Youth Transitions Evidence
Base: 2012 Update
Department of Education,
Employment and Workplace
Relations
19 November 2012
Deloitte Access Economics Pty Ltd
ACN: 149 633 116
The Director
Transitions Policy and Stakeholder Engagement Section
Youth Attainment and Transitions Branch
Department of Education, Employment and Workplace Relations
Level 1, 9 Sydney Ave
Barton ACT 2600
PO Box 6334
Kingston ACT 2604
Tel: +61 2 6175 2000
Fax: +61 2 6175 2001
www.deloitte.com.au
19 November 2012
Youth transitions evidence base: 2012 update
In 2006, Access Economics prepared a paper for the then Department of Education, Science
and Training which examined the economic and social benefits accruing when young people
make a smooth transition from school to further education, training and/or work. The Youth
Transitions Evidence Base paper was produced for the Ministerial Council on Education,
Employment, Training and Youth Affairs Pathways for Post-compulsory Youth Advisory
Committee) as part of its reporting to the Council of Australian Governments.
Since then, additional data and other evidence have become available, and a number of
changes in the Australian economy and labour force – both positive and negative – have been
realised. As such, an update of the 2006 report is timely. This update report provides the
Department with an overview of the most contemporary evidence and analysis of the relative
success of youth transitions in Australia.
The report draws on the Longitudinal Survey of Australian Youth, supported by other datasets
such as the Survey of Education and Work and graduate destination surveys, in order to profile
the transitions undertaken by young people after school.
I trust that this report will assist the Youth Attainment and Transitions Branch to continue to
foster and support engagement by young people and encourage positive transitions to
post-school education, training and/or employment.
Yours sincerely,
David Rumbens
Director
Deloitte Access Economics Pty Ltd
Liability limited by a scheme approved under Professional Standards Legislation.
© 2011 Deloitte Access Economics Pty Ltd
Youth Transitions Evidence Base: 2012 Update
Contents
Glossary ...........................................................................................................................................i
Executive Summary .........................................................................................................................i
1
Introduction ........................................................................................................................ 1
2
Defining youth transitions .................................................................................................. 2
3
2.1
Relevant variables .................................................................................................................. 3
2.2
Definitions in earlier research ................................................................................................ 4
2.3
Preferred data source ............................................................................................................ 7
2.4
Definitions of school transitions ............................................................................................ 8
2.5
Definitions of post-school study transitions ........................................................................ 15
Transitions from school .................................................................................................... 21
3.1
All school leavers ................................................................................................................. 21
3.2
Year 12 completers and non-Year 12 completers ................................................................ 23
3.3
Gender ................................................................................................................................. 25
3.4
Participation in part-time work while at school................................................................... 26
3.5
Participation in VET while at school ..................................................................................... 27
3.6
Indigenous Australians ......................................................................................................... 28
3.7
Those with a disability.......................................................................................................... 29
3.8
Migrants ............................................................................................................................... 30
3.9
Literacy and numeracy ......................................................................................................... 31
3.10
Location................................................................................................................................ 31
3.11
Socio-economic status ......................................................................................................... 32
4
Transitions from post-school study .................................................................................. 34
5
Other transition data sources ........................................................................................... 38
6
5.1
ABS Survey of Education and Work ..................................................................................... 38
5.2
ABS survey of those not in the labour force ........................................................................ 40
5.3
State-based school leaver surveys ....................................................................................... 41
5.4
NCVER Student Outcomes ................................................................................................... 48
5.5
Graduate Destination Survey ............................................................................................... 49
5.6
Beyond Graduation Survey .................................................................................................. 50
Broader labour market and education trends .................................................................. 53
6.1
Overall labour force participation and unemployment ....................................................... 53
6.2
Labour force status of young people ................................................................................... 54
6.3
Unemployment of young people ......................................................................................... 58
6.4
Long-term unemployment ................................................................................................... 63
6.5
Underemployment ............................................................................................................... 64
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© 2011 Deloitte Access Economics Pty Ltd
Youth Transitions Evidence Base: 2012 Update
7
8
9
6.6
Part-time work ..................................................................................................................... 65
6.7
School retention rates.......................................................................................................... 67
6.8
Participation in higher education ......................................................................................... 68
6.9
Participation in VET .............................................................................................................. 70
International comparisons of transition experiences ....................................................... 73
7.1
Labour market and education benchmarks ......................................................................... 73
7.2
OECD detailed comparative analysis for Australia ............................................................... 77
7.3
OECD Thematic Review ........................................................................................................ 78
Broader economic outcomes ............................................................................................ 80
8.1
Workforce participation ....................................................................................................... 80
8.2
Labour productivity and earnings ........................................................................................ 83
8.3
Implications for wages ......................................................................................................... 84
8.4
Skill shortages ...................................................................................................................... 86
8.5
Economy wide outcomes ..................................................................................................... 89
8.6
Longer term impacts ............................................................................................................ 95
Conclusions ....................................................................................................................... 99
References................................................................................................................................. 101
Appendix A : Detailed data on youth transitions ...................................................................... 104
Limitation of our work................................................................................................................... 118
Charts
Chart 3.1 : Transition from school by gender............................................................................. 26
Chart 3.2 : Transition from school for those working part-time at school ................................ 27
Chart 3.3 : Transition from school by participation in VET in school ......................................... 28
Chart 3.4 : Transition from school for indigenous Australians ................................................... 29
Chart 3.5 : Transition from school for those with a disability .................................................... 30
Chart 3.6 : Transition from school for migrant/Australian born ................................................ 30
Chart 3.7 : Transition from school by literacy and numeracy .................................................... 31
Chart 3.8 : Transition from school by location ........................................................................... 32
Chart 3.9 : Transition from school by socio-economic status .................................................... 33
Chart 4.1 : Occupational profile for post-school study completers ........................................... 35
Chart 4.2 : Transition from post-school study – those who complete study ............................. 36
Chart 4.3 : Transition from post-school study – those who do not complete study ................. 36
Chart 5.1 : School leavers in 2010 by enrolment and labour force status in May 2011 ............ 38
Chart 5.2 : Labour force status of those studying in May 2011 ................................................. 39
Chart 5.3 : Completers of non-school qualification enrolled in 2010 by labour force status in
May 2011..................................................................................................................................... 39
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Youth Transitions Evidence Base: 2012 Update
Chart 5.4 : Post-school destinations of Victorian Year 12 completers in 2010 .......................... 42
Chart 5.5 : Main destinations in 2011 of Queensland Year 12 completers in 2010 .................. 45
Chart 5.6 : WA school leaver destinations ................................................................................. 47
Chart 5.7 : Destinations of graduates surveyed in the GDS, 2011 ............................................. 49
Chart 5.8 : Main activity of bachelor degree graduates, 2008-11 ............................................. 50
Chart 5.9 : Bachelor graduates available for full-time employment, 2008-11 .......................... 51
Chart 5.10 : Broad occupation types, bachelor graduates in full-time employment, 2008-11 .... 51
Chart 5.11 : Broad occupation types, bachelor graduates in part-time employment, 2008 and
2011 52
Chart 6.1 : Labour force participation rate ................................................................................ 53
Chart 6.2 : Unemployment rate ................................................................................................. 54
Chart 6.3 : Share of 15-19 year olds not in full-time education or full-time work ..................... 55
Chart 6.4 : Share of 20-24 year olds not in full-time education or full-time work ..................... 55
Chart 6.5 : Education and labour force status of young people, 2011 ...................................... 56
Chart 6.6 : Education and labour force status of young people by single year of age, 2011..... 57
Chart 6.7 : Labour force participation rates by age ................................................................... 58
Chart 6.8 : Unemployment rates for young people seeking full-time work .............................. 59
Chart 6.9 : Unemployment rates for young people seeking full-time work by gender ............. 59
Chart 6.10 : Unemployment to population ratio for each age group – seeking full-time work 60
Chart 6.11 : Unemployment to population ratio for each age group – seeking full-time or parttime work .................................................................................................................................... 61
Chart 6.12 : Share of total unemployed seeking full-time work for each age group ................. 62
Chart 6.13 : Share of total unemployment for each age group ................................................. 62
Chart 6.14 : Long term unemployment rates for young people, and total persons .................. 63
Chart 6.15 : Long term unemployment rates for young people by gender ............................... 64
Chart 6.16 : Underemployment for young people by gender .................................................... 64
Chart 6.17 : Share of labour force employed part-time for young people ................................ 65
Chart 6.18 : Share of labour force employed part-time by gender............................................ 66
Chart 6.19 : Share of part-time workers who would prefer to work more hours ..................... 67
Chart 6.20 : Apparent retention rates in Australia from Years 7/8 to Year 12 .......................... 68
Chart 6.21 : Young people’s participation in higher education ................................................. 69
Chart 6.22 : Attrition rate for domestic commencing bachelor students .................................. 69
Chart 6.23 : Young people’s participation in VET ....................................................................... 70
Chart 6.24 : Young people’s commencement of Australian apprenticeships ............................ 71
Chart 6.25 : Senior students’ enrolment in further training while at school ............................. 72
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Youth Transitions Evidence Base: 2012 Update
Chart 7.1 : Youth unemployment rates in OECD countries, December 2007 to March 2012 ... 74
Chart 7.2 : Youth neither in employment nor in education or training (NEET) among youth in
OECD countries in 2011............................................................................................................... 74
Chart 8.1 : Labour force participation rate by single year of age, 2011..................................... 80
Chart 8.2 : Occupational profile of full-time workers by age ..................................................... 81
Chart 8.3 : Nature of employment for 15-24 year olds .............................................................. 82
Chart 8.4 : Australian labour productivity (measured by GDP per hour worked) ..................... 83
Chart 8.5 : Average weekly total cash earnings, May 2010 ....................................................... 84
Chart 8.6 : Salary profile of transitions to full-time work .......................................................... 85
Chart 8.7 : Salary profile by transition category......................................................................... 85
Chart 8.8 : Salary profile of full-time workers by transition category ........................................ 86
Chart 8.9 : Internet vacancy index, selected occupations and Australian total ......................... 88
Tables
Table 2.1 : Outcome measures examined in recent youth transitions literature ........................ 5
Table 2.2 : Classification of activities – changes from 2006 report............................................ 13
Table 2.3 : Classification of activities – changes from 2006 report............................................ 19
Table 3.1 : Transition from school – all school leavers ............................................................... 21
Table 3.2 : Transition from school – year 12 completers ............................................................ 24
Table 3.3 : Transition from school – early leavers ...................................................................... 24
Table 5.1 : Main activity of NSW school leavers in 2009 by Year 12 completion status ............ 41
Table 5.2 : Employment and further study outcomes for VET graduates and module
completers, 2011 ........................................................................................................................ 48
Table 5.3 : Median salary, bachelor graduates in full-time employment, by broad field of
education, 2008–11 ($, ‘000s) ..................................................................................................... 52
Table 7.1 : Scoreboard for youth aged 15-24, 2000 and 2010 ................................................... 76
Table 8.1 : Additional labour income and addition to GDP from an increased number of good
transitions ................................................................................................................................... 92
Table 8.2 : Potential net increase in labour income per person ................................................ 93
Table 8.3 : Average marginal effect of increased educational attainment on the probability of
labour force participation (%-pts) ............................................................................................... 96
Table 8.4 : Average marginal effect of increased educational attainment on hourly wages (%)96
Table 8.5 : Estimated potential workforce effects from improvements in educational
attainment, 2030......................................................................................................................... 98
Table A.1 : Transition from school – females – early leavers.................................................... 104
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Youth Transitions Evidence Base: 2012 Update
Table A.2 : Transition from school – females – Year 12 completers ......................................... 105
Table A.3 : Transition from school – females – all .................................................................... 105
Table A.4 : Transition from school – males – early leavers ....................................................... 106
Table A.5 : Transition from school – males – Year 12 completers ............................................ 106
Table A.6 : Transition from school – males – all ....................................................................... 107
Table A.7 : Transition from school – Indigenous Australians .................................................... 107
Table A.8 : Transition from school – those with a health problem or disability ....................... 108
Table A.9 : Transition from school – part-time work at school................................................. 108
Table A.10 : Transition from school – VET in school ................................................................. 109
Table A.11 : Transition from school – VET in school – males .................................................... 109
Table A.12 : Transition from school – VET in school – females................................................. 110
Table A.13 : Transition from school – migrants ........................................................................ 110
Table A.14 : Transition from school – English ability ................................................................ 111
Table A.15 : Transition from school – Maths ability ................................................................. 112
Table A.16 : Transition from school – location......................................................................... 112
Table A.17 : Transition from school – socioeconomic status ................................................... 113
Table A.18 : Transition from post-school study – university.................................................... 114
Table A.19 : Transition from post-school study – apprenticeships .......................................... 115
Table A.20 : Transition from post-school study – traineeships ................................................ 116
Table A.21 : Transition from post-school study – other VET.................................................... 117
Figures
Figure 2.1 : Transitions from school ........................................................................................... 14
Figure 2.2 : Transitions from post-school study ......................................................................... 20
Figure 5.1 : Victorian Year 12 Completers, main activity in 2010 by main activity in 2008 ....... 43
Figure 5.2 : Victorian early school leavers, main activity in 2010 by main activity in 2008 ....... 44
Figure 5.3 : Queensland Year 12 Completers, main activity in 2009 by main activity in 2006 .. 46
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Youth Transitions Evidence Base: 2012 Update
Glossary
ABS
Australian Bureau of Statics
ACER
Australian Council of Educational Research
ANZSCO
Australian and New Zealand Standard Classification of Occupations
ASBA
Australian School Based Apprenticeships
COAG
Council of Australian Governments
DEECD
Department of Education and Early Childhood Development
DEEWR
Department of Employment Education and Workplace Relations
EPL
Employment Protection Legislation
EU
European Union
EULFS
European Union Labour Force Survey
GDS
Graduate Destination Survey
GFC
Global Financial Crisis
HILDA
Household Income and Labour Dynamics in Australia
HISEI
Highest International Socio-Economic Index
ISEI
International Socio-Economic Index
ILO
International Labour Organisation
ISCO
International Standard Classification of Occupations
ISCED
International Standard Classification of Education
LSAY
Longitudinal Survey of Australian Youth
NCVER
National Centre for Vocational Education Research
NEET
Neither in Employment Education or Training
NILF
Not in Labour Force
NILFET
Not in Labour Force Education or Training
NLSY-97
National Longitudinal Survey Year 1997 (United States of America)
NSW
New South Wales
OECD
Organisation of Economic Co-operation and Development
PISA
Program for International Student Assessment
SES
Socio-Economic Status
SOS
Student Outcomes Survey
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Please see www.deloitte.com/au/about for a detailed description of the legal structure of Deloitte Touche Tohmatsu Limited
and its member firms.
© 2011 Deloitte Access Economics Pty Ltd
Youth Transitions Evidence Base: 2012 Update
UK
United Kingdom
UR
Unemployment Rate
US
United States of America
VET
Vocational Education and Training
WA
Western Australia
Deloitte Access Economics
Youth Transitions Evidence Base: 2012 Update
Executive Summary
In 2006, Access Economics prepared a paper for the then Department of Education, Science
and Training which examined the economic and social benefits accruing when young people
make a smooth transition from school to further education, training and/or work.
Deloitte Access Economics has been commissioned by the Department of Education,
Employment and Workplace Relations (DEEWR) to prepare an update of the 2006 report
reflecting the most recent available data and evidence.
The primary data source used in developing profiles of transitions is the Longitudinal Survey
of Australian Youth (LSAY), a longitudinal survey tracking cohorts of students on an annual
basis from the age of 15. LSAY is managed and funded by the Australian Government
Department of Education, Employment and Workplace Relations (DEEWR), with support
from state and territory governments. The National Centre for Vocational Education
Research (NCVER) provides analytical and reporting services, while the LSAY data are
collected by computer assisted telephone interviewing by the Wallis Consulting Group..
Two cohorts of students are examined in this report – a group of students who were aged
15 in 2003, and a group who were in Year 9 in 1998.
This report presents a statistical profile of these transitions and in doing so measures them
against an objective of successfully entering the labour force, or undertaking further study
with that goal. While that is of interest from a society point of view it is not necessarily the
objective of every individual. Hence, identification within this paper of groups who are ‘at
risk’ or experiencing ‘poor transitions’ does not imply that all the individuals in those groups
are unhappy with where they are and/or will require additional assistance. Rather, it
highlights groups who may be on a path where they may not maximise their economic
potential (whether that is by their choice or due to some constraint), which is of interest
from a workforce participation and labour productivity perspective.
Defining youth transitions
A key issue is defining a ‘good transition’ and a ‘poor transition’, both from school and
following a period of post-school study.
Previous research focuses mainly on school leavers. The common theme is that those who
are unemployed, or not in the labour force are seen as having a poor transition or being at
risk. The best outcomes are seen as full-time work and/or full-time study.
This research continues that approach, with some variations. As in previous literature,
good and poor outcomes are measured against an objective of successfully entering the
labour force or preparing to enter the labour force by undertaking further education and
training. The group who have poor transitions will include some people who would rather
not be in that situation, but will also include some who choose to be, for example to travel
or to raise a family (with significant longer term economic and social benefits accruing from
the latter).
For this study, individuals making good transitions from school are those who over three or
four of the four annual surveys since leaving school have been fully engaged in either fullDeloitte Access Economics
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Youth Transitions Evidence Base: 2012 Update
time work, full-time study at or above Certificate III level or a combination of part-time
work and part-time study at or above Certificate III level.
Individuals making poor transitions from school are those who over three or four of the
four surveys since leaving school are unemployed, not in the labour force, or have only part
time work (where they have been seeking additional work or additional hours), or some
combination of these three. This definition isolates those who, over quite a considerable
length of time, have had little or no experience in the labour market.
The term ‘mixed outcome’ is applied where an individual over four years following school
has two of the good transition outcomes and two of the poor transition outcomes. In
addition, those who are only undertaking part-time work (where the individual was
satisfied with the amount of hours being worked) or only part-time study over a long period
of time are also seen as potentially being susceptible to poor transitions. Similarly, those
who are undertaking full-time study below Certificate III level or are undertaking a
combination of part time work and part time study below Certificate III level for a long
period of time are defined as having a ‘mixed outcome’.
The ‘initial at risk’ are those who one year after school are either unemployed, not in the
labour force or only in part-time work (where they have been seeking additional work or
hours). Given this initial experience post-school, there would be a notable risk that
members of this group may end up making poor transitions.
Finally, transitions from post-school study are defined in a similar way, but part-time work
(where the individual was satisfied with the amount of hours being worked) is defined
within the good transition group. We also note that within those who have good outcomes
from post-school study, there would be some who we would describe as ‘short of
potential’. These relate to those who are employed but are in an occupation which is
seemingly below the skill set of their qualifications (a ‘skill mismatch’ occupation).
Transitions from school
The LSAY 2003 data shows that across all school leavers, around 76% of individuals were
fully engaged in work and/or study in the first year after having left school, while around
15% of individuals were seen as at risk of a poor transition. That is, one year after school
15% are either unemployed, not in the labour force, or employed part-time in a position
where they are seeking additional hours or additional work. By definition, these people are
not studying.
Chart i shows the cumulative outcomes over four years after having left school, with 82% of
the LSAY Y03 group defined as having a good transition, and 4% a poor transition – a
noticeable improvement from the outcome one year after leaving school.
The propensity for poor outcomes for those who have left school prior to year 12 is
substantially higher than for those who have completed year 12 – they are about four times
as likely. This is particularly true for female early leavers.
There is greater risk of poor transitions or mixed outcomes for those who have disabilities,
come from a family with a lower socio-economic status, or are Indigenous. The proportion
of poor transition outcomes for young Indigenous Australians is also likely to be under-
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Youth Transitions Evidence Base: 2012 Update
stated as many young Indigenous Australians leave school before age 15 and so would not
have been captured in the LSAY data.
Those with lower levels of literacy or numeracy tend to have a lower propensity for good
transitions.
Being a migrant (born outside Australia) or one’s location (metropolitan, provincial or
remote/very remote) is not associated with major differences in transition outcomes.
Having undertaken some part-time work while at school appears to help transitions for
both early leavers and Year 12 completers, while VET in Schools shows a small positive
association with good transition outcomes for early leavers.
Chart i: Transition from school – cumulative outcome over four years
Source: LSAY, Y03 dataset
The results for the LSAY Y03 cohort are broadly similar to the results for the LSAY Y98
cohort presented in the 2006 report. However, a larger proportion of the LSAY Y03 cohort
was in employment one year after leaving school, and a smaller proportion was in study.
The initial at risk group was also slightly larger. A comparison of the cumulative four year
outcomes showed a smaller proportion of the LSAY Y03 cohort were in full-time work in all
four years and a larger proportion in full-time study. There was also a small increase of 1%
in the proportion making poor transitions over four years for the LSAY Y03 cohort.
A caveat on the comparative results above is that transition paths have been defined
slightly differently for the LSAY Y03 cohort, compared with the LSAY Y98 cohort analysed in
the 2006 report. These are discussed in sections 2.4.5 and 2.5.5. The results discussed
above are unlikely to have been affected by these definitional changes, but a comparison of
other transition paths would be affected more significantly. Small changes in the method
of data extraction were also made for the analysis of the LSAY Y03 cohort. Small
differences in the results may therefore not be statistically significant.
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Youth Transitions Evidence Base: 2012 Update
Transitions from post-school study
LSAY Y98 data was used to examine a three year period of transition following post-school
study, both for completers of that study and those who commence but do not complete.
The rate of good transitions following completion of post-school study is generally high.
University and apprenticeship completers do best with good transition outcomes recorded
for 96% of each group. Traineeship completers and other VET completers have good
transition outcomes of between 89% and 91%.
However, within the ‘good transition’ group we define a subset who are working in an
occupation which is short of the potential implied by their qualifications. This ‘short of
potential’ group is significant for all forms of post-school study, and is highest for university
graduates at 42%, and ranges from 12% to 21% for the other post-school study groups.
This suggests a significant degree of under-utilisation of skills in the three years following
completion of post-school study. In a macro environment of skill shortages this suggests
there is a significant latent pool of skills which is not being fully utilised.
The rate of good transition outcomes is notably lower for those who drop out of postschool study. That is with the exception of those dropping out of university, where 92% of
these people still make a good transition.
Overall, the results for post-school study transitions for the LSAY Y98 cohort showed some
improvement compared with the results for the LSAY Y95 cohort presented in the 2006
report. The rate of good transitions was 6% and 4% higher for university and
apprenticeship completers respectively (including those making good transitions but falling
short of potential). Non-apprenticeship VET completers had rates of good transition that
were 11% higher than found for the LSAY Y95 cohort, while traineeship completers did
about the same as found for the LSAY Y95 cohort. However, for the most part, labour
market conditions were better for the LSAY Y98 cohort than the LSAY Y95 cohort (with the
LSAY Y98 cohort facing lower unemployment rates on average post school or study).
Other transition data sources
Other transition sources shed further light on youth transitions from school and post-school
study. The most similar to the LSAY surveys are some state-based surveys, with the findings
of these surveys largely consistent with the findings for the LSAY Y03 cohort.
The ABS Survey of Education and Work found that 17% of school leavers in 2010 were not
working nor studying in the following year, a slightly larger proportion than suggested for
the LSAY Y03 cohort.
State-based surveys of school leavers generally show that more than half of school leavers
transition to further study in the year after leaving school, while around one tenth end up
unemployed or NILFET (not in the labour force nor in education or training).
Longitudinal surveys of school leavers conducted by Victoria and Queensland show that
more than half of school leavers were still in education or training after 3-4 years. Both the
Victorian and Queensland longitudinal surveys showed relatively good outcomes after 3-4
years for those initially undertaking apprenticeships after school. The Victorian survey
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Youth Transitions Evidence Base: 2012 Update
showed outcomes were better for Year 12 completers than non-Year 12 completers three
years after leaving school.
For transitions from post-school study, the most recent survey data show that 77% of VET
graduates were employed six months after graduating, and 76% of university graduates
seeking full-time work were employed full-time four months after graduating. However,
labour market outcomes for both VET graduates and university graduates have weakened
since the global financial crisis. The 2011 Beyond Graduation Survey shows that labour
market outcomes continue to improve for university graduates in the four years after
graduating from university.
Broader labour market and education trends
Recent years have seen the fallout from the global financial crisis take its toll on the
Australian labour market. The bad news is that youth unemployment rates in Australia for
those aged 15-24 have increased by more than the overall unemployment rate. Young
people aged 15-19 have been hit particularly hard. Not surprisingly, rates of long-term
unemployment and under-employment for young people have also increased. In total,
young people now account for 40% of all unemployed people in Australia.
The silver lining is that associated with the diminished labour market prospects for young
people has been an increase in school retention rates and increased participation in higher
education since 2008. However, apprenticeship commencements have declined due to the
economic downturn. Participation in VET has remained fairly steady, increasing slightly in
2010.
There has been a very strong lift in the share of 15-19 year olds that are in the labour force
who are working part-time, from around 30% in 1988 to around 59% today. Around one
third of people aged 15-24 who are engaged in part-time work would prefer to be working
more hours. Having a significant proportion of Australia’s youth unemployed or
underemployed is not achieving to the nation’s potential.
International comparisons of transition experiences
The experience of other countries provides an important gauge for how well Australia is
performing in youth transitions to the labour market and further education. International
comparisons can also provide benchmarks relating to world’s best practice in terms of
outcomes for young people.
Recessionary conditions in other advanced economies, particularly in Europe, has seen
Australia’s relative performance improve on some key indicators. That is true for the youth
unemployment rate and the incidence of young people in long-term unemployment. The
proportion of youth neither in employment nor in education or training (NEET) is also
better than the OECD average, and young Australians are more likely to get experience in
the labour market at a young age by holding a part-time job. However, the youth
unemployment rate relative to the overall unemployment rate is higher than average, and
so are school drop-outs.
Australia’s labour market institutions are generally seen by the OECD as supportive of good
school to work transitions, while recent reforms that aim to lift educational attainment,
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Youth Transitions Evidence Base: 2012 Update
encourage VET in schools, and improve school to work transitions are considered to be
steps in the right direction. There remains room for improvement in some areas, including
education performance, particularly in early childhood, for indigenous Australians, and in
increasing retention to Year 12.
Broader economic outcomes
Australia might be said to be operating at its economic potential when all our resources –
our workers (and their human capital), our physical capital (factories, warehouses,
computers, office blocks, mines, roads, ports and the like) and our land – are being used in
a manner which maximises our national income over the longer term.
Other things being equal, if we operate at our ‘potential’, then workers will tend to be in
those occupations, sectors and regions where their productivity is highest (and hence their
wage or salary is highest).
Those with poor transitions are, by definition, operating at less than their potential. Others
who are employed may be operating at less than their potential also – individuals may work
part-time but want to be a full-timer or they work as a waiter but are trained as a structural
engineer.
The shortfall between actual labour market outcomes and potential can be measured in
terms of lost participation and productivity – and hence as lost output. For transitions from
school, Deloitte Access Economics estimates that shortfall amounts to up to $1.5 billion
from a single year’s cohort (LSAY Y03 results applied to the youth cohort of 2010 who are
experiencing poor transitions or mixed outcomes).
However, that measure of ‘lost potential’ may not measure the full true cost of poor
transitions. That is because, as a host of academic studies have argued, this loss lingers.
Those with poor transitions run the risk of operating below their productivity potential for a
long time, which then in turn leads to them operating at below their potential on
participation too.
Conclusions
This report has used the LSAY datasets and supporting information to examine the quality
of transitions made by young people in Australia from school to further education, training
and/or work.
The policy implications of this work are well established, and good transitions by young
people into the labour force will become increasingly important for the Australian economy
over time. In particular, as the Australian population ages, the supply of workers in the
economy will diminish. Good transitions from school to further education and/or work will
help to lift productivity growth and labour force participation, and in turn will support the
productive capacity of the economy.
The results presented in this report suggest that, overall, young people in Australia make
relatively good transitions from school, and Australia compares relatively well
internationally.
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Identifying the characteristics of individuals who are less likely to make a good transition
from school allows policy efforts to be targeted more effectively. Poor transitions were
more likely to occur for individuals that leave school prior to completing Year 12;
Indigenous Australians; and individuals with a disability, or who come from a low socioeconomic background. The challenges facing many of these socio-economic groups are
well recognised, and the results here reinforce the need for policies to assist transition by
young people among these groups.
These results broadly mirror the outcomes of Access Economics’ 2006 report, Youth
Transitions Evidence Base, on which this document is based.
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Youth Transitions Evidence Base: 2012 Update
1 Introduction
In 2006, Access Economics prepared a paper for the then Department of Education, Science
and Training which examined the economic and social benefits accruing when young people
make a smooth transition from school to further education, training and/or work.
The Youth Transitions Evidence Base paper was produced for the Ministerial Council on
Education, Employment, Training and Youth Affairs Pathways for Post-compulsory Youth
Advisory Committee) as part of its reporting to the Council of Australian Governments
(COAG). Since then, additional data and other evidence have become available, and a
number of changes in the Australian economy and labour force – both positive and
negative – have been realised.
Deloitte Access Economics was commissioned by the Department of Education,
Employment and Workplace Relations (DEEWR) to prepare an update of the 2006 report
reflecting the most recent available data and evidence. As was the case in the earlier work,
this report presents analysis of youth transitions, focusing on transitions from school to
work, further education or training. The report also examines transitions which occur from
post-school study.
The primary data source used in developing profiles of transitions is the Longitudinal Survey
of Australian Youth (LSAY), a longitudinal survey tracking cohorts of students on an annual
basis from the age of 15. The survey is managed by the National Centre for Vocational
Education Research (NCVER). Two cohorts of students are examined in this report – a
group of students who were aged 15 in 2003, and a group who were in Year 9 in 1998.
The analysis is complemented by other data sources, including the Australian Bureau of
Statistics’ (ABS) Survey of Education and Work and graduate destination surveys.
This report is structured as follows:

