Large differentials in health outcomes of mask significant variation within country across different groups (men/women, different ethnicities). The key question is whether improving access to health facilities for certain (otherwise excluded) sections of society could significantly improve aggregate health outcomes? If so, then this could be significantly cheaper than alternative policies that seek to expand health service provision, as encouraging use does not necessarily involve spending on new health infrastructure.

A key part of this problem is understanding why certain groups do not have access to health facilities. Is there active discrimination, in which case some role for anti-discrimination policy could be of use, or is the discrimination more passive (i.e. based on cultural norms/preferences) in which case policy may have to play a more indirect role in encouraging participation?


Civil Rights, the War on Poverty, and Black-White Convergence in Infant Mortality in the Rural South and Mississippi D. Almond et al (MIT Working Paper 07-04)

In a Nutshell

This paper provides a good example of the role that policy can play in encouraging participation with health services through decreasing active discrimination, and also the health benefits of including an otherwise excluded section of society as beneficiaries of health facilities.

In the 20th Century there was a marked improvement in the infant mortality rates of black infants in the rural South. The paper argues that this was driven by federally mandated desegregation of hospital facilities that had the effect of increasing access to hospital care for black babies. The policies which were part of the Civil Rights act effectively opened up what had previously been white only hospitals. They present quantitative evidence to support this assertion. Firstly, the reduction in black infant mortality began immediately after integration and was the most pronounced in the rural South, where access to hospital was most constrained for black families. Secondly, the decline was driven by declines in post-neonatal rather than neonatal deaths (as post-neonatal were more preventable than neonatal at that time). They also use Mississippi as a testing ground, as there was significant variation in when hospitals desegregated – they strong effects in mortality reductions when a hospital in the county was certified as desegregated, relative to those that were not yet desegregated. This evidence refutes any alternative hypotheses based upon improvements in medical care.

They estimate that over 25,000 deaths were prevented with a welfare contribution of c.$7bn. In other words, through a simple mechanism of anti-discrimination, a large section of society was now able to use the health service and this had significant health impacts without the need to invest heavily in new infrastructure.


Missing Women: Age and Disease S. Anderson & D. Ray (Review of Economic Studies (2010)

In a Nutshell

In many parts of the world (China/India especially) it has been noted that the ratio of women to men is suspiciously low. Amartya Sen calculated that had the ratio been the same as in the world as a whole, there are millions of “missing women”. This has often been attributed to selective abortion (due to a preference for males) and a systematically lesser degree of care for girls relative to boys.

This paper performs an accounting exercise to see at what point in the age distribution these women are missing in different regions of the world, and investigates what could be causing this. They do so by comparing death rates in the specific country to the death rates observed in the developed world whilst controlling for the sex ratio at birth (as different ethnicities have different birth rates for boys/girls), and controlling for different disease compositions (that may differential affect the sexes).

Their findings indicate that whilst in India and China there are similar overall imbalances in the sex ratio, there are distinct age profiles of these missing women. Sub-Saharan Africa has exhibited birth rates very similar to the developed world. However, when the natural birth rate is controlled for, Africa has relatively more missing women than either India or China. SSA’s missing women are not however missing at birth, which is confirmed when the age clusters of missing women are analyzed. India on the other hand has 11% of its missing females at birth, and China has c.40% which indicates there is selective abortion practices occurring in China and to a lesser degree India.

They find that the changing composition of the disease profile explains very little of the variation in missing women. In India preventable diseases explains missing girls in childhood, maternal mortality and injuries kill women of reproductive age, and cardiovascular mortality explains death at older ages (which is actually the largest component of the missing women in India). In SSA the dominant source of missing women is HIV/AIDS which may reflect differential treatment received by women, or prevalence of sexual violence among other possible explanations.  In China, other than the prenatal missing women, women over 45 seem to be missing too.

This analysis cannot disentangle whether active or passive discrimination is occurring, or whether it is another mechanism, but it helps in knowing where to look for effects. For example how the elderly receive care in India and China is clearly an issue, as are termination practices in China.

To the extent that active discrimination is occurring the Almond et. al paper shows that there could be a positive role for anti-discrimination policies, and that such policies can lead to better aggregate health outcomes.


Why do Mothers Breastfeed Girls Less than Boys? Evidence and Implications for Child Health in India S. Jayachandran & I. Kuziemko (Quarterly Journal of Economics)

In a Nutshell

This paper is about passive discrimination. It is also concerned with differential health effects for girls as opposed to boys, but proposes that the mechanism at work is that girls receive less time breastfeeding than boys, and the reason for this is that there is a cultural preference for boys. Since breastfeeding reduces fertility, then mothers of girls are likely to breastfeed their female children less if they still desire to have a male child. To the extent that there is a “stop-after-a-son” fertility pattern, when a daughter is born the parents will likely want to try again (and hence she will stop breastfeeding) indicating that girls will be weaned earlier than boys. Given the large health benefits of breastfeeding, particularly in the presence of widely contaminated water and food, such an attitude can lead to disparities in child health between the sexes. Note, this is not active preferential treatment for boys over girls, but rather a prediction that girls will be breastfed less even when parents value equally the health of all their existing children.

