young women 15 – 24-years-old are NEET, compared to only 30% of young
men (Graham and Mlatsheni 2015).
11
SIYAKHA YOUTH ASSETS REPORT
South Africa’s growing youth unemployment challenge is in part driven by a high general unemployment
rate and it is to this landscape and the explanations for its persistence that we turn rst before considering
the specic features of the labour market that might explain the particularly high unemployment rates
aecting youth.
Explanations for unemployment
For the past two decades South Africa has experienced low to no job growth. In the six years leading
up to 2001 for instance GDP growth went hand-in-hand with labour displacement due to the use of new
technologies (Mahadea 2003). In 2002 the tide began to turn with modest job gains as GDP grew, reaching
a peak in 2008 (Mahadea and Simson 2010). However, even then the job growth was low. As Mahadea and
Simson (2010) note:
Except for the year 2008, the ratio of GDP growth to employment growth has been far less than one,
reecting that South Africa's job creation performance against GDP has been rather weak for most years
of the period 2002-2008.
Burger and von Fintel (2009) also explain that the high levels of unemployment can be explained by increases in
labour market participation during economic downturns (as people lose jobs and move into the job searching)
combined with slow labour market absorption during economic upswings, leading to sustained high levels
of unemployment. One of the reasons for low levels of labour absorption despite economic growth, is that in
the post-apartheid period economic policy shifted from a growth in job intensive sectors such as agriculture
and mining, towards a high-technology growth path. In turn, this strategy was intended to be matched by
investment in skills development, with the promise of increasing wages (Banerjee et al. 2007). However, over
the same period we had growth in a largely unskilled labour force as education and training systems failed
to meet the skills needs of the economy. With a contraction in the agricultural sector, which is able to absorb
low-skill workers, unemployment rates increased. The result has been a drop in the employment of unskilled
labour and minimal job growth in sectors that were intended to drive the growth path (Seekings and Nattrass
2005; Banerjee et al. 2007). This shift in our economic growth path has resulted in a skills mismatch within
the economy with demand highest for skilled labour, alongside a severe oversubscription for jobs that require
lower levels of skill.
South Africa felt the eects of the 2008 global economic crisis in 2009 when it had negative economic growth
(as measured by Gross Domestic Product (GDP)), with commensurate job losses. Since then it has recovered,
but in 2015 GDP gures again dipped below zero. South Africa has not been unaected by global downward
economic trends. Reduction in economic growth globally has reduced demand for products that we do export,
thus constricting the manufacturing sector (Industrial Development Corporation 2016). This decline in economic
growth has occurred at the same time as increases in unemployment rates.
At the end of the rst quarter of 2016 the South African economy had demonstrated a further quarter of job
losses resulting in a narrow unemployment rate3 of 26.7% – one percentage point higher than the previous
quarter (Statistics South Africa 2016a), and 5% higher than 2009 levels – just after the global economic crisis
(Trading Economics 2016).
Unfortunately future upturns in the economy are unlikely to immediately result in job gains. An analysis of
employment in relation to the business cycle shows that as business cycles swing downwards labour supply
increases (as companies shed jobs and as those involved in household production move into the labour market).
However, as the business cycle turns upwards, labour absorption lags behind, suggesting that businesses are
resistant to taking risks on hiring new sta, even as they reap the benets of economic growth (Burger and von
Fintel 2009). Yet it is private companies that in the longer-term must absorb labour if we are to see signicant
employment growth. There is some agreement that the growth years of 2000 to 2008 were largely stimulated
by public spending, which in the longer-term is unsustainable. Going forward, employment expansion requires
that the private sector be stimulated to hire sta, particularly those with low levels of skills, who make up the
bulk of those who are unemployed (Centre for Development and Enterprise 2010).
Yet our current labour market system is not set up to stimulate employment in the private sector. The focus
on technology led-growth and high-value export products, means that investments in labour-absorbing
industries has been minimal (Banerjee et al. 2007; Centre for Development and Enterprise 2016). In addition,
many economists would argue that the costs of employing labour (particularly non-wage costs such as costs
of hiring, ring and replacing labour when required) are too high to stimulate employment, particularly of
people with an unproven work record (such as young work seekers) (Centre for Development and Enterprise
2010). Onerous and overly bureaucratic systems also do not stimulate small rms to grow and employ new
people, meaning that the “critical mass” of employers that is required to stimulate employment, remains elusive
(Centre for Development and Enterprise 2010).
3 The narrow unemployment rate includes those people who looked for work and did not work in the four weeks
preceding the survey. It does not include those who have given up looking for work (discouraged work seekers).
12
These explanations provide insight into the persistence of unemployment in South Africa, but they also aect
youth most profoundly and it is to this that we now turn.
Explanations for youth unemployment
The above explanations for the country’s high rate of structural unemployment point to low rates of economic
growth coupled with low rates of employment growth particularly since the economic crisis of 2008. During
this period youth unemployment increased and continues to increase. In this section we consider some of the
specic factors that have a bearing on youth unemployment.
As mentioned previously, the labour absorption rate of youth 18-25 years is low (19.5%) compared to 40%
for the general population with young women being most signicantly aected (Statistics South Africa
2016a). This aects young people most as they are passed over for or replaced by experienced workers
(Grimshaw 2014). This is particularly the case because youth employment is concentrated in small rms – 68%
of employed youth are employed in small businesses (Statistics South Africa 2015c) – which are arguably the
most vulnerable in economic downturns and therefore take the longest to recover in positive growth climates.
Young people are therefore the last to be absorbed back into the labour market. Signicant numbers of young
people are employed in temporary jobs, especially in the wholesale and retail sector (32.7%), leading to them
moving in and out of the labour market. Other sectors where youth are employed such as community, personal
and social services (14.3%) and manufacturing (11%) have also been negatively aected by the economic
downturn (Patel et al. 2016).
In addition, specic labour market interventions that are intended to protect workers could also have the
opposite eects. For instance, relative shares of youth employment dropped in sectors during periods of the
promulgation of sectoral determinations, with these sectors also sustaining lower rates of growth of youth
employment relative to other sectors (Bhorat et al. 2016). South Africa’s current sectoral determinations
are argued as having contributed to youth unemployment due to it being set too high, at levels which do
not account for the limited productivity of young people (National Treasury 2011). This falling demand for
youth workers proportionally greater in certain sectors, reects their marginal position in the labour market.
Preference by employers for older workers who are more experienced and/or for more skilled workers have
also been cited as a possible explanation for low levels of labour absorption of youth. While this preference is
a global reality (Grimshaw, 2014), in South Africa it appears to be particularly pronounced.
The skills mismatch that is the demand of the economy for higher levels of skills discussed above also aects
youth in particular. Despite young people today having more years of education than their parents, they are
not yet reaping the rewards in terms of access to the labour market (South African Labour and Development
Research Unit (SALDRU) 2016a). The fact that there is demand for higher levels of skills in the labour market
is evidenced in Figure 1 below which shows that the chances of employment increase with a matric certicate
– a worrying statistic given the high numbers of young people who drop out of the education system prior
to completing matric (Spaull 2015). Employment prospects are better once one has a post-secondary
qualication (Van der Berg and van Broekhuizen 2012), but there are far too few young people who manage
to access and complete post-secondary education (Perold, Cloete, and Papier 2012; van Broekhuizen, van der
Berg, and Hofmeyr 2016).
0 10 20 30 40 50 60 70 80 90 100
Less than matric
Matric
More than Matric
Employed Unemployed (expanded) Other Not Economically Active
Figure 1: Employment status by education status for youth 15-34 years
(Statistics South Africa, 2015; own analysis)
13
SIYAKHA YOUTH ASSETS REPORT
These gures suggest that the youth unemployment challenge is in part driven by the fact that young people
exiting the schooling system do not have the skills to compete for jobs where there is demand. Rather they
enter the back of the labour market queue, joining thousands of workers with low-levels of skills, most of
whom have more work experience than they do (Reddy et al. 2016; Pauw, Oosthuizen, and Van Der Westhuizen
2008; Altman 2007).
Lack of qualications is not the only explanation for youth unemployment. Economic research demonstrates
that although having a matric places individuals at a slight advantage in the labour market, investment in
education for individuals only demonstrates higher returns once an individual has some post-secondary
education (Yu 2012; Lam et al 2008). Even young people with a matric struggle to nd work and when they
do, it is often in low paying, low-skill jobs.
In part, the disconnect between the education system and the labour market is a result of the actual skills
decit that young people have when they leave the school system. This is a problem that the labour market
cannot address. Research by Spaull (2015) demonstrates that almost a quarter of children in Grade 9 (age
15) did not display the most basic numeracy skills such as an understanding of whole numbers and decimals.
Compared internationally, South African Grade 9 learners performed far worse than Grade 8 learners from
comparable middle-income, and even much poorer countries. Many of these challenges are rooted in literacy
gaps that are evident in Grade 4, by which time a signicant proportion of learners (particularly rural learners)
are functionally illiterate and therefore unable to engage meaningfully with the curriculum from Grade 4
onwards. By Grade 9 learners in Quintile 1-3 schools test functionally a full four grades behind their Quintile
5 counterparts (Spaull, 2015). The poor quality of basic and secondary education is a signicant factor that
inuences the employability of youth.
Although actual skills decits play a role, employer perceptions of the value of matric also need to be considered.
Because of the widely publicised challenges in the education system, employers do not trust the quality of
a matriculation certicate. They thus tend to push requirements for entry into jobs higher than is necessary
(Bhorat 2014). Retail outlets may for instance require job applicants to have a matric with a mathematics and
science pass for entry into a basic retail job. Neither subject is required at the matric level for an individual
to function in this type of job adequately. But employers use this as a method to quickly sort people in the
labour market queue and assume that those who have matric with mathematics and science are the “cream of
the crop”. Such practices eectively shut out a large proportion of the youth labour force, and can result in a
mismatch of skills and interests with available jobs, with resultant costly churn in the youth workforce.
An oft-cited reason for young people’s unemployment is the assumption that they have high reservation
wages. However, reservation wages are under-investigated in relation to youth unemployment, particularly in
the South African context. Reservation wages are dened as the lowest wage an individual is willing to work
for (Brown and Taylor 2013). At wages lower than the reservation wage, the individual would choose not to
work, or choose leisure or continued job-searching (Nattrass and Walker 2005; Zoch 2014).
14
Calculating a reservation wage for an individual is complex. Job-search costs, transport costs, childcare costs
and the like all impact on how individuals calculate their own reservation wage. Where costs such as travel and
childcare are incurred during job-search, or expected while working, job-seekers are likely to decline job oers
where wages oered do not allow them to meet these costs (Nattrass and Walker 2005). This is in contrast to
the standard neoclassical assumption that job-seekers should be willing to accept any wage greater than zero
as this would be better than receiving nothing at all (Falk, Fehr, and Zehnder 2005; Wang 2012).
In South Africa, it is often claimed that low-wage job-seekers, and young people in particular, are divorced
from the realities of the labour market, and that their unrealistic expectations about work and remuneration are
responsible for reservation wages which are unjustiably high given high unemployment, and their (limited)
skills and experience (Kingdon and Knight 2001; Roberts 2011; Rankin and Roberts 2011; Mlatsheni 2012; Yu
2012). Roberts (2011) nds that young unemployed people consistently overestimate their chances of nding
work given employment rates of similar people in the same regions. This is due to the inability to correctly
identify both (a) what their labour is worth given their skills, experience and other characteristics, and (b)
what other people who are similar to them are actually earning, possibly because of young people being new
to the labour market and lacking information. However, being provided with facts about the labour market
did not lead the majority to adjust their expectations, and this inability to navigate their way in the labour
market is cited as a cause of youth unemployment, with job-seekers also being more likely to have turned
down job oers. Rankin and Roberts (2011) also nd evidence of ‘inated’ or unrealistic expectations. They nd
reservation wages of 20-34 year olds are consistently anchored to their predicted wages in large rms, which
are higher than those in small rms where the bulk of young people are employed and where they are more
likely to nd work. Rankin and Roberts (2011) do, however, indicate that job-search and other costs were not
considered in their research; nor did they investigate whether prevailing market wages would be sucient to
cover them.
Patel et al (2016), in a qualitative study, demonstrate that young people think quite carefully about their
monthly costs and set reservation wages at slightly higher than this monthly amount. Their mean reservation
wages in fact corresponded quite closely with median costs of living. However, when participants of the study
were probed further about the wage at which they would reject a job, most in fact indicated that they would
not reject a job, regardless of the wage oered. There was a widespread belief amongst the participants
that they ought to take whatever job they can, given the low probability of another oer being made. This
suggests that while young unemployed people have a reservation wage in mind, this does not necessarily
translate into their job-seeking behaviour. In fact, many were willing to work for wages that were lower than
sectorally determined minimum wages. Recently the National Income Dynamics Study (NIDS) data has shown
that reservations wages among youth are typically in line with average wages and that they decrease the
longer that young people are out of work, suggesting that reservation wages do not play a role in persistent
unemployment among youth (South African Labour and Development Research Unit (SALDRU) 2016b).
The above explanations provide some insight into why youth unemployment is so persistently high. Besides
the lack of jobs due to the country’s high structural unemployment problem, supply side factors have not been
adequately probed such as diculties experienced in the job search process, a lack of support for work seekers,
a lack of work experience and knowledge and information about the labour market. These are other possible
explanations for the low levels of absorption of youth in the labour market which is the focus of this study.
Inequalities in youth unemployment
Past inequalities in the labour market continue to shape the present. African and Coloured youth continue
to be markedly more aected by unemployment than their White counterparts. But these inequalities, albeit
rooted in the past, are shaped in new and nuanced ways.
Education inequalities play a signicant role in shaping labour market outcomes for youth. As discussed above,
Spaull (2015) notes how, despite signicant investments into the education system, learners from Quintile 1-3
schools (still largely catering for African learners) continue to achieve at far lower rates than their Quintile 5
counterparts (where White learners are more represented). His research clearly demonstrates how learners
from the lower quintiles consistently exit the education system and fall either into unemployment or are only
able to access low paying, low skilled jobs. In contrast their Quintile 5 counterparts exit the schooling system
and transition quite smoothly into higher or further education and onto jobs; often jobs that have a clear
pathway to professional and/or managerial positions (Spaull, 2015).
Income inequality also plays a role. Recent ndings from the NIDS demonstrate how household income in
the year a young person is in matric signicantly determine whether or not they will be able to access post-
secondary education and training (Branson and Khan 2016). This nding suggests that most young people
from poor households are destined for low wage work, blocked o from accessing opportunities that will
mould them for higher paying, higher skilled work.
Gender also continues to play a role. Young women continue to be more vulnerable to unemployment than
young men as is demonstrated in Figure 2.
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SIYAKHA YOUTH ASSETS REPORT
33,8
35,1
38,1
39,3
33,2
36,8
37,5
27,6
30,5
25,6
40,7
45,5
52,6
42,8
46,9
44,4
42,6
32,4
36,8
37,2
0 10 20 30 40 50
60
South Africa
Free State
Northern Cape
Eastern Cape
Mpumalanga
North West
Gauteng
Western Cape
KwaZulu Natal
Limpopo
Female Male
Figure 2: Unemployment rate (excluding discouraged work-seekers)
by province and gender, youth aged 15 – 34 years (Statistics South Africa, 2015).
Finally, location continues to play a role with those living in urban areas far more likely to be employed than
those in rural areas (Ranchhod and Mlatsheni 2016). Urban/rural location aects employment chances, primarily
because of the availability of jobs in urban as compared to rural areas. But even location within an urban
area shapes access to employment given the costs of work-seeking if one lives far away from city centres.