Chapter 2 discusses relevant factors in defining whether youth transitions are good or
poor, and provides the definitions to be used for this report.

Chapter 3 provides a profile on post-school youth transitions from the LSAY Y03 data.

Chapter 4 provides a profile on transitions following post-school study from the LSAY
Y95 data.

Chapter 5 examines a range of other data sources of relevance to profiling youth
transitions.

Chapter 6 examines recent developments in broader labour market and education
trends, providing context for recent data on transitions.

Chapter 7 provides some international comparisons for youth labour market and
transition indicators, as a benchmark for Australian performance.

Chapter 8 reports on workforce participation and labour productivity outcomes,
focusing on the difference in these measures resulting from good transitions relative to
poor ones. Broader economy wide outcomes and longer tem impacts are also
discussed.

Chapter 9 summarises the conclusions of the report.

Finally, Appendix A provides a more detailed statistical examination of youth transitions
profiles.
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Youth Transitions Evidence Base: 2012 Update
2 Defining youth transitions
A key issue is defining a ‘good transition’ and a ‘poor transition’, both from school and
following a period of post-school study.
Previous research focuses mainly on school leavers. The common theme is that those who
are unemployed, or not in the labour force, are seen as having a poor transition or being at
risk. The best outcomes are seen as full-time work and/or full-time study.
This research continues that approach, with some variations. As in previous literature,
good and poor outcomes are measured against an objective of successfully entering the
labour force or preparing to enter the labour force by undertaking further education and
training. The group who have poor transitions will include some people who would rather
not be in that situation, but will also include some who choose to be, for example to travel
or to raise a family (with significant longer term economic and social benefits accruing from
the latter).
How does this report define transitions from school and post-school study?
For this study, individuals making good transitions from school are those who
over three or four of the four annual surveys since leaving school have been
fully engaged in either full-time work, full-time study at or above Certificate III
level or a combination of part-time work and part-time study at or above
Certificate III level.
Individuals making poor transitions from school are those who over three or
four of the four surveys are unemployed, not in the labour force, or have only
part time work (where they have been seeking additional work or additional
hours), or some combination of these three. This definition isolates those
who, over quite a considerable length of time, have had little or no experience
in the labour market.
The term ‘mixed outcome’ is applied where an individual over four years
following school has two of the good transition outcomes and two of the poor
transition outcomes. In addition, those who are only undertaking part-time
work (where the individual was satisfied with the amount of hours being
worked) or only part-time study over a long period of time are also seen as
potentially being susceptible to poor transitions. Similarly, those who are
undertaking full-time study below Certificate III level or are undertaking a
combination of part time work and part time study below Certificate III level
for a long period of time are defined as having a ‘mixed outcome’.
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Youth Transitions Evidence Base: 2012 Update
The ‘initial at risk’ are those who one year after school are either unemployed,
not in the labour force or only in part-time work (where they have been
seeking additional work or hours). Given this initial experience post-school,
there would be a notable risk that members of this group may end up making
poor transitions.
Finally, transitions from post-school study are defined in a similar way, but
part-time work (where the individual was satisfied with the amount of hours
being worked) is defined within the good transition group. We also note that
within those who have good outcomes from post-school study, there would be
some who we would describe as ‘short of potential’. These relate to those
who are employed but are in an occupation which is seemingly below the skill
set of their qualifications (a ‘skill mismatch’ occupation).
2.1 Relevant variables
This research examines direct and broader economic impacts resulting from young people
making a good transition through school and from school to further education, training
and/or work, relative to those making a poor transition. Young people are those aged from
15 to 25, though in exploring the relevant issues the age range may be lowered for
Indigenous Australians.
The central focus in this analysis is on transitions after leaving school (for those completing
year 12 and for those leaving earlier). Some of those transitions are to further education or
training, and this analysis also examines, as a secondary focus, transitions following the
completion of post-school study.
The definitions of ‘good’ and ‘poor’ transitions are fundamental here. Ultimately the best
transitions are those where individuals set about achieving to their potential. For
individuals a good transition provides benefits in terms of higher wages or salaries
(rewarding a higher level of skill or productivity) and/or enhanced personal satisfaction
from doing what they want to do. For society as a whole, good transitions mean a more
productive economy, better long run participation prospects, and less expense in assisting
those who may miss out. The following are relevant considerations in presenting a profile
of youth transitions:

Period examined – for what period after completing school or post-school study are
individuals examined? For example, are individuals monitored for one year, two years,
four years or more?

Time lags – within that total length of time being examined, how long individuals take
to move between school, study and occupations may be important in defining a good
transition and a poor one. If an individual is unemployed for two years after school, but
then finds full-time work, is that a good transition or a poor one?

Nature of job – whether employment is full-time or part-time.
employment a good outcome and how is ‘part-time’ defined?

Occupation – is employment in a field commensurate with an individual’s skills? This
may be particularly relevant for transitions from post school study. How do we account
Deloitte Access Economics
Is part-time
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Youth Transitions Evidence Base: 2012 Update
for those who may have trained in one field, but then gained employment in an
occupation which seemingly requires a lower level of skill?

Voluntary disengagement from work or study – some people are content not to make
a transition to a job or to further study. How do we account for those who may quite
happily be not in the labour force for a long time, for example to raise a family, noting
that longer term benefits to society also accrue from such a role?
Definitions of transitions are constrained by the data. The key data source for this research
is the Longitudinal Survey of Australian Youth (LSAY). It is a national survey with a large
sample size and has been specifically designed to examine youth transition issues, so it
collects information on a range of relevant characteristics.
The survey is managed by the Department of Education, Employment and Workplace
Relations (DEEWR), with support from state and territory governments. This report
examines the extended profile for two cohorts of students – those who were in year 9 in
1998 (LSAY Y98), and those aged 15 in 2003 (LSAY Y03). The LSAY Y98 cohort was
interviewed on an annual basis until 2009 (a total of 12 waves), while the LSAY Y03 cohort is
still being interviewed yearly (a total of 8 waves to date, with latest data available from the
2010 interviews).
LSAY Y03 is the most recent, comprehensive longitudinal data which allows for four postschool surveys. To examine transitions from post-school study LSAY Y98 allows for three
surveys following post-school study.
2.2 Definitions in earlier research
This section describes the findings of a literature review of definitions used in earlier
research, as well as consideration of how recent policy work has defined a successful youth
transition.
2.2.1
Literature review
How have others defined youth transitions? As part of this project, a review of recent
youth transitions literature was undertaken to identify the ways in which others have
attempted to classify some transitions as being more successful or better than others.
A summary of the findings of this literature review is provided in the table below.
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Youth Transitions Evidence Base: 2012 Update
Table 2.1: Outcome measures examined in recent youth transitions literature
Source
Data examined
Outcome measure(s)
Ryan (2011)
LSAY Y95 and
LSAY Y98
Karmel and Liu (2011)
LSAY Y95
Thomson and Hillman (2010)
LSAY Y03
Lee (2010)
LSAY Y95
Curtis (2008)
LSAY Y95
Lamb and Vickers (2006)
LSAY Y98
Anlezark and Lim (2011)
LSAY Y03
Education and labour force status; experience of unemployment;
weekly gross earnings and hours worked; participation in further
training and development; job satisfaction.
Studying full-time or part-time at a university; studying full-time or
part-time in TAFE or another form of vocational training; in an
apprenticeship or a traineeship; working full time and not in study;
working part-time and not in study; unemployed; not in the labour
force
Post-school full-time study or full-time employment
Marks (2009)
LSAY Y95
Occupational status and weekly earnings
Deloitte Access Economics
Being in full-time employment; being in a full-time activity (i.e., either
full-time employment or full-time study); being in unemployment;
current wages and earnings; occupation in which individuals are
employed (its skill or status level).
Full-time study or work; full-time employment only; job status of fulltime employment; job status of part-time work (for women not in fulltime work or study because of family commitments); gross weekly pay
of full-time employment. Lifestyle outcomes—financial wellbeing, life
satisfaction, work satisfaction and having children (for women).
Satisfaction with life and whether fully occupied with education and/or
employment, or a combination of these
Occupational prestige/status using the ANU3 scale
Time of
assessment
Six to eight
post-school years
At age 25 years
At age 19
Up to eight postschool years
In 2004 for
programs started
by 2001
One year
post-school
One to two years
post-school
At age 24 years
(on average)
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Youth Transitions Evidence Base: 2012 Update
In brief, a range of different outcomes are analysed by different researchers, and no
commonly accepted definition of what precisely makes a successful youth transition has
emerged in the literature.
However, there are some common themes evident. The clearest one is that those who
are unemployed or not in the labour force are seen as having a poor transition or at least
being at risk. The best outcomes are generally seen as full-time work and/or full-time
study. Those just engaged in part-time study are not often specifically mentioned, but on
the above definitions may also be seen as at risk.
Beyond this initial classification, it is also common to distinguish transitions based on the
quality of employment (and, for that matter, the quality of education or training). This was
neatly summarised by Karmel and Liu (2011):
However, irrespective of the complexity, a successful youth transition typically
occurs when a young person leaves school and/or further study and becomes
employed (in various states), rather than being unemployed or not actively
participating in the labour force. But is being employed an adequate measure
of a successful youth transition? Consideration could also be given to the
quality of employment, which may be measured by earnings, job status, the
nature of employment (contract or permanent), job security, training
opportunities, flexibility, promotional opportunities or self-assessed job
satisfaction.
It is arguable, however, that for school leavers the quality of employment shortly after
leaving school is less of a differentiator between students than simply being employed (or
in further study). That is because the vast majority of school leavers are uniformly
inexperienced and relatively lowly skilled (and, therefore, most can be found in low skill
level occupations). At that stage of life, participating in the workforce, even in a low quality
job, is a way to up-skill. In contrast, for post-school study transitions, the quality of
employment is much more important, with employment at that time likely to reflect future
career paths.
A further consideration is that the group who have poor transitions will include some
people who would rather not be in that situation, as well as some who choose to be (see
‘voluntary disengagement from work or study’ in section 2.1) – a successful labour force
outcome is not necessarily the same as a successful personal experience.
However, previous research has shown a positive relationship between measures of life
satisfaction and young people’s level of engagement in work or study. For example,
Hillman and McMillan (2005) analysed this relationship over four post-school years for the
LSAY95 cohort. This research found that those young people who were fully engaged in
work and/or study reported higher levels of career satisfaction and general life satisfaction
than those who were only partially engaged, while those who were partially engaged
reported higher levels of career and general life satisfaction than those who were
unemployed or not in the labour force. Thomson and Hillman (2010) reported a similar
finding for the LSAY03 cohort at age 19.
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Youth Transitions Evidence Base: 2012 Update
The objective of this study is to measure and profile those who do not easily make it to the
labour force, for whatever reason. The above research suggests that this group of young
people is likely to be less satisfied with their lives than those who are fully engaged and
more likely to need assistance, but we note that some young people in this group will not
need assistance (although young people who do not enter the labour force due to family
reasons may need assistance at a later stage in their lives, for example when their children
start school and they may then be looking to enter the labour force, and at that point
governments can try to assist with appropriate re-connection services).
Finally, the point in time at which outcomes are examined varies widely across studies.
This largely reflects the different research objectives of the various studies. Some focus on
transitions immediately after study, while others examine outcomes at a single point in
time such as in the mid-20s, and others look at transitions over a long period of time. This
study will assess transitions one year after study, as well as over a period of four years after
study for transitions from school, and a period of three years after study for transitions
from post-school study (as explained in more detail later in this chapter).
2.2.2
COAG’s reform agenda
How have policy makers defined a successful youth transition?
COAG’s reform agenda is implemented through various agreements between the
Commonwealth and the States and Territories. One of the key outcomes of the National
Education Agreement which commenced on 1 January 2009 is that:
“Young people make a successful transition from school to work and further study.”
Three performance indicators are associated with this outcome:
1. The proportion of the 20-24 year old population having attained at least a Year 12 or
equivalent or AQF Certificate II or above
2. The proportion of young people participating in post-school education or training six
months after school
3. The proportion of 18-24 year olds engaged in full time employment, education or
training at or above Certificate III
In particular, the third performance indicator above has been defined further as referring to
the proportion of 18-24 year olds engaged in either full time employment, full time
education/training at or above Certificate III, or a combination of both part time
employment and part time education/training at or above Certificate III.
2.3 Preferred data source
The LSAY Y03 data set is the preferred data source. It is the most recent, comprehensive
longitudinal data with four years of surveys post-school. A four year period provides quite
a considerable length of time to examine post-school experiences, and so may minimise the
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Youth Transitions Evidence Base: 2012 Update
influence of short term or one-off events on the results. LSAY Y98 is also examined in the
context of transitions from post-school study, with this data providing for the tracking of
people for three years after post-school study.
A range of data is available, but longitudinal data sets have the advantage of tracking
individuals over time. Annual surveys may, for example, show 10% are unemployed at a
point in time and 10% of that group are still unemployed a year later. Yet the implications
of such an outcome can be quite different depending on whether those 10% are the same
individuals, or different individuals from that group. The former may signal real problems
in the labour market for those individuals, while the latter may be consistent with
‘frictional’ unemployment as people move in and out of jobs depending on the overall
sources of demand in the economy. Longitudinal surveys allow for such outcomes to be
reported.
In short, the advantages of LSAY Y03 as a primary source are that it:

provides longitudinal data;

allows for school leavers to be tracked for at least four years after school (with LSAY
Y98 tracking people for three years following post-school study);

is a national survey;

