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7/27/2019 Overcoming son preference in India remains a daunting challenge as even educated women are prone to it.docx

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Overcoming son preference in India remains a dauntingchallenge as even educated women are prone to it

Have women fared better than men, and girls better than boys in the last decade or so? In

the din over a dramatic reduction in poverty in the period 2009/10-2011/12 that isunlikely to die down, deep questions about the discrimination and deprivation thatwomen face from the womb to the rest of their lives are either glossed over or, worse, justignored.

The Sen norm

Amartya Sen sought to capture the cumulative impact of multiple forms of deprivationthat women face over their lives in an intuitively appealing measure of “missing women.”It aims to capture women’s adversity in mortality and to better understand thequantitative difference between (1) the actual number of women, and (2) the number we

expect to see in the absence of a significant bias against women in terms of food, andhealth care. First, the difference between the sex ratio norm of women per 1,000 malesand actual sex ratio is computed. Second, multiplying it by the number of males, thenumber of missing women is obtained. This is an absolute measure. A relative measurerequires division of missing women by surviving women. In the same way, absolute andrelative estimates of missing girls are computed.

Dr. Sen’s original estimate of missing women in India in the 1980s was 37 million in aglobal total of more than 100 million missing women. Another estimate is lower for India(23 million) in a total of 60 million in selected countries, based on the westerndemographic experience. More recent estimates point to higher numbers of missing

women. The important point, however, is not that the differences are large but the factthat “gender bias in mortality takes an astonishingly high toll” (Sen, 2003).

The sex ratio rose in India from 932.91 per 1,000 males in 2001 to 940.27 in 2011,implying a decadal growth of 0.70 per cent. Using the same norm that Dr. Sen used, our estimates of missing women rise from 46.35 million in 2001 to 49.73 million in 2011, anincrease of 3.38 million. The decadal increase was thus 7.30 per cent. As the number of missing women depends on the difference between the sex ratio norm and the actualmultiplied by the number of men, a narrowing of the difference between these ratios wasmore than compensated for by the larger number of men. However, as a share of surviving women, there was a reduction — from 9.33 per cent in 2001 to 8.48 per cent — implying a decadal reduction of 9.17 per cent.

Rural and urban picture

Disaggregation into rural and urban missing women reveals an interesting picture. Thesex ratio in the rural areas rose slightly, from 946 in 2001 to 947 in 2011. The absolutenumber of missing women rose from 28.35 million to 31.30 million, an increase of 2.95



million. This implies a decadal increase of 10.40 per cent. However, the share of missingwomen declined from 7.9 per cent to 7.7 per cent, a decadal reduction of 2.53 per cent.

The sex ratio rose from 900 in the urban areas in 2001 to 926 in 2011, a decadal increaseof 2.89 per cent. Yet the absolute number of missing women increased slightly — from

18 million to 18.42 million — a decadal increase of 2.33 per cent. This is a fraction of themuch larger increase in rural areas. However, the share of missing women declined — from 13.3 per cent to 10.20 per cent — a decadal reduction of 23.30 per cent. This isconsiderably larger than the reduction in rural areas.

The sex ratio (girls/1,000 boys) in the age group <6 years fell from 927 in 2001 to 914 in2011, a decadal reduction of 1.40 per cent. The number of missing girls rose from 2.13million in 2001 to 3.16 million in 2011, a decadal increase of 48.36 per cent. The share of missing girls in surviving girls also rose from 2.7 per cent to 4.2 per cent, an increase of 55.55 per cent. Both absolute and relative measures of missing girls thus shot up over thisdecade. That the bias against girls rose so sharply is alarming.

In the rural areas, the sex ratio fell from 934 in 2001 to 919 in 2011, a decadal reductionof 1.60 per cent. The number of missing girls rose from 1.23 million to 2.07 million, adecadal increase of 68.29 per cent. The share of missing girls rose from 2.0 per cent to3.7 per cent, an increase of 85 per cent. As these rates are much larger than those at theall-India level, it follows that the already more pervasive sex-selective discriminationgrew more rapidly in the rural areas.

Our regression analysis focusses on some of the key factors underlying discriminationagainst women resulting in missing women, using State level data for 2001 and 2011.This allows us to isolate the effect of each variable and assess its magnitude. As a few

States that had a pronounced sex imbalance grew rapidly (e.g. Haryana, Rajasthan,Gujarat, Delhi, Maharashtra), it is not surprising that the share of missing women rosewith higher income. States with higher female literacy rates, as a proxy for better schooling of women, witnessed lower shares of missing women, as also those with ahigher ratio of female workers to male workers. The latter is often used as a women’sempowerment indicator. A higher proportion of adult women (15-59 years) raised theshare of missing women, presumably because of higher maternal mortality. Higher

proportions of Scheduled Castes and Scheduled Tribes relative to Others, as proxies for cultural factors, were associated with higher shares of missing women. The higher thenumber of crimes against women, the higher was the share of missing women. A north-south divide in the shares of missing women persists with the north and west regionsfaring worse than the south. Much of this disparity is attributed to whether it is amatriarchal or patriarchal society and whether inheritance laws favour women. Finally,media exposure significantly reduced the share of missing women.

The child sex ratio depends on two factors: sex ratio at birth and gender specific mortalityrates among children ever born. While preventing the abortion of female foetuses reducesthe masculinity of the sex ratio at birth, it has the likely consequence that unwanted girl



foetuses grow into girls who will be deprived of nutrition and health care. Theseunwanted girls will then be more vulnerable to infant and child mortality.

Sex determination

Although foetal sex determination for selective abortion has been illegal in India since1994 — the Pre-Conception and Pre-Natal Diagnostic Techniques (Prohibition of SexSelection) Act, 1994 however, became effective in 1996 — evidence suggests that the

practice flourishes. A Lancet study shows that a woman is substantially more likely tohave a boy if she has a large number of girls. For families who already have one child,the probability of the second child being a girl is 0.515 if the first child is a boy, but only0.422 if the first child is a girl. On some assumptions — including the birth order effects

— about 0.5 million sex selective abortions occurred annually. Other more recentestimates are higher (about 0.62 million in 2011 or well over six million includingabortions largely performed in non-registered institutions, by untrained people, and inunhygienic conditions). Unsafe abortions account for nearly eight per cent of maternal

deaths.

In sum, while women’s empowerment through education, employment opportunities andsocial networks that give them a voice against discrimination, greater media exposure andenforcement of laws that penalise violation of women’s rights are central to reducing thisscourge, the challenge of overcoming son preference remains a daunting one, as evenworking and educated women are prone to it. Besides, and somewhat surprisingly, morerapid growth alone in States with pronounced sex imbalance, so often touted as a panaceafor all forms of deprivation, is likely to make matters worse.

(Vani S. Kulkarni is a research associate in sociology, Yale University, while Manoj K.

Pandey is a doctoral candidate in economics, Australian National University, and Raghav Gaiha is a visiting scientist, department of global health and population, Harvard School of Public Health.)

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