WPS6802


Policy Research Working Paper                    6802




          Why Are Adult Women Missing?
         Son Preference and Maternal Survival in India

                             Annamaria Milazzo




The World Bank
Development Research Group
Human Development and Public Services Team
March 2014
Policy Research Working Paper 6802


  Abstract
  This paper is the first to show that excess mortality                             among those in the older age group, they appear to be
  among adult women can be partly explained by strong                               significantly better off in terms of various predetermined
  preference for male children, the same cultural norm                              characteristics. These findings are consistent with a
  widely known to cause excess mortality before birth or                            selection effect in which maternal and adult mortality
  at young ages. Using pooled individual-level data for                             is higher for women with first-born girls, especially the
  India, the paper compares the age structure and anemia                            poor and uneducated with limited access to health care
  status of women by the sex of their first-born and                                and prenatal sex diagnostic technologies. To ensure the
  uncovers several new findings. First, the share of living                         desired sex composition of children, these women resort
  women with a first-born girl is a decreasing function of                          to a fertility behavior medically known to increase their
  the women’s age at the time of the survey. Second, while                          risk of death. The observed sex ratios for first births imply
  there are no systematic differences at the time of birth,                         that 2.2–8.4 percent of women with first-born girls are
  women with a first-born girl are significantly more likely                        ‘missing’ because of son preference between the ages of 30
  to develop anemia when young (under the age of 30) and                            and 49.
  these differences disappear for older women. Moreover,




  This paper is a product of the Human Development and Public Services Team, Development Research Group. It is part
  of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy
  discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org.
  The author may be contacted at amilazzo@worldbank.org.




         The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development
         issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the
         names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those
         of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and
         its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.


                                                       Produced by the Research Support Team
                                    Why Are Adult Women Missing?
                                                                                                    ∗
                         Son Preference and Maternal Survival in India

                                                Annamaria Milazzo†




JEL classification: J16, J13, I10, D63
Keywords: missing women, maternal mortality and morbidity, son preference, fertility, birth spacing, India




   ∗
       I am grateful to Eliana La Ferrara for continued guidance and support, and to Alberto Alesina, Siwan Anderson, Sonia
Bhalotra, Maristella Botticini, Abel Brodeur, Jishnu Das, Jed Friedman, Robert Garlick, Selim Gulesci, Eeshani Kandpal,
Elaine Liu, Owen Ozier, Debraj Ray, Dominique van de Walle, and Adam Wagstaff for very helpful comments. I thank seminar
                                                                                               eal for comments and
participants at Bocconi University, 2012 NEUDC conference, and 2013 CEA Conference at HEC Montr´
suggestions. All errors are my own. The findings, interpretations, and conclusions expressed in this paper do not necessarily
represent the views of the World Bank, its Executive Directors, or the countries they represent.
   †
     The World Bank. Email: amilazzo14@gmail.com; amilazzo@worldbank.org




                                                              1
1        Introduction
Research on missing women has documented severe gender bias at birth and at young ages due
to pervasive son preference in India and other Asian countries (Das, 1987; Das Gupta, 1987; Sen,
1990; Arnold, Kishor and Roy, 2002; Jha et al., 2006, 2011). Recent studies confirm these previous
findings but also demonstrate that most women are instead missing at adult ages (Anderson and
Ray, 2010, 2012; World Bank, 2011).1 , 2 Anderson and Ray (2012) find a large state-wise variation
in the distribution of excess mortality across age groups in India and argue that the traditional
explanation of strong preference for male children can only explain the phenomenon of missing
women in states with abnormally male-biased sex ratios at birth. They contend that the explanation
for excess mortality in adulthood must reside in other, unspecified, factors.3 This paper provides
evidence that, on the contrary, strong son preference is also partly responsible for high mortality
rates among adult women.
        India has the world’s largest number of maternal deaths. The ‘female disadvantage in mortality
during the reproductive ages is in part driven by the risk of death in pregnancy and childbirth and
associated long-term disabilities’ (World Bank, 2011, p. 78). It is estimated that for every maternal
death there are twenty other women who suffer pregnancy-related illness, infection, injury, and other
physical and psychological long-term consequences (Nanda, Switlick, and Lule, 2005; Filippi et al.,
2006; UNICEF, 2008). Anemia, one of the most common indirect causes of maternal mortality
in Asia, is pervasive among Indian women. Medical research has shown that repeated and closely
spaced pregnancies are associated with increased risk of maternal mortality and morbidity. This
behavior is common among women who have only daughters and want to conceive again for a
son. The diffusion of prenatal sex diagnostic technologies in the late 1980s has been found to be
associated with increasing sex ratios at birth (the fraction of male births) in India which is strongly
suggestive of sex selection (Arnold, Kishor, and Roy, 2002; Bhalotra and Cochrane, 2010). Research
    1
        Missing women, or excess female mortality, is based on a counterfactual in which there is no discrimination based
on gender (Sen, 1990). As a counterfactual, Anderson and Ray (2010) use developed countries, while in their study
on India, Anderson and Ray (2012) also use Kerala as an alternative benchmark.
   2
     Klasen and Vollmer (2013) challenge the methodology developed in Anderson and Ray (2010) and argue that the
data used in their computations are largely unreliable (especially those on adult mortality for sub-Saharan Africa) and
use a reference benchmark that does not account for differences in the disease and mortality environment. Anderson
and Ray (2012) replicate their decomposition exercise for India and find that their results are robust to using Kerala
as a benchmark (rather than developed countries), though of smaller magnitude. It is important to note that the
issues at stake in this debate do not alter the motivation for this paper, which is to analyze the factors contributing
to the high number of maternal deaths in India. High maternal mortality is certainly partly due to generally poor
health conditions and services and, as argued in this paper, it is aggravated by strong son preference.
   3
     Jayaraman, Ray, and Wang (2013) find evidence that women seek treatment for eye care later than men, while
they do not seem to receive less surgical care in India.



