|Intra-household Resource Allocation: Issues and Methods for Development Policy and Planning (UNU, 1990, 204 pages)|
The study of internal household dynamics poses difficulties of definition, access, and measurement. Defining the household for study or for programme/project planning is already a difficult task. Households are private institutions, and their interactions and relationships may be considered too personal to discuss. Moreover, there is still much to be learned about what needs to be measured and how to measure it. Most of the empirical research on these issues has been carried out in the context of long-term research projects and doctoral dissertations where the cost of time-consuming data collection methods was not a deterrent to their use. Approaches are needed which can provide at least some guidance to project planners within a practical time horizon. One such approach is presented in the Appendix to this volume.
As a start, certain information may be obtained from the analysis of secondary data such as census information, household income and expenditure surveys (if they contain demographic information), and consumption and nutrition surveys. Valuable information can also be located in the ethnographic literature available on the area. There are few instances of planning for development in a location where no prior research has been done.
This is not to suggest that data collection as part of the planning process is superfluous, but any project should be evaluated in terms of its potential rate of return for the effort and resources expended. As this paper has demonstrated, knowledge of intra-household dynamics is vital to an accurate assessment of project outputs. It is therefore crucial to identify the most efficient ways of obtaining such knowledge. The issues which need to be addressed in this context are the following:
Defining the Unit of Analysis
The difficulty of defining precisely what a household is has already been discussed. Aside from this theoretical question, the practical problem exists that household composition and structure are highly variable over time. One study of household economy found that, over a one-and-a-half-year period, 20 per cent of the sample Embu households in Kenya were disrupted in some way (Haugerud, 1981). In a study of food consumption in Zambia, household structure was charted anew in each monthly round of data collection because variations in composition were so great (Kumar, 1982). Households adapt by changing their structure (Nieves,1979; Jelín, n.d.), so that information on the flexibility of household units over time is an important indicator of their ability to cope with economic stress and change (cf. Jelín, this volume).
In addition, individuals may belong to several different households at one time (Loufti, 1980), as when they receive support from both their natal and affinal families. While people cannot be studied outside the context in which they live, an effective way of getting around this problem is to take the individual as the point of departure, and to analyse the household or other support network to which he or she belongs as a characteristic (Watts and Skidmore, 1976). Heywood discusses a practical application of this approach in part III of this volume.
Income and Expenditure
Most income and expenditure surveys measure all income (cash and kind) flowing into the household and the household's total expenditure or consumption in a given reference period. It is still unusual to find a survey which distinguishes income by separate earner (exceptions are Kumar, 1978; Guyer, 1980; Jones, 1983b; Kennedy and Cogill, 1987; Rogers and Swindale, 1988) or expenditure by individual. Yet it is well recognized that, to obtain accurate income data, each earner must be questioned and each source of income separately identified: household members often lie to each other about the amount of their income or simply keep it secret. While useful for some purposes, aggregate household income does not provide the information needed to study intra-household processes. In many cases, this data is obtained in household interviews, and simply needs to be preserved in disaggregated form so that it can be used in later analyses.
Obtaining details about individual income flows requires making the trade-off of a smaller sample size. For planning purposes this does not pose a problem: the statistical accuracy preserved in quantity measures of large-scale surveys is likely to be less important than capturing the nature and approximate relative size of resource flows in and out of households and among their members.
Data from large-scale surveys may in some cases be used to infer patterns of intra household resource allocation. An example of one such innovative analysis is the Rosenzweig and Schultz (1981) study which used census data on male-to-female ratios and additional information of female employment opportunities by region to infer something about the determinants of investment in child health and survival. Many countries use household-level income and expenditure surveys to establish the basis for a consumer price index. These might also be used to compare the spending patterns of households of varying composition, and then to make some educated guesses about the consumption patterns of given categories of individuals. This type of analysis must be viewed in most cases as indicative rather than conclusive, because it is often impossible to distinguish between equally plausible explanations of an outcome. For example, Hanger and Moris (1973) attribute reduced expenditure on food in the Mwea-Tebere rice project, with no reduction in income, to the shift in income earner. An alternative explanation might be the shift from a steady flow of small amounts of income to an annual, lump-sum payment. The observation that spending patterns and task allocation are different in households where women work may be explained by women's greater power and influence in such households, or simply by the difference in the implicit cost of women's time once they have entered the labour force. This confusion confirms the real need for undertaking studies which are explicitly designed to investigate intra-household questions.
Time Use and Task Allocation
The literature amply illustrates the danger of relying on recall and self-report to obtain information on time use. Studies which have compared recall with direct observation have found substantial differences between the two methods. One study in Upper Volta found that 44 per cent of women's work activities measured by direct observation were missed in a recall questionnaire (McSweeney, 1979). This is even greater than the 30 per cent difference measured between a 24-hour and a one-month time-use recall questionnaire in Java (Sajagyo et al., 1979). In the Philippines, King-Quizon (1978) found that children's market work time was three times as great when measured by direct observation than by recall. Relying on recall data to measure time use raises several problems. First of all, people simply may not know how much time they spend at a given task. Even in cultures that are not ruled by the clock as ours is, it is possible to construct appropriate chronometric references, as Zeitlin explains in part 111 of this volume. Furthermore, people may not define their tasks in the same way as the researcher; some activities done by one group may simply not be recognized as work by another. For instance, the women lacemakers in Narsapur, India, spend six to eight hours a day at the task, yet their husbands report this as leisure time, because it is not perceived as work (Mies, 1982).
