Social inclusion research at NATSEM: recent findings and future plans

Social inclusion research at NATSEM: recent findings and future plans

Justine McNamaraPresentation to Department of Planning and Community

Development, Victoria31 July 2009

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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

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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

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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

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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