For instance, the majority of low-wage work-seekers live in areas that are far from major centres where job
opportunities are available. This means that transport costs to seek work may become prohibitively expensive
and if they do manage to secure work far from home, the transport costs make it unlikely they will remain in
the job (Graham and Mlatsheni, 2015; Patel et al., 2016). Further, Seekings (2010) found that a typical return
trip could be in the region of R30-R40 (about US$2-$2.63). For working people, this may mean spending
more than a third of their monthly income on travel. For those seeking work, the costs are prohibitive.
The issue is exacerbated by a lack of access to information and employment services at the community level. By
and large, there are no functional job centres where relevant, up-to-date information about job openings and
job advice can be found. Most youth thus have to search for this information on the internet or in newspapers
– both of which cost them money (Graham and Mlatsheni, 2015; Patel et al., 2016). They also report having to
use the internet and computers for job applications. Few have these resources at home, so they are forced to
use (sometimes distant) often expensive internet cafés to do so. In addition, many employers demand paper
applications, which entails the costs of printing, copying, certication and postage (Patel et al., 2016). Taken
together, these costs are too expensive for young people without jobs to incur, and thus limit the frequency
with which they are able to apply for positions.
There are also inequalities in access to social capital that shape youth unemployment. Social capital is often
mentioned as a key asset when navigating the labour market – “it’s not what you know, it’s who you know”.
Certainly Putnam, one of the rst theorists to coin the term “social capital”, noted the importance of bridging
networks (connections with people outside of one’s household or immediate community) in facilitating
business and job opportunities (2001). His ideas have been subsequently conrmed by others researching the
eects of social capital (Woolcock and Narayan 2000).
In the South African context dierences in social capital can have a marked eect on the ways in which young
people are included in or excluded from the labour market (Kruss 2016; Mlatsheni and Rospabe 2009). For
instance, young White South Africans typically, while studying, work in part-time jobs that they nd through
their parents’ social networks. This work experience gained, in turn, places them at an advantage when it
comes to seeking full-time work (Seekings 2012). In contrast, it is telling that the bulk of young people who are
not in employment, education or training are living in households where nobody is employed (Statistics South
Africa 2015a). Their situation therefore may be as much a function of poverty as it is a lack of productive social
networks – that is, social networks that can be used for information about and access to the labour market –
which is an important asset for navigating entry into the labour market.
The individual experience of being young and unemployed
At the individual level there are multiple factors that coalesce to shape young people’s ability to break into the
labour market. Firstly, it must be stated that, despite popular perceptions, young people are not lazy nor do
they have a sense of entitlement. Rather they engage in a wide range of work-seeking and livelihood activities
(Graham and Mlatsheni 2015). Graham (2012) presents accounts of young people in an informal settlement in
Gauteng who seek piece jobs, buy small items to resell, and pool money to purchase the latest newspapers
16
to seek work. Graham and Geerars (forthcoming) document the multiple ways in which young people in a
township in Johannesburg attempt to access some form of post-secondary education. Young people’s actions
in trying to access opportunities for themselves are driven in part by desperation, but are also an indication
of the fact that young people generally have high hopes for themselves and demonstrate a sense of control
and agency over their lives (Ramphele 2002; Swartz, Harding, and De Lannoy 2012; De Lannoy, Leibbrandt,
and Frame 2015).
However, they are also faced with a myriad of constraints discussed above, which aect their emotional and
mental wellbeing, and ultimately their endeavours to nd work. Newman and De Lannoy (2014) detail the
lives of young people in a township in the Western Cape and demonstrates how they move through cycles
of hope and despair as they gather the enthusiasm to search for work, and are met with repeated barriers
and disappointments. Depression may well be a consequence of repeated failures, which in turn may lead to
individuals opting out of the labour market. Further research is needed to better understand this relationship.
Young people are often negatively represented when it comes to popular discussions about youth
unemployment. They are variously described as lazy, entitled, and passive. The above research suggests the
opposite. Instead, young people are positive, hopeful and optimistic, want to work, and are in fact willing
to work for very little. However, they face marked challenges. They bear the major cost of the country’s
structural unemployment problem and of an education system that leaves them ill-equipped to be employed
in a labour market seeking higher levels of skills. Since most come from poor households, dicult decisions
and trade- os need to be made about work-seeking and its costs. Having considered the various drivers
of youth unemployment we now turn to considering literature on interventions aimed at addressing youth
unemployment.
2.3. Responses to youth unemployment – a review
of interventions
The underlying causes of unemployment outlined above point to structural and systemic factors that are
related to reforms in economic and social policies that could promote employment and more inclusive
economic growth. This is a signicant challenge in a context of economic globalisation and its impacts on
the South African economy. Systemic failures in the education system perpetuate historical inequalities in
the labour market requiring urgent interventions to improve the quality of education and the skills mismatch.
Furthermore, a set of inter-connected social factors, such as the cost of work-seeking as well as knowledge
and information about the labour market and its dynamics, require a dierent set of interventions. Solving the
unemployment challenge for young people requires a multi-faceted approach. In line with the purpose of the
study we focus the review of the literature on responses to unemployment in two key areas, namely, increasing
the demand for young work seekers, and how to increase their employability in the labour market.
Enhancing the demand for young work seekers
Demand side interventions refer to a combination of public policies and programmes that could stimulate
employment growth and work opportunities for youth. In this review we consider a few national demand side
policy initiatives that were designed to increase youth employment namely, public employment programmes,
tax incentives to companies to employ young people, youth ‘opportunity wages’ and interventions directed
at changing employer attitudes to young work seekers.
The primary aim of public employment programmes (PEPs) is to stimulate demand for labour in the public
sphere. They may also have a training component, as in the case of the South African EPWP. PEPs typically
use public funds towards large scale programmes that oer part-time, infrequent and/or temporary work
to people who are unemployed, allowing them to access a wage for the time that they work. Sometimes
such programmes are considered part of a social protection package and form part of short-term temporary
solutions as people nd their way back into work. In other cases, such programmes are a way of guaranteeing
all citizens an opportunity to work for a proportion of the year – focusing on the social value of work and the
need to guarantee some form of income – as in the Indian example.
In South Africa, the EPWP and the CBPWP represent massive investments in ensuring that people have
an opportunity to engage in work through publicly funded programmes. Both are large-scale PEPs aiming
to provide short-term employment alongside training to people who are otherwise unemployed. Both
programmes are delivered through various state departments, allowing publicly funded labour to be
directed towards promoting public and community assets such as environmental protection, infrastructure
development, community development and social care. They include activities as varied as removing invasive
species, re protection, construction, home-based care for the elderly and ill, and early childhood development
amongst others. These policies are novel and innovative while simultaneously contributing to the public good
(Philip, 2016) and to social cohesion and social care (Patel 2015). The aim of the programmes is to provide
an opportunity for short-term, temporary and/or infrequent employment. But both were also intended to
prepare people for more permanent or longer-term employment (Hemson, 2008; McCord 2012). Critics of the
programmes have pointed to problems of inadequate skills training in both the EPWP and CBPWP (Hemson
2008; Nzimakwe 2008); a lack of preparation of participants for jobs in the open labour market and a lack
of skills transfer to enable them to pursue livelihoods activities in the informal economy (Nzimakwe 2008;
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SIYAKHA YOUTH ASSETS REPORT
McCord 2012). International evidence on subsidised or public employment programmes suggests that, when
viewed as a stepping stone into the open labour market, they are rarely eective. In fact, in some studies, they
were proven to decrease participants’ chances of nding work in the open labour market (Puerto, Kluve and
Rother, 2016). Despite its limitations, PEPs do provide important temporary work for those who select these
options and are a long-standing public policy option that has been used extensively internationally to respond
to the challenge of high unemployment.
Although neither the EPWP nor the CBPWP are youth specic, both are supposed to ensure that at least
40% of placements are reserved for young people (aged 18 – 35 years). To date, these targets have been met
and were exceeded (Department of Public Works 2010). They therefore represent a signicant state nancial
investment to support young people’s attempts to work.
Since 2004 the state has invested in the National Youth Service (NYS) programme, currently operated by
the National Youth Development Agency (NYDA). Young people volunteer to deliver services in their local
communities. One of the primary aims of the NYS is to increase the skills levels of participants. Patel (2009),
in a comparative study of youth volunteering in ve Southern African Development Community (SADC)
countries, found that many youth service programmes focus on developing livelihood and employability skills,
and increasing opportunities for employment. According to Delany and Perold (2017), in a wider review of
African youth service programmes, service programmes do this by focusing deliberately on technical skills
training, the provision of stipends, experiential learning, and providing active linkages to exit opportunities.
Although South Africa has been investing in the NYS for some time, there is a lack of evidence regarding the
extent to which it does contribute to the employability and employment outcomes of young people.
Other options lie in direct labour market interventions. The ETI is an example of such an intervention aimed at
increasing demand for young employees. Companies who employ youth aged 18 – 29 can apply for a reduction
in the amount of Pay As You Earn (PAYE) tax, which is intended to help companies oset the costs of training
young employees (SARS, 2016). Results from a randomised control trial of the pilot programme demonstrated
that young people with wage subsidy vouchers4 were 25% more likely to nd and retain work than those
who did not have vouchers (Levinsohn et al. 2014). Based on these ndings, the ETI was implemented in
January 2014. Evaluations of the ETI were carried out six and 12 months after inception and ndings reected
no discernible eects on youth unemployment rates (Ranchhod and Finn 2015; Ranchhod and Finn 2016). A
possible reason for this nding is that employers may not yet be fully aware of the programme. Furthermore,
hiring decisions would not be governed solely by the availability of the ETI, increased hiring would also depend
on feasibility of expansion, a decision process that may take more than a year. We may therefore still see
benets in the longer-term. International evidence suggests that this should be the case. There seems to
be some evidence across studies internationally to show that wage subsidies that are intended to stimulate
demand for young work seekers are eective in the short-term, although most studies were not able to
determine whether this was as a result of young people displacing older workers, or due to the creation of new
jobs (Puerto, Kluve and Rother, 2016).
The development of a National Minimum Wage (NMW) for South Africa is under consideration by a specially
appointed Presidential Review Panel. While a NMW could benet employed young people, if the level is set to
high, it may lead to the further exclusion of unemployed youth from the labour market. Half of the countries
that have adopted a NMW have also adopted a youth sub-minimum wage to address youth unemployment
(Patel et al 2016). A policy option for South Africa may be to exclude certain age groups from the NMW
dispensation or to consider the introduction of an “opportunity” or “training” wage for young work seekers for
a limited period in order to stimulate demand for such workers (Patel et al. 2016).
Another approach to promoting demand for young work-seekers has been to try to shift employers’ perceptions
about the pool of potential workers. Impact sourcing is a process by which employers intentionally employ
people who are vulnerable to unemployment and who would not normally be seen as viable employees
(Monitor Company Group 2011). Through this approach companies shift their perceptions of the minimum
requirements for entry-level positions, implement policies and programmes that recruit such work-seekers,
and support them to stay and grow in the workplace. Successes have been seen in the business process
outsourcing sector5 in which individuals, and particularly young people, from poor areas in Africa and Asia
are targeted for entry-level positions. However, there is a need for more research to understand whether
such interventions are in fact stimulating demand for young work seekers, which sectors it works best in, and
whether shifting perceptions about young work seekers leads to employers creating new jobs or whether it in
fact simply creates churn in the labour force.
The abovementioned interventions are important programmes for stimulating demand for young work seekers.
However, the primary focus of this study is on programmes that enhance the supply of work seekers, both in
terms of their employability and in terms of their labour market engagement (frequency and ecacy of job
search and application). It is to literature about such interventions that we now turn.
4 A wage subsidy voucher allows the employer of the young person to claim back a portion of the wage that is paid
to the worker.
5 A process of outsourcing particular business processes (such as call centres or data analytics) to a third party. These
processes often involve high levels of engagement with information and communication technology, making young
people an attractive potential workforce.
18
Enhancing the employability of young work seekers
Given that most young people do not manage to access post-secondary education and training, and the
additional challenges they face in navigating the labour market discussed above, a key intervention is enhancing
the employability of young people. Employability refers to the skills and attributes that make young persons
more marketable in the workplace, and that may assist them to navigate the labour market and workplace
more eectively (Harvey 2001; Pegg et al. 2012). Such interventions may include learnerships, entrepreneurship
development programmes, youth service programmes, short-term skills development programmes, job search
and workplace readiness programmes. Such interventions could be run by the state, civil society and/or the
private sector (Graham and Mlatsheni, 2015).
An overview of youth employability interventions in South Africa
In 2013, as part of the preparatory phase of this study, 20 such programmes were purposively selected to gain
insight into their nature and viability for participation in the Siyakha study (Centre for Social Development
in Africa 2013b). Only programmes that met the initial criteria of the study were included; that is, they had
to include technical skills training, human capability training, and workplace experience as part of their
programme design. The study found that most of the programmes involved shorter-term classroom based
activities and longer-term work placement activities. At the time the review was conducted most of the
programmes had minimal interaction with potential employers. However, over the time of the study this has
shifted somewhat. A key feature of the programmes was that they were locally based, easily accessible to
young people and involved minimal costs to the young person. Most of these programmes are run through
civil society organisations. This ensures they are locally accessible. However, funding constraints limit the
potential to scale up these programmes. In contrast, programmes run through the state, such as the NYDA’s
YouthBuild programme, are well funded but often constrained by bureaucratic processes. Private sector run
programmes are often the most responsive to employer demands, more closely connected with employers
to facilitate exit opportunities, and are typically well-funded (through access to the skills development levy
(SDL)and the ETI as well as corporate spend), but may not be accessible to poor work seekers living far from
major work centres.
The review further considered questions of scale and sustainability. In terms of scale, it was clear that taking
the programme to scale was not an option for most of the programmes except some of the private and
government funded programmes, primarily due to limited funding and concerns about programme quality
if scaled up. Of those reviewed only seven programmes reached at least 200 young people per year and
only three reached more than 1 000 per year. In terms of sustainability, private sector programmes had good
19
SIYAKHA YOUTH ASSETS REPORT
nancial sustainability models because they could access public funding through the ETI and SDL and could
draw on their own internal investments and/or corporate social responsibility spending. In contrast, civil society
organisations spend signicant resources on trying to secure funding and rely on long-standing reputations
to maintain a funding stream. Although most of the programmes engaged in monitoring and evaluation
activities that tracked their progress against their stated objectives, most, albeit with some exceptions, had not
conducted an evaluation of their impact on employability and employment outcomes for their participants.
International review of evidence on employability programmes
The lack of evidence on the impact is not unique to South Africa. A current systematic overview notes that there
is very limited evidence about what programmes work to address youth unemployment. In their study Kluve
et al (2014) noted that of all the programmes they identied internationally, only 13% included an evaluation
that could assess impact. A further 36% had conducted process evaluations. They also point out that in South
Africa, and in Sub-Sahara Africa (SSA) more broadly, evidence about what types of employability programmes
(often also referred to as workforce development programmes) are feasible is limited (Kluve et al. 2014). While
a range of studies have been conducted (discussed below), few are able to demonstrate impact. Further,
only one systematic review (Cho and Honorati 2013) on the impacts of entrepreneurship programmes was
conducted. A CSDA overview in partnership with the Poverty and Inequality Initiative (PII) at the University of
Cape Town (UCT) on evidence of youth unemployment interventions since 1990 is in process (De Lannoy and
Graham 2015; Graham, Patel, Baldry and Williams, forthcoming).