has a large sample size; and

has been specifically designed to examine youth transition issues, and hence it collects
information on a range of relevant characteristics.
Accordingly it is the primary data source examined for this report, though data from a
range of other sources is also used (in some cases to report on characteristics which might
not be covered by LSAY).
The LSAY results are weighted to make the remaining sample representative of the original
LSAY Y03 sample group. This should largely adjust for any potential sample bias where
those with less successful outcomes may be more likely to drop out of the annual
interviews. It may however have a very small under-reporting of unsuccessful outcomes as
the sample is drawn from students who were initially aged 15 in 2003. This would not
capture a very small number of young people who leave school before age 15, and who
would be more likely to have unsuccessful outcomes.
The weights that have been applied allow the sample to be compared from one year to the
next. The weights are adjusted each year to allow for attrition of the survey group as a
whole and higher rates of attrition within subgroups. These weights have been defined and
provided by the NCVER to make the remaining sample representative of the original LSAY
Y03 sample group.
2.4 Definitions of school transitions
The definitions used for school transitions and post-school study transitions differ a little
from each other. This section describes school transitions, while the next section describes
post-school study transitions.
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Youth Transitions Evidence Base: 2012 Update
Figure 2.1 provides a flow chart of possible transition outcomes for those leaving school,
focusing on the situation one year after school, and the sum of experiences over four years
(representing four LSAY surveys).
Cumulative outcomes shown on these figures represent the sum of experience over the
point in time responses from the annual surveys (over four surveys for post-school
transitions). The ordering of outcomes over time does not matter for the definitions here.
Except for ‘part-time work and part-time study (concurrently)’, references to a combination
of activities (such as work and study) do not imply work and study at the same time –
rather, it is work at one point in time and study at a different point in time from among the
annual surveys.
As a variation to the analysis described above where part-time work may be seen as part of
a poor transition, the LSAY survey allows for further analysis of part-time work. In
particular, those working part-time are asked whether they are seeking further work. That
allows for separate identification of part-time (satisfied) – those who are working part-time
and are not seeking additional work or additional hours, and part-time (unsatisfied) – those
who are working part-time but would like to work more hours than they currently do.
There is a risk that such an approach captures some unmotivated individuals into the part
time work (satisfied) criteria, who are working only a handful of hours per week but are
happy with that, where those individuals are not forming enough of an attachment to the
labour market to hold them in good stead later in life. As such, these individuals have
generally been classified as a mixed outcome. An alternative criteria to examine part time
work could be a threshold of hours worked per week, eg. 15 hours (below that benchmark
may be seen as inadequate; above the benchmark as adequate). That would see such
unmotivated individuals instead classified within a category which forms a poor transition
outcome.
By the same token, using a criteria for splitting part-time work where the individual is
satisfied may allow for greater flexibility in classifying to suit individual circumstances. For
example, an individual who is caring for children, but is also working part-time may be
working all the hours they think they can manage in their individual circumstance (and
hence be satisfied), even though that may be below a particular benchmark.
Hence the approach of splitting part-time work into part-time (satisfied) and part-time
(unsatisfied) has been adopted here, though it would also be feasible to perform a similar
set of analyses by splitting part-time work by an ‘hours of work’ threshold.
The broad categories of outcomes used through this report are ‘good transitions’, ‘mixed
outcomes’ and ‘poor transitions’, with some sub-sets of these categories also shown in
Figure 2.1. The specific definitions applying to these categories are shown below.
Note that at any point in time, individuals may be doing more than one thing. Where that
is the case, for that survey point individuals are classified according to the following
hierarchy of most important activity:
1.
Full time study at or above Certificate III
2.
Full-time work
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Youth Transitions Evidence Base: 2012 Update
3.
Part-time work and part-time study at or above Certificate III (concurrently)
4.
Full time study below Certificate III
5.
Part-time work (satisfied)
6.
Part-time study
7.
Part-time work (unsatisfied)
8.
Unemployed
9.
Not in the labour force
2.4.1
Good transition
For transitions from school, individuals making good transitions are those who have mainly
been engaged in any of the top three activities noted (full-time study at or above Certificate
III, full-time work, or a combination of part-time work and part-time study at or above
Certificate III). Those with three out of four or four out of four observations in these
categories are classified as having made a good transition.
Figure 2.1 shows four components within good transitions which are defined as follows:
Full-time study – those who at every survey are engaged in full-time study at or above
Certificate III. People undertaking an apprenticeship or traineeship which involves both
work and study at or above Certificate III are shown here. If individuals are also
undertaking additional full-time work, part-time work or part-time study, they are still
classified here, as long as they are undertaking full-time study at or above Certificate III at
every survey point.
Full-time work – those who at every survey are engaged in full-time work (which is
classified as more than 30 hours of work a week). If individuals are also undertaking
additional part time work or part-time study, they are still classified here, as long as they
are undertaking full-time work at every survey point.
Part-time work and part-time study – those who at every survey are engaged in part-time
work (which is classified as between 1 and 30 hours of work a week) as well as part-time
study at or above Certificate III at the same time. Of these individuals engaged in part-time
work, some will be satisfied with their hours, while some will be unsatisfied and seeking
additional work or hours. However, both are included within this category, so long as they
are also engaged in part-time study at or above Certificate III at the same time.
Full-time work or full-time study – those who at every survey are engaged in full-time work
or full-time study.
Fully engaged in study and work (other) – those who at every survey (or every survey
except for one) are fully engaged in either full-time study at or above Certificate III, full time
work, or part-time work at the same time as part-time study at or above Certificate III, but
they are not included within one of the above categories. For one survey point they may be
classified to one of the mixed or poor transition criteria – full-time study below Certificate
III, part time work (satisfied), part-time study, part-time work (unsatisfied), unemployed or
not in the labour force.
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2.4.2
Mixed outcomes
This report classifies some individuals as having recorded mixed outcomes. These people
have not made a poor transition over four years of observations with some successful
labour market or further study.
The term is applied where an individual over four years for school leavers has two
observations from the annual surveys where they are unemployed, not in the labour force
or engaged in part-time work (where they have been seeking additional work or additional
hours). These individuals have had some success in meaningful work or full time study but
it has also been mixed with some experience of being detached from the labour market.
In addition, those who are only undertaking part-time study are also seen as potentially at
risk. That may particularly be the case for those who change between different part-time
study courses over time (while a continuous course of part-time study may be seen as
offering greater purpose). Figure 2.1 shows the following categories of mixed outcomes.
Full-time entry-level study – those who at every survey are engaged in full-time study
below Certificate level III. While full-time study would generally be regarded as a good
outcome, individuals engaged in only entry-level study over a long period of time may be at
risk of not sufficiently developing their skills for future entry into the labour force.
Part-time work (satisfied) – those who at every survey are engaged in part-time work
(where have not been seeking additional work or additional hours). These individuals are
solely engaged in part-time work, and are not studying full-time or part-time at above
Certificate III level at the same time.
Part-time study – those who at every survey are engaged in part-time study. While
part-time study would generally be seen as enhancing skill development, there may be a
risk that some individuals who only engage in courses of part-time study over a long period
of time do not engage with the labour force.
Other mixed outcome transition paths – Excluding the transition paths above, a number of
other transition paths exist, reflecting combinations of criteria. These are included within
this category.
2.4.3
Poor transition
This definition isolates those who over quite a considerable length of time have had little or
no experience in the labour market. The term is applied where an individual over four
years for school leavers has three or four observations from the annual surveys where they
are unemployed, not in the labour force or engaged in part-time work (where they have
been seeking additional work or additional hours). The following categories are shown in
Figure 2.1.
Part-time work (unsatisfied) – those who at three or four surveys are engaged in part-time
work (which is classified as between 1 and 30 hours of work a week) and they are seeking
additional work or additional hours. They are not undertaking any study.
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Unemployed – those who at three or four surveys are unemployed (seeking work but
unable to secure it). They are not undertaking any study.
Not in the labour force (NILF) – those who at three or four surveys are not in the labour
force (not working and not seeking work). They are not undertaking any study.
Combination of poor transition outcomes – those who at three or four surveys are in one
of the above categories, but not exclusively in any of the categories.
2.4.4
Initial at risk group
Figure 2.1 notes an ‘initial at risk’ group who one year after school are either unemployed,
not in the labour force or only in part-time work (where they have been seeking additional
work or additional hours). Given this initial post-school experience, there would be a
notable risk that members of this group may end up making poor transitions. However, for
some of them their ‘initial at risk’ status would be explained by factors such as travel or
other voluntary temporary withdrawal from the labour force or study.
The one year definition for ‘initial at risk’ allows some comparison of LSAY Y03 data with
more contemporary data sources, such as the ABS Survey of Education and Work and
surveys of school leavers at the state-level, which examine transitions for a shorter period
of time post school.
Similarly, Figure 2.1 also includes an ‘initial fully engaged’ group who one year after school
are fully engaged in work, study or a combination of work and study.
2.4.5
Changes to definitions used in 2006 report
Transitions from school were defined in a similar, albeit slightly different way in Access
Economics (2006) which analysed school transitions for the LSAY Y98 cohort.
As can be seen from Table 2.2, the changes from the 2006 report are that (i) part-time work
(satisfied) has been shifted from a good outcome to a mixed outcome (ii) part-time work
and part-time study at or above Certificate III (concurrently) is added as a good outcome,
when previously it would have been classified as a good outcome if the individual was
satisfied with their working hours and as a mixed outcome otherwise (iii) full-time study
below Certificate III has been shifted from a good outcome to a mixed outcome. A change
has also been made to the classification of those undertaking part-time study at three out
of four survey points – these individuals were previously classified as experiencing a good
transition, but are now classified as a mixed outcome.
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Table 2.2: Classification of activities – changes from 2006 report
2012 Activity
2012 Classification*
2006 Activity
2006 Classification*
1. Full time study at or
above Certificate III
Good
1. Full time study
Good
2. Full-time work
Good
2. Full-time work
Good
3. Part-time work and
part-time study at or
above Certificate III
(concurrently)
Good
3. Part-time work
(satisfied)
Good
4. Full time study
below Certificate III
Mixed
4. Part-time study
Mixed
5. Part-time work
(satisfied)
Mixed
5. Part-time work
(unsatisfied)
Poor
6. Part-time study
Mixed
6. Unemployed
Poor
7. Part-time work
(unsatisfied)
Poor
7. Not in the labour
force
Poor
8. Unemployed
Poor
9. Not in the labour
force
Poor
* Classification if undertaking the activity at every survey point.
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Figure 2.1: Transitions from school
2003 cohort
Outcome 1 year after school
Initial fully engaged group
Full-time study at or above Cert III
Full-time work
Part-time work and part-time study
(concurrently)
School leavers
analysed by:
Year 12 completers
Non year 12 completers
Full-time entry level study
Part-time work
(satisfied)
Part-time study
Part-time work
(unsatisfied)
Unemployed
NILF
Initial at risk group
Deloitte Access Economics
Cumulative outcome over 4 years
Full-time study at or above Cert III
Good transition
Full-time work
Good transition
Part-time work and part-time study (concurrently)
Good transition
Full-time work or full-time study
Good transition
Fully engaged in study and work (other)
Good transition
Full-time entry level study
Mixed outcomes
Part-time work (satisfied)
Mixed outcomes
Part-time study
Mixed outcomes
Other mixed transition outcomes
Mixed outcomes
Part-time work (unsatisfied)
Poor transition
Unemployed
Poor transition
Not in the labour force
Poor transition
Combination of poor transition outcomes
Poor transition
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Youth Transitions Evidence Base: 2012 Update
2.5 Definitions of post-school study transitions
The definitions used for post-school study transitions are slightly different to those for
school transitions.
Figure 2.2 provides a flow chart of possible transition outcomes for those leaving postschool study, with separate examination of those leaving University, those leaving an
Australian Apprenticeship, and those leaving non-apprenticeship Vocational Education and
Training (VET).
Cumulative outcomes shown on these figures represent the sum of experience over the
point in time responses from the annual surveys (over three surveys following completion
of post-school study). The ordering of outcomes over time does not matter for the
definitions here.
References to a combination of activities (such as work and study) do not imply work and
study at the same time – rather, it is work at one point in time and study at a different point
in time from among the annual surveys.
The broad categories of outcomes used through this report are ‘good transitions’, ‘mixed
outcomes’ and ‘poor transitions’, with some sub-sets of these categories also shown in
Figure 2.2 (those described as ‘short of potential’ are still making a good transition just not
as good in terms of occupation as it might have been). The specific definitions applying to
these categories are shown below.
As with school transitions, individuals may be doing more than one thing at a particular
survey point. For post-school study transitions activities are classified according to the
following hierarchy of most important activity:
1.
Full time study
2.
Full-time work
3.
Part-time work (satisfied)
4.
Part-time study
5.
Part-time work (unsatisfied)
6.
Unemployed
7.
Not in the labour force
The hierarchy above for post-school study transitions is different to the hierarchy for
school transitions.
For post-school study transitions, being fully engaged in work, study or a combination of
work and study is seen as less critical – these individuals have already demonstrated that
they are motivated, having invested the time to gain additional skills after leaving school (a
genuine concern for some school-leavers who are only partially engaged). Therefore,
having shown that they are motivated by undertaking further study, individuals working
part-time and not seeking additional work or hours are now classified as a good transition.
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Youth Transitions Evidence Base: 2012 Update
On the other hand, for post-school study transitions, a combination of part-time work and
part-time study is not necessarily a good outcome. This is because for those completing
post-school study, further study is not necessarily a good transition if they have chosen this
path because their first qualification left them unable to find a suitable job. Instead, such
individuals are classified based on whether they are seeking additional work or hours –
those who are working part-time and studying part-time because they were unable to find
a full-time job would therefore be classified as a poor transition.
Finally, distinctions between entry-level study and higher-level study are no longer relevant
and have been removed.
To summarise, for school transitions, being engaged in post-school study on a part-time
basis was given greater weight in determining a good transition. For post-school study
transitions, being engaged in part-time work is given greater weight in determining a
good transition.
2.5.1
Analysis by occupation
The analysis of post-school study introduces a consideration of occupation as part of
defining transitions, with a view to highlighting those who may be working in an occupation
which is seemingly below the skill set of their qualifications. This is described here as
working in a skill mismatch occupation. Those working in an occupation with a skill level
commensurate with or above their qualifications are described as working in a skill
appropriate occupation. These concepts are relevant for the productivity and skill shortage
discussions later in this report.
The occupation specific dimension in analysing transitions is only reported for those who
have undertaken post-school study. That is where one can fairly readily identify a set of
occupations where the skill level required appears to be below that of the qualification
held. Defining which occupations are commensurate with school level education and which
are below that level of skills is a more marginal choice, and so is not attempted here.
2.5.2
Good transition
Individuals making good transitions are those who have mainly been engaged in any of the
top three activities noted (full-time study, full-time work, part-time work (satisfied). For
post-school study either three out of three or two out of three observations in these
categories defines a good transition. Figure 2.2 shows the following components within
good transitions which are defined as follows:
Full-time study – those who at every survey are engaged in full-time study. People
undertaking an apprenticeship or traineeship which involves both study and work are
shown here. If individuals are also undertaking additional full-time work, part-time work or
part-time study, they are still classified here, as long as they are undertaking full-time study
at every survey point.
Work in skill appropriate occupation – those who at every survey are working in a skill
appropriate occupation, either in full-time work or engaged in part-time work where they
are not seeking additional work or additional hours. This is classified as a good transition
(to potential).
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Mostly work in skill appropriate occupation – those who at every survey except for one
are working in a skill appropriate occupation, either in full-time work or engaged in part
time work where they are not seeking additional work or additional hours. For one survey
point they are classified to one of the poor transition criteria – part time work (unsatisfied),
unemployed or not in the labour force. This is classified as a good transition (to potential).
Study and work (other) – those who at two surveys are in either full time study, full time
work, or engaged in part time work where they are not seeking additional work or
additional hours but are not included within any of the above categories.
Work in skill mismatch occupation - those who at every survey are working in a skill
mismatch occupation, either in full-time work or engaged in part-time work where they are
not seeking additional work or additional hours. This is classified as a good transition (but
short of potential).
Mostly work in skill mismatch occupation - those who at every survey except for one are
working in a skill mismatch occupation, either in full-time work or engaged in part time
work where they are not seeking additional work or additional hours. For one survey point
they are classified to one of the poor transition criteria – part time work (unsatisfied),
unemployed or not in the labour force. This is classified as a good transition (but short of
potential).
2.5.3
Mixed outcomes
This report classifies some individuals as having recorded mixed outcomes. For post-school
study transitions these individuals have been engaged in part-time study for two or three
survey years. For one survey year they may have been classified to one of the good or poor
transition criteria.
If an individual had also been engaged in one of the good transition activities concurrently
(full-time study, full-time work, part-time work (satisfied)), they would be classified under
the good transition activity for that year. Therefore, someone working full-time who
commenced a postgraduate course part-time would be classified under full-time work.
Figure 2.2 shows three categories of mixed outcomes.
Part-time study – those who at every survey are engaged in part-time study. While
part-time study would generally be seen as enhancing skill development, there may be a
risk that some individuals who only engage in courses of part-time study over a long period
of time do not engage with the labour force.
Mostly part-time study with one good year – those who at two surveys are engaged in
part-time study but for one survey point they are classified to one of the good transition
criteria – full time study, full time work, part time work (satisfied).
Mostly part-time study with one bad year – those who at two surveys are engaged in
part-time study but for one survey point they are classified to one of the poor transition
criteria – part time work (unsatisfied), unemployed or not in the labour force.
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Youth Transitions Evidence Base: 2012 Update
2.5.4
Poor transition
This definition isolates those who over quite a considerable length of time have had little or
no experience in the labour market. The term is applied where an individual over three
years for post-school study leavers has two or three observations from the annual surveys
where they are unemployed, not in the labour force or engaged in part-time work (where
they have been seeking additional work or additional hours). The following categories are
shown in Figure 2.2.
Work in skill appropriate occupation and poor transition outcomes – those who for one
survey are working in a skill appropriate occupation, either in full-time work or engaged in
part time work where they are not seeking additional work or additional hours, but for two
survey points they are classified to one of the poor transition criteria – part time work
(unsatisfied), unemployed or not in the labour force.
Work in skill mismatch occupation and poor transition outcomes - those who for one
survey are working in a skill mismatch occupation, either in full-time work or engaged in
part time work where they are not seeking additional work or additional hours, but for two
survey points they are classified to one of the poor transition criteria – part time work
(unsatisfied), unemployed or not in the labour force.
Study and poor transition outcomes - those who for one survey are in full-time study, or
part-time study, but for two survey points they are classified to one of the poor transition
criteria – part time work (unsatisfied), unemployed or not in the labour force.
Part-time work (unsatisfied) – those who at three surveys are engaged in part-time work
(which is classified as between 1 and 30 hours of work a week) and they are seeking
additional work or additional hours. They are not undertaking any study.
Unemployed – those who at three surveys are unemployed (seeking work but unable to
secure it). They are not undertaking any study.
Not in the labour force (NILF) – those who at three surveys are not in the labour force (not
working and not seeking work). They are not undertaking any study.
Combination of poor transition outcomes – those who across three surveys are in one of
the three poor transition criteria at each survey (part-time work (unsatisfied), unemployed,
not in the labour force), but are not exclusively in any of the categories.
2.5.5
Changes to definitions used in 2006 report
The definitions used for transitions from post-school study are largely unchanged from
Access Economics (2006).
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Table 2.3: Classification of activities – changes from 2006 report
2012 Activity
2012 Classification*
2006 Activity
2006 Classification*
1. Full time study
Good
1. Full time study
Good
2. Full-time work
Good
2. Full-time work
Good
3. Part-time work
(satisfied)
Good
3. Part-time work
(satisfied)
Good
4. Part-time study
Mixed
4. Part-time study
Mixed
5. Part-time work
(unsatisfied)
Poor
5. Part-time work
(unsatisfied)
Poor
6. Unemployed
Poor
6. Unemployed
Poor
7. Not in the labour
force
Poor
7. Not in the labour
force
Poor
* Classification if undertaking the activity at every survey point.
As can be seen from Table 2.2, there are no changes to the classification of activities
undertaken at every survey point from the 2006 report.
However, transition paths involving different activities over time have been classified
differently. Specifically, those undertaking part-time study for two out of three years are
now recorded as a mixed outcome, when previously they would have been recorded as a
good outcome.
Further, those recorded as either part-time work (unsatisfied),
unemployed, or not in the labour force for two out of three years are now classified as a
poor transition, when previously they would have been classified as a mixed outcome.
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Youth Transitions Evidence Base: 2012 Update
Figure 2.2: Transitions from post-school study
1998 cohort
Post-school study participants
analysed by:
University completers
University leavers
Non apprenticeship VET completers
Non apprenticeship VET leavers
Aust. Apprenticeship completers
Aust. Apprenticeship leavers
Deloitte Access Economics
Cumulative outcome over 3 years
Full-time study
Good transition
Work in skill appropriate occupation
Good transition
Mostly work in skill appropriate occupation
Good transition
Study and work (other)
Good transition
Work in skill mismatch occupation
Good transition
(but short of potential)
Mostly work in skill mismatch occupation
Good transition
(but short of potential)
Part-time study
Mixed outcomes
Mostly part-time study with one good year
Mixed outcomes
Mostly part-time study with one bad year
Mixed outcomes
Study and poor transition outcomes
Poor transition
Work in skill appropriate occupation and poor transition outcomes
Poor transition
Work in skill mismatch occupation and poor transition outcomes
Poor transition
Part-time work (unsatisfied)
Poor transition
Unemployed
Poor transition
Not in the labour force
Poor transition
Combination of poor transition outcomes
Poor transition
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Youth Transitions Evidence Base: 2012 Update
3 Transitions from school
This chapter presents profiles of youth transitions from school, following the transition
paths discussed in Chapter 2. It contains an overview of transitions based on LSAY data
across the full samples available, and provides an analysis of transitions by groups with
different characteristics (sub-sets of the broader LSAY sample). Further details from this
analysis by specific characteristics are provided in Appendix A.
Profiles of transitions from school are derived from the LSAY Y03 data set. The sample size
for the full cohort (the number of people who participated in the first year of the survey in
2003 when they were aged 15) was 10,370. The analysis in this chapter is limited to those
individuals who were observed for four consecutive years after leaving school. This reduces
the initial sample size to 5,571 individuals due to sample attrition and the small number of
individuals who left school after 2006 (and thus had not had four consecutive years after
leaving school in the LSAY data).
3.1 All school leavers
Table 3.1 presents results for all school leavers in the survey, with the data representing the
share of this group who are on the respective transition paths.
Table 3.1: Transition from school – all school leavers
Year 1
Good transition
76.6%
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
48.1%
27.6%
0.9%
Cumulative 4 years
Good transition
82.0%
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
20.3%
12.5%
21.8%
0.0%
27.5%
Mixed transition
8.4%
Mixed transition
14.0%
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
1.1%
6.6%
0.6%
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
0.0%
0.0%
0.1%
13.9%
Initial at risk
15.0%
Poor transition
4.0%
Part-time work (unsatisfied)
Unemployed
Not in the labour force
5.1%
6.1%
3.8%
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
0.2%
0.2%
3.6%
Note: Sample size is 5,571.
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The table shows that for year 1 (the first year after having left school):

Around 77% of school leavers were fully engaged in work and study. Almost half were
studying full-time at or above Certificate III level. Note that this definition includes
those undertaking full-time apprenticeships or traineeships. It is also a classification by
their main form of activity – some of these individuals may well have been also working
part-time or even full-time.

Some 15% of people were seen as at risk of a poor transition. That is, one year after
school they are either unemployed, not in the labour force, or employed part-time in a
position where they are seeking additional hours or additional work. By definition,
these people are not studying.1
The cumulative outcomes over four years represent the sum of experience across four
annual surveys after having left school. Key points from Table 3.1 are:

Some 82% of the group have a good transition, and are fully engaged in work and
study in at least three out of four years after leaving school. Those who have done
full-time study in each year accounted for around a quarter of these good transitions. A
transition pathway involving either full-time study or full-time work in each year was
also common, while those undertaking only full-time work in each of the four years
comprised a smaller, but still very significant portion of school leavers. In total, around
55% of school leavers were fully engaged in work and study in each of the four years
after leaving school.

Only 4% of this group are defined as having a poor transition. Note that the definition
of poor transition is that an individual is either unemployed, not in the labour force, or
under-employed (i.e. working part-time and seeking additional hours or additional
work) for either three or four of the four surveys.

While the low proportion from this group experiencing a poor transition is a good
result, an additional 14% of this group is defined as experiencing a ‘mixed outcome’.
That is, they may be classified to one of the poor transition criteria (unemployed, not in
the labour force, or part-time employed (unsatisfied)) for two of the four surveys. The
transition pathways captured within this category are varied, and may include a couple
of years of poor and good transitions, or various combinations of poor, mixed (i.e. parttime work (satisfied), part-time study, or low level full-time study), and good transition
years.

The proportion of the group making a good transition across four years (82%) is
higher than for the first year after leaving school (77%). Similarly, the proportion
making poor transitions across four years (4%) is lower than the group defined as
initially at risk (15%). This indicates some transition success is achieved over time for
the LSAY Y03 cohort as a whole.
The majority of the LSAY Y03 cohort would have left school in 2005 for Year 12 completers
and between 2003 and 2004 for early leavers, at a time of fairly low unemployment (4.8%
average in 2006). Earlier cohorts such as the LSAY Y98 cohort faced a less supportive macro
1
The year 1 poor transition outcomes reflect those of a particular cohort and then tracks those same individuals
for future years. Chart 5.1 later in the report shows aggregate labour force status in May 2011 for all school
leavers in 2010 from the ABS Survey of Education and Work. That chart shows that around 8% of school leavers
in 2010 were unemployed and not studying in May of the following year and a further 9% were not in the labour
force and not studying.
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Youth Transitions Evidence Base: 2012 Update
environment when completing Year 12, with the unemployment rate averaging 6.4% in
2002. Comparing the results one year after leaving school for the LSAY Y03 cohort with
those of the LSAY Y98 cohort presented in the 2006 report, the LSAY Y03 cohort had 2%
more in full-time work, 1% more in part-time work (satisfied), but almost 6% fewer in fulltime study. The initial at risk cohort was 2% higher for the LSAY Y03 cohort, with 1% more
unemployed and 1% more not in the labour force compared with the LSAY Y98 cohort.
Cumulative four year outcomes for the LSAY Y03 cohort are likely to have been affected by
the fallout from the GFC from mid-2008. While the cumulative four year outcomes of
those who left school in 2003 and 2004 would not have been substantially affected by the
GFC, the majority who left school in 2005 and 2006 would have affected by the GFC in their
first four years after school. The unemployment rate averaged 5.6% in 2009, although fears
of higher unemployment and recession were widespread at the time and may have
influenced decisions to undertake further study as opposed to joining the labour force.
Comparing the four year outcome against the LSAY Y98 cohort (who faced an average
unemployment rate of 5.0% in 2005), 3% more of the LSAY Y03 cohort had been in full-time
study in all four years, while 2% fewer of the LSAY Y03 cohort had been in full-time work in
all four years. The proportion making poor transitions was 1% higher for the LSAY Y03
cohort.
As discussed in Chapter 2, transition paths have been defined differently for the LSAY Y03
cohort, compared with the LSAY Y98 cohort. The results discussed above are unlikely to
have been affected by these definitional changes, but a comparison of other transition
paths would be affected more significantly. Small changes in the method of data extraction
were also made for the analysis of the LSAY Y03 cohort. Small differences in the results
may therefore not be statistically significant.
3.2 Year 12 completers and non-Year 12
completers
Table 3.2 and Table 3.3 present the same information for those who left school before year
12 and those who completed year 12 respectively. As can be seen from the sample sizes
indicated below Table 3.2 and Table 3.3, of the sample of 5,571 individuals who were
available for four consecutive years after leaving school, 920 were early leavers and 4,260
completed year 12. Thus 17% of the sample comprised early school leavers.
The propensity for poor outcomes for those who have left school prior to year 12 is
substantially higher than for those who have completed year 12 – they are about four
times as likely:

25.9% of early leavers are initially at risk, compared with 12.7% of year 12 completers.

11.1% of early leavers have poor transitions over four years, compared with 2.5% of
year 12 completers.

