Growing up in the panel Towards longitudinal measurement of child poverty

1

Katharine Hall

Children’s Institute, University of Cape Town

3rd Conference of the International Society of Child Indicators

York

July 2011

Growing up in the panelGrowing up in the panelTowards longitudinal measurement of child povertyTowards longitudinal measurement of child poverty

South Africa

Provinces: 9Population: 49 millionChild population: 19 million (38%)

High unemployment (2010 official: 25% | expanded: 36%)

High income povertyPoverty levels have declined only slightly since democracy, despite massive roll-out of social grants

High (and growing) income inequality (Gini: 0.7 in 2008)Pronounced and persistent racial inequality

Spatial poverty traps – previous Bantustans remain pockets of poverty: little infrastructure, few employment opportunities, and home to disproportionate numbers of children and pensioners.BUT also an increase in urban poverty – partly due to migration.

Child-centred poverty measuresChild-centred poverty measures

1. The child population is distributed differently to the adult population

Internal labour migration, uncertain job prospects, urban housing backlogs, the availability of extended family for child care, dual household arrangements and urban-rural oscillation – all contribute to unequal spatial distributions (i.e. combination of choice & constraint)

Households with children are larger than adult-only households:

Aggregated household-level and population figures mask the situation of children – who are, by many measures, ‘worse off’ than adults.

Adult only Mixed generation

Proportion of households

42% 58%

Mean household size

1.9 5.0

Total pop Adults Children

Income poverty (lower bound = PPP $121) 54% 46% 67%

Rural ‘tribal authority’ area 34% 29% 43%

Metropolitan area 35% 38% 29%

Adequate water (on site) 70% 74% 64%

Adequate sanitation (on site) 42% 45% 36%

Overcrowded dwelling 20% 16% 27%

Source: NIDS Wave 1, 2008



2. ‘Adult’ indicators, such as unemployment, have important consequences for child poverty. But reports seldom, if ever, use children as unit of analysis.

Unemployment is directly linked to poverty. Using the lower bound… 55% of children are “poor” when there is at least one

working adult; 90% of children are “poor” when there are no working

adults.

INDICATOR Unemployment rate

Adult (narrow): % of economically active population who are unemployed despite actively looking for work

25%

Adult (broad): % of economically active population unemployed, including ‘discouraged’ work seekers

36%

Children: Proportion of children who live in households where all members are unemployed

36%


3. Sometimes, ‘standard’ or official indicators are not child-appropriate

Eg. minimum norms and standards for “adequate water” = potable water within a 200m radius of the dwelling.

Similarly for sanitation (where minimum service level is ventilated pit latrine).

But qualitative research suggests that off-site communal services are inappropriate, even dangerous, for children.

INDICATOR – ADEQUATE WATER Proportion

Official (MDGs): Proportion of households with potable water within 200m of the dwelling (Office of the President: Development Indicators 2009)

92%

Child-centred: Proportion of children with potable water in the dwelling or on site(Children Count analysis of General Household Survey 2009)

64%


4. Child-specific indicators

Education

Mortality, health and nutrition

Social grants targeted to children

Household context and care – co-residence & care arrangements, orphaning

Child-centred indicators:

• Demography (incl. orphaning and care arrangements)

• Income, unemployment & social grants

• Housing and services

• Nutrition

• HIV & Health

• Education

40 indicators in 6 domains

Child-centred indicators:

• Demography (incl. orphaning and care arrangements)

• Income, unemployment & social grants

• Housing and services

• Nutrition

• HIV & Health

• Education

40 indicators in 6 domains

Interactive indicatorsInteractive indicators

Child-centred trends in income povertyChild-centred trends in income poverty

Limitations of cross-sectional dataLimitations of cross-sectional data

Repeated household surveys can be treated longitudinally to show a general trend, but do not allow us to ask…

Who is progressing out of poverty and who is not?

What are the factors that drive these dynamics

– why does poverty persist?

– what are the pathways out of poverty? (“bucking the trend”)

What is the long-term impact of social benefits and interventions?

A new national panel study: NIDSA new national panel study: NIDS

NATIONAL INCOME DYNAMICS STUDY

Inclusion of data on children – unusual for income-focused survey

Broad definition of the household (unlike official surveys)

Relationships of care, information about caregivers

Longitudinal v. cross-sectional – follows panel members

National focus v. discrete site

Rather than presenting a static picture, it is possible to link individuals across rounds so that children’s progress can be followed as they grow older and move into adulthood.

Possibilities for examining income mobility, geographic mobility, care arrangements and outcomes over space and time.