Despite the limited evidence on the impact of programmes, a few studies have sought to understand the
nature and outcomes of employability interventions. Across the literature reviewed, many studies suggest
that participation in youth workforce development programmes in Latin American countries such as
Argentina, Mexico and Colombia and other developing countries such as Liberia are positively associated with
employment and earnings (Aedo and Nunez 2004; Betcherman et al. 2007; Attanasio, Kugler, and Meghir
2008; Monk, Sandefur, and Teal 2008). Programme participants were also found to be more likely than non-
participants to nd formal employment and to experience increase in wages over time (Attanasio, Kugler,
and Meghir 2008; Christopher Blattman, Fiala, and Martinez 2008; Ibarrarán and Shady 2009; Christopher
Blattman, Fiala, and Martinez 2013). However, none of the studies are able to attribute the associations they
demonstrate to the programmes they assessed.
There is also contestation over whether workforce development programmes are more eective than
entrepreneurship programmes. While Card, Kluve and Weber (2010) claim that programmes that combine
apprenticeship, classroom vocational skills training, life and work-readiness skills, training vouchers, and job
matching tend to be more eective in inuencing employment than entrepreneurship programmes, Cho and
Honorati (2013) found that the balance of evidence suggests that entrepreneurship programmes are in fact
more eective in employment outcomes than other types of programmes. The evidence on outcomes is
therefore mixed.
Early evidence from the international systematic review on youth employability programmes (Puerto, Kluve,
and Rother 2016) notes some points of relative consensus across the evaluation studies reviewed. The
systematic review assessed impact in terms of employment and/or earnings outcomes. They note rstly, that
skills training programmes are modestly eective in the short-term, but that they seem to have long-term
positive outcomes. These outcomes include increased earnings and an ability to retain work. Secondly, job
search assistance programmes tend to be very eective in the short-term and are one of the most cost-
eective types of interventions. Thirdly, programmes that involve employers show far more impact than those
that do not. This is a point that was also found to be critical in the OECD Local Economic and Employment
Development (LEED) research programme – employer involvement is a critical success factor in programmes
(Barr 2016). Lastly, success seems to be related to a comprehensive approach. That is, programmes that
combined skills training, with job search assistance and matching were more likely to succeed than those
that focused only on one element. Again, this nding is conrmed by the LEED study, which notes that a key
success element is training young people comprehensively to equip them with a wide range of skills rather
than narrowly focused technical skills (Barr, 2016).
Compared with employment and income-related outcomes, fewer studies have evaluated the eects of
workforce development programmes on more proximal outcomes such as work-readiness skills, life skills and
re-enrolment in higher education or other training programmes. Nonetheless, some evidence, predominantly
from Europe and the United States of America but also including a few cases in Latin America, suggests
that workforce development programmes, including training, service, and entrepreneurship programmes,
are associated with positive outcomes such as acquisition of business-related skills (e.g., business planning,
marketing, and nancial management), cognitive skills (e.g., dierentiating needs versus wants, decision-
making), emotional coping skills (e.g., higher self-condence and self-esteem), positive time use (e.g. spending
more time enhancing, practicing and learning skills), and other life skills (e.g., positive work ethic, nancial
literacy) (Eberly and Sherraden 1990; Flanagan et al. 1998; Funk 1998; Perry and Katula 2001; Murray and
McKague 2010; Whalen 2010; Blattman and Annan 2011). However, little is known about whether the observed
eects on work-readiness and life skills are applicable across dierent sub-populations of youth (e.g., low-
income youth, out-of-school youth, and youth from rural areas).
Some programmes have also been shown to positively impact other economic activities of youth. We may
refer to these as multiplier eects. For instance, the systematic review of entrepreneurship programmes shows
20
that they increase saving and borrowing activities among youth
(Cho and Honorati 2013). In Liberia they were found to positively
inuence the accumulation of assets, particularly household
durable assets (Blattman and Annan 2011). The positive impact of
workforce strategies on asset ownership suggests that programme
participation contributes to higher income or prots, which in turn,
allows youth to invest prots in durable goods that may improve
quality of life, act as non-cash form of savings, and buer against
future income and economic shocks.
Gaps in knowledge and research on youth
employability programmes
Critical gaps in knowledge remains in youth employability
programmes. For instance, there remains limited evidence on the
impact of such programmes on employment and earnings outcomes,
particularly in the South African context. Further, the evidence
seems to coalesce and suggest that critical skills factors (such as
employer involvement and comprehensive training) are pertinent
in the OECD countries (Puerto, Kluve and Rother, 2016; Barr, 2016).
These remain untested in the South African context. Also unclear
is the extent to which the longer-term outcomes identied are as
a result of the interventions, or simply a matter of young people
maturing into the workforce.
Most workforce programmes combine several components, and
while evidence suggests that a combination of these programmes
is eective in improving employment and earning capacity of
young people (Puerto, Kluve and Rother, 2016), little is known
about the optimal mix of components or activities required for
success. Similarly, it may be that activities designed for dierent
subpopulations of youth in various contexts would work best in
achieving a pre-determined set of relevant outcomes.
Given that the youth populations between and within countries are heterogeneous, it is important to examine
what combination of components or activities are relevant and work best for specic segments of the youth
population. What works for urban youth may not always work for rural youth. Gender-specic challenges
to youth employment indicate that young men and women may require dierent sets of skills and training.
Variation in cultural, social, economic, educational, and geographic contexts localises employment barriers faced
by youth, and workforce programmes should include activities that would address or alleviate such barriers.
Life skills and work-readiness skills have become a regular component of youth workforce development
strategies. However, the denition of life and work-readiness skills varies between programmes. In addition,
the specic links between these skills and employment and increased income have not always been clearly
dened. Current research provides little guidance on what set of skills, particularly life skills, are most benecial
for youth to gain employment and improve earnings.
Although there have been numerous workforce programmes for youth in SSA and other developing regions, few
programmes have been implemented at scale and have been found to be sustainable. Key questions include:
(a) how to maintain intervention delity when programmes are expanded to larger groups of youth; (b) what
components of intervention should be scaled up; (c) what youth perspectives on these programmes are; and
(d) how much would programmes cost when implemented on a larger scale and over time. Similarly, future
programmes should explore potential partners (public or private) beyond the initial project implementation to
sustain the programme and promote local ownership.
Many evaluation studies tend to focus mostly on employment and earnings. However, future research should
also examine the potential impact of workforce programmes on other outcomes such as health and health
risk behaviours, future orientation, resilience in work-seeking, food security, savings and asset ownership,
nancial capability, peer quality, family relations, and social support and cohesion. To date, fewer evaluation
studies have attempted to examine the impact of workforce development programmes on youth’s sexual and
reproductive health behaviours, psychosocial and mental health (e.g., depression, stress, anxiety), and social
life (e.g., various types of community participation, family relations, social support, residential stability).
Financial assets as a mechanism to activate employability?
Interestingly, a factor that has largely been missing from design of employability programmes, and therefore
from most evaluations, is an assessment of how income can shape employability, employment, and earnings
outcomes. Often income is seen as an outcome of programmes. However, it has not been conceptualised as an
input. This is despite ample evidence showing that the costs of work-seeking severely hamper young people’s
chances of nding work and accessing post-secondary education and training (Seekings 2010; Branson and
Khan 2016).
21
SIYAKHA YOUTH ASSETS REPORT
Income for the poor has largely been assessed in the social protection, specically cash transfers literature.
Within this literature there is recognition that approaches to addressing poverty have largely focused on
mechanisms that ensure a basic income level for the poor, often through the provision of grants or goods that
ensure a minimum level of living is met. Common to almost all conceptualisations of welfare policy therefore is
its contribution to consumption-smoothing – the provision of a level of income which would enable households
to maintain a previously dened level of immediate consumption to satisfy basic needs. In many countries,
including South Africa, large numbers of poor people derive a signicant proportion of their earnings from
grants disbursed by the state. This focus on income, however, is argued by Sherraden to be a factor which has
“sustained the weak without making them strong” (1991) and thus he advocates interventions that build the
assets of the poor. Assets, he argues, could go some way towards strengthening poor households. In this way
social protection mechanisms in various forms may be both protective and transformative (Sabates-Wheeler
and Devereux 2008).
We view nancial asset interventions such as savings and nancial education as one amongst other interventions
aimed at promoting human development outcomes. In line with the social development approach discussed
below (Patel 2015), we assume that a combination of interventions that include nancial assets development
(alongside for instance human capability development) are most likely to result in positive outcomes. Financial
assets are however an essential component of human capability interventions.
Ownership of assets can also reduce the volatility of earnings when earnings are derived solely from labour
income, and/or when this income is low (Banerjee and Duo 2007). It is also associated with changes in the
way in which people perceive their futures. Stimulating the development of nancial assets can make the
path to further education seem more ‘open’, or more achievable, and hence bring about more future-oriented
and positive behaviour (Destin and Oyserman 2009). In addition, nancial assets were found to raise parents’
expectations for their children (Elliott and Sherraden 2013), and thereby increase the likelihood that they will
take steps to save for their children’s future education. Moreover, ownership of savings accounts has been found
to be a signicant predictor of college enrolment and progress in the United States (Elliott and Friedline 2013).
Applying the theory of asset building to young people is a more recent endeavour. If people save when they
are young, they are more likely to save later in their lives (Friedline, Elliott, and Chowa 2013). Similar ndings are
outlined by Elliott and Friedline (2013) who found that when savings accounts were owned as children, young
adults are twice as likely to own savings accounts, twice as likely to own credit cards, four times as likely to own
stocks, and have signicantly more total assets, both nancial and non-nancial. Furthermore, the earnings owing
from the ownership of nancial assets compound over time with larger assets also providing higher earnings.
Savings are also associated with a greater sense of control amongst
young people. When the young own their own nancial assets, they
could feel a greater sense of control over their own lives (Elliott, Destin,
and Friedline 2011). It was also found to enable the development of
resilience and self-ecacy, which are strong predictors of academic
performance and progress through college in the United States (Elliot,
Constance-Huggins, and Song 2011; Elliott and Sherraden 2013).
More recently, research attention has been paid to how savings might
aect employability outcomes. In a four-country study on youth
savings, conducted in Ghana, Nepal, Colombia and Kenya, research
shows that young people who are saving are often doing so to pursue
further education (Johnson et al. 2013). Research in various countries in
Africa including Uganda, Kenya and Ghana demonstrates that savings
behaviour is associated with better school achievements (Chowa,
Ansong, and Masa 2010). In Ghana, nancial assets of the household
are strongly associated with better school outcomes (Chowa et al.
2013), but this is in turn mediated by higher educational expectations
that young people from households with more household assets have
(Ansong, Chowa, and Sherraden 2015). Higher educational expectations
and achievement may in turn result in better employability outcomes.
The eld of nancial capability has received a great deal of research
attention, with rigorous studies demonstrating positive eects. What is
less known is how particular environments – cultural and social – shape
the development of nancial capabilities. It is argued, for instance,
that in South Africa young people face a great deal of pressure to buy
into consumerist values, which may undermine their desire to save.
In addition, household responsibilities and whether a young person
is a parent or not may strongly shape their ability to save. Research
is required to better understand the youth savings culture in South
Africa and what kinds of nancial products are likely to appeal to
young people. Research on stokvels6 suggests that few young people
6 Community-based peer savings groups
22
are members (Centre for Social Development in Africa 2013a). Young people’s savings culture might be a local
contextual factor that may constrain savings outcomes.
Most important, rarely have studies looked at the combined eects of youth employability programmes and
nancial capability programmes. Little attention has been paid to whether nancial capabilities and assets
oer a way of enhancing young people’s employability or not.
The above suggests that nancial asset accumulation seems to enhance other human and social assets,
including the assets that may enable young people to take further steps towards employment or sustainable
livelihoods. In addition, savings are strongly associated with access to further and higher education – a
signicant predictor of later employment and earnings.
The evidence presented in the above sections demonstrates the gaps in our knowledge on youth employability
interventions, and areas of promise that emerge from studies conducted elsewhere – both in relation to
employability programme design and nancial capability inputs. This evidence provides the basis for the
theory of change that was developed for this study (discussed in section 2.5 below). But before outlining the
theory of change, we rst consider the theoretical approach guiding the study.
2.4. A youth development approach to understanding
pathways to the labour market
Many youth interventions approach young people from a remedial approach, starting with a focus on their
decits, and not prioritising their agency. For instance, programmes are often conceptualised to address young
people’s skills deciencies or lack of workplace and job search awareness. While we acknowledge the gaps in
young people’s skills (discussed above) we take a youth development approach to youth employability that
begins with an assumption that young people have agency and capabilities – in the form of some education,
energy, high hopes for themselves, a sense of self-ecacy and determination. Starting with this assumption
we argue that employability interventions that harness and channel the capabilities of young people could
support and enable them to make a smoother transition to work.
A youth development approach to employability is rooted in Sen’s capabilities approach (1999). For Sen
(1999), “development can be seen […] as a process of expanding the real freedoms that people enjoy”
(1999: 3). Thus, rather than seeing development as a measure of income outcomes only (or in the case of
employability as employment and earnings outcomes), Sen advocates a much more human-centred view of
development. This view insists on creating the circumstances under which people can be free agents in their
own lives. Thus freedom is a means to development. However, Sen is insistent that freedom is also an end in
itself and thus becomes a “constitutive part of development” (1999: 4). Freedom in this context is understood
as being a state in which people are able to fully realise their capabilities. This is in contradiction of a state of
‘unfreedom’, which limits the ability of individuals to pursue their capabilities. Freedoms are therefore essential
in that if they are present, individuals can use their agency, access opportunities and pursue their capabilities,
thereby fostering development. Freedom is thus a means to development and a developmental end. Thus,
a youth development approach that follows Sen (1999) leans towards a more human-centred approach to
development theory, policy and practice. Its contention is that under the right circumstances of freedom,
young people are capable of and have the assets and capabilities to pursue opportunities and improve their
life chances. Applying the capabilities approach to youth development is useful as it draws our attention to
young people’s capabilities and the choices and freedoms they wish to pursue. Often, youth are dened in
ways that serve to marginalise them from mainstream society.
According to Patel (2009) youth development is conceptualised in at least three ways. The rst is development
as it is conceptualised in the life course; that is physical, emotional and social maturation of young people. This
is a perspective on youth that is often used in developmental psychology. The second conception of youth
development is practice-oriented and refers to programmes and youth work that is focused on enhancing
youth’s developmental outcomes. The third conception of youth is understood to be a theoretical approach
that is embedded in the capabilities approach and which takes as its starting point young people themselves
and what they actually want to be and are able to do (Nussbaum 2001). Such an approach is therefore youth-
centred and requires researchers and those working in the eld of youth development to embrace at least
three key assumptions: (1) that young people have strengths, assets as well as resilience that can be built upon;
(2) that we need to create spaces in which young people’s voices are heard; and (3) that we work alongside
young people towards their social inclusion and greater participation in society in the present as well as for the
future good. Furlong (2009, 1) notes that thinking in the eld of youth studies has gone some way to embrace
this shift in thinking, focusing increasingly on individual agency and the ability of young people to shape their
biographies, while still acknowledging that structural impediments do shape their ability to make choices.
Applying a capabilities lens to youth (un)employment is crucial as work is viewed as a key capability. Work is
not simply about material well-being, although this is a central aspect of the capabilities approach (Sen 1999;
Nussbaum 2001). Work is also about being able to have control over one’s environment; exercising practical
reasoning; and entering into meaningful relationshipscon or mutual recognition with other workers as key
capabilities (Nussbaum 2001). Work (whether in the formal or informal sector) is therefore a fundamental
aspect of capability and freedom as it addresses various aspects of the human condition.