                                                             2
has shown that sex-selective abortion is more common among educated women and after the first
child is born (Das Gupta, 1987; Jha et al., 2011).
   The central idea of this paper is that maternal and adult mortality is higher among women
with a first-born daughter. As a result of strong son preference, such women are more likely to
engage in fertility behavior that adversely affects their health. This effect should and is found to be
stronger among women with generally more vulnerable health, lower access to maternal care and
to technologies for fetal sex determination, typically the poor and uneducated.
   I pool three rounds of the India National Family Health Survey (NFHS) and find several signif-
icant findings. First, there are no systematic differences between women whose first birth is male
and women whose first birth is female close to the time they give birth. Significant differences
appear in the sample of older women (i.e., aged 30 to 49), both in terms of variables related to
fertility behavior, and predetermined characteristics. The latter is suggestive of selection among
women with a first-born girl as a result of higher mortality. The empirical strategy rests on the
identifying assumption of conditional exogeneity of the sex of the first-born. Second, compared
to women with first-born sons, women with first-born daughters are 5.1 percentage points more
likely to desire more children, 6.8 percentage points less likely to be sterilized, 2.5 percentage points
more likely to have undergone an ultrasound test, 1.1 percentage points more likely to have had a
terminated pregnancy, and to have given birth to 0.3 additional children. These results reinforce
findings from the existing literature on son-preferring stopping behavior and sex-selective abortion.
I investigate heterogeneous effects by women’s education level (with education as a proxy for socio-
economic status) and find that, as expected, educated women with a first-born girl are more likely
to have had a terminated pregnancy and to exhibit an attenuated effect on fertility (compared to
uneducated women). Moreover, a first-born girl increases the probability of a short birth interval
by 0.5 percentage points (the effect is 0.8 percentage points for women with a second-born girl
conditional on a first-born girl). This result is robust to the inclusion of mother fixed effects and is
larger for uneducated women. Although the effects of two or more successive daughters on fertility
outcomes are consistently larger (reflecting increasing pressure for having a son), I focus on the
sex of the first-born to maintain a causal interpretation. Third, among women under the age of
30, those with a first-born girl develop anemia at a higher rate: they are in fact 1.4 percentage
points more likely to be anemic (compared to those with a first-born boy), even after controlling
for height, current pregnancy and breastfeeding status. Fourth, differences in anemia prevalence
disappear for women older than 30. Fifth, the share of living women whose first birth is female
decreases with mother’s age at the time of the survey, especially among the uneducated. This
suggests that maternal and adult mortality is higher among uneducated women with a first-born
girl. State-wise variation confirms that this decreasing pattern is found in states with the highest
proportion of missing women of adult ages (Assam and Bihar), and not in states with the most


                                                   3
male-biased sex ratios at birth (Punjab and Haryana).
       I address potential alternative interpretations of the findings. First, based on evidence that poor
maternal nutrition might be associated with the sex of the child (Mathews, Johnson, and Neil, 2008;
Almond and Mazumder, 2011), I estimate the timing of the emergence of anemia differences. If
predetermined health affects the sex of the child, differential incidence of anemia between women
with a first-born girl or boy should be present at the time of birth (and even before, but this cannot
be verified with the data at hand). The results indicate no differential incidence of anemia close to
the time of birth. Women with a first-born girl start developing anemia approximately one and a
half years after birth. Therefore, biological differences do not seem to explain the anemia pattern,
which is rather consistent with behavioral factors. Second, I test whether the estimates are affected
by selective reporting bias according to which women might under-report female births, and find
no evidence supporting it. Third, I show nonparametric evidence that the decreasing share of
women as a function of their age (found for the uneducated) cannot be affected by the diffusion
of the practice of sex-selective abortion.4 Finally, I check whether women suffer other forms of
overt discrimination as direct ‘punishment’ for having had a first-born daughter. I do not find
evidence that they are punished through withholding of food (or receive less iron supplements),
while they appear to be more likely to have been the victims of severe domestic violence inflicted
by their husbands. The effect on violence is specific to the period close to the time of birth and
to uneducated women. Therefore, increased violence is possibly contributing to higher mortality
among women with daughters as the result of strong preference for male children. All these findings
are consistent with a model in which son preference induces women whose first birth is female into
a fertility behavior that is medically known to be associated with higher risk of maternal mortality
and morbidity. This pattern is especially found among uneducated women who have poorer access
to maternal care. These women develop anemia at a higher rate and appear to suffer a higher risk
of death.
       This paper is related to three strands of literature. The first is the recent literature on the age
distribution of missing women (Anderson and Ray, 2010, 2012; World Bank, 2011). While previous
studies use aggregate data on mortality and find that most women are missing in adulthood, this
paper uses individual-level data to examine the possible channels generating this phenomenon.
       Second, it is related to the literature on the effects of son preference on children’s health. Son-
preferring fertility stopping rules can in fact lead to less resources being allocated to female children
within the household even unintentionally on the part of parents. Jayachandran and Kuziemko
   4
       Abortion was legalized in 1971 in India. In 1994, the Government of India passed the Prenatal Diagnostic
Techniques Regulations and Misuse Act (PNDT Act) to make the use of ultrasound or amniocentesis for the purpose
of sex determination illegal. However, there is evidence that this Law is often ignored and not enforced (Arnold,
Kishor, and Roy, 2002; Bhalotra and Cochrane, 2010).