The NIDS child panelThe NIDS child panel

Full panel: 7,300 households (all members become part of the panel in Wave 1 – total of 28,000 individuals

11 500 children aged 0-17, evenly distributed (± 640 in each year)

- Nationally representative in Wave 1

Panel rounds at 2-year intervals

All household members are followed, even if they change household or move province

Children born to female sample members become part of the panel

Extent of attrition not yet known

Future of panel not yet sure (at least three rounds)

What to focus on? What to focus on?

The Multiple Deprivations Model. Centre for the Analysis of South African Social Policy www.casasp.ox.ac.uk

IncomeIncome

Income distribution – where to benchmark?Income distribution – where to benchmark?

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Proportion of children

Per capita income capped at R10 000SOURCE: General Household Survey 2009

Distribution of per capita income - quantiles

Child income inequalityChild income inequality

Child poverty & the effect of social grantsChild poverty & the effect of social grants

Data source: NIDS Wave 1(H & Ö = Hoogeven & Özler)

From: Hall & Wright (2010) A profile of children living in South Africa in 2008.

Co-residence and care arrangementsCo-residence and care arrangements

Only 34% of children live with both their parents

A quarter of children do not live with their biological mother.

The majority of these mothers live somewhere else.

NIDS records information about absent household members, and also (in the child questionnaire) specifically about absent (and deceased) parents). It also records information about household members who are de facto caregivers

Source: NIDS 2008

Co-residence & outcomes for childrenCo-residence & outcomes for children

MOTHER CO-RESIDENT

MOTHER LIVES ELSEWHERE

Prop 95%CI Prop 95%CI

parents married 40% (37.1–41.9) 14% (10.9–16.5)

child has birth certificate 94% (93.3–95.0) 91% (89.0–92.9)

rural 'tribal' area 40% (37.9–42.2) 57% (52.6–60.6)

traditional dwelling 17% (15.7– 9.0) 27% (23.9–30.9)

Income poor (lower bound) 61% (58.2–63.0) 71% (67.6–74.6)

Employment in the HH 65% (62.9–67.8) 50% (45.8–53.9)

HH income from grants (median & inter-quartile range)

R740 (R400 – R1270) R940 (R630 – R1470)

Data source: NIDS Wave 1

Location is key to dimensions of poverty, linked to child outcomes.

Apartheid spatial arrangements persist – many children in under-resourced areas.

Changing patterns in adult migration likely to affect children

• Increasing female migration + signs of permanent migration

• Children do not necessarily move together with adults.

Independent female migration linked to motherhood, and to the presence of maternal substitutes in ‘sending’ household

Urban in-migrant children worse off than urban-born children (BT20)

Policy implications – need to anticipate increased urban child population (through in-migration and urban births).

Spatial mobility among childrenSpatial mobility among children

Spatial mobility among childrenSpatial mobility among children

21% of children have moved since birth (3.7 million)

Proportion of mobile children increases with age

Source: NIDS Wave 1

Living environments & child outcomesLiving environments & child outcomes

Many children live in “traditional” dwellings - in turn associated with poor services.

Children are particularly vulnerable to the effects of poor services:

• 11% of child deaths (under 5) are attributed to diarrhoea;

• every year, children are burnt in shack fires.

Children are disproportionately represented in overcrowded dwellings, particularly informal urban settlements; they are vulnerable to the risks associated with overcrowding – including rapid spread of infectious disease, and abuse.

Difficult to measure these health outcomes directly

Child outcomes: what is feasible?Child outcomes: what is feasible?

HEALTH

Birth details: birth-weight, head circumference (unavailable for many)

Anthropometric data - can calculate: stunting (height for age – chronic malnutrition affects cognitive

development) underweight (weight for age, under 10 only) wasting (weight for height) / obesity (BMI)

EDUCATION

School access – pre-school participation; school attendance (days absent from school in a month), distance to school

School achievement / progress – grade repetition, age-for-grade;

Numeracy tests (not useful?)

Main thematic focus of analysisMain thematic focus of analysis

Child poverty is structural – racial, spatial; part of the political economy.

Access to services and resources, opportunities and even family structure is pre-determined.

income and expenditure dynamics

living environments

spatial mobility

household composition & care

NIDS is designed to provide good information in these areas.

www.childrencount.ci.org.za

[email protected]

This work was undertaken with the financial assistance of the PSPPD, a partnership programme between The Presidency,

Republic of South Africa, and the European Union (EU).

Growing up in the panel Towards longitudinal measurement of child poverty

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