23
SIYAKHA YOUTH ASSETS REPORT
A youth development approach to young people shifts our practice orientation away from dealing with
problems after they have occurred towards implementing policies and programmes that work to enhance
the agency and capabilities of young people. Such an approach is promotive and preventative. Applied to
employability, it shifts the question from “how do we address youth unemployment?” towards “how do we
support young people to make a smoother transition to the labour market?” It asks us to consider not just the
young person’s labour market related skills and potential, but to work with a young person in a holistic fashion
– connecting with their interests, agency, and dreams; emphasising their talent and energy; and supporting
them to overcome any personal, household and structural barriers they face.
A youth development approach that is rooted in the capabilities framework aligns well with the social
development approach to policy and practice. The social development approach (Patel 2015), rooted in a human
rights framework, advocates for interventions that enhance the wellbeing outcomes of people. In this way it
departs from approaches that focus only on economic outcomes or only on social outcomes. It argues rather
that interventions that seek to address both social and economic needs of people are critical to enhancing
people’s wellbeing. A key tenet of the social development approach is the promotion of greater participation
of people in their communities and societies, both for their own benet (as a freedom that is important in and
of itself in Sen’s terms) and because greater participation may contribute to better development outcomes in
communities. Applied to work, a key tenet enshrined in the South African Constitution is to free the potential of
each person and improve the quality of life of all. Work is a central aspect of inclusion, growth and the freeing
of each individual’s potential. In India, the right to work is recognised through the employment guarantee
scheme where every adult is guaranteed work for 100 days of the year.
The social development model is a pluralistic one, noting that the state, private sector and civil society all have
unique strengths, positionalities in society and access to dierent resources, that when combined can bring
about better outcomes in society. Finally, the social development approach promotes bridging the divide
between micro and macro-level policies and interventions, to ensure that all available interventions (policy and
programmatic) work to enhance the wellbeing of people and society more broadly.
Applying the social development approach to youth and employability provides the theoretical backdrop for
the theory of change presented below. As mentioned above, our starting point is to view young people as
active agents that have assets and capabilities to work with and that any intervention should seek to enhance
opportunities for them to participate and activate those assets and capabilities, both within the intervention and
as an outcome vis-à-vis greater participation in the labour market. As is demonstrated in the theory of change
below a key feature of the social development approach when applied to employability is a consideration of the
connection between both social and economic interventions. In this study we are testing the combination of
human capital development interventions and nancial capability interventions. Further we are interested in both
social and economic outcomes – whether such interventions strengthen the social, personal and nancial assets
of individuals. Further, the approach leads us to think about the assets that institutions across sectors bring to
the youth employability question. For instance, non-governmental organisations are well placed to reach young
people at the local level. The state often has the resources needed to support such programmes and can also
intervene to enhance demand for young workers in the labour market. Private companies are viewed as partners
as they are the primary employers. Applying pluralism to youth employability means activating partnerships
that synergise the strengths of all sectors. Finally, a social development approach to youth employability seeks
to consider how micro and macro-level interventions can work in a complementary way to enhance social
outcomes. For instance, how can local employability programmes be scaled through macro-level policies such
as public employment programmes, labour activation strategies or social protection mechanisms?
The social development approach is a normative one and shapes current social welfare policies in South
Africa. There are however signicant gaps in the implementation of welfare, education, health, employment
and economic development policies that have impacted negatively on the social and labour market inclusion
of young people (Patel 2015). Systemic failures in social provision and in the educational system were alluded
to previously which in turn aects young’s people’s future employment prospects.
Having considered the broad theoretical basis for the study we now turn to explaining the theory of change
that emerged from both the theoretical approach and our analysis of employability programmes that were
operating in the country at the time of planning for the study.
2.5. Conceptualising pathways to the labour market for
youth – a theory of change
Increasingly worldwide there has been the recognition that young people are entering the labour market later
in life (Furlong et al. 2003; Furlong and Cartmel 2007). This has in part to do with changing patterns in the
labour market in post-industrial societies. Technology-led growth requires higher levels of skills. As a result
more young people are entering higher or further education and staying for more years in post-secondary
education and training (Arnett 2004). In addition, jobs are being eroded by technology as machines replace
workers, resulting in a need to reconceptualise work. The drive for global competitiveness has resulted in a
demand for highly skilled labour. But almost half of the young population in the age group which is the target
of this study have not completed secondary schooling, thus limiting their employability. The changed global
and national situation has resulted in young people not only facing a protracted period of transition to work,
but also an uncertain future with a high possibility of chronic unemployment (Chen 2012).
24
The term “pathways” to employability refers to the social structures and institutions facilitating school-to-work
passages, as well as the plans and decisions of young people in navigating these passages (Heinz 2009). Heinz
(2009) has noted that such pathways have become more extended as the connections between dierent
institutions and the labour market become more complex. In addition, with changes in the global labour
market these pathways become more precarious. Heinz (2009) thus argues that current institutions intended
to facilitate transitions or to provide pathways to employment are not adapted to the changing global labour
market, nor are they suited to preparing young people for economic downturns and rising skills requirements
of the labour market.
Further, as demonstrated above, these challenges tend to impact young people in ways that reinforce social
inequality. While young people from non-poor households are likely to be able to travel along conventional
pathways from school into further or higher education, for those from poor households, these pathways
to work are likely to be inaccessible or precarious for many of the reasons already mentioned. Traditional
pathways to livelihoods such as access to communal land and the accumulation of livestock as assets, were
largely disrupted as people were disposed of their assets and rights to land under colonial and apartheid
rule (UN Habitat 2010). Further disruptions occurred as African people migrated to urban areas in search of
employment leading to a loss of assets in rural areas.
Against this backdrop, what might pathways to employability look like for young people who are not able to
access the conventional pathways from school to education and work? Part of the answer lies in expanding
access to further and higher education. But in the absence of such seamless and structured pathways to
employment, new and dierent employment opportunities and interventions are needed to support young
people to make the transition into labour markets (Heinz, 2009). There is therefore room for alternative
interventions in the form of youth employability programmes that might act as stepping stones for young
people to eectively transition to employment. Drawing on the evidence on youth employability programmes,
theoretical insights on youth transitions, individual capabilities and the structural changes in the global and
local economy discussed thus far, we devised a conceptual framework that synthesises these ideas.
The Siyakha Youth Assets research project can be conceptualised graphically as follows:
Cluster 1: Young
person’s assets
• Numeracy potential
and learning
• Literacy potential
and learning
• Creativity and
innovation
• Household
relationships/ social
capital/ support
• Level of condence
• Level of leadership
• Willingness to learn
• Initiative
• Educational
qualication
Demographic
characteristics
• Age
• Gender
• Race
• Geographical
location
• Socio-economic
status
• Parental and marital
status
Cluster 2:
Employability
programme inputs
• Human capability
skills development
• Technical skills
development
• Job preparedness
skills training
• Assistance with job
-seeking
• Practical experience
• Stipends
• Exit opportunities
Financial capability
inputs
• Financial education/
literacy
• Access to nancial
assets/product
Cluster 3: Individual
level mediating
variables
• Future orientation
• Expectations &
aspirations
• Self-esteem
• Competence (self-
ecacy)
• Connectedness
(social networks)
• Financial literacy
• Financial capability
• Savings
Design features of
programme
• Length of
programme
programme content
• Combination of
programme elements
• Adherence
• Class size
• Inclusion of stipends
Cluster 4:
Primary outcomes
(short-term)
• Enhanced
employability
{ Technical skills
{ Job preparedness
{ Increased job
search & job
search resilience
{ Life skills
{ Knowledge of how
to apply skills
{ Work experience
Secondary outcomes
(long-term)
• Employment
• Retention in
employment
• Earnings
• Self-employment
• Access to further
education or training
INDIVIDUAL
PARTICIPANT INTERVENTION INTERMEDIATE SHORT & LONG-TERM
OUTCOMES
Figure 3: Conceptualising pathways to youth employability and employment
Four clusters of variables are crucial to the outcomes to be achieved by the Siyakha project. Drawing on the
work of positive youth development theorists (Catalano et al. 2002; Pittman et al. 2003) and the capabilities
approach (Sen 1999), on the left side of the diagram is cluster 1 which consists of background variables such as
the individual assets that young people may have at the point at which they are ready to transition out of the
schooling system and begin taking steps towards employment. In addition, demographic and socio-economic
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SIYAKHA YOUTH ASSETS REPORT
characteristics including their age, gender, race and socio-economic status amongst others are also pertinent
to whether they will eectively transition to work. For instance, many middle-class young people will leave
school and enter immediately into further education or training programmes that will place them in good
stead to nd work. Those without access to the nancial assets to access such institutions will not be able to
take such a step smoothly. Thus, for some there may be a more direct pathway to further education and/or
employment, while for others intermediary organisations are necessary to enable them to take those steps.
Cluster 2 consists of the intervention programme that will be delivered by the implementing partners in the
Siyakha project. Here, based on evidence from other parts of Africa and internationally (Attanasio et al, 2008;
Blattman et al, 2011; Cho and Honorati, 2013; Cho et al, 2012), we assume that programmes aimed at enhancing
young people’s employability play a crucial role in assisting them along the pathway to employment. Such
programmes may take dierent forms and could include all or some of the listed inputs in the diagram.
Cluster 2 also accounts for the programme inputs in the form of nancial capabilities. Based on evidence
from developing country contexts and elsewhere (Elliot, Constance-Huggins and Song 2011; Chowa, Masa, and
Sherraden 2012; Chowa et al. 2013; Elliott and Sherraden 2013), the assumption informing this addition is that
access to nancial assets (in the form of nancial literacy, nancial products and savings) assists young people
to transition more eectively to further education and training as well as work.
The third cluster consists of a set of variables that may mediate the outcomes. Mediating variables are those
individual level characteristics and the programme design features that are hypothesised to be the mechanism
promoting the cluster 4 outcomes. These variables are based on the recognition that human agency might
play an important role in mediating how young people might use the programme inputs. Individual factors, as
well as the ways in which programme inputs might shape these individual factors or combination of factors
may inuence the outcomes achieved. These include psychosocial outcomes such as a sense of future, self-
ecacy and self-condence (Catalano et al. 2002; Catalano et al. 2004). In addition to these individual
factors, programme design features e.g. the length of the intervention may also inuence the outcomes.
Finally, in cluster 4, the primary and secondary outcomes that will be assessed are identied. Employability
is dened as individual characteristics that are attractive to potential employers and are considered to be
predictors of success in the workplace (Pegg et al. 2012). These include acquisition of human capability
skills, job preparedness skills, technical skills, and enhanced knowledge of for instance numeracy and literacy.
Employability outcomes are referred to as primary outcomes in this study and may be evident in the course
of programme participation (short-term outcomes). Longer-term outcomes (actual employment, access to
further education and training, securing of a sustainable livelihood possibly in the form of self-employment,
and earnings) are referred to as secondary outcomes in this study and are likely to only be realised after
programme participation.
2.6. Conclusion
The South African youth unemployment landscape is complex and multi-faceted. It is driven by global trends
in economic competitiveness as well as the changing nature of work as machinery increasingly replaces
labour. It is also shaped by national factors including the chosen economic growth path, with its cost of
low labour absorption, labour market regulations that tend to aect youth negatively, and inequalities in
education, location, social capital, and income; which in turn constrain access to the labour market, particularly
for poor youth. The complexity of the issue points to the fact that a multiplicity of interventions is required. The
conceptual framework sets out the theory of change that informs the study including the envisaged outcomes
that will be evaluated. The next chapter sets out the design and the method of the study.
26
3. METHODOLOGY
3.1. Introduction
The study aim is to test the outcomes of youth employability programmes both on their own and in combination
with a nancial capability intervention. The study thus required a comparative element – between groups
and over time – and a randomisation element – to ensure that no other explanations for the relationships
between participation in the intervention and observed outcomes are plausible. The randomisation aspect
was used to determine dierences between those participants receiving the nancial capability intervention
(the treatment group) and those that did not (the control group). In addition, we dened each programme
according to a set of programme methods and will be able to test whether dierent programme aspects
contributed to any changes observed.
As mentioned above, the inspiration for the study came from an awareness of the innovation of organisations
running youth employability programmes and an interest in assessing the eects of what was already being
rolled out. A key element of the research design therefore was to reasonably compare a wide range of
programme oerings and assess their eects.
This section outlines the nature of the youth employability programmes, the research design, methodology,
sampling and implementation of the study.
3.2. Implementing partners
The implementing partners were recruited in 2013. Two implementing partners (loveLife and NYDA) attended
a Round Table discussion in October 2012 at which the concept for the study was discussed. Both agreed to
participate. From there the study team began investigating what other youth employability programmes were in
existence and interviewed programme managers to assess whether the programmes met the inclusion criteria
(discussed below). If they did they were approached to participate in the study. Benets to the implementing
partners included an independent evaluation of their programme as well as access to the nancial education
module and materials to roll out as they saw t once the baseline and endpoint data collection was completed.
Eight implementing partners were included in the study. Although the implementing partners delivered a wide
range of intervention types there had to be some similarities to ensure there was an element of comparability.
All of the interventions had to:
• Oer workplace human capability skills training (skills that are pertinent to the general work environment
e.g. self-esteem, leadership, communication skills)7.
• Oer technical skills training (skills that are pertinent to particular job types e.g. welding, call centre skills).
• Oer some kind of workplace experience (simulated or on-the-job).
• Include participants between the ages of 18 and 25 years who are not in education, training or employment.
• Run the same programme at more than one site.
Initially we also had time limitations on the programme length as part of the inclusion criteria. Programmes
were intended to run for longer than six weeks but not more than one year. The lower limit was eventually
discarded as it became evident that more programmes were converting to shorter programme times. One
of the objectives of the study is to assess whether these shorter programmes deliver the same or dierent
outcomes than the longer ones.
Programme descriptions
Despite the similarities in the programmes discussed above, the eight partners represent varying youth
employability interventions in terms of reach, type of technical skills, length of programme and type of
workplace experience.
In terms of reach, Harambee engages with the largest number of young people annually through their various
programme oerings – from one day assessments through to full bridging programmes. Only two of the bridging
programmes were included in our study. Harambee assesses 100000 individuals per year and approximately
9200 participate in their various bridging programmes. The other programmes reach comparatively fewer
participants, but are also longer in duration than Harambee’s programmes. loveLife reaches approximately
1200 groundBREAKERS who participate in a year-long programme. NYDA YouthBuild – also a year-long
programme – reaches 500 youth. The other programmes range from 12 weeks to six months in duration and
reach between 100 and 500 young people per year. In combination the programmes put approximately 12500
participants through skills training each year.
Most of the organisations had sites in at least two provinces (Gauteng and the Western Cape) with the only
exception being Thabiso Skills Institute which runs in Gauteng only. loveLife groundBREAKERS was the
largest programme with operations in all nine provinces. The NYDA and EOH have sites in three provinces.
Harambee also has sites in multiple provinces although we could only include their Gauteng sites in the study
for logistical reasons.
7 Sometimes referred to as soft or life skills
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SIYAKHA YOUTH ASSETS REPORT
The programmes represent the value of pluralism in social development with organisations from various
sectors rolling out programmes. EOH was the only private sector partner but Harambee has close associations
with private sector clients who use their services. The NYDA was the only national government partner. Their
programme is rolled our primarily through local municipalities. The remaining partners were civil society
organisations. The organisations are funded through a combination of state funding (such as the Jobs Fund,
national government department budgets, local municipal budgets), private sector funding (such as Corporate
Social Investment spending and Human Resource expenditure), and philanthropic disbursements. Together
they represent a signicant investment into addressing the issue of youth unemployment.