                                                        4
(2011) show that gender disparities in breastfeeding duration arise because parents want to try again
for a son and therefore girls are weaned sooner than boys as a result. Jensen (2003) finds that the
gender differential in education is the consequence of the fact that girls tend to be born in larger
households. Barcellos, Carvalho, and Lleras-Muney (2014) develop a methodology to account for
the effect of son-preferring stopping rules on family size and find that boys still receive more parental
inputs (including childcare time, breastfeeding, vaccinations, and vitamin supplementation) than
girls in India. Recently, Jayachandran and Pande (2013) find that the cultural norm of eldest
son preference can in part explain the child height gap between India and Africa. This paper
contributes to this literature by suggesting another channel through which strong son preference
can affect children’s health, namely higher mortality of mothers (which often results in mortality
of the newborn or increased health risks for older children).
       Third, it refers to the literature on the consequences of the diffusion of prenatal sex diagnostic
technologies and sex-selective abortion. Research has shown evidence of massive female foeticide in
India, especially from the late 1980s with the diffusion of ultrasound testing (Arnold, Kishor, and
Roy, 2002; Jha et al., 2006; Bhalotra and Cochrane, 2010; Jha et al., 2011).5 The ability to detect
the sex of the fetus has also been found to be associated with preferential prenatal treatment for
boys (Bharadwaj and Lakdawala, 2013). Other authors have argued that sex selective abortion
implies a substitution in discrimination against female children from the postnatal to the prenatal
period (Goodkind, 1999). Hu and Schlosser (2011) find that the practice of selective abortion is
associated with lower malnutrition among girls likely due to differential reductions in family size
(larger for girls than boys). This paper provides evidence that, in addition to its general health
benefits, easier access to maternal antenatal care, and in particular to prenatal sex determination
technologies, can also reduce the risk of maternal mortality as women tend to rely less on a fertility
behavior that entails major risks to their health. Importantly, lower maternal mortality does not
necessitate easier access to sex-selective abortion, but is instead the outcome of improved maternal
care for all women, especially those practicing son-preferring fertility behavior due to increased
access to treatment of the complications deriving from it.


       The remainder of the paper is organized as follows: section 2 provides some background infor-
mation on the prevalence of maternal mortality and anemia in India; section 3 describes the data;
section 4 presents nonparametric evidence; section 5 introduces the empirical methodology used
to analyze fertility outcomes, birth spacing, health outcomes, and describes the results; section 6
discusses alternative interpretations; section 7 reports some calculations of the implied fraction of
missing women due to son preference; and section 8 concludes.
   5
       Akbulut-Yuksel, and Rosenblum (2012) find that, after the initial introduction of ultrasound, a recent rapid
spread in ultrasound use in the 2000s in some parts of India is not associated with further increase in sex selection.



