Literature review

To construct a model incorporating a large number of explanatory variables to potentially explain the tendency to neglect girls in India, we need to investigate the existing literature on gender bias in mortality. From this perspective, this section offers insights into the existing work on the topic, the theoretical framework for the analysis and a possible justification for incorporating some variables in our empirical model.

Most studies on gender bias in mortality show that unequal access to healthcare is the most important process driving excess female mortality and leading to a higher mortality for young girls (Basu 1999, Klasen 1999, Alderman and Gartler 1997).

Differences in access to nutrition appear to be a smaller factor (Chen 1981, Sen 1992, Basu 1992). This comparative neglect of female children, generally worse in rural areas, appears to be particularly severe for later-born girls, especially for the girls with elder sisters (Das Gupta 1987, Dreze and Sen 1989, Klasen 1999).

The scarcity of economic resources is a necessary but not sufficient condition for experiencing gender bias in mortality. Poor households are forced to ration scarce resources allocated to nutrition and healthcare, which could disadvantage females, but many country studies notice that the poorest sections of the population experience less gender bias in mortality than slightly richer groups (Murthi, Guio and Dreze 1995, Klasen 1999).

Another point of interest for further investigation is provided by the dispute initiated by Das Gupta & Mari Bhat and Murthi & Dreze (1995, 1997, and 1999). The first two authors studied the relationship between fertility decline and gender bias in child

44For the society, however, the social benefits are different. There are relevant positive externalities involved in having a gender neutral society. The role of the policy maker should be to equalize the private and social benefits: in this case a good policy option would be to subsidize girls’ schooling or to provide any help that justifies an investment in girls.

mortality, showing evidence for the spread of sex-selective abortion, especially among women with lower fertility. Murthi and Dreze (1999) found that the association between fertility and gender bias is firmly positive rather than negative, casting doubt on the argument used by Das Gupta and Mari Bhat. Further research is needed to settle this dispute. If a decline in fertility leads to the intensification of gender bias in India, it will be necessary to intervene immediately (Klasen, 2009) so the already existing large bias is not exacerbated.⁴⁵

Last but not least, there is evidence that state policies can influence gender bias in mortality (Oster, 2009). State-supported free access to healthcare and nutrition would lessen the need to ration scarce resources (Asfaw, Lamanna and Klasen, 2010). Having state supporting policies that promote female education and employment would have a positive impact on the return on investment for girls and therefore improve circumstances for girls nationally (World Bank 2001).

While female mortality rates in excess of male rates in the reproductive years are likely to reflect the hazard of childbirth, the evidence for differential morbidity not directly or indirectly related to reproduction is not clear. In Bangladesh, Chen et al. (1981) conclude that while there is no gender difference in the incidence of disease, there may be gender difference in the duration and intensity of illness. Gender differences in clothing quality and expenditure may also influence health status (Das Gupta 1987). In cases from north India and Bangladesh, a marked gender imbalance in health expenditure on children is recorded (Das Gupta 1987) and the treatments given to females are often less orthodox.

Mitra (1978) found that gender differences in child mortality rates from vitamin deficiency, respiratory and gastrointestinal diseases arise from relatively late stage of illness at which girls were brought for treatment.

Gender bias in health expenditures

Low availability of health facilities and low public expenditure on health per capita are other important aspects related to increased mortality rates. A conspicuous number of studies show that gender difference in mortality rates vary positively with the distance from home to treatment centre. Disadvantages in female access to treatment, especially at

45A number of cultural practices and customs appear to hurt females in some regions, including virilocal marriage patterns, ancestor worship undertaken by sons and high dowry for brides.

young age, may have a remarkable influence on future female health. Gender differentials in access to state medical facilities may be further extended to access to other types of state institutions and to political life at village level and beyond. Asfaw, Klasen and Lamanna (2007) find that the strong preference for boys in India is reflected in the higher chances for girls to die at home than boys.

In India and Bangladesh despite the enactment of legislation after Independence to guarantee equal inheritance rights to men and women, women’s control over property is thought to have diminished throughout the subcontinent in the past fifty years. There remains notable differences between south and north, with southern women having greater access to property.

Potential sources of discrimination

Similarly despite the Dowry Prohibition Act of 1961, the practice of transferring resources on marriage as dowry is said to be increasing in prevalence and size both in the south and north of India. The commercialization of females via resource transfer at marriage is punitive for households with a preponderance of daughters. This phenomenon could be linked directly to another unfortunate practice, seclusion, which may restrict the selected woman to the interior of the home.

Female discrimination also manifests in wage work. Although they play a roughly equal role in agriculture production, women receive less for it. Other better-paid sectors of female activity, such as trade, are restrictive in their dependence on male sanction for physical premises, credit and prices.

Female education plays a fundamental role advantageous to the welfare of women and may be a major source of change in domestic productive and reproductive behaviour (especially fertility decisions). The rise in female literacy rates and the increasing confinement of illiteracy to those over the age of 25 indicates the possibility of a rise in female status over the next decades. Yet female literacy lags behind that of males, especially in north and centre of India, areas with a high concentration of scheduled castes and tribes.

An interesting paper that contributes to the policy debate on effective policies benefiting disadvantaged groups is the one recently published in the Journal of Devleopment Economics by Oster (2009). The paper investigates weather increases in Policy Debate

access to social services decreases inequality in the level of these services between advantaged and disadvantaged groups. The paper, using a very large dataset of over 90,000 women (NFHS)⁴⁶

2.4. Methodology

shows that in India there is a strong non-monotonic relationship between access to services and gender inequality, where at low levels of access to investments, there is no gender bias in investment while an increase in access increases investments for boys in India, generating inequality. This result is collaborated also in our analysis (see section on empirical results).

Using a Cox proportional hazard model, this paper investigates which household, mother, father and child characteristics are associated with higher child mortality rates in India. Specifically we investigate if there is any significant difference in the survival rates of girls and boys. Our dependent variable is child mortality under five years of age. After surveying the existing literature, we include as explanatory variables household composition and characteristics (location, income, number of people in the household, etc.), mother, father and child characteristics (mother and father education, mother nutritional and health status, exposure to media, birth spacing, sex of the child, having older sisters, etc.).

Further, in the context of India, there are significant variations in child mortality across the various geographical regions. To capture those differences, we added state dummies into the model. While on the one hand there are states like Kerala that have demographic features typical of middle-income countries, there is also a large part of India (in particular the northern states) that scores among those world’s least developed in terms of demographic indicators.

In order to conduct our analysis we use a very rich and representative dataset (NFHS 1998-99 for India) that comprises more than 90,000 ever-married women across 26 Indian states. India makes an interesting laboratory for the study of demographic processes. It has one sixth of the world’s population and almost a quarter of under-five child deaths in the world (Black et al. 2003). Infant mortality in India has been gradually declining, having halved between the early-1970s and 2000, but the rate of decline is less impressive than that observed in some other South and South-east Asian countries.

46 Using the same dataset we are using in our analysis.

The Millennium Development Goal to reduce the mortality rates among children under five by two thirds by 2015 (MDG 4) represents a huge challenge for India. In 1999, the under-five child mortality rate in India was 100 children per 1000; where the infant mortality was very high, 70 every 1000. Mortality rates overall decreased recently but the pace is not sufficient to ensure satisfying results in the next future and particularly the rates for girls’ mortality are much higher.