The programmes train young people for dierent sectors of the economy. Some such as NYDA YouthBuild and
TSI, trained young people in artisanal work such as welding and construction. Others, such as Harambee, ATS
and EOH, were training for oce work in the business process outsourcing, information and communication
technology, and nancial services sectors. Harambee also trained youth for the retail and hospitality sector.
Only loveLife trained youth for the social sector, and Raymond Ackerman Academy was unique in its
entrepreneurship focus.
The programmes had dierent ways of providing youth with workplace or practical experience. Harambee
and ATS ensure that their training simulates the workplace. Workshops for artisanal training ensure that TSI
participants have practical experience of the tools and methods they will be required to use. EOH oers work
placements with supervisor support to participants. NYDA YouthBuild and loveLife expect participants to
engage in a year of service to their communities in order to develop workplace experience.
Some of the programmes oered stipends to participants. For Harambee participants this was a small amount
that covered their transport costs during training. loveLife and YouthBuild participants receive a stipend for
the duration of their service amounting to between R1500 and R2000 per month. The highest value stipends
were for EOH participants who received around R5000 per month8.
Exit opportunities also varied across programmes. For programmes like Harambee, EOH and ATS, exit
opportunities form part of the programme design, with participants being recruited based on client9
requirements. Others provide support after the completion of the programme but do not directly connect
youth with employers. For example FFLFFW provides ongoing mentorship support and access to their
computer facilities. loveLife will send job opportunities to their alumni network and encourage them to apply.
In sum, the programmes represent a wide spectrum of the kinds of interventions that are being delivered
to enhance youth employability. Programmes range from one week to one year, include a combination of
classroom and workplace-based training, and have varying exit opportunities for participants. This means
that we are able to isolate programme features (e.g. length of programme, ratio of classroom to workplace
based training, exit opportunities) and assess which features seem to deliver better impact (e.g. are shorter or
longer-term programmes more successful?).
3.3. Research Design
Experimental research design
In the Siyakha study we used a cluster randomised, experimental design. In the study we have one pre-test
and three post-tests, which will allow us to test the immediate and longer-term outcomes of the programmes
and to assess whether the nancial capability intervention had any eect on the participants’ employability,
nancial assets, nancial knowledge, employment, and other related outcomes. The longitudinal design is
shown in Figure 4 below.
Assessment
as participants
enter the
programme
(pre-test)
Assessment as
participants exit
the programme
(post-test 1)
9 months after
completing the
programme
(post-test 2)
18 months after
completing the
programme
(post-test 3)
Programme
roll-out
Figure 4: Diagram of longitudinal design
Experimental designs allow us to make causal inferences because they a) assess whether changes occurred
over the period of the intervention; b) establish associations between participation in the programmes on their
own (control) and with the nancial intervention (treatment); and c) use random assignment to ensure that
no other explanations for the relationships between participation in the intervention and observed outcomes
may be plausible. Randomised studies are considered to be the gold standard of studies establishing causal
8 EOH stipends were dependent on participants’ qualications and the type of work they were doing as part of their
workplace experience.
9 Clients refer to employer partners seeking young employees.
28
linkages because they reduce the plausibility of alternative explanations for observed eects (Shadish, Cook
and Campbell 2002).
Although we describe the methodology for the full study, in this report we present only the ndings from the
baseline assessment, providing primarily descriptive statistics on the sample, along with some bivariate analysis
to test whether there are any dierences in the sample that can be explained by the geographical location of
the participants, their gender, and whether they are older (older than 25 years) or younger (18 – 25 years old)
youth. Statistical signicance is tested at the p=0.05 level. An impact report will include comprehensive results
on the eects of the nancial capability input as well as on the relative eects of the programme types.
Randomisation
In the study randomisation was done at the cluster level. That is, we assigned clusters (instead of individuals)
to either treatment or control conditions. In the Siyakha study, the clusters were the training sites of each
implementing partner organization. Forty-eight clusters were included in the study. Half of the clusters
(24 sites) were randomly assigned to the treatment condition, and the other half (24 sites) were randomly
assigned to the control condition10. A trainer from each treatment site was trained on the nancial capability
curriculum during a one-week training session. Each treatment site was provided with the nancial capability
module materials and Standard Bank South Africa (SBSA) was present to open savings accounts at these
sites. Control sites were not provided with any of the above and treatment site trainers were advised not to
divulge information to their colleagues working at control sites (most had limited if any contact with trainers
at other sites).
We relied on randomisation at the cluster (site) level for three reasons. First, the intervention in Siyakha was
inherently group-based and delivered in a classroom-like setting at each training site. Second, it was not
practical to isolate each youth within a site to receive a dierent intervention, because resentful demoralization
or diusion (cross-contamination) of treatment might result. In other words, in the Siyakha case, concern for
the scientic integrity of the study becomes an issue when cluster randomisation is not used. Third, youth
within the same training site might no longer be independent of each other because they were exposed to
common inuences at the training site level, in addition to the intervention. For example, youth within the same
site interacted with each other in and outside the classroom, had the same trainer, and had received treatment
at the same time of the day (e.g., training sessions were conducted at the same time for all participants from
the same training site). These interdependencies may contribute to violation of the statistical assumption
that observations are independent of one another which would limit our ability to attribute changes to the
treatment (Raudenbush and Bryk 2002).
We also had to ensure that randomisation took into consideration the dierent oerings that each programme
made. Within each programme we are fairly condent that the programme oering is the same (i.e. same type
of skills, length, curriculum etc.) and that the main dierence between treatment and control sites within each
programme is the delivery of the nancial capability intervention. For this reason we had to rst dierentiate
sites by programme and then ensure that there was an even spread of treatment and control sites within
each programme. For instance, we grouped all loveLife training sites together and then randomly assigned
loveLife training sites into either treatment or control condition. This ensured that there was an even spread of
treatment and control groups for each organisation, allowing us to control for programme dierences in the
assessment of treatment and control outcomes.
Table 1 below demonstrates the site level characteristics of the sample. It shows that there were two more
control sites than treatment sites11 but that treatment sites had on average, nine more participants than
control sites. Most of the sites were located in metropolitan areas (made up of metropolitan municipalities
and surrounding or peripheral urban areas) as opposed to non-metropolitan areas such as small towns and
rural areas. This is in part a reection of an urban bias in employment (some programmes specically target
areas where participants are more likely to nd work). However, it should also be noted that over two thirds
of youth reside in urban areas (Statistics South Africa 2016), which might also explain the reasons why the
programmes operate predominantly in urban areas. For further information about the sites and inclusion
criteria see APPENDIX 1.
n average no of
participants per site
Geographic location of sites
metro non-metro
Control 23 38.6 18 5
Treatment 21 49.4 16 5
Total 44 43.5 34 10
Table 1: Site level characteristics of the sample by treatment/control
10 Two treatment sites and one control did not run due to lack of participants, leaving us with 45 sites in the sample.
One control site was dropped as the client of the programme insisted on the nancial capability intervention being
implemented. This left a total of 44 sites.
11 Two of the treatment sites did not run as planned due to lack of participants.
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SIYAKHA YOUTH ASSETS REPORT
At each cluster or training site, we randomly selected youth to participate in the study by using the programme
enrolment list. That is, eldwork supervisors received the list of programme participants and a random number
grid. They used the random numbers generated to pick participants from the list.
Randomisation of youth within each cluster ensured that each participant had an equal chance of participating
and that volunteer bias was eliminated. The average number of youth per site was 43.5. The lowest number
of youth participants per site was 9 at a Thabiso Skills Institute site. The highest number of youth participants
per site was 93. These dierences are as a result of the dierent training programme types and methodologies
with Thabiso Skills Institute training welders in a small workshop setting and NYDA YouthBuild and loveLife
groundBREAKERS bringing together relatively large numbers of young people at particular points during the
programme for short periods of face-to-face training.
Table 2 presents results of the randomisation procedure at the individual level. It shows that the sample is
slightly weighted to the treatment group with 51% of the sample falling within treatment sites. There were no
dierences in the sex of the participants. The majority of the sample was African but the control group had
more Coloured participants than the treatment group.
Treatment Control
Mean age at baseline 22.9 23.6
Sex Male 39% 39%
Female 61% 61%
% with nancial or care responsibilities for at least one child 47% 53%
% that were CSG beneciaries whilst growing up 27% 22%
Mean self-esteem score (out of 40) 30 31
Mean future orientation score (out of 44) 32 32
Mean self-ecacy score (out of 40) 32.5 33.2
% that pursued formal post-secondary education 38% 48%
Average unemployment duration (months) 12.9 13.5
Perceived job application ecacy (out of 6) 4.2 4.3
Perceived interviewing ecacy (out of 6) 4.4 4.5
Entrepreneurial orientation (out of 6) 4.8 4.7
Perceived entrepreneurial ecacy (out of 6) 3.6 3.7
Table 2: Individual level characteristics of the sample by treatment/control
In sum, the random assignment process created a treatment and a control group that were broadly equal on
most observable characteristics. The only major dierence was in the percentage of participants who had
pursued formal post-secondary education and training. Other dierences were minor. All dierences will be
controlled for in the analysis of outcomes. By equating treatment and control groups before the intervention
begins, any observed dierences in outcomes between treatment and control groups can be condently
attributed to the intervention.
Longitudinal design
The longitudinal design of the Siyakha project is another advantage of the research design. Pre-test (or
baseline data collection after random assignment) and three post-tests provide evidence to examine whether
signicant dierences exist between treatment and control groups at several points. Post-test data has
already been collected for one point – immediately after the intervention ends (post-test 1). Data for post-
test 2 (nine months after the intervention) is being collected at the time of writing this report. Data at the
18 month post-completion point (post-test3) will also be collected in 2017. The three post-tests will examine
whether treatment gains are maintained or if they change over time. The longitudinal design will also allow us
to explore the validity of the conceptual framework. For instance, the intervention is hypothesised to inuence
acquisition of work-readiness skills and improve psychosocial outcomes and social connections in the shorter-
term, which in turn, contributes to employment and other positive outcomes in the longer-term.
3.4. Sample
The total number of youth interviewed at baseline was 1993. Of these most were from loveLife with Thabiso
Skills Institute having the fewest participants as is demonstrated in Table 3 below. This was the full sample
size. Of these participants from some sites were subsequently dropped from the randomisation process as
mentioned above. The total sample size of participants that is included in the random assignment is 1915. For
further information about the selection criteria used for individuals see APPENDIX 1.
30
Implementing partner Total n n random assign
NYDA YouthBuild 330 330
loveLife groundBREAKERS 729 729
Afrika Tikkun 289 289
Thabiso Skills Institute 37 22
Raymond Ackerman Academy 61 61
Harambee 194 194
EOH 282 219
Fit for Life, Fit for Work 71 71
Total 1993 1915
Table 3: Sample by implementing partner
3.5. Data collection
In the Siyakha study data was collected using a survey questionnaire completed by participants; monitoring
questionnaires completed by participants, the trainers and an independent observer; administrative records
(such as curriculum materials); and nancial transaction data received from SBSA. Details about each of these
are provided below.
Survey
Survey data was collected from participants as they entered the programme (within one week of commencing
the programme for longer-term programmes and within two days of commencing the programme for shorter-
term programmes); and as they exited the programme. In addition, at the time of writing this report, data
collection for nine months post completion of the programme was being collected.
Survey data included items measuring the following constructs: (a) youth demographics and family
characteristics, (b) income and asset ownership, (c) nancial capability, (d) household food security, (e)
psychosocial indicators (such as self-ecacy, perceived stress, and future orientation), (f) employment,
earnings, and job characteristics, (g) knowledge acquisition and skills development, (h) job-related and
entrepreneurial attitudes, (i) education and training, (j) social connection and mobility, and (k) health
perceptions and behaviours.
The questionnaires were completed in a facilitated self-completion process. Ideally we would have preferred
to collect data in a face-to-face closed ended interview format, but due to time limitations with the site
trainers we reverted to a facilitated self-completion process. Groups of 8 - 10 participants were paired with a
trained eldworker who worked through the questionnaire with the participants in a systematic way, assisting
participants with understanding the questions and skip patterns if necessary. The eldworkers checked the
completion of the questionnaire and were trained to identify where errors had been made so that these could
be rectied in the eldwork situation.
Trained eldwork supervisors were deployed to each site to conduct the random selection of participants
(where necessary), to oversee the smooth roll out of the survey process, and to conduct a quality check
on the questionnaires. Additional information about the recruitment and training of eldworkers, eldwork
supervisors and eldwork managers is provided in APPENDIX 1.
Once questionnaires were completed they were delivered to CSDA oces for a further round of checking
before being delivered to data capturers.
The same process was followed for endpoint data collection. However, at certain sites, site trainers or programme
managers failed to inform the research team of programme end dates. This necessitated a process of calling
participants to complete the questionnaires shortly after completing the programme through a telephonic
interview. In such instances we had quite a high attrition rate as many participants could no longer be traced
on the numbers they had provided. The total realised sample size at endpoint was 1183 participants.
Financial data
Anonymised nancial records were and continue to be provided by Standard Bank South Africa. This data
includes youth savings patterns and other nancial transactions. These data are collected using the partner
nancial institution’s electronic data monitoring system. Financial transactions include deposit and withdrawal
frequencies, interests and fees, and gross and net savings. Financial records will be provided on a quarterly
basis going forward as we assess the longer-term impacts of the intervention.
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SIYAKHA YOUTH ASSETS REPORT
Monitoring data
At each site we monitored at least two training sessions – one human capabilities session and one technical
skills session. At the treatment sites we also monitored one nancial education session. In certain instances the
research team was not informed of changes to the training roll out plan, meaning that we may have monitored
two human capabilities sessions and no technical skills sessions.
At each monitoring session an independent observer observed the session and completed a questionnaire.
The trainer was asked to self-evaluate the session, and 3-4 willing participants were asked to complete an
evaluation of the session.
Administrative data and materials
Administrative data was collected where necessary. Such data included the enrolment records (for purposes
of random selection), and numbers of participants not completing the programme. In addition, curriculum
materials were gathered, both to assess whether the programme should be included in the study and later
to assess compliance during the monitoring sessions. Administrative data regarding the programme roll-out
was also obtained through the key informant interviews conducted in the planning phase of the study. This
data was used to develop the programme typology dataset which included information regarding the length
of the programme, the ratio of classroom to workplace time, the nature of exit opportunities, and whether
participants received stipends during training or not.
Cluster level data
For each site, secondary data were collated and inserted into a site-level dataset (also containing variables
derived from monitoring sessions at each) in an attempt to describe local socioeconomic conditions at that
site. This was informed by the realisation that due to the very wide variation in site location, it would be
plausible to assume that geographic location may itself be a factor inuencing outcomes, particularly those
relating to employment. For example, it is conceivable that the likelihood of nding employment for a young
person living in the City of Johannesburg (where many of the training sites of this study are located) may
be considerably better than that for a young person living in Ratlou, a village in the North West province
(location of one of NYDA’s training sites), due to greater rates and intensity of economic activity in Gauteng.
Secondly, knowing more about local labour markets will allow us to compare employment rates of our sample
at the site-level with local employment rates, to assess whether the intervention, as well as going through a
youth employability programme, gives youth a better chance of being employed compared to the general
youth population living in the same area as them. Further information about the site level data is included in
APPENDIX 1.