Johnson's paper in this volume reviews the various methods for measuring time allocation. Time use can be directly observed by following a small sample of individuals continuously during a day or a sample of days; by observing a random sample of individuals during randomly selected 15-minute periods (Johnson, 1975); or by participant observation over some period of time (24 hours minimum). The method of spot-checking at random moments has the advantage of minimally disrupting normal activities and of providing a systematic body of observations. Pre-defined categories are not used, and multiple activities can be recorded. However, these random moments do not provide a sense of the organization and sequencing of activities, which may be important factors in how time is used and constrained. Therefore, this method should be combined with the observation of whole tasks (see Appendix, table A) or a time-use record that accommodates simultaneous and frequently interrupted tasks and maintains their temporal relationships (cf. Schlossman, 1986).
Access to Resources
The special case of intra-family food distribution has received considerable attention (Horowitz, 1980; Carloni, 1981; Nutrition Economics Group, 1982). The importance of individual-level measures has long been recognized, and various data-collection methods have been tested. The food question is complex because, unlike education and other resources, food consumption has meaning only in relation to nutrient need. Chaudhury (1983) suggests that one explanation for the commonly held notion that women receive less than their fair share of household food is that careful controls for activity level and body weight have not been used in data analysis. Making such adjustments, his study in one village in Bangladesh found no evidence of sex discrimination in food distribution in most age-groups. The question of whether the recommended nutrient intake used to determine dietary adequacy levels (WHO/FAD, 1985) may be set too high adds another dimension of uncertainty.
It is easier to measure outcomes (e.g. weight gain or loss, or nutritional status) than food consumption directly, but such measures do not distinguish patterns of food allocation from differences in energy expenditure, or in morbidity which affects growth. For purposes of simply indicating patterns of distribution, short-cut methods may be adequate. Check-lists and food frequencies have been used to indicate overall dietary quality, but once again methods designed specifically to measure intra - household distribution of food have not been widely used. Pinstrup-Andersen and Garcia, in part III of this volume, show clearly that such methods are indispensible, as household-level measures are inaccurate indicators of individual food intakes.
Power and Decision-making within the Household
The measurement of decision-making power within the household poses serious conceptual problems. First, genuine differences of opinion are likely to exist among household members as to who makes what decisions (Safilios-Rothschild, 1969). Second, people may not admit the true allocation of influence. Alamgir (1977) suggests that the female contribution to household decision-making is greater than either party will publicly acknowledge. A third consideration is that decisions take place in a context which limits alternatives. Studies from many countries indicate that women and men make decisions which pertain to their own spheres of activity (Laird, 1979 [Paraguay]; Cloud, 1978 [Sahel]; Alamgir, 1977 [Bangladesh]), but presumably in the female sphere some of these decisions are fairly limited in scope: not what type of crop to plant, but how much to plant. Roldan (1988) makes the important point that management of household finances need not imply control over them. In an environment of severe resource constraint, she points out that there are no decisions to be made; expenditure patterns are dictated by survival needs.
The best way to observe the allocation of decision-making may be to look at the results, that is, to look at investment and consumption decisions among households of a given type: female- versus male-headed, households where women do or do not work outside the home for pay. The only other approach is to use psychological methods or measurements which are not well suited to project planning.
Participant Observation Methods
Several researchers have argued that it is essential to have a fundamental understanding of a culture, such as can only be obtained by living in it, before more specific research questions can be addressed or interventions developed (e.g. Haugerud, 1979). Certainly, project experience has demonstrated the danger of treating, as it were, one symptom rather than the whole patient. One can view household dynamics as the fundamental and complex expression of a culture, requiring an integrated study of its various dimensions.
Epstein (1975) has suggested that the aid agencies make greater use of the relatively cheap resource of anthrolopogical studies, and argues that ordinarily there is sufficient lead time for such studies to be carried out in an area which has been targeted for aid
before specific projects are planned. An effort should at least be made to seek out those who have already worked in the target area and to review the work which has been done in the light of the specific questions which pertain to household dynamics. In this way, specific knowledge gaps can be identified, and resources can be most efficiently concentrated on obtaining the missing pieces of information. An awareness of the need for this information is probably the most important first step. The Appendix contains an approach to obtaining the information on intra-household dynamics needed for effective development planning.
DIRECTIONS FOR FUTURE RESEARCH
The study of household dynamics in relation to development policy is a relatively new field. There are still a number of important empirical questions to be answered. Among these, perhaps most relevant to economic development, are questions of the effect of changing income-earning opportunities on the behaviour and well-being of household members. This relates to the ways in which the form, period, and reliability of income, as well as who earns it, influence how it is spent, and how these alter household decisions about consumption , investment, and fertility. Another important question underlying sound development policy is the balance between market work, home production, and the care of children. A third area of exploration is how to influence patterns of control over productive resources, especially as technological or marketing interventions alter their productivity and value.
As vital as these empirical questions are, it is perhaps even more important to identify timely and low-cost ways of obtaining information on development programmes. Such information has seldom been sought outside an academic or research context, and, as a result, the development of innovative and efficient data-collection methods has not been a priority. Now that the relevance of these questions is being recognized by the aid community, the development of systematic, practical approaches to their resolution should be placed high on the policy agenda. This volume is offered as a contribution to this process.
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