Social inclusion research at NATSEM: recent findings and future plans Justine McNamara Presentation...
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Transcript of Social inclusion research at NATSEM: recent findings and future plans Justine McNamara Presentation...
Social inclusion research at NATSEM: recent findings and future plans
Justine McNamaraPresentation to Department of Planning and Community
Development, Victoria31 July 2009
2
Overview
● Child Social Exclusion Index: work completed to date and main findings
● Opportunity and Disadvantage at a small area level
● Other related work and future research plans
3
Social exclusion
● Multidimensional measure of disadvantage
● Limitations of income-based measures of disadvantage
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Social exclusion
“Social exclusion happens when people or places suffer from a series of problems such as unemployment, discrimination, poor skills, low incomes, poor housing, high crime, ill health and family breakdown. When such problems combine they can create a vicious cycle.” (SEU,
Office of the Deputy Prime Minister)
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Spatial differences
Increasing interest in Australia in examining geographical differences in advantage and disadvantage
- federal government SIU’s early priority areas include locational disadvantage:
• ‘Focusing on particular locations, neighbourhoods and communities to ensure programs and services are getting to the right places’ (Social Inclusion Website, http://www.socialinclusion.gov.au/Priorities/Pages/default.aspx)
- ABS – Community Indicators summit (July 2009)
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Child Social Exclusion Index
● Child-focused, place-based, composite index
● Funded from an ARC Discovery Grant and an ARC Linkage Grant
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AcknowledgmentsFellow authors: Anne Daly, Robert Tanton, Ann Harding
This work was funded by an Australian Research Council Discovery Grant (DP 560192) and an Australian Research Council Linkage Grant (LP775396)
Linkage partners
Based on data provided by the Australian Bureau of Statistics from the 2001 and 2006 Census of Population and Housing
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2006 CSE Index
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2006 index - methodology
Data: Australian 2006 Census of Population and Housing
Spatial Unit: Statistical Local Area (SLA)
Statistical method: Principal Components Analysis
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Variables in the 2006 modelVariable in Census
Social Exclusion Measure Developed
Family Type Proportion of children aged 0 – 15 in single parent family
Education in family Proportion of children aged 0 – 15 with no-one in the family having completed Year 12
Occupation in family
Proportion of children aged 0 – 15 with highest occupation in family blue collar worker
Housing tenure Proportion of children aged 0 – 15 in public housing
Labour force status of parents
Proportion of children aged 0 – 15 in family where no parent working
Internet connection Proportion of children aged 0 – 15 living in dwellings with no internet connection
Motor Vehicle Proportion of children aged 0 – 15 in household with no motor vehicle
Volunteering
Proportion of children aged 0 – 15 in family where no parent did voluntary work over the past 12 months
Income
Proportion of children aged 0 – 15 in household with income in bottom quintile of equivalent gross household income for all households in Australia
Note: Occupation proportions are calculated using only those families in which at least one person was working.The public housing definition used includes community housing.Data source: ABS Census of Population and Housing 2006
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12
13
State and territory differences, 2006 Index
47.546.3
15.8 17.923.9
7.3
0.0
25.8
7.5
21.5 23.1
11.7
20.6 22.9
9.4
41.7
0
10
20
30
40
50
60
NSW VIC QLD SA WA TAS NT ACT
Bottom CSE 06 quintile Top CSE 06 quintile
% o
f all c
hild
ren
with
in st
ate i
n bo
ttom
/top
quin
tiles
Data source: ABS Census of Population and Housing 2006, authors’ calculations
14
Capital city/balance of state, 2006 Index
15.5
23.319.4
28.8
13.1
21.3
28.0
14.6
4.7
31.5
05
101520253035
Mostexcluded
20%
Quintile 2 Quintile 3 Quintile 4 Leastexcluded
20%
2006 Child Social Exclusion (CSE) quintile children 0-15 years
% o
f chi
ldre
n
Capital City Balance of state
Data source: ABS Census of Population and Housing 2006, authors’ calculations
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Analysis of characteristics, 2006 Index
Capital cities
Balance of
Australia % point
difference %
difference
Child and family characteristics
Mean proportion of children
One parent family
18.2 21.6 3.4 18.4
Not Year 12
16.5 25.3 8.8 53.1
Blue collar
15.8 19.1 3.3 20.6
Rent –public
4.6 7.0 2.4 52.8
Parents not working
14.9 17.6 2.7 18.4
No internet connection
17.5 23.9 6.4 36.6
No motor vehicle
3.7 4.7 1.0 27.0
No parent volunteering
68.3 62.0 -6.3 -9.2
Bottom income quintile
17.1 22.1 5.0 29.4
Note: Percentages shown here relate only to those children with valid data for that characteristic.Occupation proportions are calculated using only those families in which at least one person was working. The public housing definition used includes community housing.Data source: ABS Census of Population and Housing 2006; authors’ calculations.