3.6. Questionnaire development and pilot testing
The questionnaire sections were decided upon based on the conceptual model discussed above. For each
section the research team rst attempted to identify suitable standardised scales and question sets. The
advantage of using such scales is that they enhance the validity of the instrument. Where such scales were not
available questions were developed by the research team. The full questionnaire was then reviewed by experts
from key elds of study and their feedback was incorporated into the questionnaire.
The instrument was then piloted twice. In the rst instance we completed the questionnaire with ten
participants of the loveLife groundBREAKERS programme (from the cohort that preceded the study cohort)
and followed the questionnaire completion with cognitive interviews. The primary purpose of this piloting
phase was to assess whether participants understood the questions in the same way that they were intended
to be understood, and to assess how they responded to seemingly sensitive questions (such as sexual and
reproductive health questions). By and large the questions were understood as intended and the participants
were surprisingly open about the potentially sensitive questions. Where there was confusion the questions
were amended to account for this.
The instrument was piloted a second time with a group of eldworkers (also young people) in order to test
the skip patters and how long it would take to complete the questionnaire. Final editorial changes were made
to the questionnaire and notes were made about vernacular words that could be used if participants did not
understand particular English words.
3.7. Reliability and validity
The validity of the research instruments was enhanced with the use of previously tested and standardised
questions and standard response options (such as the Likert scale). In addition, cognitive interviewing in the
piloting phase ensured that questions were being understood as intended. Signicant investments in training
of eldworkers, the use of experienced eldworkers, a standardised research instrument, and standardised
training all contributed to the reliability of the data collection. The longitudinal design also enhances reliability
as we are able to assess consistency in responses over time.
32
3.8. Analysis
The analysis plan for the baseline report focused on descriptive statistics. These statistics included sample
characteristics, i.e., youth, organization, and site-level data. For categorical variables, we obtained frequency
distributions or sample proportions. For continuous-level data, we analysed the mean and standard deviation,
and the median in cases where this made sense (for example earnings-related data). For each set of descriptive
statistics, the research team looked for dierences by age category; gender; and between treatment and
control groups, with signicance testing of these dierences using t or Chi-squared statistics, tested at the
p=0.05 level. All data analyses were conducted using Stata 14.
3.9. Ethics
Ethical approval for the study was received from both the University of Johannesburg’s Faculty of Humanities
Ethics Committee as well as the University of North Carolina Chapel-Hill’s Independent Review Board. All
participants were provided with detailed information about the study purpose, what would be required of
them, their rights to privacy and condentiality, and potential risks and benets in an informed consent letter
which they were required to sign if they volunteered to participate. The informed consent form was available
to them to read but was also explained in full by eldworkers before data collection commenced. Additional
informed consent was sought for the release of the nancial data amongst treatment participants.
Having discussed the ways in which the study was conceptualised and designed we now turn to the ndings.
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SIYAKHA YOUTH ASSETS REPORT
4. PARTICIPANT BACKGROUND
AND CHARACTERISTICS
From the literature discussed above we know a great deal about the statistics on youth unemployment and
the explanations for why we have such high and increasing levels of youth unemployment. What is less well
known is what it is like to be unemployed as a young person and who these unemployed youth are. In the
ndings section we reveal a little of the lived experiences of a particular group of young people who are trying
to better their lives.
The picture that emerges from the data regarding the participants’ prole is one of an optimistic young
person, characteristically coming from a poor and vulnerable household. The households typically experienced
income and asset poverty as well as its consequences – lived poverty and food insecurity. Yet they are young
people who take initiative, evidenced both by their high levels of self-esteem and future orientation as well as
the fact that they self-selected into a youth employability programme.
4.1. Demographic overview
The average age of participants was 23 years old with most of them in the younger cohort (75% were between
18 and 25 years) and 25% older than 25 years. It is quite encouraging to know that participants who are involved
in these programmes are younger youth. One of the reasons we originally targeted 18-25 year olds is because
we expect that intervening to support young people as they transition from school towards education and
work would prevent young people from falling into chronic unemployment. As young people age and remain
unemployed it is likely to become more dicult to intervene to support them to nd work.
The majority of the respondents (61.1%) in our sample are female as compared to 38.9% of male respondents.
This is quite a signicant dierence and could be attributed to various factors. It is well documented in
employment research that in general, females are more vulnerable to unemployment than their male
counterparts (Statistics South Africa 2016a). The higher percentage of women in these programmes could
mean that more women are attracted to these youth employability programmes because of their employment
circumstances. In addition, some programmes intentionally target more females for participation because of
an awareness of the higher vulnerability women face.
A large majority of the respondents were African, making up 94.4% of the sample, followed by the Coloured
population, which makes up about 4.7% of the sample. This is no surprise, as these youth employability
programmes target historically disadvantaged communities where the prevalence of unemployment in youth
is higher.
4.2. Living arrangements and care responsibilities
As might be expected, given their age, the majority of respondents reported they were single (78.6%), followed
by those in a relationship but not living with a partner (about 15.2%). Older youth and women were more likely
to indicate that they were married or living with a partner but these gures are small.
A small proportion of the respondents (5%) were living alone at the time of starting their training. However,
most respondents (45%) were living with another 2-3 people. The average household size (including the
respondent) for the sample was 3.8 people.
The majority of the sample (87%) were living with relatives and most had a parent living in the household
(58%). This correlates with data from Statistics South Africa, which indicates that most youth live in nuclear or
extended family households (Statistics South Africa 2016b). Older youth were more likely than younger youth
to be living on their own.
Thirty four percent of the participants were living with their mothers but not their fathers and 19% were living
with both parents. Only 5% were living with their fathers and not their mothers. As might be expected, older
youth were signicantly less likely than younger youth to be living with either or both of their parents.
n %
Not living with parents 833 42
Living with mother 676 34
Living with father 99 5
Living with both parents 385 19
Total 1993 100
Table 4: Living arrangements – cohabitation with parents
34
More than a third of respondents (37.4%) indicated being responsible for the daily care or nancial needs of
a child. As expected, nancial or care responsibility for children predominantly rested with females (73%) as
opposed to males (27%). A larger proportion of participants in the control (53%) vs. the treatment group
(47%) indicated nancial or care responsibility for children.
On average, respondents who were responsible for the daily care need of children indicated that they provided
daily care to one child. However, when it comes to nancial care, participants were typically responsible for two
children. Respondents received at least one child support grant, on average, for children that they supported
nancially.
Just under a quarter of respondents (22%) indicated playing an important role in making nancial or in-kind
contributions to adults not residing in the household. Youth who assisted adults were likely to be older. They
mainly provided help in-kind including clothing and household items. Close to half of the respondents who
indicated providing support to adults noted they did so frequently.
In our theory of change, we posit that youth characteristics will play a major role in the success of youth
participating in Siyakha. In that vein, understanding who these youth are at baseline has implications for
how the outcomes will play out post the intervention and indeed in the long-term. Age, gender, race, marital
status, whether a parent or not will inuence the outcomes of youth employability programme participation
in Siyakha for youth. Findings in baseline indicate that participants who are involved in these programmes are
younger. We hypothesise that targeting 18-25 year olds to strategically intervene with support for transition
from school towards education and work could propel youth towards gainful employment. If intervention is
not implemented at this crucial stage in a young person’s life they are likely to remain unemployed for longer
periods of time.
Gender presents another important youth characteristic that impacts outcomes for youth employment
interventions. The higher percentage of women in these programmes could mean that more women are
attracted to these youth employability programmes because of their employment circumstances. In addition,
some programmes intentionally target more females for participation because of an awareness of the higher
vulnerability women face. A higher percentage of females in the study will allow for opportunities for gender
analysis of outcomes. This may provide information that could inform policies that might provide more
opportunities for young women that are tailored to address the unique needs of young women in the labour
market. Young women who are mothers and have to navigate parenting demands and job requirements may
face particular challenges. In many households, the division of labour remains skewed towards the woman,
putting these young woman in a potentially disadvantageous position when it comes to taking part in activities
which could contribute to her access into the labour market.
4.3. Household prole
Given the targeting of the youth employability programmes, participants typically came from poor and
vulnerable households – both in terms of income and asset poverty and the experience of poverty.
Household income and assets
Of the participants who knew their household average monthly income12, most lived in households that had
a combined average monthly income of between R3000 and R5000. A further 20% lived in households that
received between R1000 and R3000 per month. Cumulatively, 66% of the sample lived in households receiving
R5000 or less per month. This is broadly in line with the national youth population in which just under 60%
of the households within which youth reside are in the rst three income quintiles (earning R6000pm or less)
(Statistics South Africa 2016b).
The mean per capita income for the households in which participants reside is R527 per month with a median
of R250 per month. Over 40% of the participants indicated that they had no household income.
The primary income source for households was earnings and wages, either from formal or informal work, or
from running their own business (42%). This was followed by government grants (19%), with the remainder
being made up of other income sources including remittances.
Assets are items that are owned by individuals and households that can be used to sustain a living, for
subsistence, or could be sold for income. Assets are made up of classes including material assets, livestock,
household goods, and productive assets. Material assets incudes a house, motor vehicles and bicycles.
Household goods refers to items such as sewing machines, fridge, radio, microwave and the like. It also includes
cell phones. Productive assets are items such as a wheelbarrow and plough.
12 37% of the sample indicated that they did not know what the household monthly average income was. A further
1.5% refused to answer the question.
35
SIYAKHA YOUTH ASSETS REPORT
Individual (n=1993) Household (n=1993) Other household
(n=626)
Material assets 0.19 1.6 1.9
Livestock 0.86 5.5 5.8
Household goods 3.3 9 9.1
Productive assets 0.09 0.7 0.85
Table 5: Individual and household asset ownership
Table 5 above shows that in general households and individuals have low asset ownership, particularly when it
comes to material and productive assets –the assets that typically have higher values and can be used more
readily to convert into income should the need arise. In comparison they have higher numbers of household
goods. These numbers are largely made up of cell phones and radios. It is evident that households do have
some access to livestock (typically chickens and cattle) but that individual respondents had very limited access
to livestock. This may be because they are largely still living at home with shared ownership of the livestock. It
may also demonstrate that young people are less concerned than their elders with livestock ownership.
Given the income situation of the households, most of the participants should have been eligible as beneciaries
of the Child Support Grant (CSG) when they were growing up. Our analysis indicates that 24% of the sample
were CSG beneciaries, with a further 15% indicating that they did not know whether they were beneciaries
or not as shown in Figure 5 below. These numbers are fairly low given the income prole of the households
they come from.
61%
15%
24%
No Yes Don’t know
Figure 5: Child Support Grant beneciaries (n=1933)
One of the reasons may be the age of participants. Older youth were far less likely to report receiving the
CSG than younger youth. Only 7% of the older youth as opposed to 28% of the younger youth indicated being
CSG beneciaries. Given that the age limits for receipt of the CSG were gradually increased, some of the older
youth may have missed out on being age-eligible for the CSG while they were growing up. Treatment group
participants were more likely to indicate having received the CSG (27% indicated that they had received it)
than control group participants of which only 22% indicated having received the grant.
The household income and asset poverty is oset to some extent by access to basic services. The expansion
of access to services for poor communities since 1994 has benetted young people as well with over 80% of
the national youth population living in formal housing (Statistics South Africa 2016b). Our sample seemed to
be slightly worse o than the national youth population in terms of access to basic services. This is likely to be
because the programmes target youth from poorer communities.
The majority of young people (60.8%) lived in formal dwellings on a separate stand. Consistent with the
formal nature of housing, the roofs were mainly made of corrugated iron/zinc (53.6%) and the walls of bricks
(68.5%). Interestingly, older youth were less likely to live in formal dwellings than younger youth suggesting
that as young people in this sample move out of their parental homes they are more likely to be living in poorer
circumstances.
In terms of access to drinking water, there was variation in proximity to drinking water despite the majority of
participants occupying formal dwellings. Less than half (45%) had access to piped drinking water inside the
dwelling. About a quarter of participants (24.8%) collected drinking water at public taps. Electricity was the
main source of energy used for lighting (94.1%), cooking (87.9%) and heating (75.5%). Less than half of the
respondents (43.5%) had a ush toilet inside the dwelling. About a third of youth (31.8%) had access to a ush
toilet outside the house.
36
The experience of household poverty
Lack of access to assets and income results in various experiences of poverty which are considered from a
multidimensional perspective of poverty.
These low income levels in part explain why most young people in the sample lived in households that had
very high levels of food insecurity. In the study we used the Household Food Insecurity Access Scale (HFIAS)
– a validated scale that measures access to food and experiences related to lack of access to food (Coates,
Swindale, and Bilinksy 2007). Based on this scale, over half of the respondents came from households that
were severely food insecure. For many participants, this is because they answered that they (or a household
member) did not eat for a whole day or went to sleep hungry due to lack of food in the household once or twice
within the past 30 days. A further 20% are moderately food insecure as is demonstrated in Figure 6 below.
Food secure
Mildly food insecure
Moderately food insecure
Severely food insecure
14%
15%
20%
51%
Figure 6: Food insecurity (n=1874)
An analysis of household “shocks” is often used to assess lived poverty and experience of vulnerability – the
risk of falling deeper into poverty. Household shocks refer to changes that households experience ranging
from the death of a household member, to theft of household items and job loss of a household member.
Household shocks are understood to aect poor households more so than wealthier households because
they add nancial pressure to already limited resources and may push a household into a precarious existence.
Wealthier households tend to have more assets (such as insurance or savings) to cover the economic eects
of shocks.
The analysis shows that only 9% of households had not experienced a household shock in the last year. Most
households (52%) had experienced 2-4 of the listed shocks in the past year. This indicates that most of the
young people came from households that had to manage signicant additional economic burdens in the past
year, on already limited resources.
Certain household shocks aect households more adversely than others. For instance, death of a household
member, loss of income, and severe illness of a household member are typically viewed to be the three most
dicult shocks for households to cope with (de Wet et al. 2008). Further analysis of the data shows that
39% of the participants came from households that had experienced death of a close family member in the
past year. Fifty-ve percent (55%) came from households that had experienced loss of income, and 40%
had experienced severe illness or injury in their household. This suggests that not only are the households
that these young people come from households that are vulnerable to household shocks, many are also
experiencing the shocks that aect households most adversely.
The Lived Poverty Index (LPI) is a further measure that allows us to understand the lived experience of poverty
beyond a simple economic measure. The LPI measures experiences of scarcity of food, medicine, water and
other essential items in the past year and is answered on a ve-point Likert scale from “never” to “always”
(Mattes 2008).
The analysis shows that the households within which the participants reside fare relatively well on the LPI. Most
(60% or more) had either not experienced or rarely experienced scarcity in any of the essential items as is shown
in the gure below. This should not be confused with the food insecurity question, which asks participants about
their availability of food in the last month. The lived poverty index pertains to the previous year.
37
SIYAKHA YOUTH ASSETS REPORT
Never Once or twice Several times Many times Always
Cash
Fuel
Medicine
Wate r
Food
6%
4%
5%
9%
3%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
31%
48% 28% 14% 6%
42% 30% 16% 8%
56% 19% 11% 6%
46% 27% 17% 8%
29% 21% 13%
Figure 7: Experience of scarcity in ve essential items in the last year (n=1921)
It is concerning though that more than 20% of households experienced moderate to severe scarcity in fuel,
medicine, water and food in the past year.
Across a range of indicators of poverty and vulnerability it is evident that the participants of these programmes
come from extremely disadvantaged households. While most have adequate access to basic services they
remain food insecure with large numbers coming from households in which there is very low to no income.
