social policy research centre seminar, 13th april 2016 · social policy research centre seminar,...
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Gill Main, University of Leeds Melissa Wong, University of New South Wales
Social Policy Research Centre seminar, 13th April 2016
Youth transitions ◦ Increasingly: Diverse Prolonged Fragmented (Eurostat, 2009)
The Global Financial Crisis ◦ Particularly strong impact on young people ◦ Exacerbating existing trends ◦ Youth unemployment ◦ Political ideology vs economic necessity
Australia-UK comparison ◦ Liberal/Anglo-Saxon welfare regimes ◦ Similarities in current policy and rhetoric ◦ Conditionality and reductions to youth benefits ◦ Stronger impact of crisis in UK
Higher risk of poverty
Mismatch between skills and jobs
Higher risk of: ◦ Unemployment ◦ Under-employment ◦ Work insecurity
Housing difficulties
‘Youth’ not homogeneous: vulnerable groups Experience of child poverty Disability Ethnic minority/Indigenous population
UK: Telfer, ND Australia: Foundation for Young Australians, 2015
Drastic changes in response to crisis in both countries ◦ Pre-2010: stimulus ◦ Post-2010: austerity ◦ Post-2015: ongoing austerity; increased cuts to welfare
Attempts to increase conditionality/decrease entitlements for youth ◦ UK: Housing Benefit (under 35s); community work after 6 months ◦ Australia: Proposals to increase waiting times for Newstart Allowance for
under 30s (rejected by Senate), increase age of eligibility for under 25s (not passed yet)
Deregulation and fees in universities
Necessity or ideology? (UK) ◦ Pensions protected; cuts focused on working-age benefits ◦ Cutting working-age benefits impacts families with children ◦ Neutral impact of austerity
“We’re all in it together” – but youth are more ‘in it’ than most
Policies targeted youth – direct and indirect
impacts ◦ Hostile rhetoric – “well-worn path from the
school gate onto a life on benefits” ◦ Direct and indirect discrimination against youth
in welfare reforms Direct: higher conditionality for youth (e.g. 30 hours
unpaid ‘community work’); housing benefit withdrawn for under 35s living alone
Indirect: ‘bedroom tax’ limits ability to draw on family resources for poor youth
Focus on pathways and transitions
Cuts to education budget Youth Employment Strategy (2015 Budget): ◦ High levels of investment in supporting young
people not in education or employment ◦ Intensive support for vulnerable youth (mental
health, migrants) ◦ Early School Leaver policy: increased conditionality
Can a comparable typology of youth
transitions from education to the labour market be identified for the Australian and UK contexts?
What socio-demographic characteristics are associated with different trajectories and do these differ between Australia and the UK?
Youth ◦ No agreed age range 15 (Australia)/16 (UK)-29 (see Eurostat, 2009)
◦ Descriptive of a transition, not a state (Eurostat, 2009) Being/becoming as characteristic of youth? Extension of childhood?
Not in Education, Employment or Training (NEET) ◦ Problematic and contested term ◦ Heterogeneous group ◦ ‘Unemployed’ and ‘inactive’ more useful cross-sectional classifications ◦ ‘Stable’ and ‘unstable’ more useful longitudinal classifications
Labour market trajectories ◦ Movement from compulsory education towards labour market
participation (or not) ◦ ‘Trajectory’ may be over-simplified (see Dorsett and Lucchino, 2012)
UK: Understanding Society (US) ◦ UK’s representative longitudinal household survey ◦ Annual coverage of 40,000 households ◦ All adults (16+) interviewed ◦ Diverse range of topics – covers health, work, education,
income, family, and social life
Australia: Household Income and Labour Dynamics (HILDA) ◦ Australia’s representative longitudinal household survey ◦ Annual coverage of 7,000+ households ◦ All adults (15+) interviewed ◦ Covers family dynamics, economic and subjective well-
being and labour market dynamics
Selected if: ◦ Aged 15/16-29 at wave 1 (2009) ◦ Valid responses to labour market status in each wave
Resulting sample: ◦ Australia: 2,384 ◦ UK: 4,561
Identifying trajectories ◦ Two-step cluster analysis ◦ Based on labour market status at each wave
Examining trajectories ◦ Logistic regression examining socio-demographic characteristics
associated with clusters ◦ Comparative analysis: most comparable variables/common denominators
0
10
20
30
40
50
60
UK Australia UK Australia UK Australia UK Australia