The predictions are borne out by the data. Breastfeeding duration increases with birth order as the demands for the contraceptive element of breastfeeding increases. Overall girls are breastfed less than boys. Children with older brothers are breastfed more. The gender effect is largest as the family size approaches the (self-reported) target family size.

Back of the envelope calculations show that breastfeeding could account for between 8000 and 25,000 missing girls per year in India.

Policy wise this is more difficult than the active discrimination case. Any breastfeeding awareness campaign could be offset by the preference for boys, a norm which in itself will be hard to change using public policy. So some indirect options are available:

Firstly contraceptive could be promoted. However, this has ambiguous effects. Contraception may crowd out breastfeeding inasmuch as mothers rely on breastfeeding more (for its contraceptive properties) when other contraception is unavailable – thus promoting contraception may decrease breastfeeding. Alternatively, if access to modern contraception better allows for family planning and particularly the timing of birth, then this may encourage breastfeeding.

Secondly, water and sanitation should be improved such that when children of any sex are weaned off breastmilk they have a better chance of survival due to clean water etc.



Missing Women and the Price of Tea in China: The Effect of Sex-Specific Earnings on Sex Imbalance N. Qian (Quarterly Journal of Economics 2008)


In a Nutshell

Amartya Sen once theorized that the reason that the sex ratio was much more balanced in Africa was that women were more integrated into the labour force, and thus the value of a female life was greater than in parts of the world where women were excluded from the labour force. This paper does not quote him directly, but it is investigating this mechanism in China. In other words it investigates whether changes in relative female income (as a share of total household income) affects life outcomes for boys and girls. Previous studies suffered endogeneity problems as areas where the female component of the workforce earned more money may have been areas where women had higher status already. In order to get around this problem, the paper uses quasi-experimental data based upon two reforms in post-Mao China which increased the price of cash crops including tea and orchards. Women have a comparative advantage in tea (due to the delicate nature of the work and the low lying bushes) and men have the advantage in orchards. This meant that areas that cultivated tea experienced an increase in female income and so on meaning that a difference in difference strategy can be used to identify the effect of rising income on survival. The setting is advantageous as migration was strictly controlled, there was little technological change in the period, and sex-revealing pre-birth technologies were not widely available (thus ruling out certain confounding elements).

She compares the sex-imbalance for cohorts born before and after the reforms with counties that plant sex specific crops as the treatment and counties that do not as the control. Firstly she compares the sex ratio in counties that plant tea to counties that do not between cohorts born before and after the reform (thus effectively holding male income constant), and does the same for orchards (holding female income constant). She repeats this analysis for educational attainment. The results indicate that increasing female income by 10% increases the fraction of surviving girls by 1% and educational attainment for boys and girls by 0.5 years. Increasing male income by the same amount decreased survival rate for boys and girls and had no effect on educational attainment for boys.

This is a special kind of difference in difference (bit sketchy on the details). Comparing sex imbalance within counties between cohorts removes time-invariant community characteristics (fixed effects) whereas comparing sex imbalance within cohorts between tea-planting and non-tea planting counties removes changes over time that affect the regions similarly.  As she has to use 1997 agricultural data on what crops were planted this introduces measurement error and attenuation bias. Similarly there could be endogeneity if families that prefer girls switch to tea planting after the reform. To counter these issues she does an IV strategy also which used slope as an instrument for planting tea.

The identifying assumption is the usual DID one. This is not reliant on the fact that only women pick tea. In fact, as tea is a proxy for female income, if men or children pick tea then the proxy would actually exceed real female income so the strategy would underestimate the true effect of female income on the sex ratio. She provides some graphic evidence that there is a trend break around the time of the reform, and that there were some parallel trends.

How might increasing female income increase survival rates of girls?

  1. Increase parental perceptions of future earnings potential of girls and hence increase their relative desirability
  2. Increase in total household income may increase desirability of girls relative to boys if for some reason daughter are luxury goods relative to sons
  3. Increasing female specific income can increase female bargaining power, and this will increase survival of girls if mothers prefer girls more than fathers
  4. Increasing the value of adult female labour can raise the cost of sex selection since pregnancies must be carried to term before the sex of the child is revealed.

Which mechanism is at work is partly a function of how the household behaves. If the household is unitary (income –pooling), it makes no difference whose income is raised, it will have an equal effect on household consumption. However, this can be ruled out as there are differences between the effects of raising tea income as opposed to orchard income.  This points to a model of intra-household bargaining where mothers value education more than fathers and face higher costs of neglecting the children of either sex which will lead to equal treatment of boys and girls which is why we see increased education for both, and improved survival rates for girls.

Policy implications are pretty clear. One way to increase female survival rates and educational attainment for all is to increase the income of women.

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