Transcript The commodity chain of the household: From survey design to policy planning

The Concept of the Household: From
Survey Design to Policy Planning
Ernestina Coast, Tiziana Leone (LSE)
Sara Randall (UCL)
Funded by ESRC survey methods initiative
Do household definitions matter?
•
More variables being added in ‘household section’
•
Way of measuring wealth / poverty / access to facilities which
influence health
•
New level of analysis / explanation
•
More use (researchers & policy makers) made of publicly available
data
•
Recognition of importance of society’s basic unit as influence upon
members’ well-being
•
Increasing use of ‘indicators’ based on household data (e.g. MDGs,
asset indicators)
•
Increasing importance of poverty mapping which uses household
level data
The Issue
Why does the definition matter?
What are consequences of household definition?
– Data commissioners
– Data collectors
– Data analysts
– Data users
• Policy makers
• Planning / implementing targeted interventions
What are the implications for “household” members?
Data designers & collectors have:
clear ideas about why need something called ‘household’
clear aims
clear understanding of household definition
BUT what about analysts / users / consumers far
removed from collection?
MIGHT: look at definition and assume this is the unit of
production, consumption, socialisation central to the
development process
MIGHT: not even look at definition because they assume
they know what a household is
We are not…..
Redefining the definition of the
household
Methods
1. Document review (1950-present) Sub-Saharan Africa
1. Review census reports, enumerators manuals, questionnaires >1950
2. Review major household surveys since 1980
2. Key informant interviews (International)
1. 45 interviews in Tanzania, UK, USA
3. Ground truthing fieldwork (Tanzania case study)
1. Maasai area Northern Tanzania
2. Dar es Salaam 2 low income neighbourhoods
3. Rural areas: Planned for next year
4. Modelling differences, to include:
1. Female headed households
2. Household dependency ratios
3. Household size
Census Data Collection: issues in household definition
AIM: complete enumeration of population along with individual level characteristics
for planning purposes
Recurrent themes in definitions of African households
•Eating together
•Common housekeeping
•Living together
•Answerable to head
Census Data Collection: issues in household definition
AIM: complete enumeration of population along with individual level characteristics
for planning purposes
DIFFICULTIES EVOKED
•Servants – are they part of household or separate?
•Boarders / lodgers
•Absent household head
•Polygamy
•Complicated patterns of male female residence (Ghana)
•Children in boarding school
•Seasonal migration
Census Data Collection: issues in household definition
Summary:
• household definition is practical solution to
census aims of total enumeration
• recognition (usually) that is a reduced social
unit
• recognition that compromises are made
• set of rules for enumerators to follow
• continuity over time – comparability
Creation of what van de Walle (2006) calls ‘a statistical household’
Sample surveys: issues in household definition
(eg: WFS, DHS, WHS)
Household definition
practical:
to enable the identification of individuals for
individual questionnaires
“The household is a device used to
get at the individual. The
household is the sampling unit
while the individual is the
observational unit.”
‘main purpose of household
questionnaire was to identify
women who were eligible for the
individual interview’
World Health Survey 2002
Zambia DHS 1992, 1996
Sample surveys: issues in household definition
(eg: WFS, DHS)
• Much more standardised (still some local variations)
•WFS left more space for interpretation
• Little variation between core questionnaires and those
used by countries
• Little development over time
•Emphasis on comparability across time and space
Interviews with data producers, collectors,
users, analysts
• Clear distinction between the ‘Operational’ household of
the data collectors and the unit of analysis of the users
• Data collectors have very clear idea of household
definition
– Loss of information rather minimal
– Not a major issue for comparative purposes
– Contrasting preferences when it comes to decide the focus of the
definition (eg social, eating, economic)
• Users not aware of definition issues
– The main concern is to have a survey at all
– Need for updated information is the strongest drive
Emerging themes from interviews
• Single person households
• Urban affluent
• Household headship?
• Migrants and mobility
• Low-income rental neighbourhoods
• Occupations
• Mining
• Agribusiness
• Construction
Defining a household=‘headache’?
