Gender-based Indicators in Human Development: Correcting for ‘Missing Women’

Nathan, Hippu Salk Kristle (2014). 'Gender-based Indicators in Human Development: Correcting for 'Missing Women'' Paper presented at the annual conference of the HDCA, 2-5 September 2014, Athens, Greece.

This paper starts with United Nations Development Program pre-2010 use Gender Development Index (GDI) and Gender Empowerment Measure (GEM) as indicators to assess human development after adjusting for gender inequality. The study highlights how these indicators suffer from the limitation that countries with unbalanced sex ratio get unduly rewarded when the sex ratio favors the better performing gender (typically male). The population proportions of the two genders enter into formulation of these measures in such a way that, for a given level of female and male achievements, a rise in the population proportion of the better performing gender i.e. the gender with higher level of achievement, results in higher index. This can lead to further additions to 'missing women' as explained below in the example.[1]

In 2005, the life expectancy indices of female and male for United Arab Emirates (UAE) are 0.892 and 0.905 respectively (UNDP 2007).  The corresponding values for United Kingdom (UK) are 0.895 and 0.903. UK, with a higher mean and lower difference between these values, is expected to get a better rank than UAE in health dimension of GDI.  However, this is not so; and UAE fetches a rank of 19, which is better than that of UK, which is at 21. This anomaly results due to UAE's skewed sex ratio of 2.137 vis-à-vis a UK's balanced sex ratio of 0.955.[2] The UAE story repeats for countries like Quatar, Kuwait, Bahrain, Oman, and Saudi Arabia. For these countries, the skewed sex ratio biased towards male, which is the better performing gender, acts to their advantage. This anomaly affects all the dimensions of GDI and GEM. So, these measures give signal to countries to favor the better performing gender and neglect the other (typically female). This can lead to policies contributing to 'missing women'. For instance, a country, where female literacy is lower than male can improve its education dimension of GDI by practising female- foeticide and infanticide or promoting male-biases in health care, or furthering any such discrimination which induces higher female mortality and thereby improves male/female ratio in population. This implication of GDI and GEM measures is counterintuitive and opposed to gender justice. As gender sensitive development indicators, these measures ought to signal countries to correct the imbalances in sex ratio, rather than to distort it further.

This paper revisits the gender-based indicators and proposes a correction to take care of the above anomaly. A correction is proposed to capture the above mentioned anomaly. The alternative measure satisfies an axiom of Monotonicity, which is proposed to characterize the measure with respect to sex-ratio. The paper provides empirical illustration to demonstrate the advantages.

Since GDI and GEM are abandoned by UNDP since 2010, the paper looks into other gender inequity measures (e.g., Social Watch, World Economic Forum, SIGI, etc.) which makes use of population data (and the underlying sex ratios). The study revisits these measures with the introduction of sex ratio correction factor and notes the implications through empirical illustrations.

In short, this study demonstrates how gender sensitive measures dependent on population data suffers from the limitation that countries with unbalanced sex ratio get rewarded where sex ratio is biased towards the better performing gender. This way, theoretically, these indicators reduce to achievement of one gender when the other goes extinct. This paper questions the rationality of such gender sensitive indicators which take note of, for instance, inequality in life expectancy without consideration of the 'life' itself! New measures are proposed with introduction of sex-ratio correction factor which do not suffer from these limitation. The advantages of the new measures over the old measures are shown both axiomatically and empirically.

[1] 'Missing women' is the term coined by Sen (1992) to describe the terrible deficit of women in substantial part of Asia and North Africa due to sex bias in relative care. This term is used in the present paper as an analogy to describe disadvantaged gender which can be male as well. For instance, a country prone to war will have male life expectancy relatively lower than female due to decimation of men in wars.

[2] Sex ratio is expressed in this paper as (male population)/(female population)

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