The Dangers of Disciplinary Culture: Unpacking Demography’s Use of the ‘Household

1. The Dangers of Disciplinary Culture: Unpacking Demography’s Use of the ‘Household Sara Randall (UCL) Ernestina Coast, Tiziana Leone (LSE)

2. LSE Anthropology of Africa seminar • 14th October 2008

3. AIMS of research project Study the different definitions and understandings of the same term ‘household’ for: • Data producers: demographers / statisticians • Data users / consumers: national governments, NGOs, international organisations • The subjects of research: populations / individuals • Other people along the chain of data production and consumption: enumerators, supervisors, academics To establish: • Whether all these different interest groups have the same understanding of ‘household’ • the implications of misunderstandings for policy and interventions and activities such as poverty mapping

4. ‘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

5. Why are ‘households’ important? • Critiques by anthropologists / sociologists • Practical tool in data collection • Essential for surveys • Household sample surveys are now ‘indispensable’ for development planning (UN 2005) • DHS (Demographic and Health Surveys) • Since 1986, some countries 4 /5 surveys: 81 countries, 40 in Africa • Standardised questionnaires and definitions • specific modules (eg HIV / FGM / Violence against women) • Data in public domain • comparative studies: multi-level modelling • Other Household Survey series:

6. Methods • Review of household definitions used in : • African (anglophone) censuses and surveys done since 1960s. • A selection of European surveys since 1980. • In-depth semi-structured interviews with: International level - individuals involved in the development and coordination of major data collecting exercises such as DHS  Tanzania - people working for international organisations (WFP, UNFPA) embassies, NGOs all who use data to develop their policies and programmes - University academics who are involved in survey development and training and in analysis of demographic and other survey data - Employees of National Bureau of Statistics (NBS) • In depth field interviews with household members • Maasai (north Tanzania) • Low income districts in Dar es Salaam 4. Modelling the implications of differences between different household definitions

7. Different cultural understandings of ‘household’ • The professional culture of the demographers, statisticians and survey designers • The Tanzanian nation • Different Tanzanian sub-populations • Maasai • Low income urban communities • International / national data users

8. Demographic disciplinary culture: Definition of the household (Africa) • Eating together • Co-management of daily economic expenditure and consumption • Co-residence • (those who recognise the same household head) Statistical household (van de Walle 2006)

9. Demographic disciplinary culture: Historical role of census • Often censuses predate surveys • Methods and definitions developed for census • Count everyone ONCE and once only • Mainly looking at numbers of people + characteristics • Households / dwelling units / sleeping places = practical tools for identifying individuals • Early censuses (1960s/1970s) very country specific: local conditions / residence arrangements / terminologies

10. Demographic disciplinary culture: “For the unit of enquiry, the household was proposed but owing to difficulties of definition which enumerators were expected to encounter, it was decided to record in the Census individuals by house or compound and to use the 'household' concept only in the Post Enumeration Survey It was realised that the house or compound may not necessarily correspond to particular economic or social concepts but it was regarded as a suitable 'physical enclosure' for ensuring complete enumeration. (Ghana 1960: Census)

11. Demographic disciplinary culture: Historical role of census • censuses predated surveys • Methods and definitions developed for census • Count everyone ONCE and once only • Mainly looking at numbers of people + characteristics • Households / dwelling units / sleeping places = practical tools for identifying individuals • Early censuses (1960s/1970s) very country specific: local conditions / residence arrangements / terminologies Surveys build on census • Definitions the same • Census = sampling frame for surveys

12. Demographic disciplinary culture: Important values • sampling • The household is the basis for identifying a sampling frame for individuals eg. Reproductive age women / children / married men etc “ The main purpose of the Household Questionnaire was to identify men and women who were eligible for individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit” Tanzania DHS, 2004, p6