‘An example: A woman, whose husband lives and works in Kumasi, lives
with her son, his wife and two children in one house that has two
rooms. Both have their own farms, own income and make independent
decisions but share the same kitchen and most days it is the mother
who is cooking for the rest of the family, often using her own food
crops and the son contributes meat. These two are classified as
independent households and contributions to meals are recorded as
respective gifts. Difficult enough but now the woman's daughter has
moved in with her husband and two children for two months. No clue
where they managed to squeeze in but for now most food that the
mother and her son's family consume comes from the son-in-law's
farm with various contributions from the two households. As the
daughter's family is joining the meals, not all the farm production can
be recorded as gifts…..’
Bjorn Schulte-Herbruggen
In depth interviewing on the concept of
household
• Mix of cognitive interviewing and in depth
• Household grid sheet-flexible data collection
– Longido in prevalently Maasai area (9 ‘households’)
– Urban Dar es Saalam (23 ‘households’)
An example from 2007 fieldwork in Tanzania
Steven
Victoria
=
An example from 2007 fieldwork in Tanzania
Steven
Victoria
=
Anna
Mary
Joy
Ernest
Judy (13)
An example from 2007 fieldwork in Tanzania
Steven’s household
Maria (13)
Anna
Steven
Victoria
=
Mary
Joy
Ernest
Judy (13)
1 Male headed household
6 adults and 9 children
Dependency ratio =1.5
An example from 2007 fieldwork in Tanzania
Steven’s household
Maria (13)
Anna
Steven
Victoria
=
Mary
Joy
Ernest
Judy (13)
1 Male headed household
6 adults and 9 children
Dependency ratio =1.5
An example from 2007 fieldwork in Longido
Maria (13)
Maasai
Anna
Steven
Sleeping last night
(Census)
Victoria
=
Mary
Joy
Ernest
Judy (13)
3 households: 1 male & 2 female
headed
3 adults + 6 children (DR= 2)
1 woman+2 children (DR=2)
1 woman + 2 children (DR=2)
An example from 2007 fieldwork in Longido
Eating last night (DHS)
Maria (13)
Maasai
Anna
Steven
Victoria
=
Mary
Joy
Ernest
Judy (13)
1 household: male headed
5 adults + 10 children (DR= 2)
Modelling definition differences
• ‘Translated’ the household grid interviews into
SPSS dataset
• We allowed for extra columns to include variables
such as:
– Would this person make it into DHS
– Would this person make it into Census
• Created simple demographic indicators such as
– Dependency ratio
– % female headed household
– Household size
Scenarios: from low income Dar es Salaam
Whole
household
Slept there
last night
Ate there last
night
Mean
household size
Dependency
ratio
6.83
5.71
6.13
1.33
0.82
0.80
Sex ratio
0.74
0.73
0.59
Female HH
30%
32%
35%
Summary of fieldwork experience
• Dar urban: very high mobility between households of
children and young people
– Children:
• Instability / death of parents,
• get resources from somewhere else
• Often get resources from several different households where they may
live for short periods
– Young men: work mobility, sharing costs, poverty or sharing
responsibility among relatives while they find a job
• Share some costs but not others
• Kin solidarity when someone has no money
Summary of fieldwork experience
• Maasai have interdependent groups that are split up in
surveys but considered by themselves to be one economic
unit of production and consumption
The Tanzanian definition of
household
•Reduces the average household
size
•Increases the proportion of
female headed hhs
•Distorts the characteristics of
household heads
•Disassociates people from
resources to which they have
access
Discussion and few thoughts
• Data collectors clear about what a household is, users less
so
• Definition does matter for analysis and policy intervention
– Not just a matter of leaving ‘unusual’ groups out
• Household members relationships need to be spelt out.
• No need to change definitions but possibly more flexible
data collection?
– Need to think about data collection, back to the 70s?
• How can we add warnings about household data for
users?
‘The household is central to the development process. Not only is
the household a production unit but it is also a consumption, social
and demographic unit’ Kenya: Ministry of Planning and National
Development 2003, p59