They regularly experience household shocks and have limited resources with which to mitigate these risks. It
is remarkable therefore that they still demonstrate a positive sense of future and that they have high levels of
self-ecacy. It is to their psychosocial characteristics that we now turn.
4.4. Future orientation and self-ecacy
In general young people in South Africa are optimistic about the future (Kamper and Badenhorst 2010; Steyn,
Badenhorst, and Kamper 2010; Graham et al. forthcoming). This is despite the realities of structural poverty,
inequality and unemployment that young people face. The participants in this study were no dierent. They
were condent in themselves and had a high sense of their ability to control their futures and make something
of themselves.
Self-esteem refers to the degree to which we perceive ourselves positively or negatively; our overall attitude
toward ourselves (Baron and Branscombe 2011). In order to assess self-esteem we used the well-established
Rosenberg scale (Rosenberg 1965) – a 10 item scale with four response options ranging from Strongly Disagree
to Strongly Agree. The highest possible score for each item is 4, with a total possible high score of 40. The
higher the score was the higher the self-esteem was of the respondents.
For the whole sample the self-esteem score was 31 indicating that the participants had relatively high levels
of self-esteem. The older youth had slightly lower levels of self-esteem (30) than the younger youth (31) and
the treatment group had slightly lower levels of self-esteem (30) than the control group (31). However these
dierences, whilst statistically signicant, were minor. There were no gender dierences in self-esteem.
The high levels of self-esteem are borne out by qualitative research (Swartz, Harding, and De Lannoy 2012;
Graham et al. forthcoming), which repeatedly points to high levels of self-esteem and positive future orientation
among youth. In addition, because the programmes allow participants to self-select into the programmes,
they are likely to attract young people with high levels of self-condence. It should be noted that self-esteem
is responsive to life events. When we achieve important goals self-esteem can increase, while failures can
temporarily harm self-esteem (Baron and Branscombe 2011).
Future orientation involves the ability to set or develop goals for one’s life and the ability to pursue these
goals (Lee et al. 2010). Condence is also theorised to be linked with a sense of future in self-determination
theory (Ryan 1995; Catalano et al. 2004), which suggests that the experience of autonomy, condence and
competence helps people to feel as if they have control over their future and that they can plan and see goals
coming to fruition through their own eorts. It is strongly associated with reduced risk behaviour and better
stress responses among youth.
Respondents could receive a high score of 44 in the future orientation scale if they scored positively (4)
on each of the 11 items. The mean score for the sample was 32 indicating that respondents were very goal-
orientated. There was a small dierence in future orientation for control and treatment group participants with
control group participants scoring higher than treatment group participants by 0.7 points.
Self-ecacy is the belief that we can achieve a goal as a result of our own actions (Baron and Branscombe
2011). It too is strongly associated with positive development amongst adolescents including better ability
to cope with stress and reduced engagement in risk behaviours (Catalano et al. 2004). Overall, respondents
gravitated toward high levels of condence in their abilities to achieve tasks. This is evidenced by the high
38
mean score for self-ecacy – 32.8 out of a possible 40. Again there were small dierences between treatment
and control groups with the control group scoring 0.7 points higher than the treatment group.
Respondents’ higher self-esteem, self-ecacy, and future orientation may be a result of their successful
selection into the youth employability programme. The programmes also typically would attract young people
who are goal-oriented as they are individuals who self-selected into the programmes.
4.5. Health and risk behaviour
The young people who participated in this study also typically indicated that they were healthy and reported
risk behaviours that are in line with, if not slightly better than national averages. Most youth (75%) reported
either excellent or very good health. Twenty one (21%) of youth reported good health, with only 4% fair to
poor health.
Substance use
Youth were asked to answer questions about their use of alcohol, cigarettes, and drugs over the past 30 days.
Sixty percent (60%) of respondents reported not drinking at all, while 21% reported drinking either once or
twice in the past 30 days. Eight percent (8%) reported drinking once a week in the past 30 days, and 3%
reported drinking at least one drink of alcohol more than once a week in the past 30 days. This is broadly in
line with national data which shows that 32% of youth had had at least one drink in the last month (S. P. Reddy
et al. 2013).
Those who responded that they had consumed at least one drink of alcohol within the past 30 days were
asked about binge drinking. Youth were asked whether, in the past 30 days, they had consumed ve or more
alcoholic drinks consecutively over the course of a couple of hours. Seventy percent (70%) of surveyed youth
reported that they had not taken part in binge drinking in the past 30 days, whereas 25% reported that they
had had ve or more alcoholic drinks in a row. Again this in line with national results which show that around
25% of respondents had engaged in binge drinking in the past month (S. P. Reddy et al. 2013). Asked about
frequency of smoking cigarettes over the past 30 days, 6% reported smoking daily. Eighty two percent (82%)
of youth reported that they had not smoked at all. Youth were also asked whether they had tried any drugs
over the past 30 days. Ninety two percent (92%) of youth reported that they had not tried any type of drugs,
and 5% reported that they had. These gures are lower than national gures. Reddy et al (2013) report
that 13% of survey respondents had ever used Cannabis, and 9.7% had used other types of drugs (inhalants,
prescription drugs, heroine, Mandrax and “club drugs”).
Sexual and reproductive health
Eighty percent (80%) of youth reported past experience of having sex. For these respondents, the average
number of sexual partners was 2.5. Those who reported sexual experience were asked about sexual risk
behaviours. A key risk factor for HIV infection is engagement in sex with someone ve or more years older (for
women) or younger (for men) than themselves. Generally sex with someone who is ve or more years older is
considered a risk factor primarily for women. Thirty four percent (34%) of the female respondents answered
in the armative to this question. Conversely, for men, the risk factor is sex with someone ve or more years
younger. Of the male respondents 26% indicated that this was the case.
Seventy-two percent (72%) had used a condom during their most recent sexual encounter; 21% had not. This
is higher than the national average for youth which was 68% for males and 50% for females in 2012 (Shisana
et al. 2014). Sixteen percent (16%) have had sex while under the inuence of alcohol or drugs. Three percent
(3%) had engaged in transactional sex.
Figure 8 below summarises positive responses from questions regarding sexual behaviours or experiences.
80
70
60
50
40
30
20
10
0
Sex with
someone ve
or more years
older
Sex with
someone ve
or more years
younger
Condom use
when most
recently had
sex
Sexual
experience
while under
inuence of
substances
Sex given or
received in
exchange for
resources
Figure 8: Summary of Positive Responses to Sexual Behaviour Questions (by percent, multiple response)
39
SIYAKHA YOUTH ASSETS REPORT
Young people who are participating in the youth employability programmes therefore seem to be engaging in
risk behaviours at around the same rate as the general youth population, with a slightly lower risk for engaging
in the use of illegal substances. They were also more likely to engage in protective behaviours such as condom
use, and very few reported engaging in transactional sex.
4.6. Conclusion
The above ndings demonstrate that despite coming from poor backgrounds the young people enter the
programmes with high levels of self-esteem, condent of their ability to change their fortunes by participating
in the programmes. Their high levels of self-esteem, self-ecacy and future orientation are likely to be both
a function of a generally positive youth population, as well as a feature of the particular kinds of young
people that opt-in to youth employability programmes. Their positive attitudes are coupled with household
circumstances that severely limit their ability to make signicant changes in their lives. The high levels of
income poverty and vulnerability they are exposed to are structural conditions that are likely to result in the
intergenerational transmission of poverty (Finn, Leibbrandt, and Ranchhod 2016), leading young people to
ultimately be frustrated and depressed. They experience a disjuncture between their dreams for themselves
and their realities. They experience the structural violence of social and economic exclusion – what Swartz et
al (2012) refer to as “the quiet violence of dreams.” Success in accessing the labour market upon completing
an employability programme may be their only option to change their fortunes.
40
5. EDUCATION
If, as discussed above, one of the key explanations for high levels of youth unemployment is low skills levels,
then it follows that education and training should assist young people to access the labour market. One of
the key outcome indicators for the study is whether participants are better able to access formal further or
higher education and training on completing the programme. We therefore assessed education levels as they
entered the programme.
5.1. Secondary education
Figure 9 demonstrates that the majority of youth (90.5%) attained grade 12. This is in contrast to their parents’
level of education. Only 35% of respondents indicated that their mother had a matric certicate or higher
qualication; and 39% indicated the same for their fathers. This means that young people in this sample
are achieving higher levels of education than their parents. This conrms research conducted by Statistics
South Africa (2016b) and Finn, Leibbrandt and Ranchod (2016), which shows that nationally, young people
have higher levels of education than their parents. However, the same research shows that increased years of
education has not resulted in better labour market or earnings prospects for youth.
Of those who had obtained a matric, just over one fth (21.7%) attained grade 12 with a bachelor pass. More
younger youth (25%) compared to older youth (11%) attained grade 12 with a bachelor pass. A recent study in
the Labour Market Intelligence Project (LMIP) reports that 34% of unemployed and 39% of employed youth
(15-34 years) respectively in South Africa had completed secondary education in 2014 (Isdale et al. 2016).
Grade 12
Grade 12 with Bachelor pass
Some primary school
Some secondary school
3,9%
5,6%
68,8%
21,7%
Figure 9: Highest level of primary or secondary education (n=1954)
About 10% of the participants had less than matric. Nationally about 60% of unemployed youth (15-34 years)
had less than matric (Isdale et al. 2016). The fact that more of the youth in the Siyakha study had grade
12 than youth nationally is a feature of the programme entry-level requirements and shows that most of
the programmes tend to target youth with somewhat higher levels of education than the national youth
population. Fit for Life Fit for Work, Afrika Tikkun, Raymond Ackerman Academy, Harambee, loveLife and EOH
all indicated grade 12 as one of their programme admission requirements. Some programmes do relax this
requirement on a case by case basis. The only programme that specically targets those that do not have a
matric certicate is Thabiso Skills Institute.
5.2. Post-secondary education
Respondents were asked if they pursued formal studies after completing school. A large proportion of
respondents (42.9%) indicated they did. A larger proportion of the control group compared to the treatment
group had pursued formal studies after school.
Thirty four percent (34.8%) of the sample completed post-secondary training. Of these, more than a third
(37%) acquired a National Diploma and 44% acquired an occupational certicate as indicated in Figure 10
below. Thus, despite young people coming from very poor households, many are managing to access and
complete some form of further education and training. Yet their participation in the programmes suggests
that they have not been able to convert their education into employment outcomes.
41
SIYAKHA YOUTH ASSETS REPORT
National Diploma
Bachelors Degree
General Trade/Occupation Certicate
Other
10%
37%
9%
44%
Figure 10: Highest level of post- secondary education (n=694)
Research has repeatedly demonstrated that further or higher education signicantly increases an individual’s
chances of employment and that graduate unemployment rates in South Africa are low (Van der Berg and
van Broekhuizen 2012). However, such research has not analysed the eects of education for dierent groups
of young people. Our research seems to suggest that the eects of post-secondary education and training do
not necessarily convert into positive labour market outcomes for the youth from poor households in this study.
Participants who pursued formal studies after school were asked if they had ever enrolled for a course and
subsequently dropped out. Almost two-fths responded in the armative. As can be expected the main
reason for course drop out was the inability to aord fees. This conrms research recently released by the
National Income Dynamic Study team demonstrating that income levels of the matriculant’s household in the
year they matriculate signicantly aect the chances of that individual accessing and completing any post-
secondary education and training (Branson and Khan 2016).
In addition to formal post-secondary education and training (through universities or TVET colleges), all
respondents were asked about other forms of training or skills development programmes that they had been
involved in prior to joining the youth employability programme. More than half of the respondents (55.8%) had
previously participated in some form of training. Older youth were signicantly more likely than younger youth
to have previously participated in other skills training programmes. These were largely short-term classroom
or on the job training programmes. Those who had attended a previous programme indicated that they
had attended on average two dierent training or skills development programmes before enrolling for the
programme under assessment.
This suggests that young people tend to participate in multiple skills training programmes before entering
employment or further or higher education and conrms the notion of how transitions to the labour market
are staggered (Graham and Mlatsheni 2015; Isdale et al. 2016). It also points to the fact that there seems to be
a great deal of churn in the youth employability training sector. This is a key issue that needs to be addressed.
5.3. Conclusion
Evidently programme participants have worked hard to complete their secondary schooling successfully. They
have done so despite dicult socio-economic circumstances. It is quite remarkable that so many of them also
managed to access, and in many cases complete, some form of post-secondary education and training. This
is contrary to the experiences of most youth from poor backgrounds who struggle to access post-secondary
education and training (Branson and Khan 2016; van Broekhuizen, van der Berg, and Hofmeyr 2016). Yet they
are still struggling with nding employment and turn to short-courses and other training programmes as
stepping stones that may assist them to nd work. This reinforces the importance of understanding the role
that youth employability programmes play in supporting young people to nd work.
42
6. EXPERIENCES OF EMPLOYMENT,
UNEMPLOYMENT, AND WORK-SEEKING
Youth employability programmes represent, for these young people, an opportunity to break out of a cycle of
unemployment or underemployment. It is a chance to change their fortunes. What role do these programmes
therefore play in the transition to work for a young person? Literature suggests that young people are often
passed over in favour of older workers who have work experience (Grimshaw 2014). This is an oft-cited reason
for higher unemployment levels among youth. Youth employability programmes therefore may be viewed as
an opportunity to gain work experience. Yet our data suggests that many of the participants had prior work
experience and that the programmes represented one of many dierent steps that young people had taken
to nd their way into work.
6.1. Employment and work experience
At the time of baseline data collection, 20.8% of the 1993 entrants to youth employability programmes were
in paid employment and just over half of the sample had had some prior work experience. This was surprising
given that many of the programmes target young people who are not currently working. Paid employment,
as dened in the questionnaire, excludes any unpaid working activity, or work for which respondents were
paid a stipend. This condition means that respondents were encouraged to not consider being a participant in
their respective programmes as a form of employment – a feasible possibility given the fact that many of the
programmes include a working component, for example in the form of volunteering or internship, either unpaid
or stipended. However, we suspect that some of the respondents did consider participation in the programme
as work. This is borne out by the fact that younger respondents (aged 18-25) were signicantly more likely
to report currently working (22.6%) than respondents aged 25 and above (14.4%). Younger participants are
more likely to have less experience of the labour market and therefore may view stipends as being equivalent
to the concept of wages. Interestingly, more women are likely to say they are currently working – 22.2% versus
17.9% for men.
The overall gure for labour absorption of 20.8% corresponds with the absorption rate of 18-25 year olds in
the South African labour market13, which hovered around 20% from the last quarter of 2014 to the rst quarter
of 2016, a period corresponding to that during which baseline data for the Siyakha project was collected
(Statistics South Africa 2015d; Statistics South Africa 2016a). Forty seven percent (47%) of the respondents
had never worked, again with signicant age dierences (45% for younger and 75% for older respondents).
Those who had worked before had held an average of 1.8 jobs. Again this diered highly signicantly by age.
Older participants had held an average of 2.4 jobs as compared to 1.6 for younger respondents.
Nature of work experience
Respondents who indicated that they had worked in the past (53% of the sample) were asked a series of
questions relating to the job they considered to be the most important in terms of their future employability
in order to understand the kind of work in which they had been engaged. Fifty seven percent (57%) had
been employed in formal jobs, with formality dened as the existence of a work contract. The control group
was signicantly more likely to have had a work contract. The mean wage earned in this job was R2233 per
month (n=953); with a median of R1800 per month. Ninety percent (90%) of the participants had earned
below R4400 per month. These gures are slightly lower than the national average for youth where the mean
wages for 18-25 years olds was R2538 with a median of R2200 per month (Statistics South Africa 2015d).14 In
qualitative research conducted by the CSDA with employed youth across ve provinces participants indicated
a mean wage of R2865 per month with a median of R2036 (Patel et al. 2016).