Age % women English as first language Born
Mea
n ag
e/%
over
all
0.0
10.0
20.0
30.0
40.0
50.0
60.0
UK Australia UK Australia UK Australia
Low qualifications Medium qualifications High qualifications
% ov
eral
l
Low: up to year 11 Medium: year 12 or higher, lower than degree High: Bachelor’s degree or higher
Fixed at five clusters ◦ Conceptually relevant ◦ Good fit ◦ Comparable across Australia and the UK
Clusters identified: ◦ Employed ◦ Education to employment ◦ Unstable ◦ Education ◦ Inactive (not engaged with labour force)
0
5
10
15
20
25
30
UK Australia
Mea
n ag
e
Education
Education to employment
Unstable
Employed
Inactive
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
UK Australia
% w
omen
Education
Education to employment
Unstable
Employed
Inactive
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20.0
UK Australia
% no
t Enl
igh
as fi
rst l
angu
age
Education
Education to employment
Unstable
Employed
Inactive
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
UK Australia
% no
t bor
n in
cou
ntry
Education
Education to employment
Unstable
Employed
Inactive
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
UK Australia
% lo
w q
ualif
icat
ions
Education
Education to employment
Unstable
Employed
Inactive
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
UK Australia
% m
ediu
m q
ualif
icat
ions
Education
Education to employment
Unstable
Employed
Inactive
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
UK Australia
% hi
gh q
ualif
icat
ions
Education
Education to employment
Unstable
Employed
Inactive
01020304050607080
UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia
Lone adultwithoutchildren
Lone adultwith children
Couplewithoutchildren
Couple withchildren
Multipleadults
withoutchildren
Multipleadults with
children
% in
edu
catio
n
0
10
20
30
40
50
60
70UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia
Lone adultwithoutchildren
Lone adultwith children
Couplewithoutchildren
Couple withchildren
Multipleadults
withoutchildren
Multipleadults with
children
% ed
ucat
ion
to e
mpl
oym
ent
05
101520253035404550
UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia
Lone adultwithoutchildren
Lone adultwith children
Couplewithoutchildren
Couple withchildren
Multipleadults
withoutchildren
Multipleadults with
children
% un
stab
le
0
5
10
15
20
25
30
35UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia
Lone adultwithoutchildren
Lone adultwith children
Couplewithoutchildren
Couple withchildren
Multipleadults
withoutchildren
Multipleadults with
children
% em
ploy
ed
0
10
20
30
40
50
60UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia UK
Aust
ralia
Lone adultwithoutchildren
Lone adultwith children
Couplewithoutchildren
Couple withchildren
Multipleadults
withoutchildren
Multipleadults with
children
% in
activ
e
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
UK Australia
% liv
ing
with
par
ents
Education
Education to employment
Unstable
Employed
Inactive
Characteristics at wave 4 ◦ Not predictors ◦ Overall and by age group at wave 1 (15/16-24; 25-29)
Range of demographic characteristics examined ◦ Age ◦ Gender ◦ Educational qualifications ◦ Household structure ◦ Living with parent(s) ◦ English as first language ◦ Born in Australia/UK
Characteristics: ◦ Education: younger people without children ◦ Education to employment: younger people ◦ Unstable: low-qualified women with children (UK only) ◦ Employment: older men in couples without children ◦ Inactivity: older women, lower qualifications, children
Clear similarities in clusters based on young people’s labour market trajectories
Differences in relation to inactivity ◦ Dominated by women with children in the UK ◦ Slightly less clear in Australia
No clusters marked by constant unemployment ◦ “Inactivity” evident among women with children…
Instability an important consideration ◦ 1 in 5 in UK and over 1 in 4 in Australia in unstable situations ◦ Partly driven by women with children – especially in the UK ◦ May also be a result of type of work - temporary/unstable/under employment
Number and quality of jobs
Socio-economic factors ◦ Poverty ◦ Deprivation ◦ Social security claims ◦ Housing ◦ Ethnicity/Indigenous/CALD populations ◦ Parental characteristics (education, income) ◦ Location ◦ Health, disability ◦ Caring responsibilities
Outcomes ◦ Subjective well-being ◦ Health ◦ Income, poverty, deprivation (outcome or predictor?)
Longitudinal analysis, additional waves