Gender Sensitivity of Well-Being Indicators

Development is based not only on economic growth, but also on the achievement of social goals, including gender equity. Indicators capable of reliably identifying gender differences in well-being are thus essential. In this paper the gender sensitivity of indicators of health, nutrition and education, and of some composite indices, is critically examined with reference to developing countries. The relationship between poverty and gender differences in these conventional indicators is also explored. The important issue of social processes which result in gender differences is, however, beyond the scope of the discussion.

The paper assesses indicators within the analytical framework of “functionings”. In this framework, it is not the possession of a commodity or the utility it provides that proxies for well-being, but rather what a person actually succeeds in doing with the commodity and its characteristics. Findings are outlined below.

Indicators of health: Indicators of differential mortality and differential morbidity are assessed. Indicators of mortality (for example, life expectancy and age-specific mortality rates) are easily measurable and economically affordable relative to other social indicators. The reliability of some (such as life expectancy), which can mask gender differentials in specific age groups is, however, questionable. Among the age-specific indicators, juvenile sex ratios (particularly disaggregated into the female male ratio 0–4 and 5–9) appear to be gender sensitive and of greatest relevance. This has been assessed for India and is worthy of investigation in other developing countries. With respect to morbidity, reliable indicators are difficult to construct due to the inherent unreliability of the data.

Indicators of nutrition: Indicators are assessed in two groups: indicators of intake and indicators of outcome. Measurements of food intake and outcome both, however, suffer from a number of methodological and interpretation problems that make it difficult to construct reliable indicators.

Indicators of education: Indicators are assessed in two main groups: indicators of access (which include stock variables, such as adult literacy and mean years of schooling per person aged 25 and over, and flow variables such as enrolment and drop-out ratios); and indicators of content and purposes. Indicators of access appear to be important in identifying gender gaps in primary, secondary and tertiary education. In developing countries with a larger proportion of younger age groups, flow variables provide more reliable and up-to-date information than stock variables. While research at the global level suggests that enrolment ratios are reliable indicators of gender differences, micro-level research is required to compare the reliability of enrolment ratios with drop-out and repetition ratios. Indicators of content and purposes, like the gender segregation index, may be useful to assess gender differences in the field of education.

Composite assessment: Assessing indicators of particular single functionings (as above) may give the false impression of equality (if inequality is present in unassessed functionings). (In sub-Saharan Africa, for example, some countries may show a balanced female male ratio but have large gender gaps in enrolment rates.) Although a multidimensional approach to evaluation has many merits, the current trend to compress multiple elements of a functioning vector into composite indices raises other issues. Value judgements have to be made about the components to be included (based on the intended use of the index) and excluded, and the weights to be allotted. However, composite indicators constructed with specific purposes in mind can be useful and have proved helpful for preliminary comparisons in global analyses. Currently available composite indices (for example, the Gender-related Development Index — GDI — and the Physical Quality of Life Index) may need to be adapted if they are to be used for comparing gender gaps among or within developing countries. Indicators used would have to take into account the young nature of the population. With respect to the GDI, for example, the use of age-specific disaggregated female male ratios (for the under-10 age group) rather than life expectancy, and an increase in the weight attached to average enrolment component of the education indicator relative to the adult literacy component, may be more appropriate. Furthermore, the income component of the GDI, if standardized for skills and supplemented by a “drudgery” indicator, could provide gender-sensitive information superior to that provided by the functionings components.

The relation between household poverty and gender discrimination: The limited evidence suggests that gender differentials in indicators of functionings do not necessarily conflate with differences in opulence indicators. Except for the gender gap in education, it is not evident that gender inequality is universally higher among lower income groups. The paper briefly reviews opulence indicators — largely in the form of income poverty — but it is very likely that property ownership would reveal the same lack of deterministic relationship.

The findings of the paper point to the importance of, first, the collection of gender-sensitive indicator data in national censuses (especially for the indicators identified as useful, as well as “time allocation”) and second, the gender disaggregation of data for differing levels of income. However, research on social processes resulting in gender differentials (which is generally conducted at the micro-level) needs to be fed more effectively into policy making.