                                                          5
2        Son preference, fertility behavior and maternal health outcomes

2.1        Maternal mortality, morbidity, and anemia prevalence in India

Maternal mortality and morbidity related to childbirth are among the main drivers of excess female
mortality during the reproductive years in India (Anderson and Ray, 2010; World Bank, 2011).6
        The WHO estimates that 117,000 maternal deaths occurred in India in 2005 (out of 536,000
worldwide), more than in any other country (WHO, 2007). These figures are considered to un-
derestimate the real burden of maternal mortality due to problems with its standard definition,
measurement issues, and lack of adequate data (AbouZahr, 2003; Koblinsky et al., 2012). A ma-
ternal death is defined as the ‘death of a woman while pregnant or within 42 days of termination
of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to
or aggravated by the pregnancy or its management but not from accidental or incidental causes.’
(WHO, 2010, p. 10). The dominant direct causes of maternal mortality are severe bleeding, hy-
pertensive diseases, and infections, while indirect causes include anemia, HIV/AIDS and malaria
(Ronsmans and Graham, 2006). Many direct causes, like severe bleeding, are themselves symptoms
of underlying indirect causes such as anemia (Center for Reproductive Rights, 2008). Kahn et al.
(2006) conduct a systematic review of the geographical variation in the distribution of the causes
of maternal deaths. They find that anemia is the second most common cause after hemorrhage in
Asia (causing 12 and 30 percent of maternal deaths, respectively).7 , 8 Unsafe abortion is another
direct cause, probably resulting in a significant number of deaths, although precise estimates do not
exist due to underreporting and misclassification. Despite abortion having been legalized with the
1971 Medical Termination of Pregnancy Act, many Indian women continue to have illegal abortions
performed by unqualified practitioners often in unsanitary conditions. Arnold, Kishor, and Roy
(2002) argue that there are several reasons why women do not seek safe and legal abortions. These
include that they might want to abort for reasons not allowed by the Act (i.e., abortion for sex
selection or due to contraceptive failure); they cannot afford the cost of an abortion performed by a
registered medical practitioner at a government-approved facility; or because of the unavailability
of such facilities. Even though estimates are likely to be imprecise, Kahn et al. (2006) estimate
that abortion contributes to about 6 percent of maternal deaths in Asia.
        Although not accounted for in standard estimates, maternal mortality ‘implies not only death
    6
        The other main cause of excess mortality in the reproductive years (between the ages of 15–44) is death due to
injuries, while cardiovascular disease is the most common cause among older women (Anderson and Ray, 2010).
   7
     While hemorrhage is found to be the most important cause overall in developing countries, other causes are
region-specific, such as sepsis and HIV in Africa, anemia in Asia, and abortion in Latin America.
   8
     Other studies provide higher estimates. For example, Gragnolati et al. (2005) and Kalaivani (2009) state that
anemia is responsible for almost one quarter and 40 percent of maternal deaths, respectively.




                                                            6
during childbirth but also concurrent morbidities brought on by the experience of pregnancy and
childbirth.’ (World Bank, 2011, p. 128). The global estimate of maternal deaths is considered to be
the ‘tip of the iceberg’ since an estimated 10 to 20 million women suffer pregnancy-related physical
or mental disabilities every year (Filippi et al., 2006, p.2).9 Maternal morbidities can have long-
lasting consequences –potentially affecting women’s survival– that can also lead to impoverishment,
violence, stigmatization, and marital instability (Koblinsky et al., 2012). Also not encompassed in
the standard definition, other causes of maternal deaths include injuries, accidents, suicide, murder,
and domestic violence while women are pregnant (AbouZahr, 2003; Ronsmans and Graham, 2006).
       Iron-deficiency anemia is the most common nutritional deficiency worldwide (Mukuria, Aboulafia,
and Themme, 2005). It is pervasive in India where it affects 56 percent of ever-married women
aged 15–49 (using NFHS-III data). It commonly results from a nutritional deficiency of iron, fo-
late, or vitamin B12. It is more prevalent during adolescence, pregnancy and among breastfeeding
mothers when nutritional requirements increase substantially (Sharman, 2000; Kalaivani, 2009).10
In addition to indirectly causing maternal mortality, anemia is an important risk factor for other
adverse health outcomes including impaired cognitive performance, higher incidence of infection,
prenatal and perinatal infant loss, and reduced work capacity (World Bank, 1996; Sharman, 2000;
Gragnolati et al., 2005; Ackerson, and Subramanian, 2008).
       Progress has been made in improving maternal health in India (Bhat 2002a; 2002b).11 The
maternal mortality ratio declined from 570 in 1990 to 230 in 2008 (WHO, 2010).12 World Bank
(2011) states that ‘maternal mortality is fundamentally different from excess female mortality at
other ages in that, to reduce it, societies must focus on an intrinsically female condition and
specifically on improving the maternal health care system.’ (p. 128). Notwithstanding better
health conditions in recent times, many women are still not receiving adequate maternal health
care in India.13 The decrease in maternal mortality has not been paralleled by improvements in
anemia prevalence. Instead, the incidence of anemia among ever-married women has worsened over
time: from 52 percent in 1998 to 56 percent in 2005. Given its magnitude, anemia is an extremely
   9
       Permanent and chronic conditions include obstetric fistula, urinary or faecal incontinence, scarred uterus, pelvic
inflammatory disease, palsy. Other main sequelae are severe anemia, eclampsia, and infertility. Psychological obstetric
morbidity includes puerperal psychoses, post-partum depression, suicide, and strong fear of pregnancy and childbirth
(AbouZahr, 2003).
  10
     Iron needs increase during the second and especially the third trimester of pregnancy. During pregnancy, the
required amount of iron is higher than what can be absorbed from the diet, therefore iron supplementation is necessary
(Sharman, 2000).
  11
     Safe motherhood is one of the objectives of the 1996 Reproductive and Child Health Programme and the National
Population Policy adopted by the Government of India in 2000.
  12
     The maternal mortality ratio is the number of maternal deaths during a given time period per 100,000 live births
during the same time-period (WHO, 2010).
  13
     For instance, NFHS-III data indicate that only 39 percent of births take place in health facilities and 58 percent
of women did not receive any postnatal check-up after their most recent birth (IIPS and Macro International, 2007).