13. Demographic disciplinary culture: R1. R1 and it’s not letting them self define usual residence, for example, students who live in dormitories 9 months during the year when you ask “Where is your usual residence?” they may say their parents’ house but from our definition they are not, I mean they are usual residents in the hostel where they stay most of the year so it’s not a self-defining thing ….. R2 if they ask ‘I live 9 months there’ or ‘I live in the Middle East come home for a month every year’, hum, that is not the usual residence according to our definition and we do not allow someone that is not a usual resident to be the head of the household. The head of the household has to be a usual resident in that household. So if the man is off in the Middle East… working you know, the woman, .. the wife, may say he is the head of the household but according to our definition it’s not possible because he is not a usual resident. Demographers from MACRO: US (DHS)

14. Demographic disciplinary culture: Important values • Comparability over time and place It’s true. We are obsessed with comparability….I think that if we have a concept which doesn’t really correspond with reality, we need to improve the definition. But it’s not that easy. You need a research mentality…but with official organisations like National Statistics Offices it’s very difficult to get such ideas accepted. (University demographer, West Africa

15. Demographic disciplinary culture: Important values • Avoiding double counting • Each person should be a member of one household and one only • Difficult to fulfil in resource poor urban areas • many rural-urban migrants • huge amount of intra-urban mobility especially of young adults and their children • Poor representation of reality

16. Demographic disciplinary culture: Important values • Participation in the international community

17. Demographic disciplinary culture: Important values • Participation in the international community 1960s/1970s: idiosyncratic definitions according to local traditions and conditions 1980s/1990s: standardisation: with reference to United Nations "The 1991 Population Census adopted the UN definition of household, that is, in terms of co-residence (common living arrangement for multi-person households), common cooking arrangement (sharing from one cooking pot), and the recognition of one person as the head of household." (Nigeria, 1998, p72))

18. Demographic disciplinary culture: Recognise limits of definitions but have tight definitions for precise purposes (practical and statistical) Implications of term ‘household’ are reasonably well-understood within profession • BUT many analysts are NOT aware that this is not necessarily “ production unit but also a consumption, social and demographic unit” Evolutionary dimension • Builds on what has gone before Different needs of data not always taken into account • Priorities: demographers / statisticians • Ease of analysis • NOT good representation of reality

19. Specific household issues in Tanzania • Socialist unification: 1960 & 1970s • Swahili = national language • Discouragement of tribal affiliations • Survey tools JUST in Swahili & English • Ad hoc interpreters for those who don’t speak swahili • Selection of ‘kaya’ as term for household in surveys

20. Specific household issues in Tanzania So when we , at NBS (in mid 1970s) when we sent and we discussed this in meeting and we said well, we now have to look for a word in Kiswahili – there were suggestions more than one – as usual – we said well we have the National Kiswahili Council and we have the Dept of Kiswahili at UDSM. We shall send them the definition of the household as we know it from the UN now. We shall ask them to suggest what is it the Kiswahili equivalent that would fit that UN definition, that long thing, and we shall suggest that meetings have suggested that it should probably be this or that but maybe there may be some others, and they also came up with the kaya. Kaya is the arrangement that best suits that definition of the household from the UN (Senior retired Statistician/Demographer) [1

22. NATIONAL LEVEL

23. NAIROBIPROVINCE

24. Household Definitions in Tanzania DHS: ‘for the purpose of the 2004-5 TDHS a household is defined as a person or group of persons, related or unrelated who live together and share a common source of food (Report p9) 2002 census -“For the purpose of the 2002 population and housing census a "private household" was a group of persons who lived together and shared living expenses. Usually these were husband, wife, and children. Other relatives, boarders, visitors and servants were included as members of the household, if they were present in the household on census night. If one person lived and ate by himself/herself, then he/she was a one-person household even if he/she stayed in the same house with other people (these cases were more prevalent in the urban areas). Household members staying in more than one house were enumerated as one household if they ate together."

