poor children in rich households
TRANSCRIPT
Keetie Roelen
IDS Members seminar
4 November 2015
Poor Children living in Rich Households: A Blurred Picture, Lagged Effects or Hidden Realities?
This study: aims and objectives
Investigate mismatch and overlap patterns
Repeated cross-sections
Longitudinal pattern
Explain mismatch patterns
Use mixed methods approach
Research in Ethiopia and Vietnam, complemented by research from Burundi
exploring mismatch patterns in child poverty outcomes
- Measurement error - Lagged effect - Opportunity costs - Household factors - Infrastructure and services - Awareness and attitudes - Aspirations
Outline seminar
Data and methods • Quantitative data
and measures • Qualitative data
and methods Explaining mismatch: • Measurement error • Lagged effects • Opportunity costs • Household factors • Infrastructure and services • Social protection • Coaching and support • Aspirations • Attitudes and behaviour
Policy implications: • Measurement • Targeting • Programme support • Whose responsibility?
Child poverty outcomes • Respondent perspectives • Cross-sectional findings • Longitudinal findings
Data and methods
quantitative data and measures
Multidimensional poverty measure Ethiopia Vietnam Indicators Domains Indicators not attending school (6-18) Education net enrolment (5-15) working on farm (6-18) primary completion rate (12-15) working on domestic chores (age 6-18)
Health visit to health facility (2-4)
Shelter living in house with electricity (0-15) living in proper house (0-15)
Water and Sanitation
living in dwelling with improved toilet (0-15) drinking from improved water source (0-15)
Child work child work (6-15) Social inclusion
having caregiver unable to work (0-15)
quantitative 1999 2004 2009 panel
Ethiopia (ERHS) 5054 3709 4937 1497
2004 2006 2008 panel
Vietnam (VHLSS) 12154 10696 9960 1068
monetary poverty measure
Ethiopia Vietnam
real per capita consumption real per capita expenditures
Data and methods
qualitative data and methods
qualitative adults children Total
Ethiopia 88 61 159
Vietnam 145 78 223
Data and methods
qualitative data and methods
adults children Total
91 40 131
Child poverty outcomes
respondent perspectives
Are household wealth and child wellbeing always the same?
“They are related and always the same, because rich households usually feed their children well, purchase clothes frequently, send their children to school and provide health care more than the poor families.” [14 year old boy, Harresaw, Ethiopia]
“No. If the family is rich but they do not live in peace and do not take care of their children, their health, study and entertainment, child wellbeing is not good.” [15 year old girl, Dong Thap, Vietnam]
“Parents in poor families care about and educate their children more encouraging them to aim at higher especially at school so that they have a better life. Parents in wealthy families do not have time to educate their children.” [Caregiver, Cibitoke, Burundi]
Child poverty outcomes
cross-sectional trends
Child poverty outcomes
longitudinal patterns
2006
N AB A B C Total
2004 AB 567 49.6 14.5 26.1 9.9 100
A 393 3.6 30.5 2.8 63.1 100
B 407 13.8 8.9 39.3 38.1 100
C 1126 0.1 5.9 3.5 90.6 100
2008
N AB A B C Total
2006 AB 352 53.4 10.8 26.7 9.1 100
A 304 13.8 41.5 2.6 42.1 100
B 358 18.4 7.0 35.5 39.1 100
C 1479 1.4 5.9 4.3 88.4 100
Transition matrices poverty groups Vietnam, 2004-08
Explaining mismatch
measurement error
Community criteria for household wealth and child wellbeing in Vietnam
Identification of households in Ethiopia
Explaining mismatch
lagged effects
2006
N AB A B C Total
2004 AB 567 49.6 14.5 26.1 9.9 100
A 393 3.6 30.5 2.8 63.1 100
B 407 13.8 8.9 39.3 38.1 100
C 1126 0.1 5.9 3.5 90.6 100
2008
N AB A B C Total
2006 AB 352 53.4 10.8 26.7 9.1 100
A 304 13.8 41.5 2.6 42.1 100
B 358 18.4 7.0 35.5 39.1 100
C 1479 1.4 5.9 4.3 88.4 100
Transition matrices poverty groups Vietnam, 2004-08
Explaining mismatch
opportunity costs
Livestock ownership and family work across consumption deciles for children aged 10-15 in rural Ethiopia
810
1214
16
aver
age
hour
s fa
mily
wor
k (p
er w
eek)
23
45
6
aver
age
lives
tock
ow
ners
hip
(TLU
)
0 2 4 6 8 10
real per capita consumption (deciles)
livestock (TLU) hours family work (per week)
>> Where is the tipping point?
“Parents from poor households give more responsibilities to their children from a young age, which help them to grow up with a better education compared to their peers from rich families.”
[Male caregiver, Cibitoke, Burundi]
Explaining mismatch
household factors
Ethiopia Vietnam
quantitative analysis
household size: AB↑, B↑, A↓ single hh head: AB↑, B↑, A↑
no education hh head: AB↑, A↑ no education hh head: AB↑
primary education+ hh head: A↑ unemployed hh head: AB↑, A↑
living in Mekong River Delta: AB↓,
B↓, A↑
qualitative analysis
female hh head: B↑ attitudes and awareness: B↑, A↑
attitudes and awareness: B↑, A↑
Explaining mismatch
coaching and support
Concern Worldwide ‘Terintambwe’ programme in Burundi
Explaining mismatch
aspirations and attitudes
Sara, 16 years old, living with her father, in grade 8
“I can say my wellbeing is good and bad. It is good because I am in school. My wellbeing is bad because I am working at home when I return from school.”
Her father says: “I don’t send my children to work for other households but I believe children should work at home in household production.”
“If I pass the national examination, I want to continue my education in the town of Atsbi. But my father wants me to join the Dera high school in order to support him. I want to be an engineer in order construct road to my community in particular and my country in general.”
Policy implications: measurement
Child poverty measurement requires a comprehensive use of monetary and multidimensional approaches.
Child poverty measurement requires its own measure
Longitudinal analysis is important for gaining insight into movements in and out of child poverty.
The use of both quantitative and qualitative data allows for more in-depth analysis of child poverty and its causes and solutions.
Policy implications: targeting
Targeting remains heavily focused on establishing approximations of monetary poor.
How to expand targeting practice to:
>> include all vulnerable children?
>> move from a household to individual perspective?
Policy implications: programme interventions
Livelihood strengthening and income generation can work for children but:
>> it is not enough, and
>> it may have adverse consequences.
Need for more critical reflection on role of children in asset accumulation strategies and income generating activities.
How to effectively incorporate behaviour change elements?
Policy implications: whose responsibility?
>> How to avoid that a focus on knowledge, awareness and individual behaviour does not become an unconstructive and unfair blame game?
Source: Kuenstler 2015