                                                            7
serious public health issue in India (Gragnolati et al., 2005).


2.2       Fertility behavior and maternal health outcomes

It has been argued that in contexts where the preference for male children is pervasive, parents
alter their fertility choices and can exhibit overt discrimination against their unborn and living
female children (Das Gupta, 1987; Das, 1987; Clark, 2000; Arnold, Kishor, and Roy, 2002; Jha
et al., 2006). Parents can ensure the desired number of sons in two main ways. First, they can
avoid the birth of unwanted daughters by eliminating female fetuses through sex-selective abortion.
Several studies have noted that increasing sex ratios at birth in India match the timing of the
diffusion of prenatal sex determination technologies in the late 1980s (Arnold, Kishor, and Roy,
2002; Bhalotra and Cochrane, 2010). These and other studies (Das Gupta, 1987, and Jha et
al., 2011) have also documented that sex selection is more common among educated women and
richer families. Another key finding of this literature is that there is no evidence of sex selection
at first birth (Das Gupta, 1987; Bhat and Zavier, 2007; Jha et al., 2011). Second, women can
continue childbearing until the desired sex composition of children is reached, commonly known
as son-preferring stopping behavior (as women with daughters only are more likely to keep having
children) (Chowdhury and Bairagi, 1990; Clark, 2000; Dreze and Murthi, 2001; Arnold, Kishor,
and Roy, 2002; Filmer, Friedman and Schady, 2009). Other authors have also shown that a female
birth is associated with shorter birth intervals (Trussel et al., 1995; Arnold, Choe, and Roy, 1998),
and shorter breastfeeding (Jayachandran and Kuziemko, 2011). In this paper, I use ‘son-preferring
fertility behavior’ to refer to both stopping as well as reduced birth interval.
       The adverse health consequences of a high number of births and short spacing between births are
well documented in the medical literature. A high number of pregnancies is associated with higher
lifetime risk of death due to pregnancy.14 Medical research has shown that birth intervals shorter
than 24 months are associated with poor child and maternal health outcomes (Setty-Venugopal and
Upadhyay, 2002; King, 2003).15 Closely spaced pregnancies increase the risk of maternal nutrient
depletion as the mother is not allowed sufficient time to restore the adequate supply of nutrients
needed to have a successive successful pregnancy (Sharman, 2000; King, 2003). Conde-Agudelo, and
Belizan (2000) use a large cross-sectional dataset covering 456,889 women from 18 Latin American
countries and find that, compared to women giving birth at 27 to 32-month intervals, women
  14
       The adult lifetime risk of maternal mortality is defined as “the probability that a 15-year-old female will die
eventually from a maternal cause if she experiences throughout her lifetime the risks of maternal death and the
overall levels of fertility and mortality that are observed for a given population” (WHO, 2010, pp. 14). It is related to
both the mortality associated with a single pregnancy and the number of pregnancies a woman has in her reproductive
years (UNICEF, 2008).
  15
     Birth interval (or birth spacing) refers to the time interval (number of months) between births (i.e., the length
of time from birth to next conception plus nine months).


                                                           8
with intervals shorter than 15 months (i.e., less than six months from birth to conception of the
next child) are: 1.3 times less likely to avoid anemia; 1.7 times less likely to avoid third-trimester
bleeding; and 2.5 times less likely to survive childbirth.16 Therefore, short spacing is found to affect
maternal mortality both directly and indirectly through increased risk of anemia.


