1. Approaches to measuring disadvantage at a small area level: children and older people Presentation to Measuring Disadvantage and Outcomes Based Reporting Workshop at Defining Diversity ACTCOSS Conference, November 4 – 5th 2010, Canberra Justine McNamara

2. 2 Acknowledgements ●This presentation showcases work funded by ARC Discovery Grant DP1094318, ARC Discovery Grant DP664429 and ARC Linkage Grant LP775396 ●Many people have contributed to the work presented here, including the investigators and funding partners on the above grants, and the authors of papers from which the material presented here has been drawn

3. 3 Overview of presentation ●Small areas ●Measuring child disadvantage: child social exclusion risk ●Disadvantage among older people: two worlds of ageing

4. 4 Small areas Increasing interest in Australia in examining geographical differences in advantage and disadvantage: ●Work by Vinson and others ●To what extent was economic boom shared equally? ●Are inequalities widening? ●Neighbourhood effects ●‘locational disadvantage’ part of social inclusion agenda ●Place-based service planning

5. 5 Challenges in small area measurement To name a few: ●Data, data, data ●Small sample sizes ●Choice of geographical unit ●‘Modifiable areal unit problem’ ●Ecological fallacy

6. 6 Child social exclusion risk

7. 7 Conceptualising social inclusion/exclusion Very large literature on conceptualising and measuring social exclusion, and much debate. Issues include: -Differences between social exclusion and poverty -Individual/structural -Relational aspects -Normative judgements -Overlap of risk/causal factors with outcomes -How important is persistence/intergenerational issues -Wide and deep exclusion

8. 8 Social exclusion and children ●Levitas et al. (2007)UK work on matrix of social exclusion measures which can be applied to different age groups ●UK social exclusion and poverty audit indicators for children (Opportunity for All) ●SPRC Australian work on social exclusion measures related to children ●Small but increasing number of international small area indicators of child deprivation/disadvantage (eg UK, South Africa)

9. 9 Measuring child social exclusion risk at a small area level ●Earlier ARC-funded research into child social exclusion, leading to development of NATSEM’s original Child Social Exclusion (CSE) Index ●Work under new grant (2010 – 2012): -Further development and refinement of CSE Index -Creation of an index of youth social exclusion risk -More analysis ●Unit of analysis: Statistical Local Area (SLA)

10. 10 Some additional conceptual and measurement issues ●Data availability, especially for some concepts/dimensions ●The role (and availability) of data on children’s subjective well-being ●Importance of policy relevance ●Composite index vs individual variables ●Use of domains

11. 11 Refining the index ●Re-examination of conceptual and measurement frameworks ●Investigation of new sources of data/variables ●Re-visiting methodology (first version used Principal Components Analysis to create index – similar to SEIFA indexes; this version we are creating domains, using PCA within domains and then equal weighting to combine domains) ●Comparing results ●WORK IN PROGRESS

12. 12 Domains and variables used for original and first revision of NATSEM CSE index DomainsVariablesOriginal CSE indexFirst revision Socio-economicSingle parent family√√ In bottom income quintile√√ No family member completing year 12√√ Highest occupation of family members√× No parent working√√ EngagementNo internet at home√√ No parent volunteering√√ No motor vehicle√√ HousingPublic housing√× High renting cost×√ Health services & disability Ratio of GPs×√ Ratio of dentists×√ Children with disability×√

13. 13 Additional proposed variables Housing: ●Overcrowding ●? adjustment to housing costs variable Education/development: ●literacy/numeracy ●Australian Early Development Index Transport ●? Forced car ownership ●? Fuel price vulnerability Health ●Replace disability with an alternative measure?

14. 14 Statistics of main variables, Australia, 2006 VariableUnitMeanSD Single parent family% of children0.200.07 In bottom income quintile% of children0.230.12 No family member completing year 12% of children0.240.13 No parent working% of children0.160.09 No internet at home% of children0.260.17 No parent volunteering% of children0.600.11 No motor vehicle% of children0.070.12 High renting cost% of children0.070.05 Children with disability% of children0.020.01 Ratio of GPsPer 1000 persons1.71 Ratio of dentistsPer 1000 persons0.44 Source: ABS Census 2006; authors’ calculations

15. 15 Characteristics for areas with greatest and least risk (n=50) MeanUnit 50 small areas with highest risk 50 small areas with least risk Single parent family% of children38.710.3 No family member completed Yr 12% of children50.14.8 No parent working% of children37.96.8 No internet at home% of children65.66.1 No motor vehicle% of children37.31.2 No parent volunteering% of children76.857.3 Bottom income quintile% of children50.06.9 High renting cost% of children11.93.9 Children with disability% of children1.71.2 GP to 1000 populationPer 1000 persons1.62.4 Dentist to 1000 populationPer 1000 persons0.20.7 Source: ABS Census 2006; authors’ calculations

16. 16 Two worlds of ageing

17. 17 Measuring disadvantage among older Australians ●Australia ranks low in OECD in terms of income ratios of people aged 65 + to those aged 18-64 ●BUT income alone not a good measure of economic circumstances for older Australians ●Very large differences in the distribution of income, wealth and home ownership ●Vulnerabilities of older renters ●Increasing interest in spatial dimensions of disadvantage in Australia, but little research on small areas and older people

18. 18 Income distribution by age group Data source: SIH 2005/06

19. 19 Tenure type by age group Data source: SIH 2005/06

20. 20 Coverage and definitions ●Aged 55 and above ●Contrast analysis – narrow definitions ●Two groups (the most vs the least disadvantaged) ● relative economic advantage (national top two quintiles of equivalised household disposable income, paying no rent or mortgage, and relying mainly on private household income) ● deep economic disadvantage (national bottom income quintile, paying rent, and relying mainly on government income benefits) ●Unit of analysis – statistical local area (SLA) ●Synthetic estimates

21. 21 Spatial Methodology : Reweighting Method turning the national household weights in the SIH 03-04 and 05-06 file into … … household weights for small areas

22. 22 ●Map or 2

23. 23 Other work includes: ●Interactive maps of child (available now) and older adult (coming soon) wellbeing and synthetic estimates of poverty rates and housing stress: www.natsem.canberra.edu.au www.natsem.canberra.edu.au ●Measuring persistence of social exclusion among older Australians ●Work on particular aspects of disadvantage (children in households where no parent is in paid work; child housing disadvantage; income poverty among lone person households) ●Youth social exclusion risk

24. 24 References Abello, A., Gong, C., McNamara, J. and Daly, A. (2010) Spatial dimensions of child social exclusion risk: widening the scope (2010). Presented at the 11th Institute of Family Studies Conference, Melbourne, 7 – 9 July 2010. Gong, C., McNamara, J., Vidyattama, Y., Miranti, R., Tanton, R., Harding, A. and Kendig, H. (2009) Two worlds of ageing: spatial microsimulation estimates of small area advantage and disadvantage among older Australians. Paper presented at the ARCRNSISS Methods, Tools and Technologies Workshop, Newcastle, 10-11 December 2009 Harding, A., McNamara, J., Daly, A., and Tanton, R., (2009), 'Child social exclusion: an updated index from the 2006 Census', Australian Journal of Labour Economics, Volume 12 Number 1, 41-64 McNamara, J., Gong, C., Miranti, R., Vidyattama, Y., Tanton, R, Harding, A. and Kendig, H. (2009). ‘The geography of advantage and disadvantage for older Australians: insights from spatial microsimulation’. Paper presented at the British Society for Population Studies Annual Conference, University of Sussex, UK, September 9 - 11 2009.

25. www.natsem.canberra.edu.au