25. = =

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27. Maasai • Pastoral and recently agriculture • Not nomadic but very mobile • Polygamous • Each wife has her own house and hearth • Warrior age set - Moran • Eating arrangements • Sleeping arrangements

28. Declared household: 37 people of whom 34 resident in the village, 29 slept there last night + 3 young migrants in Kenya Census households: 6 or 7, DHS households probably 5

29. Head Legend House 1 House 2 Nemanga (town) cattle camp boarding school Maasai: household 2 Structure and Composition of household His declaration: 1 man + 4 women + 20 children = 25 In the village: 1 man + 2 women + 6 children = 9 Cattle camp: 1 woman + 8 children = 9 In town: 1 woman + 4 children = 5 DHS Households : 4 of which 3 female headed HH 1: male head 4 people DR=3 HH 2: female head 5 people DR=0.6 HH 3: female head 5 people DR= 0.25 HH 4: female head 9 people DR= 0.11

30. Maasai households 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

31. Tanzania: low income neighbourhoods Dar es Salaam • Problematic individuals • genuine forgetting (young children especially in complex households) • omission of female relatives working as maids • real ambiguity about who should be included – migrants / mobile children / mobile young adults

32. Tanzania: low income neighbourhoods Dar es Salaam In Dar: 1 room (Simon pays rent) 1 bed 2 economic entreprises Household Survey: 1 household, 2 persons Real Life Each person is member of household in Dodoma to which send most of resources Simon (20) Supports Elias in Dar. Pays rent and for much of food Elias (20) All money is sent home to parents in Dodoma

33. Tanzania: low income neighbourhoods Dar es Salaam In Dar: 1 room (share rent) 2 beds No cooking materials: eat out in cafes each paying his own way 2 economic entreprises Household Survey: 1 household, 2 persons with Edward as head because he signed lease Real Life Each sees himself as member of parental household in Dodoma from where come most resources Edward (22) Signed lease Accountancy student supported by parents Siegfried (23) Accountancy student with government grant

34. Maasai: Large social units represented as much smaller Excess numbers of female headed households Household head characteristics distorted People separated from resources Low income Dar es Salaam: Little evidence for survey fragmentation of households Female headed households (25%) all genuine BUT: multiple membership of households Ambiguity about where belong Resources obtained from other households Tanzania: biases generated by household definitions

35. International USERS of household survey data • Most unaware of ‘statistical household’ • Assume ‘households’ in surveys are basic “production/ consumption / residential units of society” • Take the analysis in reports at face value • Use poverty maps to guide interventions

36. Does this matter? Yes: • Must recognise the diversity of cultural influences on this key analystical concept • Awareness of linguistic issues: the misunderstandings that can occur between different populations who use the same term WITHOUT BEING AWARE that others may be using the same term with very different connotations • The term household is used without question or clarification in much development literature, poverty analysis and mapping

37. Does this matter? Perhaps ‘no’ at the national level in Tanzania • If the errors cancel each other out statistically • If, in reality only a small proportion of people are misrepresented. • If there are no repercussions of the misrepresentations for policy and interventions Next stage of the research: • Increase the number and diversity of communities for ‘ground truthing’ • Modelling the quantitative impact of the definitions on some key outcome variables

38. What should be the response to this research? • Should we redefine the household? No: a perfect definition doesn’t exist. • Reflect on how to improve the collection of data on households and household membership that better reflect reality Eg: possibility of being a member of several households (see Timaeus & Hosegood, South Africa) Change how relationship data are collected and coded within households Collect data on absent members (Pilon, Burkina Faso) • Find ways of alerting data users to the traps in using data on ‘households’. Especially if interventions are planned at a local level

39. Acknowledgements • Co-authors: Ernestine Coast, Tiziana Leone LSE • ESRC: • Beth Bishop: literature and definitions review • Interviewers and researchers in Tanzania: Ernest Ndakaru, Deograsias Mushi, George Mkude, Eugenia Mpayo, Anthony Kija, Musa Magafuli • Everyone who has talked to us about their use of surveys and data • The Maasai and the Dar es Salaam residents who explained their lives to us