3         Data
The data used in this paper are from the India National Family Health Survey (NFHS) which
contains detailed information on women’s entire birth histories, birth intervals (at the child level),
health indicators (for children and their mothers), domestic violence, and other demographic and
socioeconomic characteristics of women and the households they live in. The NFHSs are repeated
cross-sectional surveys for a representative sample of women in India.17 The women sampled for
individual interviews in the NFHS are aged 15–49, and I consider the sample of all those who had
at least one child ever born. Moreover, I exclude women with 9 or more children ever born to
reduce heterogeneity due to women with extraordinarily high fertility (the 98th percentile of the
pooled sample of women).18 I pool the three available surveys, conducted in 1992/93 (NFHS-I),
1998/99 (NFHS-II), and 2005/06 (NFHS-III).
         Using the pooled NFHS birth history data, the sex ratio at birth (here defined as the fraction of
male births) is 0.519 for first births and 0.521 for all births. Among women who had their first birth
during the ten years before the survey the sex ratios for first and all births are 0.513 and 0.518,
respectively.19 , 20 Figures 1 and 2 show the sex ratio at birth (for all births) by birth year in the
pooled dataset and separately by survey year, respectively. Pooling different survey rounds allows
me to distinguish between age and cohort-specific effects. The figures show a decreasing trend of
    16
         see Conde-Agudelo, Rosas-Bermdez, and Kafury-Goeta (2007) for a review of medical studies on the relationship
between birth spacing and maternal health.
  17
     While NFHS-I and II only interviewed ever-married women, NFHS-III includes those never married. To ensure
comparability, I exclude never married women from the analysis. Since I only consider women with at least one child
ever born (the vast majority of whom are or have been married), the fraction of excluded women is quite small: 72
women, equivalent to 0.02% of all women interviewed in NFHS-III.
  18
     Total fertility rate (TFR) in the NFHS-III is 2.7, down from 3.4 in NFHS-I. Therefore, on average, an Indian
woman in NFHS-III will give birth to 2.7 children by the end of her childbearing years. The TFR is based on
age-specific fertility rates during the three years preceding the survey (IIPS and Macro International, 2007).
  19
     The biologically “normal” sex ratio at birth ranges from 1.03 to 1.06 (male to female births), corresponding to a
fraction of male births approximately in the range of 0.507 – 0.515 (Arnold, Kishor, and Roy, 2002).
   20
      Sex ratios have been found to be affected by several biological, environmental, and genetic factors (other than
behavioral factors). These include improvements in maternal health status (Bhat 2002a), mother’s malnutrition
(Mathews, Johnson, and Neil, 2008; Almond and Mazumder, 2011; Andersson and Bergstrom, 1998), prevalence
of Hepatitis B (Oster, 2005), birth order, timing of conception, hormonal conditions (James, 1987). Some of these
biological factors and how they might affect the findings of this paper are discussed in more detail in section 6.1.



                                                            9
the sex ratio which is common to all the survey rounds, independently of the cohort of birth of the
child, and not specific to a particular period.21 The most recent survey (NFHS-III) also shows an
increasing sex ratio at birth starting from the end of the 1980s onward, which corresponds to the
timing of the diffusion of ultrasound technologies (also consistent with the sex ratio in the Indian
Census). Figure 3 shows that the decreasing trend is specific to first births, while the sex ratio for
higher-order births is somewhat stable throughout the whole survey period and significantly higher
than that for first births in 1980 and after. This is further indicative of the use of sex selective
abortion, known to be much more common among higher order births. Indeed, pooled NFHS data
on parental gender preferences indicate that, albeit more than one third of ever-married women
want to have more sons than daughters (compared to only 2.5 percent who want more daughters
than sons), more than 80 percent of them want at least one daughter and about 86 percent want
at least one son.22 Moreover, 42 (14.5) percent desire at least two sons (daughters).
       Table 1 reports summary statistics for the pooled sample of ever-married women aged 15–49
by the sex of their first-born (refer to the data appendix for a description and availability of these
variables in the NFHSs).23 Panel (a) reports socio-demographic and fertility-related variables.
Most characteristics differ significantly between the sample of women with a first-born girl and a
first-born boy. In particular, the table shows that women with first-born girls are significantly more
likely to be educated, to have married and had their first child later in life, to have (and desire
to have) more children, to use contraception (and have undergone permanent sterilization)24 , to
have performed a prenatal ultrasound test, and to have had a shorter spacing between the first
  21
       Rosenblum (2013) uses the 2002-2004 Reproductive and Child Health Survey (RCH-II) and finds a similar pattern:
higher sex ratios for births occurred in the past, especially for lower birth orders. He tests for the exogeneity of the
sex of the first born, discusses potential recall or survival bias in the data (without attempting to test or disentangle
the two), and argues that the extent of the bias is small.
  22
     These figures are based on the NFHS question about the number of children women would like to have if they
could go back to the time before they started childbearing. NFHS-III indicates that average ideal family size among
ever-married women is 2.5 children (down from 2.9 in NFHS-I). Interviewed women were also asked the ideal sex
composition for these children: in NFHS-I they indicated 1.6 sons, 1.1 daughters, and 0.2 of either sex, while in
NFHS-III 1.2 sons, 0.9 daughters, and 0.4 of either sex.
 23
    All the estimates shown in this paper have been computed using sample weights provided by the NFHS. Given that
three surveys were conducted in different years, the sample weights used in the pooled sample have been multiplied
by the fraction of the total female population aged 15–49 in India (obtained from the United Nations Population
Division World Population Prospects: 2012 Revision, http : //esa.un.org/wpp/Excel − Data/population.htm) and
the number of women aged 15-49 interviewed in each survey round.
  24
     Knowledge of contraception is nearly universal among ever-married Indian women in NFHS-III: 99.2% of women
know one or more methods of contraception and current use is 55% (up from 98.9% and 45.3% in NFHS-II, respec-
tively). Female sterilization, with a prevalence of 37%, is a permanent contraception method (to limit the number of
births) that accounts for 67.4% of all contraceptives used. The highest adoption rate of female sterilization, is among
women with three children who have two sons. The most common spacing methods are condoms and the rhythm
method, each used by 5% of women (NFHS-III data).