23.7% of early leavers have mixed outcomes over four years, compared with 11.9% of
year 12 completers.
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Table 3.2: Transition from school – year 12 completers
Year 1
Good transition
79.8%
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
53.7%
25.2%
0.9%
Cumulative 4 years
Good transition
85.6%
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
22.5%
10.7%
23.5%
0.0%
28.9%
Mixed transition
7.7%
Mixed transition
11.9%
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
0.4%
6.8%
0.5%
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
0.0%
0.0%
0.1%
11.8%
Initial at risk
12.7%
Poor transition
2.5%
Part-time work (unsatisfied)
Unemployed
Not in the labour force
4.8%
4.5%
3.4%
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
0.1%
0.2%
2.2%
Note: Sample size is 4,651.
Table 3.3: Transition from school – early leavers
Year 1
Good transition
61.7%
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
21.8%
39.0%
0.9%
Cumulative 4 years
Good transition
65.2%
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
10.1%
20.9%
13.5%
0.0%
20.7%
Mixed transition
11.8%
Mixed transition
23.7%
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
4.5%
6.0%
1.4%
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
0.0%
0.0%
0.0%
23.7%
Initial at risk
25.9%
Poor transition
11.1%
Part-time work (unsatisfied)
Unemployed
Not in the labour force
6.7%
13.4%
5.8%
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
0.5%
0.3%
10.3%
Note: Sample size is 920.
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Youth Transitions Evidence Base: 2012 Update
For year 12 completers, over 50% go on to full-time study of some form in the year after
completing school – for early leavers it is closer to 20% of the group. As one would expect,
year 12 completers are also much more likely to be studying for the full four years after
school (22.5% of year 12 completers) than are early leavers (10.1% of early leavers). How
these people transfer to the labour market once they complete their study is investigated
with the LSAY Y98 data in Chapter 4.
3.3 Gender
Chart 3.1 shows the key outcomes achieved over the cumulative four year post-school
period by gender. It shows that females who are early leavers from school tend to have
poorer transitions than do males. For early leavers, only 48% of females are categorised as
having a good transition, while for male early leavers the equivalent figure is 76%.
There are a number of possible reasons for these differences in transition outcomes
between male and female early leavers. While this report has not sought to explore these
reasons in detail, one of the possible reasons for the improved outcomes of male early
school leavers is that they are more likely to complete an apprenticeship. Of those early
school leavers still seen in the final year of the LSAY03 survey (2010), 45% of males had
completed an apprenticeship compared to 26% of females. Another possible reason for the
difference in outcomes among male and female early leavers is that female early leavers
may take a more active role in caring for children than male school leavers. In the final year
of the LSAY03 Survey (2010), 26% of female early leavers had dependent children
compared to 6% of female year 12 completers.2 Further research should be undertaken to
explore the relative importance of these and other reasons in explaining the differences in
transition outcomes between male and female early school leavers.
Transition from school for Year 12 completers is much more similar between the genders.
While there is still a higher proportion of males making a good transition, the difference
with females is small.
2
In many cases these children were born after the individuals had left school so this statistic should not be
interpreted as indicating that 26% of females who left school early had dependent children.
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Chart 3.1: Transition from school by gender
3.4 Participation in part-time work while at
school
The evidence from the LSAY Y03 cohort is that working part-time while at school is
associated with better transitions upon leaving school.
This is most evident for early leavers. Of the students who had no part-time job only 49%
experienced a good transition, and some 17% experienced a poor transition. In contrast, of
the students who had a part-time job while at school around 77% experienced a good
transition and 7% a poor transition.
For those who complete Year 12, the discrepancy is much less but still apparent, with those
working part-time while still at school experiencing slightly better transitions after leaving
school.
These findings suggest that work experience gained at a young age assists greatly as young
people transition from school. This is certainly likely to be the case, with the work
experience gained helping to improve skill levels and also making it easier to obtain other
work, including full-time work, in the future. To some extent, the discrepancy in postschool outcomes for the two groups being examined here will also reflect underlying
differences in motivation - many of those who take up a part-time job while still at school
will be more motivated and driven than those who do not, and this will also be reflected in
outcomes after school.
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Chart 3.2: Transition from school for those working part-time at school
3.5 Participation in VET while at school
VET in Schools programs have increased participation in formal VET while at school in
recent years.
As Chart 3.3 shows, early leavers who have participated in VET while at school experience a
higher rate of good transitions after leaving school (68%) than early leavers who have not
participated in VET (64%). However, they also experience a higher rate of poor transitions
(14%) compared with those early leavers that did not participate in VET while at school
(11%). This makes it difficult to draw a definitive conclusion on participation in VET in
schools for early leavers.
For Year 12 completers, however, those who do not participate in VET while at school
clearly experience better transitions than those who do. This reflects the more academic
inclination of the former group, many of whom go onto full-time tertiary study and a good
post-school transition - they are less likely to participate in vocationally-oriented VET
courses while at school.
VET in Schools programs are well regarded by many experts however, with some evidence
suggesting that they help retention rates for less academically inclined students who may
otherwise drop out of school early.
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Chart 3.3: Transition from school by participation in VET in school
3.6 Indigenous Australians
Chart 3.4 shows that young Indigenous Australians experience much poorer transitions
from school than non-Indigenous Australians:

Only 65% of Indigenous Australians experience good transition outcomes, compared
with 82% for non-Indigenous Australians.

Around 11% of Indigenous Australians experience poor transition outcomes, compared
to 4% for non-Indigenous Australians.
The results for Indigenous Australians are based on a small (though not insignificant)
sample of 210 students . These 210 students reflect those who remain in the sample for
four consecutive years after leaving school (i.e. four consecutive post school survey
responses are available for each of the individuals). However, it is worth noting that many
Indigenous young people leave school before Year 9 and are thus not captured in the LSAY
sample which means that some caution must be used in interpreting the results.
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Chart 3.4: Transition from school for indigenous Australians
3.7 Those with a disability
Chart 3.5 shows that there is a big difference in transitions outcomes for those with a
disability.
In particular, only around 71% of those with a disability make a good transition, compared
with 83% for those without a disability. For those with a disability, there is a much higher
rate of mixed transitions, and around 6% of those with a disability experience a poor
transition, compared with 4% for the population without a disability.
As with Indigenous Australians, the sample size for those with a disability is small, at just
329 students. Each of these 329 students are observed for four consecutive years after
leaving school..
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Chart 3.5: Transition from school for those with a disability
3.8 Migrants
Chart 3.6 displays the transition experiences of migrants, who are defined as students in
the survey group that are overseas born.
The data suggests that in general migrants who are in school from at least age 15 have
much the same outcomes as locally born students. Of those students born overseas (some
of whom would have undertaken a reasonable portion of their early education overseas,
including in non-English speaking countries), 81% made a good transition and 5% made a
poor transition compared with 82% and 4% for Australian-born students, respectively.
Chart 3.6: Transition from school for migrant/Australian born
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3.9 Literacy and numeracy
Levels of literacy and numeracy are assessed in the LSAY Y03 survey, with students selfassessing their English and maths abilities. The categories used are:
1.
Very good;
2.
Better than average;
3.
Average,
4.
Not very good, and
5.
Very poor.
The chart below shows that the rate of good transitions is clearly higher for those
individuals who have stronger levels of literacy and numeracy.
Those in the top two categories for literacy and numeracy experience similarly high rates of
good transition from school. The rate of good transitions is also quite high for the third
literacy and numeracy category (‘average’). The rate of good transitions drops away much
more markedly for the bottom two categories (‘not very good’ and ‘very poor’).
The highest numeracy levels are associated with better transition outcomes than the
highest literacy levels, although the difference is minor and many individuals are likely to be
in both groups.
Chart 3.7: Transition from school by literacy and numeracy
3.10 Location
At the time of the initial survey, around 70% of participating schools were located in a
metropolitan area, 27% in a provincial area and 3% in a remote area. The participating
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schools were classified with respect to the MCEETYA schools geographic location
classification. For this report, only the broadest categories are used:

Metropolitan – mainland state capital cities and major urban districts;

Provincial- provincial cities and other non-remote provincial areas; and

Remote – remote and very remote areas.
As Chart 3.8 shows location makes little difference to the overall rate of good transitions
achieved. Of the three locations, those from a metropolitan area had a marginally higher
rate of good transitions. However, those from remote or very remote areas had notably
lower rates of poor transition outcomes (1%) compared with those from metropolitan or
provincial areas (both 4%), and slightly higher mixed transition outcomes.
It is worth noting that an individual’s location is recorded at age 15 and does not reflect any
move made from a remote area to a metropolitan zone for upper schooling. Moreover,
after leaving school the individual may be working or studying in a different location. Much
other reporting of labour force status by region refer to the region in which the young
person is living at the time of the survey, and that would tend to show poorer outcomes in
regions where jobs are less abundant.
Chart 3.8: Transition from school by location
3.11 Socio-economic status
There are a number of possible measures which could be used as a proxy for socioeconomic status. One measure which forms a reasonably well known standard is the
highest international socio-economic index of occupational status or HISEI. The index is
derived from the occupational status of the individual’s parents, and is based on either the
father or mother’s occupations, whichever is the higher. This index was used in the OECD’s
Programme for International Student Assessment (PISA) 2003, which was integrated with
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Youth Transitions Evidence Base: 2012 Update
the first survey wave for the LSAY Y03 cohort. A higher HISEI indicates a higher level of
occupational status.3
For this project, individuals were grouped into three categories to investigate the impact of
socio-economic status on transitions:
1.
High SES: HISEI of 67+
2.
Middle SES: HISEI of 50-66
3.
Low SES: HISEI of 0-49
The results in Chart 3.9 show only marginal differences between the high SES group and the
middle SES group, with the middle group having slightly more poor transitions. However,
significant differences are apparent for the low SES group, which has both a substantially
lower rate of good transitions and a higher rate of mixed and poor transitions.
Chart 3.9: Transition from school by socio-economic status
3
The OECD’s PISA 2003 Technical Report describes the calculation of the HISEI as follows: Occupational data for
both the student’s father and student’s mother were obtained by asking open ended questions. The responses
were coded to four-digit ISCO codes (ILO, 1990) and then mapped to the international socio-economic index of
occupational status (ISEI) (Ganzeboom et al., 1992). The highest occupational status of parents (HISEI)
corresponds to the higher ISEI score of either parent or to the only available parent’s ISEI score. A higher ISEI
score indicates higher levels of occupational status.
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4 Transitions from post-school study
This chapter examines profiles of transitions following post-school study based on the LSAY
Y98 dataset. For the analysis presented in this report, outcomes of individuals are tracked
for three years following a first course of post-school study.
The focus here is on examining how those people who go down the various paths of post
school study perform after they either obtain their first qualification, or if they do not
complete the initial post-school study they commenced, how they perform after they drop
out of their first post-school course of study.
The information presented here is a complement to the LSAY Y03 analysis in the previous
chapter, with LSAY Y03 the primary data source for this report. In this report, for
transitions from post-school study (using LSAY Y98), individuals are tracked for a period of
three years, while for transitions from school (using LSAY Y03) individuals were tracked for
four years.
The outcomes discussed in this chapter and the supporting tables in Appendix A reflect the
transition map discussed earlier and set out in Figure 2.2. One key difference in
terminology compared to the analysis of transitions from school is the reporting of
transition to a ‘short of potential’ group. These are people who are classified within the
group making a good transition, but are working in an occupation which is below the skill
level which might be expected from their qualification. Occupations are classified on the
last survey point.
Chart 4.1 presents the occupational profile of post-school study completers who have made
the transition to work (either full-time or part-time satisfied) by 1 digit Australian and New
Zealand Standard Classification of Occupations (ANZSCO) classification. The classification of
occupation is based on the final survey point (the third year after completing the
qualification). The hierarchy of ANZSCO tends to be in order of skill such that one can pick a
point on the ANZSCO spectrum as a threshold to differentiate skill levels. These thresholds
are shown on Chart 4.1:

For university completers, those working as managers or professionals are seen as
working at the skill level enabled by their qualification, while other occupations are
seen as ‘short of potential.

For apprenticeship completers, we add technicians and tradespersons to the list of skill
appropriate occupations.

For those completing traineeships or other VET, we add all other occupational groups
except labourers to the list of skill appropriate occupations.
Note that there is no ‘short of potential’ threshold for those who embark on post-school
study but do not complete it.
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Chart 4.1: Occupational profile for post-school study completers
Applying these definitions of ‘short of potential’ suggests that of those making the
transition to work following post-school study:

42% of university completers are in occupations which are short of the potential
enabled by their qualification;

21% of apprenticeship completers are working short of potential; and

13% of traineeship completers and 12% of other VET completers are working short of
potential.
In a macro environment of skill shortages this suggests there is a significant latent pool of
skills which is not being fully utilised.
Note that in respect of the above, university completers still have a stronger occupational
profile than for completers of other forms of study. For this measure however we apply a
tougher test for the sort of occupation they are expected to be working in.
Looking at the rate of transitions, Chart 4.2 shows that 96% of university completers make
a good transition to work or further study (adding up those who make a good transition to
their potential with those who make a good transition which is short of potential).
Apprenticeship completers have a similarly high rate of good transitions, with 96% making
a successful transition. That is not particularly surprising given that apprentices are
employed as part of their study, and the strong demand for tradespersons in recent years
has provided employers with a strong incentive to retain apprentices beyond their
apprenticeship period.
Traineeship completers have a slightly lower rate of successful transitions at 89% of those
completing.
The rate of successful transitions for other VET completers is similar to that for traineeship
completers at 91%.
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Chart 4.2: Transition from post-school study – those who complete study
Chart 4.3 shows broad outcomes for those who commence post-school study but do not
complete it.
Around 92% of those who commence university but do not complete end up making a good
transition. This is a much higher rate of good transitions compared with those who drop
out of vocationally oriented training. Some 17% of those who drop out of an
apprenticeship end up making a poor transition or experience mixed outcomes. That rate is
18% for traineeships and for other non-apprenticeship VET courses.
Chart 4.3: Transition from post-school study – those who do not complete study
Overall the results for post-school study transitions for the LSAY Y98 cohort are similar to
the results for the LSAY Y95 cohort presented in the 2006 report. However, the rate of
good transitions was 6% and 4% higher for university and apprenticeship completers
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respectively (including those making good transitions but falling short of potential). Nonapprenticeship VET completers had rates of good transition that were 11% higher than
found for the LSAY Y95 cohort, while traineeship completers did about the same as found
for the LSAY Y95 cohort. Individuals who did not complete their study also saw a slightly
improved rate of good transition compared with that found for the LSAY Y95 cohort – 4%
higher for university drop outs, 10% higher for apprenticeship drop outs, 5% higher for
traineeship drop outs, and 10% higher for those dropping out from other VET study.
For the most part, labour market conditions were better for the LSAY Y98 cohort than the
LSAY Y95 cohort. For example, an individual from the LSAY Y98 cohort who finished Year 12
in 2001 and completed a three year Bachelor degree in 2004 would have faced an average
unemployment rate of 4.7% for the three years following study, i.e. from 2005 to 2007.
The equivalent unemployment rate for an individual from the LSAY Y95 cohort was 5.9%,
i.e. from 2002 to 2004. The improvement in the rate of good transitions for the LSAY Y98
cohort may be reflective of these better labour market conditions.
Further details on these transition rates from post-school study are provided in Appendix A.
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5 Other transition data sources
This chapter examines transition experiences evident in a number of other data sources. A
number of these focus on a more limited period of time post-school (the first year only),
but are more recent. The surveys examined are the following:

ABS Survey of Education and Work

ABS Survey of those not in the labour force

State-based school leaver surveys, including longitudinal surveys

The NCVER Student Outcomes Survey

The Graduate Destination Survey

The Beyond Graduation Survey
5.1 ABS Survey of Education and Work
The ABS Survey of Education and Work (SEW) Cat No 6227.0 covers participation in
education, transition from education to work and current labour force and demographic
characteristics for people aged 15-64. The latest data was collected in May 2011 as a
supplement to the ABS Labour Force Survey. Individuals described as ‘enrolled’ in study
within this survey are persons undertaking a course of study leading to a qualification,
including those in Year 12 or below.
Chart 5.1: School leavers in 2010 by enrolment and labour force status in May 2011
Source: ABS 6227.0
Chart 5.1 shows post-school transitions for people aged 15-24 years who were enrolled in
secondary school in 2010, but were not in May 2011. Of the total of 319,900 school
leavers, around 58% had enrolled in further study, while a further 26% were working but
not studying. That left around 17% of school leavers that were neither working nor
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Youth Transitions Evidence Base: 2012 Update
studying in May 2011 (unemployed or NILF), and at risk of making a poor transition into the
workforce.
Chart 5.2: Labour force status of those studying in May 2011
Source: ABS 6227.0
Chart 5.2 summarises the labour force status of those who were studying in May 2011.
More than half of those enrolled in part time study among the 15-19 year olds and the 2024 year olds were also engaged in full time work. Only a small proportion of these groups
was looking for work (and not able to find it) while large proportions of those in full-time
study were not looking for work.
Chart 5.3: Completers of non-school qualification enrolled in 2010 by labour force status
in May 2011
Source: ABS 6227.0
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Chart 5.3 shows the labour force status in May 2011 of those who had completed the nonschool qualification in which they were enrolled in 2010. For 15-19 year olds, around 65%
were employed in the year after completing their qualification. However, only around 30%
were employed full time, while the proportion unemployed or NILF was a relatively high
35%. In contrast, 20-24 year olds had much better outcomes in the year after completing
their non-school qualification. Around 78% were employed, with over half (52%) employed
full time, while 22% were unemployed or NILF.
Overall, 20-24 year olds show a better transition from their study into full-time work than
do 15-19 year olds, which would reflect more skills developed, greater potential to have
already had labour force experience, and greater maturity.
5.2 ABS survey of those not in the labour force
While the LSAY data shows only a small number of people continuously not in the labour
force for four years post-school, there are a much larger number who are not in the labour
force for considerable periods of time, and contribute to a high share of respondents being
classed as having ‘mixed outcomes’.
The ABS survey on those not in the labour force (Cat No 6220.0) provides insights into the
reasons why some people choose not to work or to look for work. This survey collects
details about whether those not in the labour force wanted to work, reasons why they
were not actively looking for work, their availability for work, and their main activity while
not in the labour force.
The data collected in the 2011 survey shows that there were around twice as many women
aged 15-24 not in the labour force and not studying (120,000) than equivalent men aged
15-24 (62,000).
Around 68% of women aged 15-24 who are not in the labour force and not studying are
engaging in ‘home duties’ or ‘caring for children’ as their main activity. A further 11% cited
‘Own long-term health condition or disability’ and 7% travel as reasons for not being in the
labour force.
For men aged 15-24, 33% cited ‘Own long-term health condition or disability’, 17% cited
travel, and only 13% cited ‘home duties’ or ‘caring for children’.
The above data relate to those who were not in the labour force (whether or not they
wanted to work). Further detail about those not in the labour force who wanted to work,
were available to work, but were not actively looking for work is also provided in the
survey.
Of the 15-24 year olds in this group in 2011 (around 247,000 young people in total), the
most common reason for not actively looking for work was ‘Attending educational
institution’ (155,000), followed by ‘family reasons’, including ‘caring for children’ (24,000).
The number of discouraged job seekers citing reasons such as ‘no jobs at all’ was relatively
low at 11,800 in 2011, although this represented an increase from 6,900 in 2008.
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5.3 State-based school leaver surveys
In addition to the LSAY longitudinal survey which is conducted nationally, a number of
states and territories survey school leavers to examine post-school outcomes within their
jurisdictions. This includes both cross-sectional surveys conducted post-school, as well
longitudinal surveys (the latter of which are conducted by Victoria and Queensland). The
various surveys reported on here use different methodologies and therefore the survey
results are not directly comparable with each other.
5.3.1
New South Wales
The NSW Career Moves Report analysed the post-school destinations of both Year 12
completers and early school leavers one year after they left school. The report was based
on a survey in late 2010 of around 6,100 students who were in Years 10, 11 and 12 in 2009.
Table 5.1: Main activity of NSW school leavers in 2009 by Year 12 completion status
Main activity in 2010
Full-time university study
Full-time vocational
study
Full-time work
Part-time work
Unemployed
NILFET
Number of respondents
All school leavers
(%)
40.1
11.7
Year 12
completers (%)
45.7
11.0
Year 12 noncompleters (%)
0.4
16.8
25.2
14.8
6.5
1.6
2399
22.4
14.2
5.4
1.2
2087
45.4
19.1
14.1
4.1
311
Source: NSW Career Moves (2011)
As Table 5.1 above shows, around half of all school leavers were enrolled in full-time study
one year after leaving school, around a quarter were in full-time work, while around 8%
were unengaged in either work or study.
Year 12 completers were mostly enrolled in university study, while Year 12-non completers
were more likely to be engaged in full-time work. A much larger proportion of non-Year 12
completers (18%) compared with Year 12 completers (6.6%) were unemployed or Not in
the labour force or in education or training (NILFET).
The two most commonly cited reasons for leaving school early without completing Year 12
were work-related reasons, and not liking school. Boys were more likely to cite workrelated reasons for leaving school than girls, and of those males who left school early for
work-related reasons around 96% were working or studying for a qualification.
Of those not in post-school study or training, the most commonly cited reason among Year
12 completers was wanting to taking a gap year (about a third), while the next most
common reason was wanting to earn money. For non-Year 12 completers wanting to earn
money was the top reason for not studying, while “don’t like studying” was the next most
common. Around 85-90% of those not in post-school study indicated that it was at least
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“somewhat likely” that they would pursue post-school study in the next two years – this
was true for both Year 12 completers and non-Year 12 completers.
5.3.2
Victoria
The On Track survey of post-school destinations for school leavers in Victoria has been
conducted annually since 2003. Year 12 completers and early leavers are surveyed by
telephone early in the year after they leave school. The sample size for this survey is large,
with around 35,000 Year 12 or equivalent completers in 2010 contacted for the 2011
survey.
Chart 5.4: Post-school destinations of Victorian Year 12 completers in 2010
Source: Victoria On Track (2011).
The main results for Year 12 completers are shown in Chart 5.4 above, which shows that
the vast majority of Year 12 completers were engaged in further education or training in
the year after completing school, or had a deferred tertiary place.
The Victorian Government also conducts a longitudinal survey as part of the On Track
program which tracks Victorian school leavers for several years after they leave school.
The most recent survey results are reported for the 2007 cohort, three years after they had
left school. The 2010 survey results were based on interviews with 4,299 young people
who had completed Year 12 or left school without completing Year 12 in 2007. These
respondents had also been surveyed in 2008 and 2009.
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Figure 5.1: Victorian Year 12 Completers, main activity in 2010 by main activity in 2008
Source: Victorian DEECD (2010)
The main results for Victorian Year 12 completers are shown in the table above. The
column furthest to the right shows the activities engaged in one year after leaving school –
around 72% were in education and training (mostly university), while 26% were working,
and 4% were unemployed. By 2010, 70% of the 2007 cohort was still in education and
training, 25% were working, 3% were unemployed and 1% was NILFET (the row at the
bottom of the table above).
Within these broad patterns, further detail related to transitions is shown within the table,
with numbers highlighted in blue indicating the proportion of people engaged in the same
activity in both 2008 and 2010, and numbers highlighted in red showing major changes.
For example, around 88% of those who were in university one year post-school were still in
university three years post-school. A similar high percentage was found for those
undertaking an apprenticeship. For those undertaking advanced-level vocational studies
(VET) in 2008, a significant proportion had transitioned into either university or work by
2010, while for those who had undertaken entry-level VET around one third were working
full-time with around one-half in the labour force.
Perhaps encouragingly, 25-29% of those who had commenced working in the year after
completing Year 12 had transitioned into university study after three years. Moreover,
around 22% of those who had been in part-time work in 2008 were in full-time work in
2010. Around 85% of those unemployed in 2008 had transitioned into some form of study
or work by 2010. Finally, those who were NILFET in the year after leaving high school, were
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Youth Transitions Evidence Base: 2012 Update
no longer NILFET by 2010 – with around one third transitioning into university, one third
into VET, and one third into work.
Figure 5.2: Victorian early school leavers, main activity in 2010 by main activity in 2008
Source: Victorian DEECD (2010)
The table above shows the results for early school leavers – those who had left school
without completing Year 12.
The results are less encouraging than those for Year 12 completers. First, a higher
proportion of early school leavers were unengaged after leaving school (with 12%
unemployed and 3% NILFET), and this remained the case three years post-school (with 12%
unemployed and 4% NILFET). Moreover, around one half of those who were initially NILFET
after leaving school were still unemployed or NILFET three years after leaving school. For
those initially unemployed, around one third were still unengaged in 2010.
Of those who had commenced working after leaving school, 15-22% transitioned into
unemployment or NILFET status three years post-school (a much worse result than for Year
12 completers).
Of those who had commenced studying after leaving school, those initially engaged in
apprenticeships and traineeships had much lower rates of unemployment three years later
than those undertaking other study.
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5.3.3
Queensland
The Queensland Government conducts the annual Next Step survey which surveys Year 12
completers six months after they leave school. The 2011 Next Step survey interviewed
around 37,000 young people who had completed Year 12 in 2010.
Chart 5.5: Main destinations in 2011 of Queensland Year 12 completers in 2010
Source: State of Queensland (2011).
As Chart 5.5 shows, around 60% of Queensland Year 12 completers were enrolled in further
study in the following year, mostly in university study. However, around 11% were either
unemployed or NILFET in the year following school. Of those NILFET, the most common
reason given was wanting a break from study.
The Queensland Government also conducts the Next Step Longitudinal Survey, which has
been tracking Queenslanders who completed Year 12 in 2005. This cohort was initially
surveyed in 2006, with the most recent results available from the 2009 survey of 8,646
respondents (i.e. four years after completing Year 12).
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Figure 5.3: Queensland Year 12 Completers, main activity in 2009 by main activity in 2006
4.1
11.1
15.8
18.2
12.8
3.8
9.3
10.4
7.3
16.6
17.3
18.2
28.6
12.9
14.3
9
6.1
Distribution in 2009
13.2
33.4
30.4
22.7
39.6
43.7
35.8
41.9
33.2
29.8
16
NILFET
6.6
23.4
26.4
28.8
50
22
32.5
20.3
22.5
22.8
23.1
Seeking work
Working part-time
2.3
Working full-time
7.1
1.7 0.8
8
1.1
4.1
4
15.5 2.7
45.3 0.6
5.4 2.5
20 1.7
10.6 2.6
9.1 2.2
9.2 2.3
8.4 2.6
Apprentice
VET Cert IV+
1.1
3.4
3.8
2.1
2.6
2.6
1.7
1.9
3.1
4
Total VET
Distribution in 2006
36.7
Source: State of Queensland (2011).
2.4 0.6
9
1.9
13.7 4.6
3.1 3.7
1.2 0.8
8.9 2.6
6
2.2
3.7 1.7
6.4 2.9
5
3.2
3.8 4.3
Trainee
65.3
21
11
24.9
2.5
17.1
14.1
23.2
18.7
10.5
21
VET Cert I-II/other
University (degree)
VET Cert IV+
VET Cert III
VET Cert I-II/other
Apprentice
Trainee
Total VET
Working full-time
Working part-time
Seeking work
NILFET
VET Cert III
2006 Main Destination
University (degree)
2009 Main Destination
2.1 1.6 34.6
4
2.4
4.4
4.9 9.1
1.7
7.6 3.3
1.9
2.9 1.3
9.7
3.9
4
1.6
4.2
3
19.3
3.6 3.7 27.2
5.8 3.2 11.7
13.4 6.3
4.2
7.5 14.2
3
5.7
1.7
100
As the table above shows, most of those who had initially commenced in university study in
2006 remained there in 2009. For those who had commenced in vocational study (VET) in
2006, a larger proportion had transitioned to full-time work, with around 36% working fulltime in 2009 (with a further one third still in various VET studies). Around 25% of those
who had commenced entry-level VET courses in 2006 had transitioned to university-level
studies by 2009.
Of those who had initially commenced working in 2006, a large proportion was still working
in 2009. However, almost half had transitioned into either university or VET study. For
initial part-time workers, around one third transitioned into full-time work by 2009.
Around 20% of those initially unemployed or NILFET in 2006 remained either unemployed
or NILFET in 2009. The least likely to be unengaged in 2009 were those who were
undertaking university study or apprenticeships six months after leaving school (with the
most likely to be unengaged being those who had initially been unengaged six months after
leaving school).
5.3.4
Western Australia
In WA, government school year 12 completers have been surveyed by telephone in the year
after completion of Year 12 since 1996. For the 2011 survey, there were 7,967 student
responses.
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Chart 5.6: WA school leaver destinations
Source: WA School Leaver Destinations Survey, cited in Productivity Commission (2012).
As Chart 5.6 shows, the majority of school leavers were engaged in further education or
training in the year following completion of year 12. Around 11% were unengaged in either
work or study. Of those students in further education or training, 52% were enrolled in
university studies, 26% in TAFE studies, 17% were undertaking an
apprenticeship/traineeship, and 5% were either repeating year 12 or engaged in other
training.
Source: Productivity Commission (2012).
5.3.5
Tasmania
The Tasmanian Qualifications Authority collects attainment data for students after they
complete Year 10, the final year of compulsory school. The data show that:

Of the year 10 cohort in 2008, 67% continued in education or training at half time or
better in 2009 and 51% continued in education or training at half time or better in 2010

Of the year 10 cohort in 2009, 67% continued in education or training at half time or
better in 2010.
Source: Productivity Commission (2012).
5.3.6
Australian Capital Territory
The ACT conducts a telephone-based survey of government and non-government Year 12
completers six months after they complete year 12.
The 2010 survey obtained responses from 82% of 2009 Year 12 completers. The results
showed that 90% of these Year 12 completers were employed or studying. Of the 53%
studying, 64% were studying at Bachelor level or higher.
Source: Productivity Commission (2012).
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5.3.7
Northern Territory
The NT surveyed the post-school destinations of government and non-government Year 12
completers in 2010 five months after they completed school. A total of 1,037 Year 12
completers were identified, with the results showing that:

63% of Year 12 completers were in employment five months after completing school
(with 40% working full-time, and 60% part-time)

11% were working and studying

48% had entered into further education or training (with 70% studying a university
degree)
Source: Productivity Commission (2012).
5.4 NCVER Student Outcomes
The NCVER Student Outcomes Survey (SOS) is an annual survey of students who
successfully completed some vocational training in Australia. It is the main source of
information on the labour force outcomes for VET courses, and has been conducted
annually since 1997.
The key findings of the 2011 SOS are shown in the table below.
Table 5.2: Employment and further study outcomes for VET graduates and module
completers, 2011
Graduates (%)
Employed
Not employed
Unemployed
NILF
Employed or in further study after training
Enrolled in further study after training
University
TAFE
Other
77.4
22.6
12.7
9.6
87.0
32.4
6.6
16.9
8.7
Module
completers (%)
73.6
26.4
11.2
14.6
74.9
3.9
3.9
na
na
Source: NCVER (2011)
Table 5.2 shows that around three-quarters of VET graduate and module completers were
employed six months after completing their study. Around one-third of graduates
continued onto further study, while 13% of graduates and 11% of module completers were
unemployed following their study. Graduates completing higher level VET courses had
better outcomes after training.
The proportion of graduates and module completers that are employed shortly following
their study has remained fairly stable over time. However, the economic downturn
following the GFC was associated with slightly weaker employment outcomes for VET
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completers. For example, while 77% of VET graduates were employed in 2011 (similar to
77% in 2010), this was down from 78% in 2009 and 81% in 2007 and 2008.
The salary data collected in the 2011 SOS showed that VET graduates employed full-time
earned $53,500 per year on average. The highest salaries were for those completing
studies in Education ($70,000), Engineering and related technologies ($57,600), and Health
($57,500).
5.5 Graduate Destination Survey
The Graduate Careers Council of Australia’s annual Graduate Destination Survey (GDS) is a
study of the activities of new university graduates around four months after the completion
of their qualifications. The survey identifies the main activities of the graduates, including
full time study, full or part time employment, whether seeking employment or any instance
of unavailability for study or work.
Chart 5.7: Destinations of graduates surveyed in the GDS, 2011
Source: Graduate Careers Australia (2012).
Chart 5.7 shows that around half of surveyed graduates were in full-time work four months
after completing their relevant degrees. It also shows that more males that females were
unemployed and seeking full-time work while more females than males had accepted part
time or casual work but would have preferred to be working full-time.
The GDS shows that employment prospects for graduates weakened in 2009 following the
GFC, and are yet to recover. For example, of those seeking full-time employment, 76% of
graduates were in full-time employment four months after completing their course in 2010,
compared with 79% of those graduating in 2008 and 85% of those graduating in 2007.
The GDS also collects information on graduate starting salaries. The most recent data show
that the median annual starting salary for bachelor degree graduates in their first full-time
year of employment was $50,000, equivalent to some 78.1% of male average earnings
(compared to 83% of male average earnings in 2008). Starting salaries for males averaged
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$52,000, slightly higher than for females at $50,000. Dentistry graduates earned the
highest median starting salaries at $80,000, followed by optometry graduates ($70,000),
and earth sciences graduates ($65,000).
5.6 Beyond Graduation Survey
Graduate Careers Australia also collects information on the activities of recent university
graduates beyond the first year post graduation through the Beyond Graduation Survey.
The most recent Beyond Graduation 2011 Report detailed the findings for those graduating
from university in 2007. There were 11,807 responses to the 2010 Beyond Graduation
Survey of 2007 university graduates.
As Chart 5.8 below shows, the proportion of bachelor degree graduates available for fulltime work has progressively increased with each year after graduation, rising from 74% in
2008 to 80% in 2011.
Chart 5.8: Main activity of bachelor degree graduates, 2008-11
Source: Graduate Careers Australia (2012).
Chart 5.9 shows, of the bachelor degree graduates available for full-time work, a
progressively larger proportion is successful in finding full-time work with each successive
year following graduation, rising from 83% in 2008 to 93% in 2011. At the same time, the
proportion that is in part-time/casual work or unemployed declines each year. The
improvement in full-time employment outcomes is most pronounced moving from the first
year following graduation to the second year. It is notable that this improvement occurred
despite the post-GFC weakness in the Australian labour market during 2008-09.
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Chart 5.9: Bachelor graduates available for full-time employment, 2008-11
Source: Graduate Careers Australia (2012).
The trend of improved full-time employment outcomes for those seeking full-time
employment holds for all broad fields of study. The improvement across four years is
particularly notable for some fields which have relatively poor immediate employment
outcomes such as society and culture, creative arts, and agriculture and environmental
studies.
Chart 5.10: Broad occupation types, bachelor graduates in full-time employment, 2008-11
Source: Graduate Careers Australia (2012).
Chart 5.10 shows the broad occupation type in which bachelor degree graduates were
working full-time. The improvement over time is again evident, with an increased
proportion of the 2007 graduate cohort employed full-time as managers or professionals
after four years.
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Chart 5.11 shows that the improvement in the quality of employment is even more
apparent for those graduates in part-time employment.
Chart 5.11: Broad occupation types, bachelor graduates in part-time employment, 2008
and 2011
Source: Graduate Careers Australia (2012).
Finally, Table 5.3 below shows median salaries for 2007 graduates over the four years since
graduation. A steady increase in median salary over time is evident for all fields of study,
with the median salary for all graduates increasing by an average of 40% over the four years
to $66,000 in 2011.
Table 5.3: Median salary, bachelor graduates in full-time employment, by broad field of
education, 2008–11 ($, ‘000s)
Field of education
Natural and physical sciences
Information technology
Engineering and related technologies
Architecture and building
Agriculture and environmental studies
Health
Education
Management and commerce
Society and culture
Creative arts
Total
2008
47.0
50.0
55.0
45.0
45.0
45.3
48.0
47.0
46.2
40.0
47.0
2009
55.0
60.0
64.0
55.0
55.0
57.0
55.0
55.0
55.0
46.6
55.0
2010
59.3
68.5
70.0
60.0
59.0
62.0
59.0
62.0
60.0
52.5
60.0
2011
65.0
75.0
76.0
65.0
65.0
67.0
63.0
70.0
66.0
55.0
66.0
Source: Graduate Careers Australia (2012).
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6 Broader labour market and
education trends
Information on youth transitions to the labour force should be viewed in the context of
how the broader labour market is performing. This chapter looks at trends in the labour
market performance of young people, as well as an overview of participation in various
forms of education.
6.1 Overall labour force participation and
unemployment
Labour force participation is measured as the share of those aged 15 and over who are in
work or looking for it. It responds to both ‘push’ and ‘pull’ factors. ‘Pull’ factors shift with
the demand for workers. When times are good, jobs grow fast and unemployment falls, so
people are encouraged to participate (and vice versa when times are bad). ‘Push’ factors
shift with supply. Supply tends to respond to social trends (such as the move of women
into the paid workforce in recent decades) and economic factors (people want to “keep up
with the Joneses”, so they will often take on big mortgages and send Mum to work when
mortgage rates rise, and they respond to incentives such as taxes and benefits). Those
‘push’ and ‘pull’ factors broadly offset over the period from 1990 to 2005, leaving the
overall participation rate mostly stuck in a narrow groove across that period of 63-64%.
Chart 6.1: Labour force participation rate
Source: ABS Cat No. 6202.0
As Chart 6.1 shows, the overall participation rate moved above 65% in 2006 and has
remained in the 65-66% range over the past five years. There has been a lift in many agebased participation rates over recent years, particularly for older workers. As an
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illustration, the participation rate for those aged 55-59 has risen from 63% to 73% since
2005, while for those aged 60-64 the participation rate has risen from 41% to 53%.
However, the overall labour force participation rate has remained largely static over recent
years as those age-based participation trends have been offset by greater numbers of
people entering older age cohorts.
Going forward, there will likely continue to be pressure for a downward trend in overall
labour force participation as baby boomers retire in increasing numbers. There is therefore
a risk that participation rates start to fall more notably from about 2016 onwards. That will
place more pressure on Australia’s youth in order to maintain the strong rates of economic
growth seen recently.
Chart 6.2: Unemployment rate
Source: ABS Cat No. 6202.0
The national unemployment rate trended down through much of the 2000s, hitting 4.0% –
a 30 year low – in February 2008 (see Chart 6.2). The GFC then saw it rise rapidly again to
near 6%, but it has since moderated once more and remains in what is a low range given
the experience of the preceding few decades.
6.2 Labour force status of young people
The following discussion examines the labour force experience of young people based on
ABS data. The ABS data groups people into age cohorts of 15-19 years old and 20-24 years
old.
Chart 6.3 and Chart 6.4 show the share among each age cohort who are neither in full-time
education nor full-time work. These people may be working part-time, studying part-time,
job-seeking, out of the labour force for some reason or some combination of these
outcomes (which aligns relatively closely with the sum of the mixed and poor transition
criteria discussed in the previous chapter).
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Note that unlike data presented in the previous chapter which tracks individuals over time,
this data shows aggregates at points in time, but does not indicate to what extent it is the
same individuals experiencing those outcomes over time.
Chart 6.3: Share of 15-19 year olds not in full-time education or full-time work
Source: ABS Cat No. 6291.0.55.001
Chart 6.3 shows that just under one-fifth of females aged 15-19 are not in full-time
education or full-time work, and therefore potentially at risk of experiencing a poor
transition.
Chart 6.4: Share of 20-24 year olds not in full-time education or full-time work
Source: ABS Cat No. 6291.0.55.001
The proportion of males not in full-time education or full-time work is a little lower. Both
ratios had been trending down for more than a decade until the GFC weakened the
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employment prospects of those young people seeking full-time work. That led to a spike in
these ratios in 2009 as fewer young people found full-time work and there was no
corresponding shift into full-time education. While there has been a gradual labour market
recovery since then, employment prospects for young people remain weaker than before
the downturn, raising the risk of an increased number of poor transitions. Chart 6.4 shows
similar trends for those aged 20-24, where around one-third of females and one-fifth of
males are neither in full-time education nor full-time work.
Over the last decade, while there has been a general decline of those not in full-time
education and full-time work, it is worth noting that the shares of young people not in fulltime education or full-time work are not substantially lower than during the late 1980s
(despite the national unemployment rate being now notably lower than it was in the late
1980s).
Chart 6.5 separates out the labour market outcomes of those in full-time education and
compares it to those not in full-time education.
Chart 6.5: Education and labour force status of young people, 2011
Source: ABS Cat No. 6291.0.55.001
FT work – full-time work; PT work – part-time work; U/E – unemployed; NILF – not in the labour force.
Data shown are a twelve-month average from January to December 2011.
For those not in full-time education, part-time work is the most significant of the three poor
transitions criteria (of part-time work, unemployment and being not in the labour force),
though for the 20-24 age group being not in the labour force is almost as significant.
By gender, the largest disparity occurs between males and females in the 20-24 age cohort
who are not in full-time education and not in the labour force. This disparity is unsurprising
given the greater propensity for females with young families to withdraw from the labour
force. Males also engage in full-time work in greater numbers than females across both the
15-19 and 20-24 age groups.
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Chart 6.6: Education and labour force status of young people by single year of age, 2011
Source: ABS Cat No. 6291.0.55.001
FT work – full-time work; PT work – part-time work; U/E – unemployed; NILF – not in the labour force.
Data shown are a twelve-month average from January to December 2011.
Separating out education and labour force status by single year of age (Chart 6.6) shows the
transition from a majority undertaking full time secondary study at age 15 to a majority
undertaking full time work at age 24.
In addition, the chart shows that from age 18 (and for each successive single year age group
thereafter) 70-75% of young people are involved full time in either learning, or work. These
young people would be considered to be in a satisfactory position at that particular point in
time. One of COAG’s main concerns is to increase young people’s participation in
employment. Chart 6.6 shows this happening between ages 18 and 24.
The group where there is greatest potential to increase employment is the 15% who are
not studying full-time and unemployed or NILF at age 24. The proportion of young people
who are not in full-time employment or study is broadly similar across those aged 20 to 24.
This could again be related back to the workforce detachment seen in young females, as
noted earlier.
Chart 6.7 shows labour force participation rates over time for the key age groups of interest
– 15-19 year olds and 20-24 year olds:

As can be seen, the participation rate of 20-24 year olds is well above the Australian
average.

Within this group many young people are leaving full-time education for the first time
and have not yet begun to take breaks from the workforce for family or other reasons.

The 15-19 year old cohort generally has a lower than average participation rate, with a
large proportion of this cohort undertaking education and training.

Since the GFC, the labour force participation rate for 15-19 year olds and 20-24 year
olds has declined significantly. This is consistent with the finding earlier in this chapter
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that the proportion of the 15-19 and 20-24 year old age groups not in full-time
education or full-time work has risen in recent years.

