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Poverty and disadvantage among Australian children: a spatial perspective
Presentation to the ACT Branch of the Economics Society, 27 June 2006
Ann HardingNATSEM, University of Canberra
2
Innovative features of this study ARC Grant – to create multidimensional
measures of disadvantage – “social exclusion” – for children at small area level• Awarded to Anne Daly, Ann Harding and Phil Lewis – this is joint
work with Justine McNamara, Mandy Yap and Rob Tanton of NATSEM (DP 560192).
Child-focused
High level of spatial disaggregation – for 1300 Statistical Local Areas across Australia
3
Why use a multidimensional measure of disadvantage?
Limitations of income-based poverty measures
Increasing acceptance that we need to move beyond income-only measures of disadvantage
Strong emphasis internationally on multidimensional measures of disadvantage
4
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”
(British Social Exclusion Unit 1997)
5
Why study disadvantage at a small area level?
Sense that the fruits of economic growth have not been equally shared among Australians living in different regions
Evidence base to support this belief is not well developed.
Need to know what regional differences are, how they develop, and how they can be overcome
6
Data source
Australian 2001 Census of Population and Housing (ABS)
Chosen because it has adequate information at a small area level
Limitations in terms of data detail and coverage of issues (delete SLAs with < 30 children; delete children with missing family values -> NT results not accurate
7
VariablesVariable in Census Social Exclusion Measure Developed
Family Type Proportion of children aged 0 – 15 in sole parent family with low income
Schooling Proportion of children aged 5 – 15 in Government school with low income
Education in family Proportion of children aged 0 – 15 with no-one in the family completed Year 12 and low income
Occupation in family Proportion of children aged 0 – 15 with highest occupation in family blue collar worker and low income
Housing tenure Proportion of children aged 0 – 15 in public housing and low income
Parents speak English at home
Proportion of children aged 0 – 15 in family where at least 1 parent speaks a language other than English at home and low income
Labour force status of parents
Proportion of children aged 0 – 15 in family where no parent working and low income
Personal computer usage
Proportion of children aged 0 – 15 in family where no-one used computer at home in last week and low income
Motor Vehicle Proportion of children aged 0 – 15 in household with no motor vehicle and low income
Yr 12, Govt school, blue collar, computer were most important 4 variables
8
Developing a composite index
Used principal components analysis (PCA) to summarise variables into a single measure of child social exclusion risk.• ABS use this technique to create the SEIFA indexes
PCA transforms a set of correlated data into a set of new variables or components.
The first new variable or component captures most of the variation in the original set of variables, and is used as the index.
9
Interpreting the Child Social Exclusion (CSE) Index
Low values = high disadvantage
All analysis conducted with child-weighted social exclusion deciles, to overcome problems with different SLA populations across states
Bottom social exclusion decile = 10 per cent of Australian children facing highest social exclusion risks
10
Where do Australian children at risk of social exclusion live – what the CSE index tells us
11
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What percentage of children in each state fall into the top and bottom CSE Index deciles?
‘Bottom CSE decile’ is the 10% of children across all of Australia facing highest risk of social exclusion: 5.3% of NSW children fall into bottom CSE decile
0.0
5.3
0.0
5.7
17.6
25.1
2.1
36.3
5.4
24.3
6.46.4
6.8
5.7
11.0
13.3
0
10
20
30
40
NSW VIC QLD SA WA TAS NT ACT
% o
f all
child
ren
in s
tate
/terr
itory
Bottom CSE decile Top CSE decile
13
Distribution across states & territories of children in the bottom (most excluded) CSE decile
5.1
48.8
13.19.2
0.5
17.7
0.05.7
0
10
20
30
40
50
60
NSW VIC QLD SA WA TAS NT ACT
0
10
20
30
40
50
60
% o
f all
0-15
yea
r ol
d ch
ildre
n (li
ne)
% o
f chi
ldre
n in
bot
tom
CS
E d
ecile
Of all those children in the bottom national CSE decile, 17.7% come from NSW (which contains 34% of all children)
14
Capital city and balance of Australia: distribution within CSE deciles
37
63
79
98
63
2
49
46
48
53
54
93
51
54
52 4
746
37
21
70
20
40
60
80
100
Mostexcluded
10%
Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Leastexcluded
10%Child Social Exclusion (CSE) decile
% o
f ch
ildre
n
Capital City Balance of state
Of all those children in the bottom national CSE decile, 49% live in capital cites and 51% live outside capital cities
15