                                                          10
and second birth. The differences found in the variables related to fertility behavior are a direct
consequence of pervasive son preference in India, while those in the education and demographic
variables (arguably predetermined to first birth) are indicative of selection among women with a
first-born girl. Panel (b) of table 1 reports summary statistics for health indicators and shows that,
compared to women with a first-born boy, those with a first-born girl are more likely to be anemic.
Panels (c) and (d) show that there are no significant differences between women by the sex of their
first-born child in terms of food consumption or violence perpetrated by husbands against them.
       Table 2 reports selected summary statistics for three subsamples of women (by the sex of their
first-born child): those who had their first birth less than a year before the time of the survey,
and the 15–29, 30–49 age groups. The idea is to understand the timing of the emergence of the
differences highlighted in table 1. If the sex of the first-born is random at birth but subsequently
affects women’s fertility behavior (as has been documented in places with son preference), there
should be no observed differences among women with first-born girls and boys close to the time
of their first birth. Differences should instead emerge and widen over time as women engage in
son-preferring fertility behavior.25 As conjectured, panel (a) shows that, except for the desire to
have more children (expected to be immediately affected by the sex of the first-born), all the other
variables are balanced between the two samples. Panel (b) considers women aged 15–29 (who are
in their most active reproductive years) and shows that, while there are no significant differences in
terms of predetermined variables (education, age at first birth and marriage), fertility behavior and
anemia status are significantly affected by the gender of the first-born. Panel (c) shows that most of
the observed differences in table 1 emerge among women aged 30–49. Women with a first-born girl
in this age group also have better educated husbands and show no differential incidence of anemia.
       This evidence confirms that women are similar at the time of first birth and develop differences
over time as a likely result of son-preferring fertility behavior. In fact, they appear to respond
to a first female birth by having substantially more children and shorter spacing, using contra-
ceptives less often, and exhibiting a higher probability of having had an ultrasound test and a
terminated pregnancy. This behavior increases their risk of mortality and morbidity (especially
after repeated pregnancies and unsafe abortions). It is therefore likely that women who engage
most in son-preferring fertility behavior and have lower access to safe abortion –typically women of
lower socioeconomic status– are more likely to die. This selection effect might explain the observed
differences (especially in the predetermined variables) among living women by the sex of their first
child as well as the decreasing sex ratio for first births. More evidence in support of this channel
will be shown in the next sections.
  25
       This approach is conceptually similar to Barcellos, Carvalho, and Lleras-Muney (2014) who study gender differ-
ences in parental inputs in India by restricting the analysis to families with children who are still young to account
for the effect of child gender on family size.



                                                          11
4         Nonparametric evidence
This section examines the age structure and health status of women by the sex of the first-born by
using kernel-weighted local polynomial regressions. The resulting smoothed values are displayed in
graphs with 95% confidence intervals. The age range of women considered in this section is 20–49.26


4.1         Share of women with a first-born girl

The nonparametric graphs in this section plot the share of women with a first-born girl by their age
at the time of the survey. This share is simply the inverse of the sex ratio for first births. Therefore,
rather than plotting the sex ratio by birth year of the child (done in section 3), the following graphs
show the age distribution of women with a first-born girl (due to pooling, these are independent of
cohort effects, except for non-overlapping years of the NFHSs).
         The left panel of figure 4 shows that the sex ratio for first births is in the biological range
for women below the age of 30 (including the confidence bands). However, the share of women
with first-born girls decreases almost monotonically for women older than 30, where it is below the
biological range. This is equivalent to saying that, among women with at least one child ever born,
the share of those who had a first-born girl is lower among older women, particularly among those
older than 30. The right panel shows that the same pattern is found in each round of the NFHSs
(though with larger confidence bands and more fluctuation likely due to smaller sample sizes when
using each survey separately). Interestingly, the upper graph in figure 5 shows that the decreasing
pattern is found only among women who did not complete any years of schooling, while the share
is rather stable for women with at least one year of education at all ages.27 Similar patterns are
found when using each NFHS round separately (see bottom two graphs in figure 5).28
         Considering education as a plausible proxy for socioeconomic status, this suggests that poorer
women suffer higher maternal and adult mortality. Having lower access to health services (and
in particular to prenatal sex diagnostic techniques in more recent decades), uneducated women
may rely more heavily on son-preferring fertility behavior to achieve the desired sex composition
of children and thus suffer the adverse consequences on their health and survival.


         State-wise variation. There is substantial state-wise variation in sex ratios at birth and excess
mortality in adulthood within India. Anderson and Ray (2012) find a distinctive pattern: gender
    26
         Women aged 15–19 are dropped because of very large confidence bands due to a small fraction of them who
already has had a birth –these represent 4.5% of the entire pooled sample.
  27
     In Milazzo (2012), I find similar patterns when using DHS data for Nigeria. Compared to India, this is a context
in which women are also found to engage in son-preferring fertility behavior (though not as strongly), and where the
lifetime risk of maternal mortality is higher.
   28
      Appendix figure A.1 also shows a decreasing pattern for women in rural areas (not found in urban areas).