The overall labour force participation rate has held steady since the GFC as declines in
labour force participation among younger age groups has been offset by increases in
labour force participation among older age groups.
Chart 6.7: Labour force participation rates by age
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘All ages’ refers to those aged 15 and over.
6.3 Unemployment of young people
The ABS Australian Labour Force data series tracks unemployment by age cohort. This
allows us to see how young people have been faring in comparison to the general
population over the last decade.
Chart 6.8 shows the general downward trend in national unemployment rates since the
early 1990s and a matching trend for unemployment rates among young people – indeed a
better reduction for young people. However, both the broader unemployment rate, as well
as unemployment rates for young people lifted shortly after the GFC hit in mid-2008. The
spike in unemployment rates for those aged 15-19 was especially notable, and far more
severe than that for the broader population.
Moreover, even leaving aside recent cyclical movements, young people still have notably
higher unemployment rates than the Australian average. Those aged 15-19 in the labour
force are much more likely to be unemployed than those aged 20-24 or the general
population.
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Chart 6.8: Unemployment rates for young people seeking full-time work
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘All persons’ refers to those aged 15 and over.
Separating out the two groups of young people by gender (Chart 6.9) shows little difference
in the broad patterns of unemployment between the sexes. However, historically males
have had a lower unemployment rate in the 15-19 age group, while females have had a
lower unemployment rate in the 20-24 age group.
Chart 6.9: Unemployment rates for young people seeking full-time work by gender
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘All males’ and ‘All females’ refer to those aged 15 and over.
As always, a key caveat is worth noting here, because the likes of Chart 6.8 are often
misinterpreted. These are the unemployment rates for young people seeking full-time
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work. While the unemployment rate for young people seeking full-time work is
significantly higher than that for the total population aged 15 and over, many young people
are not seeking full-time work because they are studying.
One of the broadest (and best) overall measures of the unemployment situation for young
people is the unemployment to population ratio. This ratio measures the number of
unemployed people of a certain age group as a proportion of the total civilian population
for that age group. The ratio accounts for both differing labour force participation rates
across age groups, as well as differing unemployment rates.
Chart 6.10: Unemployment to population ratio for each age group – seeking full-time
work
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘All persons’ refers to those aged 15 and over.
Chart 6.10 shows that around 4% of the population aged 15-19, and around 5% of the
population aged 20-24 are unemployed and seeking full-time work. These ratios compare
unfavourably to the unemployment to population ratio for the entire population aged 15
and over, which is around 2½% for those seeking full-time work.
The unemployment to population ratio is higher for those aged 20-24 than for those aged
15-19. This reflects the fact that while the unemployment rate for those seeking full-time
work is lower for 20-24 year olds (see Chart 6.8), a much higher proportion of the 20-24
population is looking for full-time work than is the case for 15-19 year olds.
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Chart 6.11: Unemployment to population ratio for each age group – seeking full-time or
part-time work
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘All persons’ refers to those aged 15 and over.
Chart 6.11 shows the unemployment to population ratios by age group after including
those unemployed and seeking part-time work in addition to those unemployed and
seeking full-time work. Because a large number of 15-19 year olds look for part-time work,
the unemployment to population ratio for 15-19 year olds is now significantly higher.
In total, around 9% of the population aged 15-19, and around 6½% of the population aged
20-24 are unemployed, compared with 3½% for the entire population aged 15 and over.
A young person aged 15-19 is therefore around 2.6 times more likely to be unemployed
than the average person aged 15 and over, and a young person aged 20-24 is around 2
times as likely to be unemployed.
The higher unemployment to population ratios for younger age groups mean that younger
age groups tend to be over-represented among the unemployed.
Chart 6.12 shows that overall, 15-24 year olds comprise around 33% of the unemployed
people in Australia seeking full-time work. That compares with a share of the total
population within scope of the labour force survey of 17%, and of the total labour force of
18% in 2011. 20-24 year olds tend to comprise a larger share of the total unemployed
people seeking full-time work than 15-19 year olds, with that share increasing since the
GFC.
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Chart 6.12: Share of total unemployed seeking full-time work for each age group
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average.
Finally, Chart 6.13 shows that 15-19 year olds comprise a larger share of all unemployed
people in Australia (including those seeking both part-time and full-time work), with that
share increasing over the decade until 2008. Overall, 15-24 year olds comprise around 40%
of the unemployed people in Australia.
Chart 6.13: Share of total unemployment for each age group
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average.
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6.4 Long-term unemployment
While some people move relatively quickly in and out of employment, others remain
unemployed for a significant amount of time. Long periods of unemployment can be very
difficult for individuals to break out of.
Chart 6.14 presents ABS estimates of the long term unemployment rate over time, and
shows that young people aged 15-24 tend to have a higher share of the long term
unemployed than across all ages. The definition of long term unemployed used here is
‘Persons unemployed for 12 months or more, where duration of unemployment is based on
the last full-time job’.
While the long term unemployment rate for young people had been on a downward trend
for much of the 1990s and 2000s, it has recently crept higher since 2008. This is particularly
true for the 15-19 year old cohort, which now has a notably higher long-term
unemployment rate than the 20-24 year old cohort (a distinct change since the experience
of the early 1990s recession).
Chart 6.14: Long term unemployment rates for young people, and total persons
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘Total’ refers to those aged 15 and over.
Chart 6.15 shows that the long term unemployment rate for 20-24 year olds has risen more
for males than females since 2008. Movements in the long-term unemployment rate for
15-19 year olds have been more similar for males and females.
In 2001, 15-19 year olds comprised some 10.3% of total long term unemployed people in
Australia. In 2011, that same share had crept up to 12.1%. A similar increase is evident for
20-24 year olds who comprised 13.9% of total long term unemployed people in 2001 and
15.6% in 2011. This result is similar to that for overall unemployment rates for those
seeking full-time work, where relatively more 20-24 year olds are unemployed and
relatively fewer 15-19 year olds are unemployed.
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Chart 6.15: Long term unemployment rates for young people by gender
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘Total males’ and ‘Total females’ refer to those aged 15 and
over.
6.5 Underemployment
Separate to the issue of unemployment among young people is identifying those individuals
who would wish to be working more than they currently are. The ABS term
underemployment reflects ‘employed persons who want, and are available for, more hours
of work than they currently have’.
Chart 6.16: Underemployment for young people by gender
Source: ABS Cat No. 6202.0
Data shown are a twelve-month moving average. ‘All Persons’ refers to those aged 15 and over.
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Chart 6.16 shows that more females than males are underemployed for those aged 15-24.
Young people of both genders are also more likely to be underemployed than people in the
broader population. As with unemployment rates, rates of underemployment also rose
during 2008-09, with underemployment rates for young people rising more sharply. These
underemployed people represented 14.7% of employed 15-24 year olds in 2011.
6.6 Part-time work
While unemployment and underemployment are clearly poor labour market outcomes, the
role of part-time work is less clear cut. In this section, overall aggregates for part-time work
are presented, noting that in the analysis of LSAY data, poor outcomes were associated
with those who were working part-time but were seeking additional work or additional
hours.
Chart 6.17: Share of labour force employed part-time for young people
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘All ages’ refers to those aged 15 and over.
There has been a very strong lift in the share of 15-19 year olds that are in the labour force
who are working part-time, from around 30% in 1988 to around 59% today (Chart 6.17). In
part this mirrors the overall decline in youth unemployment rates over the long term, with
a significant substitution towards part-time work over full-time (though part-time work may
still generate poor transition outcomes as defined for this report).
There has been a similar, although slightly less marked upward trend in part-time
employment among the 20-24 year olds in the labour force survey as well. This age group
now has a greater propensity to be employed part-time than the whole adult population.
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Chart 6.18: Share of labour force employed part-time by gender
Source: ABS Cat No. 6291.0.55.001
Data shown are a twelve-month moving average; ‘All ages’ refers to those aged 15 and over.
Among females in the labour force, there has typically been a larger share who are parttime workers than among males (Chart 6.18). Even among the younger age cohorts, this
remains true. As one might expect, both young males aged 15-19 and young females aged
15-19 have a higher propensity for part-time work than the average Australian male/female
in the workforce. In contrast, females in the 20-24 year old age cohort in the labour force
have a lower propensity for part-time work than the average Australian female worker – at
this age women tend to be either working full-time, studying full-time or not in the labour
force, with a greater tendency towards part-time work after having children.
Underemployment as discussed earlier can also be measured as a share of those who are
currently working part-time, which is shown in Chart 6.19. Around one third of people aged
15-24 who are engaged in part-time work would prefer to be working more hours. These
people represent a significant share of the part time employed population – much more
than is the case for the part-time employed population as a whole.
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Chart 6.19: Share of part-time workers who would prefer to work more hours
Source: ABS Cat No. 6291.0.55.001
‘All ages’ refers to those aged 15 and over.
6.7 School retention rates
A key influence on the success or otherwise of youth transitions to the labour force is the
starting point of those transitions. On average, those people who stay in school longer tend
to perform better in their transitions (though that does not mean that extra schooling will
necessarily benefit every individual in their transition, particularly for those who may not be
academically inclined).
Chart 6.20 shows the apparent full time rate of school retention to year 12 from year 7/8 that is, the share of students in year 7 who end up completing year 12. Across the board
retention rates from year 7 to year 12 have continued to improve since the late 1990s.
Indeed, there has been a notable rise in school retention recorded since 2008. That may
partly be due to the weakness of the labour market, which for some individuals at present
is providing less opportunity for a smooth transition to work given the weakness in labour
demand.
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Chart 6.20: Apparent retention rates in Australia from Years 7/8 to Year 12
Source: ABS Cat No. 4221.0
6.8 Participation in higher education
Higher education (University) has traditionally provided a path for better outcomes during
transition to the labour market, and one which has tended to result in higher skilled jobs.
In 2010 there were 521,837 young Australians participating in higher education. Chart 6.21
shows that rates of participation in higher education among 15-19 and 20-24 year olds have
increased over the last five years or so. That is particularly true for 15-19 year olds where
participation rates have increased steadily since 2005. For 20-24 year olds, participation
rates held steady for several years but have increased since 2008.
As for school retention rates, increased participation rates in higher education since 2008
are likely to at least partly be driven by recent weakness in the labour market, particularly
for lower skilled workers. More broadly, the increase in higher education participation
rates over the past five years provides some evidence that the higher skill needs associated
with a larger and more sophisticated economy are beginning to translate into greater
participation in higher education over time by Australia’s youth.
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Chart 6.21: Young people’s participation in higher education
Source: DEEWR Higher Education Statistics, ABS ABS Cat No. 3101.0
Note that the above chart reports participation in higher education (i.e. enrolments) rather
than just commencements, so it incorporates the rate of drop-outs seen from University
courses, generally during the first year.
Attrition rates for students commencing a bachelor course have declined slightly over the
past decade (Chart 6.22).
Chart 6.22: Attrition rate for domestic commencing bachelor students4
Source: DEEWR Higher Education Statistics
4
The attrition rate for year (x) is the proportion of students who commenced a bachelor course in year (x) who
neither complete nor return in year (x + 1).
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Estimates of unmet demand in higher education in Australia are also available. Using a
methodology developed by the former Australian Vice-Chancellor’s Committee (now
Universities Australia), and data from the Tertiary Admission Centres in each State, DEEWR
estimated unmet demand for higher education in 2011 at 7.8% of total eligible applicants,
or around 19,400 applicants. This level of unmet demand was marginally lower than in
2010, and significantly lower than in 2003 and 2004 when the estimate of unmet demand
peaked at around 35,000 (or 15% of eligible applicants).
Following the Bradley Review of Higher Education, the Australian Government has
implemented a demand driven system of funding undergraduate places at public
universities. This allows universities to decide the number of students they wish to enrol in
their undergraduate courses, rather than being restrained as they were under the funding
arrangements of the old system which resulted in caps on places. This will change the
nature of estimates of unmet demand, which in the future are likely to reflect mismatches
in applicants’ preferences for particular fields of study or university, rather than the ability
of applicants to secure university entrance.5
6.9 Participation in VET
Further study in the form of formal vocational education and training (VET) plays a very
important role in the skills development of young Australians. In 2010 there were around
769,000 young Australians (aged 15-24) enrolled in a VET program across Australia. That
amounted to around 24% of people aged between 15 and 24 – some 31% of those aged 1519 and 19% of those aged 20-24.
Chart 6.23: Young people’s participation in VET
Source: NCVER National VET Provider Collection, ABS 3201.0 (cited in NCVER (2011) Australian vocational
education and training statistics: students and courses 2010).
5
DEEWR (2011)
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Chart 6.23 shows that overall participation in VET since 2006 has been very stable, although
within that stability there are more 15-19 year olds undertaking VET (with the VET in
schools program a key driver) while participation by 20-24 year olds declined slightly until
2009. In 2010, there was a pick-up in VET participation for both 15-19 year olds and 20-24
year olds.
The general trend in VET participation from all age groups is a levelling off since the year
2000, following a very strong lift in participation through the 1990s.
A similar trend in participation is seen with respect to Australian apprenticeships – from
2002 to 2008, participation by 15-19 year olds climbed a little, while the proportion of 2024 year olds commencing Australian apprenticeships declined. In large part this may be
due to Australian School Based Apprenticeships (ASBAs) which have formed replacements
for those who otherwise may have commenced only at the end of year 12. However, as a
result of the economic downturn, apprenticeship commencements dropped sharply in
2009, with particular weakness in apprenticeship commencements for those aged 15-19
years. As Chart 6.24 shows, there has been some subsequent recovery in 2010. Over the
longer term, commencements of Australian apprenticeships by 15-24 year olds have kept
fairly steady as a share of population since 2003.
Chart 6.24: Young people’s commencement of Australian apprenticeships
Source: NCVER National Apprentice and Trainee Collection, ABS ABS Cat No. 3101.0
Commencements are for the year ending 31 December.
Another option for many youth is to receive vocational training while at school. Programs
such as VET in Schools and Australian School Based Apprenticeships (ASBA) are designed to
facilitate this. Over the last decade there has been strong growth in the numbers of VET in
School students, as seen in Chart 6.25.
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Chart 6.25: Senior students’ enrolment in further training while at school
Source: NCVER 2011, Australian vocational education and training statistics: VET in Schools 2010 data tables
Australia, ABS ABS Cat No. 4221.0
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7 International comparisons of
transition experiences
The experience of other countries provides an important gauge for how well Australia is
performing in youth transitions to the labour market and further education. International
comparisons can also provide benchmarks relating to world’s best practice in terms of
outcomes for young people.
The following discussion of international comparisons relies heavily on data and analysis
from the OECD. The first section analyses Australia’s performance relative to other
countries’ across a range of broad benchmarks and indicators. The second section
summarises the findings of a more detailed analysis of Australia’s performance undertaken
by the OECD. The third summarises and presents a range of findings and recommendations
from the OECD aimed at improving youth transitions.
7.1 Labour market and education benchmarks
The experiences of young people in the labour force and education in other countries can
provide a useful benchmark for where Australia could be placed and just how much room
for improvement there exists.
One commonly used international benchmark is overall youth unemployment rates for
Australia and the OECD.
Chart 7.1 shows youth unemployment rates at March 2012, as well as at December 2007
prior to the global economic downturn. While Australia also experienced an economic
downturn and a rise in the youth unemployment rate, this was less severe than in many
other countries. As a result, Australia now ranks 9th on this measure (and better than the
OECD average), an improvement from 13th prior to the global economic downturn.
Nevertheless, the countries with the lowest youth unemployment rates such as Switzerland
and Norway continue to have significantly lower youth unemployment rates than Australia.
At the other end of the scale, Spain and Greece have seen youth unemployment rates hit
50%.
As noted above, Australia’s improvement in relative ranking partly reflects the less severe
economic downturn in Australia. As the OECD points out (and as shown earlier in this
report for Australia), the economic downturn has hit youth particularly hard, with youth
unemployment rates rising by more than overall unemployment rates. This phenomenon
has tended to occur historically also, with the youth unemployment rate slightly more than
twice as sensitive to the business cycle and the demand for labour as the adult
unemployment rate.6
6
Analysis by the OECD (2009) shows that over the period from 1966 to 2007, each one negative percentage
point deviation from the long-term growth rate in GDP led to a 1.4 percentage point increase in the youth
unemployment rate across the OECD (compared with a 0.7 percentage point increase in the adult
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Chart 7.1: Youth unemployment rates in OECD countries, December 2007 to March 2012
Source: OECD (2012).
OECD is the weighted average of 33 countries excluding Mexico. *Not seasonally adjusted data.
A second basis for international comparison is to track the proportions of young people
who are neither in employment nor in education or training (NEET).
Australia does not do as well on this measure, ranking 17th with a NEET rate of 11.4%. In
comparison, the best performing country is Denmark, with a NEET rate of 4.1% while
countries such as the UK and USA have NEET rates of between 13-15%.
Chart 7.2: Youth neither in employment nor in education or training (NEET) among youth
in OECD countries in 2011
Source: OECD (2012).
2011 Q1 for all countries except 2011 Q2 for Australia.
OECD, European Union and Euro area are weighted averages of 32 OECD Member countries (Excl. Chile and
Korea), 27 and 17 European countries, respectively.
unemployment rate). For Australia the equivalent increase in the youth unemployment rate was 2 percentage
points (and 0.9 percentage points for the adult unemployment rate).
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The OECD notes that the proportion of youth that are in the NEET category is of particular
concern for all OECD countries:7
Youth who are neither in employment nor in education or training are a group
at high risk of marginalisation and exclusion from the labour market, especially
the longer they remain outside the world of work.
Australia’s poorer showing here reflects a relatively large proportion of the 15-24 year old
population that is inactive (not in the labour force and not in education), which at 7% was
the 24th from best among those countries shown in Chart 7.2. For Australia, there is a
relatively high inactive share for young Australian females, who may be more likely to be
disconnected from the labour market than in other OECD countries (OECD, 2009).
It is worth noting that in some other OECD countries the compulsory age for schooling is
higher than it is in Australia. Australia (through COAG) has recently implemented
mandatory requirements for all young people to complete Year 10 and after completing
Year 10 to participate in either education, employment or a combination of these activities
until age 17. This policy change should lower the number of youth in Australia that are
NEET over time (but the full impact may not be seen in the 2011 statistics, with the new
requirements having commenced in 2010).
Table 7.1 below shows a number of other relevant indicators for youth in Australia, the EU
and OECD.
As described elsewhere in this report, youth unemployment rates are substantially higher
than average unemployment rates. The ratio of the unemployment rate for those aged 1524 to the unemployment rate for those aged 25-54 shows the extent to which young
people are worse off in the labour market compared to the older population.
Australia ranks worse than average on this measure (Australia’s ratio of 2.9 is above the
OECD average of 2.6). That means that a young person is almost three times as likely as
an older person to be unemployed in Australia, and that likelihood has increased since a
decade ago.
While all youth in all countries are more likely to be unemployed than their older
counterparts (a ratio above 1), countries such as Germany, Denmark and Switzerland have
achieved a better result on youth unemployment relative to broader unemployment.
As noted above, Australia has improved its ranking on the overall youth unemployment
rate and related indicators in recent years. Given that Australia’s labour market has been
travelling better of late than many other OECD countries, that is also true for some other
unemployment indicators. Table 7.1 shows that the incidence of long term unemployment
among those young people unemployed has also declined over the past decade, and is now
well below the OECD average. Australia’s youth unemployment-to- population ratio (which
takes account of differing labour force participation rates), is also now below the OECD
average.
7
OECD Employment Outlook. http://www.oecd.org/employment/outlook
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Table 7.1: Scoreboard for youth aged 15-24, 2000 and 2010
Employment rate (% of the age
group)
Unemployment rate (UR) (% of the
labour force)
Relative UR youth/adult (15-24)/(2554)
Unemployment to population ratio
(% of the age group)
Incidence of long-term
unemployment (% of
unemployment)
Incidence of part-time worka (% of
employment)
NEET rateb (% of the age group)
School drop-outsc (% of the age
group)
Relative UR low skills/high skillsb
(ISCED<3/ISCED>3)
Aus
2000
EU
Aus
2010
EU
OECD
62.1
40.7
44.0
OECD
60.7
33.7
37.8
12.1
16.9
14.6
11.5
22.2
18.9
2.4
2.3
2.5
2.9
2.7
2.6
8.5
7.6
6.9
7.9
8.9
8.2
17.1
26.5
20.1
12.7
27.7
22.6
41.3
17.2
20.0
43.2
24.7
27.6
11.0
19.7
13.6
19.9
13.2
22.7
10.0
23.1
11.2
15.1
12.8
19.6
3.1
2.6
2.5
2.6
2.3
2.2
Source: OECD (2012)
UR: unemployment rate; NEET: neither in education nor in employment or training; ISCED 3: International
standard of education referring to upper secondary education; EU and OECD: Unweighted average of the 21
EU and 34 OECD countries.
(a)2001 instead of 2000; (b)1999 and 2009; (c)Share of youth not in education and without an ISCED 3
educational attainment; 1998 and 2008. Youth aged 20-24 for school drop-outs.
An important finding shown in Table 7.1 is that Australia has a much higher employment
rate for youth compared to those in other OECD countries, largely driven by a much
higher incidence of part-time work – young people in Australia are much more likely to
hold a part-time job than young people in other OECD countries. In fact, Australia had the
fourth highest employment rate for young people in the OECD in 2010, and the sixth
highest incidence of part-time employment.
A less encouraging finding is that school drop-outs are relatively high in Australia, and
have increased since a decade ago. Countries such as Canada and the USA do much better
than Australia on school drop-outs, with rates of between 9-10%. This is of particular
concern, given the weaker employment prospects for school drop-outs – as the table above
shows, those Australians without an upper secondary education are more than two and a
half times as likely to be unemployed than those with a higher than upper secondary level
of education.
On a more positive note, tertiary educational attainment for young adults (25-34) is also
relatively high in Australia, being above the OECD average, although below Canada, Japan
and Korea.
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7.2 OECD detailed comparative analysis for
Australia
The OECD recently completed a detailed analysis of the youth labour market situation in
Australia, comparing the results for Australia with those for other comparable OECD
countries where possible. In that report, the OECD found that:

Young immigrants from a non-English speaking background were 1.7 times more
likely to be unemployed than Australian-born youth in 2006, compared with an OECD
average ratio of 1.9.8

Indigenous youth in Australia were far more likely to be unemployed than nonindigenous youth in 2006 (3.1 times more likely for men, and 2.7 times for women), and
these ratios have risen since 1996.9

Young Australians enter the labour market when still students at a relatively high
rate, with 47% of students up to age 16 holding a job, and 82.5% of 21-22 year old
students holding a job in 2006. The latter rate compares with 69% in the Netherlands
(one of the highest in Europe) and 80% in the US.10

Australians complete their initial education at a relatively young age, with less than
5% declaring their main status to be “student” beyond the age of 24 – the lowest of all
OECD countries. Despite finishing their study early, tertiary educational attainment
remained high for Australians (as measured by the percentage of 30-34 year olds with
an ISCED 5/6 qualification).11

While many Australians hold part-time and casual jobs as students, the incidence of
part-time jobs among those who have finished studying is similar to that in European
countries, and declines with age from 15/16 to 28/29. The same is true for the
incidence of casual/temporary jobs.

In Australia, part-time and casual jobs generally acted as stepping stones to more
stable jobs, with a strong positive correlation between holding a part-time/casual job
(as opposed to being unemployed or inactive) and the probability of holding a full-time
job at a later stage.
Beyond the findings above, the OECD also undertook an analysis of longitudinal data sets
across countries to draw further conclusions about the transitions from education to work
in Australia. It found that:

In the first five years after completing their education, young people with an upper
secondary qualification in Australia spend on average around 4.4 years employed. The
post-study employment outcome for Australia compares favourably with the
international average (3.9 years) and is close to the top European performers such as
Iceland and Switzerland (around 4.5 years). Those that complete higher level
8
Young people aged 20-29, based on the Melbourne Institute’s HILDA longitudinal survey data for Australia.
9
Youth aged 16-29, using ABS Census data for 2006.
10
HILDA data for Australia, similar longitudinal surveys for Europe (EULFS) and the US (NLSY97).
11
HILDA data for Australia.
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qualifications spend a slightly greater time employed in the five years after they
complete their qualification.12

The school to work transition is faster in Australia than in the United States. For
example, seven months after completing initial education 90% of Australians were
employed, compared with 82% in the US and only 40% in the UK. It took a further 12
months to reach 90% employment in the US, and 41 months in the UK. This was largely
driven by better employment outcomes for Australian school leavers (who did not
continue to further education) who found their first job relatively quickly after leaving
school.13
Overall, the evidence from the OECD suggests that youth transitions from education to
work in Australia are better than average when compared internationally. Given that the
analysis here focused on the period prior to the global economic downturn due to data
limitations, Australia’s performance relative to other OECD countries is likely to have
improved even further since then.
7.3 OECD Thematic Review
The OECD’s report on Australia in 2009 contained a number of findings and
recommendations for Australia which drew upon the OECD’s international comparative
analysis, and which could potentially improve youth transitions in Australia.
The report found that there was room for improvement in education performance in
Australia in the areas of pre-school education (where Australia has a relatively low
participation compared to many OECD countries), school drop-outs (which are relatively
high in Australia), and indigenous educational performance (which is dire).
“There is a growing recognition that quality pre-school provides young children,
particularly those from low income or other disadvantaged backgrounds, with
a good start in life (OECD, 2006). Participation to pre-school – where children
are exposed to an actual educational content – could be particularly good for
the latter, as it could reduce the incidence of drop-out or act as a long-term
catalyst of STW [School-to-Work] transition”.
The educational reforms recently passed by the Australian Government (and COAG) are
considered to have largely moved policy in the right direction. These reforms are designed
to improve Australia’s performance in the areas identified by the OECD’s review:
“Many sound programmes were put in place in Australia recently to buttress
educational attainment, develop vocational education and training (VET)
within the school system, as well as to improve the school-to-work transition.”
Nevertheless, educational attainment could be improved further in the areas where there
was clear room for improvement:
12
HILDA data for Australia.
13
LSAY Y98 data for Australia from 1998 to 2006. Findings for the UK may not be robust due to small sample
size.
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
Aiming to see all young people leave education with a recognised qualification that
would be sufficient for them to establish a career. This could mean establishing even
more varied educational pathways for young people at the secondary school level (and
increasing further VET and apprenticeships in secondary school). The OECD also urged
the consideration of a national certification scheme for upper secondary schooling to
complement the planned national curriculum.

Ensuring young indigenous children use more health care and pre-school services.