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Over time comparison: 2001 to 2006
What has happened over these 5 years in regard to individual variables which make up the index?
What happened to child social exclusion risk at a small area level – persistence or change?
What might be driving such persistence or change?
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Over time comparison
● Create versions of 2001 and 2006 index suitable for over time comparison
● Restricted variables (no internet, no volunteering, some issues re comparison of education over time)
● Weighting methodology
● Changes in SLA boundaries
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What happened between 2001 and 2006: national overview of small area child characteristics
Characteristics 2001 2006 in single parent families 0.19 0.19 in families with no education Year 12 0.25 0.20 with highest parental occupation blue collar 0.18 0.17 living in public housing 0.07 0.05 with neither parent working 0.18 0.16 in families with no motor vehicle 0.05 0.04 in families with low income 0.19 0.19
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What happened between 2001 and 2006: small areas
● Similar overall patterns 2001 and 2006 – generally, risk levels persist
● Slightly more capital city areas ‘high risk’ in 2006 than 2001, but ‘low risk’ areas still overwhelmingly capital city
● Some decrease in high risk areas in Brisbane and Perth (?resources boom)
● Some downward movement and growing clusters, but hard to identify spatial patterns
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Opportunity and Disadvantage: small area differences in well-being
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Opportunity and Disadvantage Discovery Grant
(with ARC research network partners and others)● To better understand how well-being varies by location
● To better understand spatial well-being for different sub-groups in the population (children and older people)
● To generate synthetic information on the small area characteristics of households
● To create databases of small area statistics and incorporate these into a GIS Based spatial decision support system to allow online access for Australian researchers
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Opportunity and Disadvantage Discovery Grant – selected outputs (current and in progress):
● Synthetic small area poverty estimates for all Australians, children and older people
● Synthetic small area housing stress estimates
● Analysis of child housing disadvantage at a small area level
● Analysis of children in jobless households at a small area level
● Small area analysis of economic disadvantage and advantage among older
Australians
● National and small area analysis of impact of increase to single age pension
● Interactive online maps of indicators of well-being for children and older people
● Literature reviews of child and older adult well-being and disadvantage
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Where older single people benefited from pension increase
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Other related work
Examples include:
● Working poverty
● Child care
● Income inequality at a small area level
● Research on carers
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Future plans
Extending child social exclusion work:
Funding through ARC Discovery grant (possible 2010)
● Extensive methodological work
● Incorporation of new variables
● Development of youth index
● Detailed analysis, including over time
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Future plans
Developing synthetic small area estimates of social exclusion variables
Funding through future Linkage grant (November round)
● Unavailability of some important social exclusion data at a small area level (eg social capital variables, financial hardship variables)
● Explore methodologies for generating this data using small area estimation techniques
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Future plans
Funding though collaborations with States:
For example:
● Further analysis of working poverty
● Further child care research
● Cost sharing arrangement between the States● Each State provide some funding; analysis done for all States
● State has input into research questions and their topics of interest.
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Funding
● Social exclusion work was funded by ARC grants (Discovery and Linkage) and consultancies
● If your Department has some ideas around social exclusion, or has some work that needs to be done by experienced methodologists in the social exclusion area, then contact us:● Justine McNamara, 6201 2776
● Robert Tanton, 6201 2769
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Data available on the web
www.natsem.canberra.edu.au
Interactive map:
http://web.natsem.canberra.edu.au/maps/AUST_CSE/atlas.html
www.natsem.canberra.edu.au