Capital city and balance of Australia: distribution over all CSE deciles
16
15
788
13
10
99
65
14
2
14
14
1
10
12
12
17
0
2
4
6
8
10
12
14
16
18
Mostexcluded
10%
Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Leastexcluded
10%Child Social Exclusion (CSE) decile
% o
f ch
ildre
n
Capital City Balance of state
14% of all children who live outside capital cites fall into the bottom (most excluded) CSE decile, while only 1% make it into the ‘least excluded’ decile
16
Components of social exclusion
17
Social exclusion characteristics by capital city/balance of Australia Capital cities
Balance of Australia
% point difference
Child and family characteristics
Mean proportion of
children
Mean proportion of
childrenCouple family 80.8 81.4 0.6One parent family 19.1 18.4 -0.7Pre-school (aged 0-4) 15.0 14.7 -0.3Government school (aged 5-15) 58.2 70.8 12.6Catholic school (aged 5-15) 19.8 14.1 -5.7Other non-government school (aged 5-15) 12.8 6.8 -6.0Post-school qualifications 62.1 49.0 -13.1Year 12 16.1 15.1 -1.0Not Year 12 18.1 31.5 13.4White collar 40.5 25.1 -15.4Grey collar 28.1 33.0 4.9Blue collar 12.9 20.3 7.4Own home 68.2 63.5 -4.7Rent -public 7.7 7.7 0.0Rent - private 19.8 18.3 -1.5Other than English 21.5 6.9 -14.6English 78.5 93.2 14.7Couple - 1 parent employed 28.8 29.6 0.8Couple - 2 parents employed 44.5 42.6 -1.9Couple - both parents not working 7.0 8.8 1.8Single parent - employed 9.0 7.3 -1.7Single parent - not working 9.7 10.7 1.0Computer used at home 72.2 61.0 -11.2Computer not used at home 24.6 35.5 10.9At least one motor vehicle 93.0 92.4 -0.6No motor vehicle 4.4 5.1 0.7
18
Proportion of children with selected characteristics by CSE decile
38.6
7.0
23.8
5.4
43.9
13.4
73.1
49.4
0
20
40
60
80
Mostexcluded
10%
Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Leastexcluded
10%Child Social Exclusion (CSE) Decile
% o
f chi
ldre
n w
ith c
hara
cter
istic
.No-one completed Year 12 Highest occupation blue collar
No computer use at home In government schools
19
Comparison between 20 SLAs most and least at risk of child social exclusion
Bottom 20 SLAs Top 20 SLAs % point difference
Child and family characteristicsMean proportion of
childrenMean proportion
of childrenCouple family 72.0 89.5 17.5One parent family 27.9 10.4 -17.5Pre-school (aged 0-4) 11.0 21.0 10.0Government school (aged 5-15) 72.5 42.4 -30.1Catholic school (aged 5-15) 8.1 17.9 9.8Other non-government school (aged 5-15) 4.0 33.3 29.3Post-school qualifications 26.9 83.7 56.8Year 12 17.5 11.4 -6.1Not Year 12 48.7 3.1 -45.6White collar 11.9 63.0 51.1Grey collar 23.4 24.7 1.3Blue collar 28.1 2.0 -26.1Own home 39.6 78.3 38.7Rent -public 33.1 3.5 -29.6Rent - private 19.7 15.2 -4.5Other than English 17.8 17.0 -0.8English 82.2 83.0 0.8Couple - 1 parent employed 31.5 31.1 -0.4Couple - 2 parents employed 24.9 53.8 28.9Couple - both parents not working 14.4 4.4 -10.0Single parent - employed 7.8 6.7 -1.1Single parent - not working 19.3 3.5 -15.8Computer used at home 37.9 89.2 51.3Computer not used at home 56.5 8.5 -48.0At least one motor vehicle 78.8 96.5 17.7No motor vehicle 17.3 1.9 -15.4
20
Comparing child income poverty and child social exclusion
Data limitations
Measure of poverty fairly rough – based on gross equivalised income ranges from Census
Created child-weighted child income poverty deciles (bottom decile=10% of children living in SLAs with the highest risk of poverty)
21
Transition matrix – CSE deciles and Child Income Poverty deciles
TotalWeighted CSE index decile 1 2 3 4 5 6 7 8 9 10
1 5.0 2.2 2.1 0.3 0.1 0.3 0.0 0.0 0.0 0.0 10.02 2.6 2.2 2.2 1.8 0.7 0.6 0.1 0.0 0.0 0.0 10.33 0.8 3.2 1.6 3.0 0.6 0.4 0.1 0.0 0.0 0.0 9.74 0.5 1.1 1.2 1.1 3.3 2.3 0.4 0.0 0.0 0.0 10.05 0.4 0.4 1.4 2.3 2.2 0.8 2.5 0.1 0.0 0.0 10.06 0.6 0.7 1.2 1.0 1.8 1.3 2.8 0.7 0.0 0.0 10.07 0.1 0.0 0.1 0.3 1.0 3.1 1.5 2.9 0.9 0.0 10.08 0.1 0.0 0.2 0.0 0.5 0.9 2.4 3.5 2.3 0.2 10.09 0.0 0.0 0.1 0.2 0.0 0.1 0.2 2.3 5.2 1.9 10.1
10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 1.3 7.9 9.9Total % 10.1 10.0 10.0 10.0 10.2 9.8 10.1 10.2 9.8 10.0 100
Weighted CIP decile
Note: Decile 1 = highest risk of social exclusion and highest poverty rate
22
Conclusions Large variations in child social exclusion
risk by state Substantial variations in exclusion risk
within cities, and between capital cities and balance of Australia
Also major differences in specific index components• bottom decile children 4 times as likely to live in a blue collar
family and 5 times as likely to live in a family where no-one has completed Year 12
23
Conclusions considerable divergence between the CSE
index and child income poverty when examining disadvantage
half of all the most disadvantaged decile of children as measured by the CSE index fall above the bottom decile of child income poverty.
Future work:• Statistical significance of spatial clustering• Comparison between CSE Index and ABS
SEIFA indexes• Examination of trends over time