Ideally, even more emphasis on early-age education of children, particularly from
disadvantaged groups.
On the demand side, the OECD found few barriers to good transitions:
“Australia’s labour market institutions are a priori also conducive to good
employment prospects for youth. Moderate to low entrance wages (ranging
from 30 to 40% of what an average worker earns) should encourage risk-averse
employers to recruit inexperienced and poorly educated individuals. And this
trend is probably buttressed by a low tax-wedge and relatively lax employment
protection legislation (EPL) framework”
In relation to gender disparities, the causes behind the relatively low propensity of young
women in Australia to work full-time and the large gender pay gap could be explored
further, particularly in relation to the effective marginal tax rate for couples and the impact
of relatively high costs of child care and pre-school on participation.
Finally, the OECD found that the recent move to a skill-first activation strategy was
warranted in Australia, given the low unemployment rate and high level of job vacancies
(and reports of skill shortages). However, it would be important to ensure that mutual
obligation remained at the core of the new system, and to ensure compliance from the
jobless. Moreover, skill upgrading services would need to be tailored to the jobless.
Given that the evidence from international evaluations of training programmes for youth
had been unpromising, the OECD considered it essential that Australia rigorously evaluate
its training programmes for youth:
“It is crucial that Australia invests in the development of a state-of-the-art
statistical apparatus to identify what works and what does not and why.”
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8 Broader economic outcomes
This chapter provides a profile of workforce participation and labour productivity for the
15-24 age group as a whole. The implications of good transitions relative to poor
transitions on these measures are also discussed.
Some implications for the broader economy of improvements in workforce participation
and labour productivity by young people are discussed, along with the potential longer
term gains arising from improvements in these.
8.1 Workforce participation
Chapter 6 noted that rates of labour force participation have declined for both 15-19 year
olds and 20-24 year olds since the GFC hit in 2008, although the labour force participation
rate for 20-24 year olds remains high.
Chart 8.1 profiles how the rate of labour force participation increases by age for the
population of 15-24 year olds in 2011.
Chart 8.1: Labour force participation rate by single year of age, 2011
Source: ABS Cat No. 6291.0.55.001
There is a steady increase in labour force participation by age from 15 to 18 and then a
small increase again between 18, 19 and 20 year olds. After this peak at aged 20, labour
force participation levels off and by age 24, labour force participation is around the level it
will stay for the next 30 years until people start to retire – different individuals will move in
and out of the labour force during this time but the overall rate of labour force participation
by age maintains a high level. Building on this participation ramp-up stage may end up
allowing for a higher level of labour force participation to be maintained when it plateaus.
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Chart 8.2 displays the occupational profile for full-time Australian workers by their age.
Occupations are numbered 1 to 8 with these numbers generally considered to be indicative
of the level of skill required to undertake the position (with 1 being the most highly skilled
and 8 having the lowest skill requirement). With the higher skilled occupations being those
shown at the top of each of the respective columns, the development of skills over time is
clearly apparent. Over the 20-24 age group is when there is entry into higher skilled
occupations in significant numbers, with some further transitions to higher skilled
occupations beyond that as further skills and work experience are obtained.
Chart 8.2: Occupational profile of full-time workers by age
Source: ABS Cat No. 6291.0.55.001
Chart 8.3 provides a profile of the nature of employment for those aged 15 to 24 by age
cohort and gender. The rise in part-time work (and decline in permanent full-time work) as
a share of total work is apparent for each of the categories shown below.
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Chart 8.3: Nature of employment for 15-24 year olds
Source: ABS Cat No. ABS 6105.0
Permanent full-time/ part-time workers are those workers who have paid leave entitlements and Casual fulltime / part-time workers are those workers who have no paid leave entitlements.
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8.2 Labour productivity and earnings
Australia’s labour productivity performance has generally been weakening over the last
decade, and has averaged growth of around 1.2% per year since 2000 (as shown in Chart
8.4).
Chart 8.4: Australian labour productivity (measured by GDP per hour worked)
Source: ABS Cat. No. 5206.0
Labour productivity is critical to long term growth in prosperity in Australia, and poor
transitions by young people into post-school education and/or work can have significant
implications for productivity growth. That is particularly the case given that Australia’s
population is ageing and that older (and in most cases more experienced and more
productive) workers are expected to retire from the labour force in increasing numbers.
At the detailed occupational level, and for age groups, labour productivity can be difficult to
measure directly from available datasets. An estimate of the relative productivity of
individuals working in different occupations is the wage received, on the assumption that
individuals are paid according to their marginal product. This expectation may be less true
for individuals who are first entering the workforce (with many graduates often paid a
common starting salary irrespective of their occupation).
Chart 8.5 shows estimates of average weekly cash earnings by broad level of occupation.
As may be expected, managers and professionals achieve the highest wages across the
occupational classifications shown. These are also the occupations where youth
participation is low (partly because such occupations generally require significant education
or experience to enter). Sales workers, community and personal service workers, and
labourers tend to receive wages below the Australian average.
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Chart 8.5: Average weekly total cash earnings, May 2010
Source: ABS Cat. No. 6306.0
Although younger workers are under-represented in the occupations which provide the
highest earnings, their salaries can be expected to improve over time as experience is
attained.
8.3 Implications for wages
Given the way that good and poor transitions have been defined for the analysis of youth
transition outcomes for the LSAY Y03 cohort in this report (see Chapters 2 and 3), the rate
of workforce participation will be higher for those making a good transition (relative to a
poor transition).
Also by definition those making a good transition will have higher salaries (and hence a
higher level of labour productivity) than those making a poor transition, as the latter will
generally not be working (or if they are it is in a part time job with a low rate of
satisfaction).
This section describes the outcomes for earnings associated with different youth transition
paths for the LSAY Y03 cohort.
Chart 8.6 shows the average salaries of those in full-time work in the fourth year after
leaving school for the LSAY Y03 cohort studied in this report. For early school leavers, the
average annual salary is $41,161, while for Year 12 completers the average annual salary is
higher at $44,031, a premium of 7.0% after four years.
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Chart 8.6: Salary profile of transitions to full-time work
Source: LSAY, Y03 dataset, Deloitte Access Economics
Chart 8.6 above showed the average salary for all early leavers and all Year 12 completers.
As noted above, both workforce participation and productivity (and, by implication,
salaries) will be higher for those making a good transition. The difference in average annual
salaries across transition categories is shown in Chart 8.7 below. Note that the chart shows
the average annual salary four years after leaving school for all individuals not studying in
that year – that includes those who are unemployed or not in the labour force (who have a
salary of zero), as well as those who are working part-time and therefore earn less than a
full-time worker.
Chart 8.7: Salary profile by transition category
Source: LSAY, Y03 dataset, Deloitte Access Economics
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Clearly, those making poor and mixed transitions earn less on average by virtue of not
being employed at the same rate as those in the good transitions category.
Finally, Chart 8.8 below shows the average annual salary of those in full-time work in the
fourth year after leaving school for each transition category. While full-time work is a good
transition outcome, an individual classified to the poor transition category across four years
can be in full-time work in the fourth year if he/she was in one or more of the poor
transition criteria for the first three years (i.e. unemployed, not in the labour force or in
part-time work but unsatisfied with their hours). The same is true for mixed transitions.
Chart 8.8: Salary profile of full-time workers by transition category
Source: LSAY, Y03 dataset, Deloitte Access Economics
Looking at only full-time work enables a comparison of salaries across categories which
controls for the amount of time worked. The chart reveals that the lower salaries for the
poor and mixed transition categories also reflect the lower productivity of the individuals
even when they do work a similar amount of time as those who made a good transition.
It is not surprising that an individual who may have been unemployed for three years and
then found a full-time job would earn less than someone in the good transition category
who may have been working full-time for those three years. However, this is an important
result when considering the potential earning power (reflecting potential productivity) of
those in the poor and mixed transition categories if those individuals were to join the
labour force and become employed. This is considered in more detail in Section 8.5.
8.4 Skill shortages
Poor transitions by young people into education and work, or individuals operating below
their potential (based on their qualifications), can be particularly damaging to the economy
during periods of skill shortages.
Skill shortages indicate that the Australian economy is not operating at ‘potential’, because
of excess demand for labour in some occupations, sectors or regions. To the extent that an
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undersupply of qualifications persists, or is exacerbated by poor transitions by young
people into the labour force, there could be wider implications for the Australian economy.
That includes pressure on wages growth and, in turn, inflation, which could lead to higher
interest rates. In other words, the failure of the supply of skills to keep pace with demand
could lead to higher than otherwise wages, prices and interest rates.
As such, in a labour market where skills are in short supply, it is an imperative that
educational providers and policy makers produce the right mix of skills to meet demand.
One measure of the wrong skill mix is the measure of over-skilling in the labour market. (a
result of individuals operating below their potential). A range of literature exists that
attempts to quantify the level of over-skilling in the labour market. For example, a paper by
Li and Miller (2011) found the persistence of over-skilling to be high, and concluded that
“over-education has been empirically shown to be associated with substantial earnings
disadvantage.”
When the analysis is broken down into field of study the report finds identifiable
differences and provides some direction for policy makers:
To the extent that the respective likelihood of over education for each field of
study are good indicators of the graduate labour market conditions,
government funding should be diverted to the fields of study where graduates
are needed (less likely to be over educated). This is particularly reinforced
where a field of study is associated with greater odds of being overeducated
and lower earnings. Thus, the choice of a field of study that is in demand in the
labour market dramatically lowers the odds of being over-educated.
This finding suggests that an inefficient education system can add to the negative
implications for the economy by producing the incorrect composition of skills while also
effectively taking young people away from full-time work.
The chart below shows the trend in vacancies for selected occupations along with the
Australian total. It is drawn from the Internet Vacancy Index published by DEEWR. There
are some shortcomings to using this data to assess skill shortages. For example, the index is
based on the number of advertised vacancies and is not a detailed measure of unmet
demand. That is, the index does not indicate whether a decline in vacancies is due to
weaker labour demand or stronger labour supply, or simply because employers are giving
up on trying to fill vacancies.
Even so, the data is useful in providing some indication of trends in demand for workers
and the potential for skill shortages to arise. As the chart shows, over the period to late
2008 and the period since early 2010, the growth in vacancies for science professionals and
engineers has significantly exceeded that within the broader Australian economy. The
sustained demand for health professionals, including during the period of weaker
employment demand in late 2009 and early 2010 is also notable.
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Chart 8.9: Internet vacancy index, selected occupations and Australian total
Source: DEEWR
Skill shortages can accentuate the opportunity cost of making a poor transition to the
labour force, both for the individual and for government. For example:

If an individual has trained to be an IT programmer, but finds there are no jobs available
in this area and instead works as a waiter that represents a loss of potential for the
individual (which could be costed as the difference between wages as a waiter and
wages as an IT programmer).

It also represents a waste of resources by governments (and hence a loss to the
economy), with no return on the cost of providing training to be an IT programmer.

However, if there are skill shortages the potential cost for the economy is even greater.
For example if there is a shortage of structural engineers, then the cost to the economy
is both the spending on training as an IT programmer (which is not being utilised) and
the difference between wages as a waiter and wages as a structural engineer (with the
latter likely to be inflated in a skill shortage environment).
As Skills Australia (2012) notes:
…the underutilisation of skills within the workplace represents a lost
opportunity for both organisations and individuals. Where existing skills are not
being used – due to job mismatch, attrition or simply lack of active use – the
resources that were invested in nurturing these skills are not being optimised.
This is perhaps more important when viewing skill shortages and underutilisation of skills
from an economy-wide perspective.
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8.5 Economy wide outcomes
This section examines the economy wide benefits of good transitions compared with mixed
and poor transitions based on LSAY transitions and salary data (as proxies for workforce
participation and labour productivity).
Specifically, this section considers the potential net economic benefits of a hypothetical
scenario in which those individuals currently making poor and mixed transitions instead
experience labour market outcomes in the fourth year after leaving school that are
similar to those experienced by individuals currently making good transitions, but
without otherwise changing their labour market characteristics.
To make the scenario more realistic we have considered only labour market outcomes that
might be achievable, in terms of the potentially higher wages that could be earned by those
currently making mixed and poor transitions.
However, it should be noted that the broader aggregates presented here are based on
rules of thumb rather than detailed modelling, and are necessarily simplistic.
Nevertheless, the analysis should assist in understanding the scale of potential benefits
which could accrue from better transitions.
To estimate the net economic benefits of this scenario we use the following framework:

First, we estimate the potential net increase in labour income per person in the fourth
year after leaving school for those currently making mixed and poor transitions.

Second, we estimate the number of people who are currently making a mixed or poor
transition.

Third, we multiply our results for the first two steps together to provide an estimate of
the total additional labour income.

Finally, we use the share of labour income in GDP to convert the estimate of additional
labour income into an addition to GDP.
The results of this calculation are shown in Table 8.1, with the estimate of the potential net
increase in labour income per person shown in Table 8.2.
Table 8.1 and Table 8.2 show that the potential net increase in labour income per person is
higher for those currently making poor transitions. This reflects the fact that they are
currently earning less four years after leaving school than those currently making mixed
transitions and so have greater potential upside in earnings if they experienced labour
market outcomes similar to those experiencing good transitions.
However, as Table 8.1 also shows, there are many more young people making mixed
transitions than poor transitions – this means that, in addition to those currently making
poor transitions, there would also be significant economic benefits that would accrue from
improved transitions for those currently making mixed transitions.
Applying the number of improved poor and mixed transitions to the potential net increase
in labour income per person for the poor and mixed transitions respectively produces a
potential addition to labour income of $252.9 million per annum for poor transitions and
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$467.8 million per annum for mixed transitions across both early leavers and Year 12
completers. This is a total addition to labour income of $720.7 million.
If all those currently making mixed or poor transitions were to instead experience similar
labour market outcomes to those making good transitions, then in terms of value added
or GDP, the addition to labour income would be equivalent to boosting national GDP by
$1.5 billion in today’s dollars..
This addition to GDP refers to the additional value contributed by young people from a
particular cohort who are in the mixed or poor transition pathways from being more
engaged with work in the fourth post-school year than they are currently. In reality, to
make a ‘good transition’ as defined in this report, these individuals would also need to
record improved labour market outcomes in the first two or three post-school years. The
economic benefits would therefore be spread across three or four post-school years for
that particular cohort. However, the overall result can be generalised to say that the
increase in GDP from young people in their fourth post-school year making better
transitions amounts to $1.5 billion annually. This is an increase to overall GDP of 0.11%.
As noted, this estimate does not include the economic benefits associated with more good
transitions in the first three years after leaving school; it also does not include an allowance
for those who are working full-time but are deemed to be operating ‘short of potential’.
Indeed, additional gains would likely be realised if the labour market characteristics of
those making mixed and poor transitions were enhanced by, for example, completing Year
12 and improving their literacy and numeracy skills.
An important parameter that underlies the estimates presented here is the productivity
ratio, which helps to determine the potential net increase in labour income per person.
This requires an estimate of the potential productivity of the individuals currently making
mixed or poor transitions, i.e. the maximum realistically achievable level of earnings for the
individuals in these transition categories. This level of earnings is lower than the earnings
of those making good transitions because the characteristics of the young people making
mixed and poor transitions are different to those making good transitions. For instance,
they might have lower levels of literacy and numeracy (and a lower raw ability in these
areas) or have a disability or health problem that simply prevents them from earning at the
same level as someone making a good transition.
As Table 8.2 shows, the potential productivity of those making mixed or poor transitions is
estimated using the information on earnings from LSAY Y03 that was first presented in
Section 8.3.
There is some uncertainty about the true potential earnings power of those currently
undergoing mixed or poor transitions, compared with those currently making good
transitions.
This report has used conservative assumptions for the productivity ratio ranging from 60%
to 83% based on the observed data for the LSAY Y03 cohort.
Of course, the more potential we think that every young person has, the higher their
potential productivity would be if they made a good transition, and the higher the
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associated economic benefits and the impact on GDP if they made a good transition.
Indeed, the right interventions could help lift the potential earnings power of those
currently making poor transitions.
As a sensitivity analysis, Box A shows the impact on labour income and GDP if a slightly
different productivity ratio was used, based on recent work by the Productivity
Commission. As Box A shows, the impact on labour income and GDP is similar, albeit
slightly higher, reflecting a slightly higher assumed productivity ratio on average for those
making mixed and poor transitions.
There are two important caveats on the above analysis of economy wide outcomes.
Labour market outcomes reflect a combination of supply and demand. Essentially the
improvements discussed above are an addition to supply – what would happen if all young
people were job ready and willing to work rather than having some who can easily slip into
making a mixed or poor transition.
But not all individuals undergoing poor or mixed transitions may be willing to work, or for
those in part-time work, to work more hours. Similarly, there may be a limit to how many
individuals can become job ready. An allowance can be made for this by adjusting the
number of improved poor and mixed transitions. For example, if we assume that only half
the people undergoing mixed and poor transitions see improved labour market outcomes
similar to that for those undergoing good transitions, then the addition to labour income
and the boost to GDP would be halved.
Second, for the additional supply of job ready youth to show up as extra employment and
labour income, there needs to be an appropriate level of demand.
Insufficient demand would mean that however job ready young people are there will not
be enough demand to cater for them all, or they will displace older people in the labour
market (unlike other markets, price adjustments won’t lead to an equilibrium in the labour
market due to wage rigidities).
In an environment of high unemployment, better preparing young people for the labour
force may not make a difference to overall labour market outcomes, at least in the short
term (there would still be longer term benefits if the long term unemployment rate were
reduced even with a constant overall unemployment rate, as unemployment would be
becoming more frictional and less of a long term destination, with the latter potentially
fostering significant social and economic problems).
But the current environment is one of relatively low unemployment, and where there are
clearly signs of skill shortage in a number of areas in the economy. Australia’s demographic
profile which means there will be slower growth in working-age population looking forward
suggests that the skill shortage environment may remain. Therefore, an assumption of
responsive demand to the additional supply seems like a reasonable one in the present
circumstance and looking forward.
Finally, we note that the analysis here has considered only the economic impacts of more
young people making good transitions. There would likely be broader impacts from more
good transitions. For instance, if more young people with a disability or health problem, or
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with an indigenous background made good transitions, there may be positive implications
for those people in terms of a variety of non-economic measures, such as increased life
satisfaction. These are difficult to quantify in an economic sense, and so have not been
attempted here.
Table 8.1: Additional labour income and addition to GDP from an increased number of
good transitions
A
1
Total size of cohort :
B
% of cohort
C
Number
Early leavers
Year 12 Completers
17%
83%
52,550
265,666
318,216
2
AxB
Proportion making:3
D
Good transitions
65.2%
85.6%
E
Mixed transitions
23.7%
11.9%
F
Poor transitions
11.1%
2.5%
Number of:
G
Mixed transitions
12,454
31,614
CxE
H
Poor transitions
5,833
6,642
CxF
Net increase in labour income
per person4
I
Mixed transitions
$7,586
$11,808
J
Poor transitions
$17,624
$22,600
Additional labour income
K
Mixed transitions
$94,484,670
$373,285,130
GxI
L
Poor transitions
$102,799,530
$150,097,985
HxJ
Total
$197,284,199
$523,383,115
K+L
47.4%
47.4%
$416,236,342
$1,104,249,979
M
N
Labour income share of GDP5
O
Addition to GDP
M÷N
Source: LSAY Y03 dataset, ABS, Deloitte Access Economics
1
ABS Australian Demographic Statistics, December 2011, Table 59.14
2
LSAY Y03 dataset. See Section 3.2.
3
LSAY Y03 dataset. See Table 3.2 and Table 3.3 in Section 3.2.
4
LSAY Y03 dataset. See Table 8.2.
5
ABS Australian National Accounts: National Income, Expenditure and Product, June 2012, Table 7. The labour
income share of GDP is calculated as ‘Total compensation of employees’ divided by GDP in 2010.
14
Specifically, the analysis in this section applies to the cohort of 15 year olds in 2003 which is assumed to be
similar in size and composition to the cohort of 22 year olds in 2010 (although it should be noted that there will
some differences, largely due to international migration into and out of Australia)
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Table 8.2: Potential net increase in labour income per person
Early leavers
Year 12 Completers
Labour income per person four
years post-school:1
A
Good transitions
$42,133
$39,481
B
Mixed transitions
$25,015
$20,759
C
Poor transitions
$7,452
$9,365
Average salary if working FT four
years post-school2
D
Good transitions
$45,672
$45,185
E
Mixed transitions
$35,340
$37,271
F
Poor transitions
$27,183
$36,582
Productivity ratio
G
Mixed transitions
77.4%
82.5%
E÷D
I
Poor transitions
59.5%
81.0%
F÷D
Adjusted labour income
J
Mixed transitions
$32,601
$32,567
GxA
K
Poor transitions
$25,076
$31,964
IxA
Net increase in labour income per
person
L
Mixed transitions
$7,586
$11,808
J–B
M
Poor transitions
$17,624
$22,600
K–C
Source: LSAY Y03 dataset, Deloitte Access Economics
1
LSAY Y03 dataset. See Chart 8.7 in Section 8.3.
2
LSAY Y03 dataset. See Chart 8.8 in Section 8.3.
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Box A: The potential productivity of those undergoing mixed or poor transitions
The approach used in this report to estimate the potential benefits of an
increased number of good transition outcomes draws on recent work by the
Productivity Commission, which has investigated the potential benefits of
additional workers moving into the workforce due to improved work incentives.
In undertaking this work, the Productivity Commission has made an allowance for
the fact that these additional workers are likely to be less productive on average
than the currently employed population:
People who are unemployed or not in the labour force have systematically
different characteristics from people who are employed. For example, they tend to
have lower levels of education, a greater incidence of chronic illness and a longer
experience of unemployment. Human capital theory suggests that given their
characteristics, if employed, these people would be expected to be less productive
on average than people who are currently working, and earn lower wages.
(Forbes et al, 2010)
Chapter 3 showed that individuals with particular characteristics such as having a
disability, or low levels of literacy and numeracy experienced a higher rate of
poor transitions from school. These individuals could also be expected to be less
productive and earn lower wages on average than those who made good
transitions and started working.
How much lower? Productivity Commission researchers Forbes et al (2010)
estimated using HILDA data that for 15-24 year olds, a person with the labour
market and demographic characteristics of the average person not employed
would be expected to earn around 76% of the average wage of the average
employed person in that age group. Similarly, in its modelling of the National
Reform Agenda, the Productivity Commission used a productivity ratio of 75% for
the additional workers as a result of changed work incentives.
Compared with the productivity ratios based on LSAY Y03, the estimate of 76% is
higher for early leavers making poor transitions, and lower for Year 12 completers
making poor transitions (see Table 8.2).
As a sensitivity analysis to the estimates provided, we also show here the
potential benefit of more good-transition outcomes using the Productivity
Commission's 76% productivity ratio for those undergoing poor transitions and
assume a mid-point productivity ratio of 88% for those undergoing mixed
transitions.
Using these parameters, the potential addition to labour income is $280.4 million
per annum for poor transitions and $592.3 million per annum for mixed
transitions. This is a total addition to labour income of $872.7 million per annum.
In terms of value added or GDP that addition to labour income would be
equivalent to boosting national GDP by $1.8 billion in today’s dollars – that would
be an addition to overall GDP of about 0.14%.
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8.6 Longer term impacts
So far, the focus of the paper has been on the effects of transition over one to four years. If
the factors that underlie poor and mixed transitions (such as low educational attainment)
persist, the cost to the economy is borne out over a much longer time period. It is primarily
by acquiring the skills, habits and attitudes that lead to good transitions that the longerterm costs associated with those who make poor and mixed transitions in the first four
years after leaving school can be reduced.
The main channels through which educational attainment, a key factor determining good
and poor transitions, would impact on the economy over the longer term are
improvements in labour force participation rates and labour productivity. Studies showing
the effects of educational attainment on labour force participation rates and on labour
productivity over the course of the working life provide the basis for calculating the
difference in economic outcomes over the working life of those who, for instance, never
gain basic school qualifications and those who complete Year 12 and/or other
qualifications.
8.6.1
Labour force participation and educational attainment
In the Australian context, a number of studies have considered the possible effect of
improved educational attainment on labour force participation rates.
For example, Treasury researchers Kennedy and Hedley (2003) found that there are notable
differences in participation rates between educational attainment groups, with higher
educational attainment correlating positively with higher participation rates. Further
studies were offered in support of these findings including a 2003 Treasury report by Gruen
and Garbutt that examined the implications of a significant rise in Australian labour force
participation over the next twenty years. A key finding of this report was that:
Some of the rise in participation rates in the [modelling within the report] could
occur as a consequence of recent rises in educational attainment flowing
through to older age groups over time.
In a follow up to the Productivity Commission's modelling of COAG's National Reform
Agenda in 2006 (discussed further below), Productivity Commission researchers Laplagne et
al (2007) examined this issue in detail using data from the HILDA longitudinal survey.
Table 8.3 shows the estimated marginal effects of increased educational attainment on
labour force participation for an individual with Year 11 or lower education.
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Table 8.3: Average marginal effect of increased educational attainment on the
probability of labour force participation (%-pts)
Year 12
Diploma or certificate
Degree or higher
Males
5.7
3.2
8.7
Females
7.7
9.1
16.4
Source: Productivity Commission (2007) estimates based on the HILDA survey 2001-04. Note that the numbers
in this table are the Productivity Commission’s ‘preferred’ estimates sourced from Table C.5 of its paper.
Results above show the marginal effect of increased educational attainment on labour force participation for
the rest of his/her working life for a hypothetical individual who has Year 11 or lower education, acquiring one
of the three specified education levels.
As the table shows, higher educational attainment raises labour force participation rates
for both males and females, all other things equal. The largest gains come from increasing
attainment at the higher education level (degree level or higher). The impact of increased
educational attainment is substantially greater for females than males. Other things equal,
a female with a Bachelor degree is 16% more likely to be in the labour force than a female
with Year 11 or lower education.
In other words, these results imply that if a female with Year 11 or lower education (for
example, an early school leaver) instead completed Year 12, her probability of labour force
participation would be 8 percentage points higher than it otherwise would have been for
the rest of her life.
More recently, Deloitte Access Economics (2009) in a report for Skills Australia found that:
Australians with qualifications at the Certificate lll level or higher have
significantly higher labour force participation rates than Australians of the
same age without such qualifications – and over all working age cohorts.
8.6.2
Labour productivity and educational attainment
Productivity Commission researchers Forbes et al (2010) also revisited the impact of
increased educational attainment on hourly wages (as a proxy for labour productivity). The
main results are shown in the table below.
Table 8.4: Average marginal effect of increased educational attainment on hourly wages
(%)
Year 12
Diploma or certificate
Degree or higher
Males
12.8
13.8
38.4
Females
10.1
11.4
36.7
Source: Productivity Commission (2010) estimates based on the HILDA survey.
Results above show the marginal effect of increased educational attainment on hourly wages for an individual
who has Year 11 or lower education, acquiring one of the three specified education levels.
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As Table 8.4 shows, higher levels of education have a large positive effect on wages
across all levels of higher educational attainment, after controlling for other factors. In
particular, relative to the base case of Year 11 or lower, completing a degree increases
wages by 37-38%, other things equal.
These results imply that if a female with Year 11 or lower education instead completed Year
12, her hourly wage would be 10% higher than it otherwise would have been for the rest of
her life.
8.6.3
Whole of economy impact from improved educational
attainment
Perhaps the best indication of the longer term impact on the economy of improved
educational attainment among young people is provided by whole-of-economy modelling
exercises.
An indication of the broader longer term economic impact from improved educational
attainment was provided by Access Economics (2005). In this study, Access Economics
modelled the outcomes from a lift in education/training over a forty year time horizon.
Specifically, the modelling focused on the benefits of retaining in education to completion
of Year 12 or equivalent qualifications up to around 45,000 to 50,000 students that were
leaving school without completing Year 12 or equivalent qualifications in 2005.
By 2040 the boost to participation in education and training is sufficient to raise
participation by 0.48% and productivity by 0.62%. The combination of the boost to both
productivity and participation leads to a lift in the overall size of GDP of 1.1% by 2040.
While lifting education and training rates would cost the government more money (around
0.05% of GDP), the modelling found that this would be offset by a lift in Government
revenues of 0.27% of GDP. This meant a net improvement in the fiscal balance of 0.22% of
GDP.
The Productivity Commission (2006) has also modelled the longer term impact on the
economy of improved transitions from school by young people as part of its modelling of
the human capital stream of COAG's National Reform Agenda. The scenario modelled was
a 13% increase in the number of Australian 20-24 years completing an upper secondary
education. This would result in the incidence of 20-24 year old Australians not in education
and without an upper secondary education declining from 17% to the lowest level in the
OECD (4%, and equal with Norway) by 2030. By 2030, the improvement in attainment of
upper secondary education would increase workforce participation by 0.38% and
productivity by 0.45%.
In addition, as part of that study the Productivity Commission modelled two other
improvements in educational attainment:

Early childhood development and literacy and numeracy: An extra 18% of children
with low basic skills (estimated at 10-15% of children aged under 5) complete high
school as a consequence of initiatives to improve those skills; Australia attains Finland's
level of literacy and numeracy so that by 2030 an additional 6% of Australian students
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achieve above PISA Level 1 for literacy and numeracy and an additional 10% achieve at
or above PISA Level 3

Adult learning: improved educational attainment for the 38% of Australians aged 25-64
who have not attained at least an upper secondary education. Improvements in
educational attainment were assumed across this age distribution, with the largest
improvements for those aged 15-24 and 25-34 in 2005.15
The results are shown in Table 8.5 below.
Table 8.5: Estimated potential workforce effects from improvements in educational
attainment, 2030
Area
Increased participation
Productivity
no.
%-pts
%
Transitions from school
81,500
0.38
0.45
ECD and literacy and
numeracy
17,000
0.08
0.27
Adult learning
48,000
0.22
0.43
146,500
0.69
1.16
Total
Source: Productivity Commission (2006)
In total, the improvements in educational attainment could increase economy-wide
workforce participation by up to 0.7% and labour productivity by up to 1.2% by 2030.
As noted above, the Productivity Commission has recently revisited the relationships
between educational attainment and workforce participation and wages (as a proxy for
productivity) which were used as inputs into its modelling. Despite some changes to the
magnitude of the estimated relationships, the impact on the modelling results was
considered to be relatively minor.
Overall, these studies provide strong evidence that improving educational attainment of
young people, and therefore youth transitions from school, not only means higher labour
force participation and productivity in the immediate post-school period, but also in the
years after that and throughout their working life.
15
For example, 24% of Australians aged 25-34 in 2005 who did not have an upper secondary education were
assumed to obtain a VET qualification by 2030, and an additional 23% of 25-34 year olds in 2005 with only Year
12 education were assumed to obtain a VET qualification by 2030. Full details are provided in Table 12.5 of the
Productivity Commission's 2006 report.
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9 Conclusions
This report has used the LSAY datasets and supporting information to examine the quality
of transitions made by young people in Australia from school to further education, training
and/or work.
The policy implications of this work are well established, and good transitions by young
people into the labour force will become increasingly important for the Australian economy
over time. In particular, as the Australian population ages, the supply of workers in the
economy will diminish. Good transitions from school to further education and/or work will
help to lift productivity growth and labour force participation, and in turn will support the
productive capacity of the economy.
The results presented in this report suggest that, overall, young people in Australia make
relatively good transitions from school. The first year following formal education is
important. The data in the LSAY Y03 dataset shows that across all school leavers, around
76% of individuals were fully engaged in work and/or study in the first year after having left
school, while around 15% of individuals were seen as at risk of a poor transition. Measured
over the four years from school, the proportion of individuals making a good transition rises
to 82%, indicating some transition success for the LSAY Y03 cohort overall. Some 4% of
individuals were defined as making a poor transition over the four year period.
The results for the LSAY Y03 cohort are broadly similar to the results for the LSAY Y98
cohort presented in the 2006 report. However, a larger proportion of the LSAY Y03 cohort
was in employment one year after leaving school, and a smaller proportion was in study.
The initial at risk group was also slightly larger. A comparison of the cumulative four year
outcomes showed a smaller proportion of the LSAY Y03 cohort were in full-time work in all
four years and a larger proportion in full-time study. There was also a small increase of 1%
in the proportion making poor transitions over four years for the LSAY Y03 cohort.
A caveat on the comparative results above is that transition paths have been defined
slightly differently for the LSAY Y03 cohort, compared with the LSAY Y98 cohort analysed in
the 2006 report. The results discussed above are unlikely to have been affected by these
definitional changes, but a comparison of other transition paths would be affected more
significantly. Small changes in the method of data extraction were also made for the
analysis of the LSAY Y03 cohort. Small differences in the results may therefore not be
statistically significant.
The results in this report also suggest a high rate of good transitions following post-school
study, with the rate of good transitions highest at 96% for university and apprenticeship
completers, and at around 90% for traineeship and other VET completers. However, there
is a significant proportion who are working in an occupation which is short of the potential
implied by their qualifications, and this ‘short of potential’ group is highest for university
graduates. The results for post-school study transitions for the LSAY Y98 cohort showed
some improvement to the results for the LSAY Y95 cohort presented in the 2006 report.
Australia compares relatively well internationally. Analysis by the OECD suggests that youth
transitions from education to work in Australia are better than average. Further, compared
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Youth Transitions Evidence Base: 2012 Update
against other OECD economies Australia has a relatively low rate of unemployment across
young people and a relatively small proportion of young people who are not either in
employment or education and training.
Identifying the characteristics of individuals who are less likely to make a good transition
from school allows policy efforts to be targeted more effectively. Poor transitions were
more likely to occur for individuals that leave school prior to completing Year 12;
Indigenous Australians; and individuals with a disability, or who come from a low socioeconomic background. The challenges facing many of these socio-economic groups are
well recognised, and the results here reinforce the need for policies to assist transition by
young people among these groups.
Additionally, females (particularly those who do not complete Year 12) were found to be
more likely to make a poor transition compared to males. That result may be influenced by
parental or other carer responsibilities that are more commonly taken on by females and
which can impede full-time work or study opportunities.
These results broadly mirror the outcomes of Access Economics’ 2006 report, Youth
Transitions Evidence Base, on which this document is based.
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Youth Transitions Evidence Base: 2012 Update
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‘low performers’, Nation Centre for Vocational Education Research, Adelaide, SA
5000.
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Appendix A: Detailed data on
youth transitions
LSAY Y03
Table A.1: Transition from school – females – early leavers
Year 1
Good transition
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
Cumulative 4 years
47.8%
14.5%
31.6%
1.8%
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
48.0%
2.6%
11.1%
11.9%
0.0%
22.4%
Mixed transition
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
17.2%
14.3%
0.0%
2.9%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
34.5%
0.0%
0.0%
0.0%
34.5%
Initial at risk
Part-time work (unsatisfied)
Unemployed
22.9%
0.0%
12.7%
17.6%
0.0%
0.4%
Not in the labour force
10.2%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
17.2%
Sample size: 356
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Table A.2: Transition from school – females – Year 12 completers
Year 1
Cumulative 4 years
Good transition
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
79.7%
55.6%
23.1%
1.1%
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
83.9%
21.4%
8.2%
12.8%
0.0%
0.0%
0.1%
12.7%
Mixed transition
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
8.2%
7.7%
0.0%
0.5%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
Initial at risk
Part-time work (unsatisfied)
Unemployed
8.0%
0.0%
4.7%
Not in the labour force
3.3%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
24.0%
0.0%
30.3%
3.2%
0.2%
0.2%
2.7%
Sample size: 2401
Table A.3: Transition from school – females – all
Year 1
Good transition
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
Cumulative 4 years
75.3%
49.8%
24.3%
1.2%
Mixed transition
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
9.5%
8.6%
0.0%
0.9%
Initial at risk
Part-time work (unsatisfied)
Unemployed
10.1%
0.0%
5.8%
Not in the labour force
4.3%
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
78.9%
18.8%
8.6%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
15.9%
0.0%
0.0%
0.1%
15.7%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
22.3%
0.0%
29.2%
5.2%
0.2%
0.3%
4.7%
Sample size: 2757
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Table A.4: Transition from school – males – early leavers
Year 1
Cumulative 4 years
Good transition
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
71.4%
26.8%
44.3%
0.3%
Mixed transition
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
8.1%
6.9%
0.0%
1.2%
Initial at risk
Part-time work (unsatisfied)
Unemployed
17.1%
0.0%
14.0%
Not in the labour force
3.2%
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
76.0%
14.9%
27.0%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
16.9%
0.0%
0.0%
0.0%
16.9%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
14.5%
0.0%
19.6%
7.1%
0.8%
0.2%
6.0%
Sample size: 564
Table A.5: Transition from school – males – Year 12 completers
Year 1
Good transition
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
Cumulative 4 years
81.3%
52.8%
27.9%
0.7%
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
87.5%
23.5%
13.4%
10.9%
0.0%
0.0%
0.1%
10.8%
Mixed transition
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
7.0%
6.7%
0.0%
0.3%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
Initial at risk
Part-time work (unsatisfied)
Unemployed
8.1%
0.1%
4.5%
Not in the labour force
3.5%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
23.0%
0.0%
27.5%
1.7%
0.0%
0.1%
1.6%
Sample size: 2250
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Table A.6: Transition from school – males – all
Year 1
Cumulative 4 years
Good transition
Full-time study Cert III+
Full-time work
Part-time work and part-time study
Cert III+ (concurrently)
79.2%
47.2%
31.4%
0.6%
Mixed transition
Full-time study below Cert III
Part-time work (satisfied)
Part-time study
7.2%
6.8%
0.0%
0.5%
Initial at risk
Part-time work (unsatisfied)
Unemployed
10.0%
0.0%
6.5%
Not in the labour force
3.5%
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all
years
Part-time work and part-time study
Cert III+ (concurrently) all years
Other combinations
85.0%
21.7%
16.3%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
12.2%
0.0%
0.0%
0.1%
12.1%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
21.2%
0.0%
25.8%
2.8%
0.2%
0.1%
2.5%
Sample size: 2814
Table A.7: Transition from school – Indigenous Australians
Cumulative 4 years
Early leavers
Year 12
All
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
64
28.3%
1.5%
13.3%
3.9%
146
78.8%
7.1%
12.0%
24.2%
210
65.3%
5.6%
12.3%
18.7%
0.0%
0.0%
0.0%
9.7%
35.5%
28.6%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
46.5%
0.0%
0.0%
0.0%
46.5%
14.7%
0.0%
0.0%
0.0%
14.7%
23.2%
0.0%
0.0%
0.0%
23.2%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
25.2%
0.0%
0.0%
25.2%
6.5%
0.0%
0.1%
6.1%
11.5%
0.0%
0.1%
11.2%
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Table A.8: Transition from school – those with a health problem or disability
Cumulative 4 years
Early leavers
Year 12
All
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
63
45.3%
1.5%
19.9%
12.1%
266
78.0%
12.2%
10.6%
21.4%
329
70.9%
9.9%
12.6%
19.4%
0.0%
0.0%
0.0%
11.8%
33.7%
29.0%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
38.4%
0.0%
0.0%
0.0%
38.4%
19.3%
0.0%
0.0%
0.3%
19.0%
23.4%
0.0%
0.0%
0.2%
23.2%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
16.3%
0.0%
0.0%
16.3%
2.7%
0.0%
0.8%
1.9%
5.7%
0.0%
0.6%
5.0%
Table A.9: Transition from school – part-time work at school
Cumulative 4 years
Early leavers
Year 12
All
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
545
76.7%
14.2%
24.1%
16.6%
3,190
87.4%
20.5%
12.6%
26.4%
3,735
85.7%
19.5%
14.4%
24.9%
0.0%
0.0%
0.0%
21.8%
27.9%
27.0%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
16.6%
0.0%
0.0%
0.0%
16.6%
11.3%
0.0%
0.0%
0.1%
11.2%
12.1%
0.0%
0.0%
0.1%
12.0%
6.7%
0.0%
0.3%
6.5%
1.3%
0.1%
0.0%
1.2%
2.2%
0.1%
0.1%
2.0%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
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Table A.10: Transition from school – VET in school
Cumulative 4 years
Early leavers
Year 12
All
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
158
68.0%
9.0%
28.1%
12.7%
1,124
82.1%
14.3%
18.9%
23.2%
1,282
80.5%
13.7%
19.9%
22.0%
0.0%
0.0%
0.0%
18.3%
25.7%
24.9%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
18.0%
0.0%
0.0%
0.0%
18.0%
13.8%
0.0%
0.0%
0.1%
13.7%
14.3%
0.0%
0.0%
0.1%
14.2%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
14.0%
0.0%
0.0%
14.0%
4.1%
0.2%
0.4%
3.4%
5.2%
0.2%
0.3%
4.6%
Table A.11: Transition from school – VET in school – males
Cumulative 4 years
Early leavers
Year 12
All
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
95
76.4%
14.3%
30.8%
15.4%
564
87.0%
15.7%
23.9%
22.7%
659
85.6%
15.5%
24.8%
21.7%
0.0%
0.0%
0.0%
15.9%
24.7%
23.6%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
11.3%
0.0%
0.0%
0.0%
11.3%
11.3%
0.0%
0.0%
0.0%
11.3%
11.3%
0.0%
0.0%
0.0%
11.3%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
12.3%
0.0%
0.0%
12.3%
1.7%
0.0%
0.0%
1.7%
3.1%
0.0%
0.0%
3.1%
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Table A.12: Transition from school – VET in school – females
Cumulative 4 years
Early leavers
Year 12
All
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
63
54.4%
0.4%
23.6%
8.3%
560
77.0%
12.8%
13.6%
23.8%
623
75.0%
11.7%
14.5%
22.4%
0.0%
0.0%
0.0%
22.1%
26.7%
26.3%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
28.7%
0.0%
0.0%
0.0%
28.7%
16.4%
0.0%
0.0%
0.2%
16.2%
17.5%
0.0%
0.0%
0.2%
17.3%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
16.9%
0.0%
0.0%
16.9%
6.5%
0.5%
0.8%
5.3%
7.5%
0.4%
0.7%
6.4%
Early leavers
Year 12
All
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
43
40.4%
2.6%
20.0%
7.2%
478
85.8%
30.6%
6.3%
18.7%
521
81.4%
27.9%
7.6%
17.6%
0.0%
0.0%
0.0%
10.5%
30.2%
28.3%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
46.3%
0.0%
0.0%
0.0%
46.3%
10.0%
0.0%
0.0%
0.2%
9.8%
13.5%
0.0%
0.0%
0.1%
13.3%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
13.3%
0.0%
0.0%
13.3%
4.3%
0.0%
0.7%
3.6%
5.2%
0.0%
0.6%
4.5%
Table A.13: Transition from school – migrants
Cumulative 4 years
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Table A.14: Transition from school – English ability
Cumulative 4 years
V good
Good
Average
Not good
Poor
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time
study all years
Part-time work and part-time
study Cert III+ (concurrently) all
years
Other combinations
1,178
84.6%
27.7%
7.4%
1,943
85.2%
23.5%
11.9%
2,125
80.7%
16.1%
15.4%
272
69.0%
10.7%
13.3%
46
60.3%
0.0%
9.6%
21.0%
23.2%
21.5%
16.5%
29.5%
0.0%
0.0%
0.0%
0.0%
0.0%
28.5%
26.7%
27.7%
28.5%
21.2%
Mixed transition
Full-time study below Cert III all
years
Part-time study all years
Part-time work (satisfied) all
years
Other combinations
11.6%
13.2%
14.2%
21.9%
29.7%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.2%
0.0%
11.6%
13.2%
14.1%
21.6%
29.7%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
3.8%
0.0%
0.4%
1.6%
0.0%
0.2%
5.2%
0.4%
0.1%
9.2%
0.0%
0.3%
10.0%
0.0%
0.0%
3.4%
1.4%
4.6%
8.9%
10.0%
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Table A.15: Transition from school – Maths ability
Cumulative 4 years
V good
Good
Average
Not good
Poor
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time
study all years
Part-time work and part-time
study Cert III+ (concurrently) all
years
Other combinations
1,104
87.4%
34.5%
7.1%
1,663
88.0%
26.0%
9.6%
2,032
80.2%
14.8%
15.7%
600
72.6%
9.4%
15.2%
131
59.2%
4.5%
15.6%
20.0%
25.4%
21.5%
19.6%
11.7%
0.0%
0.0%
0.0%
0.0%
0.0%
25.9%
26.9%
28.2%
28.5%
27.4%
Mixed transition
Full-time study below Cert III all
years
Part-time study all years
Part-time work (satisfied) all
years
Other combinations
10.4%
9.8%
15.3%
19.8%
31.2%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.1%
0.0%
10.4%
9.7%
15.1%
19.7%
31.2%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition
outcomes
2.2%
0.0%
0.1%
2.2%
0.0%
0.2%
4.5%
0.3%
0.2%
7.6%
0.4%
0.3%
9.6%
0.0%
0.0%
2.1%
2.0%
4.0%
6.9%
9.6%
Table A.16: Transition from school – location
Cumulative 4 years
Metropolitan
Provincial
Remote
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
4,012
82.9%
21.3%
11.2%
21.2%
1,461
79.8%
17.6%
16.1%
23.1%
98
81.4%
9.1%
12.2%
32.3%
0.0%
0.0%
0.0%
29.1%
22.9%
27.8%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
13.1%
0.0%
0.0%
0.1%
13.1%
16.2%
0.0%
0.0%
0.1%
16.1%
17.7%
0.0%
0.0%
0.0%
17.7%
4.0%
0.2%
0.2%
3.6%
4.1%
0.2%
0.3%
3.6%
1.0%
0.0%
0.0%
1.0%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
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Table A.17: Transition from school – socioeconomic status
Cumulative 4 years
Low
Medium
High
Sample size (number)
Good transition
Full-time study all years
Full-time work all years
Full-time work or full-time study all years
Part-time work and part-time study Cert III+
(concurrently) all years
Other combinations
1,829
77.8%
16.2%
13.3%
20.0%
1,842
84.6%
19.5%
13.5%
25.0%
1,751
86.2%
27.3%
8.6%
22.7%
0.0%
0.0%
0.0%
28.2%
26.6%
27.6%
Mixed transition
Full-time study below Cert III all years
Part-time study all years
Part-time work (satisfied) all years
Other combinations
16.3%
0.0%
0.0%
0.0%
16.3%
12.5%
0.0%
0.0%
0.1%
12.4%
12.5%
0.0%
0.0%
0.1%
12.4%
5.9%
0.5%
0.3%
5.2%
2.9%
0.0%
0.1%
2.8%
1.3%
0.0%
0.0%
1.3%
Poor transition
Unemployed all years
Not in the labour force all years
Combination of poor transition outcomes
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Table A.18: Transition from post-school study – university
Cumulative 3 years
Completers
Non-completers
95.7%
87.0%
1.5%
36.0%
2.8%
46.7%
92.2%
92.2%
12.9%
35.7%
11.2%
32.4%
Short of potential
Work in skill mismatch occupation
Mostly work in skill mismatch occupation
8.7%
7.7%
1.0%
0.0%
0.0%
0.0%
Mixed transition
Part time study
Mostly part time study with one good year
Mostly part time study with one bad year
Other mixed
1.7%
0.0%
0.0%
0.2%
1.4%
1.6%
0.0%
0.2%
0.2%
1.1%
Poor transition
Work in skill appropriate occupation and poor transition
outcomes
Work in skill mismatch occupation and poor transition
outcomes
Study and poor transition outcomes
Part time work (unsatisfied)
Unemployed in all years
NILF in all years
Combination of poor transition outcomes
2.6%
6.2%
0.6%
2.5%
0.6%
0.0%
0.6%
0.0%
0.0%
0.3%
0.4%
1.5%
0.1%
0.0%
0.6%
1.5%
Good transition
To Potential
FT Study all years
Work in skill appropriate occupation
Mostly work in skill appropriate occupation
Study and work (other)
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Table A.19: Transition from post-school study – apprenticeships
Cumulative 3 years
Completers
Non-completers
96.3%
86.6%
3.7%
52.0%
7.0%
23.9%
82.7%
82.7%
7.8%
29.9%
15.7%
29.3%
Short of potential
Work in skill mismatch occupation
Mostly work in skill mismatch occupation
9.7%
9.3%
0.4%
0.0%
0.0%
0.0%
Mixed transition
Part time study
Mostly part time study with one good year
Mostly part time study with one bad year
Other mixed
0.7%
0.0%
0.0%
0.0%
0.7%
0.5%
0.0%
0.0%
0.0%
0.5%
Poor transition
Work in skill appropriate occupation and poor transition
outcomes
Work in skill mismatch occupation and poor transition
outcomes
Study and poor transition outcomes
Part time work (unsatisfied)
Unemployed in all years
NILF in all years
Combination of poor transition outcomes
3.0%
16.8%
0.9%
6.1%
0.9%
0.0%
0.0%
0.0%
0.0%
0.0%
1.2%
0.9%
0.0%
2.2%
5.5%
2.2%
Good transition
To Potential
FT Study all years
Work in skill appropriate occupation
Mostly work in skill appropriate occupation
Study and work (other)
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Table A.20: Transition from post-school study – traineeships
Cumulative 3 years
Completers
Non-completers
89.2%
85.6%
5.9%
40.2%
8.7%
30.8%
81.8%
81.8%
7.9%
44.0%
14.4%
15.4%
Short of potential
Work in skill mismatch occupation
Mostly work in skill mismatch occupation
3.6%
2.2%
1.4%
0.0%
0.0%
0.0%
Mixed transition
Part time study
Mostly part time study with one good year
Mostly part time study with one bad year
Other mixed
3.1%
0.0%
0.6%
0.0%
2.5%
2.2%
0.0%
0.0%
0.0%
2.2%
Poor transition
Work in skill appropriate occupation and poor transition
outcomes
Work in skill mismatch occupation and poor transition
outcomes
Study and poor transition outcomes
Part time work (unsatisfied)
Unemployed in all years
NILF in all years
Combination of poor transition outcomes
7.7%
16.1%
4.3%
8.9%
0.4%
0.0%
0.6%
0.0%
0.0%
1.3%
1.1%
0.0%
0.0%
0.9%
2.3%
4.0%
Good transition
To Potential
FT Study all years
Work in skill appropriate occupation
Mostly work in skill appropriate occupation
Study and work (other)
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Table A.21: Transition from post-school study – other VET
Cumulative 3 years
Completers
Non-completers
90.6%
88.4%
8.0%
35.4%
10.4%
34.7%
82.0%
82.0%
5.6%
37.9%
11.6%
26.9%
Short of potential
Work in skill mismatch occupation
Mostly work in skill mismatch occupation
2.2%
1.7%
0.4%
0.0%
0.0%
0.0%
Mixed transition
Part time study
Mostly part time study with one good year
Mostly part time study with one bad year
Other mixed
2.1%
0.0%
0.1%
0.0%
2.0%
4.4%
0.0%
0.0%
0.0%
4.4%
Poor transition
Work in skill appropriate occupation and poor transition
outcomes
Work in skill mismatch occupation and poor transition
outcomes
Study and poor transition outcomes
Part time work (unsatisfied)
Unemployed in all years
NILF in all years
Combination of poor transition outcomes
7.4%
13.6%
1.8%
7.1%
0.0%
0.0%
2.7%
0.0%
0.5%
0.4%
2.0%
2.7%
0.0%
0.9%
2.1%
0.8%
Good transition
To Potential
FT Study all years
Work in skill appropriate occupation
Mostly work in skill appropriate occupation
Study and work (other)
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Limitation of our work
General use restriction
This report is prepared solely for the internal use of DEEWR. This report is not intended to and
should not be used or relied upon by anyone else and we accept no duty of care to any other person
or entity. The report has been prepared for the purpose of examining youth transitions. You should
not refer to or use our name or the advice for any other purpose.
Disclaimer
This report uses unit record data from the 1998 and 2003 cohorts of the Longitudinal Surveys of
Australian Youth provided by the Australian Data Archive (ADA). LSAY is managed and funded by the
Australian Government Department of Education, Employment and Workplace Relations (DEEWR),
with support from state and territory governments. The National Centre for Vocational Education
Research (NCVER) provides analytical and reporting services, while the LSAY data are collected by
computer assisted telephone interviewing by the Wallis Consulting Group. However the findings and
views reported here should not be attributed to DEEWR, ADA, the NCVER or the Wallis Consulting
Group.
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