There is a highly signicant dierence in means by age category of about R1000, with older respondents
having earned more. As expected, living in one of South Africa’s nine metropolitan municipalities also makes a
dierence: the mean wage earned by respondents at sites in metro areas was R2454 while outside the metro
areas it was R1820. For those who chose to give a pay range rather than a number in response to this question
(n=404), about half reported wages in the R1000 – R3000 range.
Respondents were asked to give a brief description of the type of work they did. These open-ended responses
were recoded into the major occupation types, loosely based on the ILO’s International Standard Classication
of Occupations (International Labour Organisation (ILO) 2012a). Figure 11 below indicates the occupation
types in which young people were employed.
13 Although our gure may also include substantial numbers of volunteers.
14 Restricting the sample to those earning less than R8000 per month (i.e. excluding the 15% of high earning youth).
43
SIYAKHA YOUTH ASSETS REPORT
35%
5%
4%
14%
21%
15%
6%
Service workers
Salespeople
Oce/clerical workers
Labourers (unskilled)
Technical/skilled workers
Craft workers/semi-skilled operatives
Other
Figure 11: Occupation type of most important job (n=1002)
Service workers provide services relating to travel, personal care, housekeeping, catering and/or protection
against re, theft or other shocks. Fifteen percent (15%), or 146 of 1002 programme participants’ jobs perceived
as their most important fell into this category. Large sub-categories include waitrons, restaurant workers
and bar sta (38); domestic workers and cleaners (32); security guards and parking attendants (13); cooks,
community works and care workers (9); bakers and caterers (8); petrol station attendants (7); and hairdressing
and beauty consulting (6). Some less-frequently-mentioned jobs include trac controllers; reghters and
decorators. Others include gardeners; car washers and painters (10).
Salespeople are workers who sell and/or promote goods. Twenty percent (21%), or 214 responses, fell into
this category. Subcategories include retail, sales, merchandising and promotions (97); cashiers (80); shop
assistants (18) and call centre agents (19).
Fifteen percent (15%) or 148 responses were classied as being oce or clerical workers – workers primarily
tasked with handling information and carrying out administrative tasks. Subcategories include data capturers,
administrative assistants and general oce workers (133); and secretaries and receptionists (15).
Unskilled labourers or workers in elementary occupations amounted to 60, or 6% of the total, and are dened
as involving “the performance of simple and routine tasks which may require the use of hand-held tools and
considerable physical eort” (ILO 2012: 337). Large subcategories include construction labourers (10) and
packers and stock-takers (36).
Technical or skilled workers perform complex work requiring specialised and extensive knowledge. Of all the
jobs mentioned, 351, or 35%, fell into this category.
The largest sub-category of skilled workers (143) included all respondents whose most important job was
cited as including one or more of the following words: volunteering; peer education; mentoring; youth
empowerment or facilitation. In a large proportion of these cases these descriptions included the words
“loveLife” or “groundBREAKER”, implying that most of the observations in the skilled worker category
represent being enrolled in a youth employability programme (specically lovelife) – which respondents were
instructed to not include in their response to their perceived most important job. In addition, 84 responses fell
into the subcategory of ‘learnership’, with many of these responses including ‘end-user computing’. A further
17 responses indicated ‘tech support’ (end-user computing and tech support are names of EOH programmes).
This implies that there is a similar dynamic at play with EOH participants.
Therefore, for many young people, being in a youth employability programme represents what is possibly the
only real working experience they have ever had, or the only experience perceived as being important to their
future employability. It also implies that of the 21% of respondents who counted themselves as employed at
baseline, at least some of them will have been thinking about their programme participation as employment.
This suggests that the way employment is interpreted and dened by respondents is highly variable, and
may often be at odds with researchers’ denitions. The close correlation between our gures and those of
Stats SA (Statistics South Africa 2015d; Statistics South Africa 2016a) suggests, however, that this is a more
general problem relating to employment-related statistics in South Africa. We will investigate this more in the
qualitative portion of this project.
Removing the abovementioned responses from the technical or skilled worker category reduces the number
of responses from 351 to 107. Large subcategories include teaching assistants and tutors (22); IT and computer
assistants, implying something dierent to EOH (19); eldwork and data collection ocers (e.g. enumerators
for Statistics South Africa – 13); employees of the Independent Electoral Commission (IEC) and South African
Social Security Agency (SASSA) (e.g. as voters roll checkers/compilers and ballot paper issuers for the IEC
– 6); quality inspectors/controllers (10). Smaller subcategories with at least two responses included student
nurses, radio producers and presenters, theatre crewmembers and debt collectors.
44
Of the total, 46 jobs or 5% could be classied as belonging to craft workers and semi-skilled operatives. These
are workers applying specialised skills to manufacturing and construction work, or workers who operate heavy
or light machinery. Large subcategories include drivers (cars and fork-lifts: 8); plumbers and handymen (6);
machine operators (11); and welders/grinders (5). Smaller subcategories included pipe tters and brick makers.
As discussed above we assume that some of the respondents considered their youth employability programme
involvement as work. In order to get a clearer picture of the occupation types of the jobs that young people
had held, we removed the responses where it was clear that the respondent was considering their involvement
in the programme as a job.
14%
6%
5%
19%
28%
20%
8%
Service workers
Salespeople
Oce/clerical workers
Labourers (unskilled)
Technical/skilled workers
Craft workers/semi-skilled operatives
Other
Figure 12: Occupation type of most important job (n=758)
As is shown in Figure 12 this change signicantly reduces the number of people who indicated technical and
skilled work as their most important job. The most common sectors in which young people therefore gain their
experience are as salespeople, followed by oce or clerical workers and service work.
Participants were asked how they found out about their most important job. As discussed above, social
networks are very important sources of information about jobs (Kruss 2016; Mlatsheni and Rospabe 2009;
Altman 2007); and in our research the most important. More than half of the respondents found out about
their most important jobs via friends, family and household members: predominately friends and relatives
living outside of their current households (36.6%) as demonstrated in Figure 13 below.
Asked a past employer
Waited on roadside
Employment agency
Visits to employers
Notice board ad
Other
Household member
Newspaper ad
Friend/relative (not in HH)
0,0% 5,0% 10,0% 15,0% 20,0% 25,0% 30,0% 35,0% 40,0%
19,9%
36,6%
13,7%
7,7 %
6,9%
5,7%
4,6%
2,6%
2,5%
Figure 13: Source of information about most important job (n=1045)
The mean duration of this job was 10.6 months, with large age dierences (16.3 months for older youth vs eight
months for younger youth). This seems to suggest that as young people age they are gaining more labour
market experience which may ultimately translate into a longer-term, stable job. Mean hours worked per week
were 33, with a median of 40.
Asked why they stopped doing this work, the bulk of respondents stated that the job ended (32%), implying
that the jobs were temporary in nature. This accords with research showing the large share of young people
with secondary education employed by the temporary employment services (or labour broking) sector,
particularly in sales and services jobs (Bhorat, Cassim, and Yu 2014). Only 4% indicated they had been red
or laid o, although participants may under-report this. Sixteen percent (16%) said they were still doing this
45
SIYAKHA YOUTH ASSETS REPORT
work, which relates to the previous nding of many respondents choosing the programme they were currently
enrolled in as their most important job. A further 10% said they had left the job in order to study. Interestingly,
9% stated that they had given up their jobs in order to join the programme.
Only 11.9% were working for themselves at the time of the interview, with highly signicant dierences by age
group (16.3% for older youth as compared to 10.5% for younger youth). Only 17.2% had ever been self-employed,
with men and older respondents being far more likely to have been self-employed in the past than women and
younger respondents. Self-employment most often took the form of selling sweets and food (as street vendors
and out of private residences) and hairdressing; followed by selling of clothes, kitchenware and cosmetics (one
respondent sold electricity); modelling; performing arts (e.g. DJ-ing); babysitting and photography. It appears
that – as with the paid employment section – interpretation of self-employment varies widely, and is generally
taken to mean survivalist activity, often referred to as “hustling” by youth in other CSDA research (Graham
2016; Centre for Social Development in Africa 2015; Centre for Social Development in Africa 2013a). This idea is
reinforced by the very low monthly average take-home earnings from self-employment of R1989 with a median
of R1200. 13.9% were doing unpaid work at the time of the interview, and only 25.6% had ever done unpaid work
before. In addition, thirteen percent (13%) left their unpaid work to join the programme they were enrolled in
at baseline.
6.2. Unemployment and work-seeking
At the time of entering the programme, 78% of participants indicated that they were unemployed, although
taking into account that some viewed the programme as employment, this is likely to be somewhat under-
reported. The mean duration of unemployment since leaving school for these respondents was 12.9 months,
with 73% having been unemployed for longer than a year. Of these, almost 20% had been unemployed for 18
months or more since leaving school. This suggests that most of the participants had experienced chronic
unemployment (dened as unemployment lasting for more than one year). This rate is higher than the national
average which shows that 63% of 18-35 year olds were unemployed for longer than a year (Statistics South
Africa 2015b). This means that the bulk of respondents were experiencing long-term unemployment at the
time of entering the programme and conrms their experience of entering the labour market queue at the
back and staying in it for long periods.
The treatment group had a signicantly lower average unemployment duration of 12.1 months against the
control group’s 13.5 months. For 18-25 year olds, the mean unemployment duration is 11.8 while for those aged
25 and above, the mean duration of unemployment is 17.7 months, a highly signicant dierence. This may in
part be explained by the fact that the youngest of the younger cohort would have only recently completed
school and would therefore naturally have fewer months of unemployment. Also highly signicant is the
dierence between metro and non-metro areas (11.6 and 15.3 months respectively). This is to be expected
given that more jobs are concentrated in metro areas.
There is a common assumption that one of the reasons youth unemployment is so high is because young
people have unrealistic high expectations of what they could earn and therefore turn down jobs where wage
oers are perceived to be too low (i.e. the suggestion that youth unemployment is often voluntary) (Rankin
and Roberts 2011). This is called the reservation wage problem and we assessed participants’ perceptions on
fair and reservation wages to assess whether these a) are unrealistic and b) change over time.
The mean response to the question asking for an estimation of a fair or reasonable salary given the respondent’s
skills and experience (although no time period is specied) is R7432, with a median of R5000 (n=1836)15.
Men and older respondents had signicantly higher mean gures (men=R9388; older respondents=R8786).
Respondents were also asked for the lowest monthly amount they would be willing to work for (their
reservation wages). Here the mean is R3504 (mean for younger respondents is R3304, a highly signicant
dierence), the median is R3000 and the 75th percentile is R4000 (n=1839). Women have lower reservation
wages, (R3283 per month vs R3867 per month for men), as do younger people (R3348 for 18-25 year olds vs
R4017 for older than 25). Interestingly, fair wages and reservation wages do not dier signicantly between
metro and non-metro areas, a nding which accords with previous CSDA research (Patel et al. 2016).
The disconnect between fair wages and reservation wages supports ndings from previous research that in
determining reservation wages, fairness is not the deciding factor, and youth are willing to work for wages
they perceive as unfair – again reinforcing the idea that youth are not unemployed because they are biding
their time and waiting for high-paying job oers (Patel et al. 2016). It does however seem that reservation
wages are somewhat higher than market-related wages for people of a similar prole. If we look at the average
earnings for this age group using Statistics South Africa’s 2014 Quarterly Labour Force Survey Data: Quarter
4 (Statistics South Africa 2015d), and excluding the high-earning population (who are conceivably also highly
educated and therefore not in need of a YEP), the mean earnings are R2538 per month. For the full 18-25
year-old sample, the mean wage is R5579 per month. The mean reservation wage from the Siyakha baseline
sample is R3504. This suggests the existence of unrealistic expectations to some extent, as found by Rankin
and Roberts (2011).
15 Figures for ideas of fair wages and reservation wages correlate closely with those obtained in Patel et al 2016:
Median fair wage: R6000 per month
Mean reservation wage: R3371 per month
Median reservation wage: R3000 per month
46
Given the high costs of job-search and transport (see below), it should be noted that it is also perhaps unrealistic
to accept jobs that do not cover these costs. In addition, caution should be exercised in the interpretation
of reservation wages as people often accept hypothetical job oers for wages lower than their reported
reservation wages (Zoch 2014; Patel et al. 2016).
Fair wage ideas and reservation wages were also checked against whether the respondent had ever worked
before, and, interestingly, there are no signicant dierences, implying that work experience and becoming
more acquainted with the realities of the labour market does not reduce one’s expectations about fair or
feasible earnings (while in Patel et al 2016, reservation wages are signicantly lower for employed people).
Work-seeking experiences
Of those who were unemployed, 81% had actively looked for work during this period of unemployment, with
this proportion increasing with age. There was no dierence by metro/non-metro area.
Job search methods
Respondents were asked to indicate all job search methods employed since the onset of unemployment.
Searching job advertisements and the internet was the most widely used strategy. This was followed
distantly by enlisting the services of a trade union or employment agency, and enquiring directly at places
of employment. Lastly the participants indicated having sought the assistance of family and/or friends. This
nding suggests that young people are not using eective strategies to nd work. Given that social networks
(Mlatsheni and Rospabe 2009) and employment agencies or temporary employment services (Centre for
Development and Enterprise 2012) are the most likely strategies to result in a job, it is worrying that so
many youth are using one of the least eective methods – blind applications to widely advertised positions.
The lower use of social networks is probably indicative of the few social networks they have (as discussed
below) and is possibly a reection of the fact that unemployed people are likely to have more unemployed
people in their social networks when compared to employed people (Patel et al 2016). It is interesting to note
though that social networks seem to be the most likely to result in nding a job. As discussed above, most
respondents indicated having found their most important job through friends or family. Very few respondents
indicated having waited on the side of the street for casual work or taking steps to start their own businesses
as job search strategies.
On average unemployed respondents had made use of 1.4 of the methods displayed in the chart above.
This seems low, and could be a reection of high search costs (see below) or a lack of knowledge about
how to go about searching for work. For those who were not currently looking for work (n=651), 27% cited
discouragement as the main reason for this (equal proportions of discouragement in metro and non-metro
areas); 27.6% had decided to go back to school or study further; and 11% couldn’t aord search costs. Only 3%
of those who were not looking for work had opted out because they perceived oered wages to be too low.
Discouragement and the inability to pay for search costs are signicantly more prevalent in the younger age
group.
Job applications
Of all respondents, 77.5% had made a job application in the three months preceding baseline, with a mean
number of job applications made in this period of 7.8 and a median of 4 (10% had made 20 job applications
or more).
Information about these jobs was gained primarily from the internet, followed by newspapers and friends and
family outside the respondent’s household as demonstrated in Figure 14 below.
Other
Asked at business places
Asked people in household
Employment agency
Notice boards
Asked friends/family outside household
Newspapers
Internet
0 10 20 30 40 50 60 70 80
67, 9
44,8
32
26,3
19,1
17,8
13,6
2
Figure 14: Sources of information about recent job applications (multiple response)
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SIYAKHA YOUTH ASSETS REPORT
Job applicants were optimistic. 57% considered their most recent job application to have been a good one
with a high chance of success; 24% saw this application as good but with a limited chance of success; while
only 6% considered the application to be bad. This seems to be borne out by reality, at least in terms of job
applications resulting in an interview. Half of the r