                                                        12
bias at birth is highest in the North-West where excess female mortality among adult women is in
turn relatively low (the “Group 1” states), while North-Eastern states have low gender bias at birth
together with the highest excess female mortality in adulthood (the “Group 2” states). Southern
states, like Kerala, exhibit the lowest excess female mortality in India (for this reason, Kerala was
used as an alternative benchmark in their analysis). This evidence is confirmed by official statistics
on sex ratios (2011 Indian Census) and maternal mortality (Office of the Registrar General India,
2011).29 Two North-Western states, Punjab and Haryana, have the most male-biased sex ratio at
birth of all Indian states. At the same time, they have below-national-average maternal mortality
ratios. On the other hand, Assam and Bihar in the North-East have below-national-average (i.e.,
less male-biased) sex ratios at birth and are among the states with the highest maternal mortality
ratios in India.
      Figure 6 shows the share of women with first-born girls by age in Punjab, Haryana, Assam,
Bihar, and Kerala. Panel (a) shows that Punjab and Haryana exhibit a steady share of women
with first-born girls at all ages. Assam and Bihar, shown in panel (b), exhibit a strikingly different
pattern: the share of living women with a first-born girl is steeply decreasing with women’s age.
This is consistent with high prevalence of sex-selective abortions in the North-West (reflected in
skewed sex ratios at birth) and higher maternal mortality in the North-East. Finally, as expected,
Kerala shows a rather flat pattern, consistent with low excess female mortality across all age groups.
      While more research is warranted, this paper offers a possible explanation for the apparent
puzzle singled out in Anderson and Ray (2012). This is based on differential prevalence of sex
selective abortion and son-preferring fertility behavior (as the two main ways through which parents
can achieve the desired sex composition of children) across the states of India.


4.2      Health indicators

Turning to health indicators (available only in NFHS-II and III), figure 7 shows the incidence of
anemia by the sex of the first-born and women’s age at the time of the survey.30 The general age
pattern reflects the fact that anemia is typically higher during adolescence and the reproductive
years due to higher physiological demand for iron while pregnant and lactating (Sharman, 2000;
Mukuria, Aboulafia, and Themme, 2005). Notably, the figure shows that the incidence of anemia
is significantly higher among women with a first-born girl (compared to women with a first-born
boy) approximately up to age 30, while there is no differential incidence for older women.
      Intuitively, this result might be the consequence of son preference: women with first-born girls
tend to be pregnant (or breastfeeding) more often during their reproductive years than women who
have first-born boys. Although higher iron needs during pregnancy are accounted for in the NFHS
 29
      The sex ratio from Census data refers to all children aged 0 to 6.
 30
      For a description of how hemoglobin testing is conducted in the NFHS and DHS surveys refer to Sharman (2000).


                                                         13
definition of the hemoglobin cut-off value for anemic women31 , I replicate the same graph using
the subsamples of women who are not currently pregnant or breastfeeding (cut-off values are not
different for lactating women). Appendix figure A.2 shows that the patterns are found also in these
subsamples. This suggests that differential incidence of anemia between women with a first-born
girl or boy may be driven by short birth spacing (or past pregnancies).
         Figure 8 shows a graph for BMI. Overall, BMI increases with women’s age (within the range
of 19 to 22).32 There are no apparent differences in BMI by the sex of the first-born for women
below age 40. It is also worth noting that the BMI index excludes women who are pregnant at the
time of the survey and who gave birth less than three months before the survey (IIPS and Macro
International, 2007). Among older women, those with a girl as first-born child show a slightly higher
nutritional status.33 Lastly, figure 9 reports a graph for height. Height reflects nutritional status in
childhood and adolescence and therefore should be affected by fertility behavior to a lower extent
than other nutritional indicators that are not predetermined to first birth. Yet, mortality selection
might also entail higher survival possibilities for taller women who have been better nourished
during childhood (similarly to Bozzoli, Deaton, and Quintana-Domeque, 2009). Moreover, taller
women are more likely to be from a higher socioeconomic status and thus enjoy better access to
prenatal diagnostics. The figure shows that, as expected, there are no height differences among
younger women with a first-born girl or boy, while there is some weak evidence that older women
with first-born girls are taller (especially above age 45).


5         Empirical strategy and results
This section first discusses the identification assumption, then explores how the sex of the first-born
affects fertility behavior, and lastly examines the age structure and anemia status of women using
parametric analysis.


5.1         Identification assumption

As shown in table 2, women with a first-born girl or boy do not exhibit significant differences in
terms of observable predetermined characteristics close to the time of first birth or when they are
    31
         A woman is defined as being anemic if the measured hemoglobin count is of less than 12 grams per deciliter
(cut-off for all women) and less than 11 grams for pregnant women.
  32
     The BMI is defined as weight (kg) divided by height (m2 ). A cut-off point of 18.5 is used to define chronic energy
deficiency and a BMI of 25 or above indicates overweight (IIPS and Macro International, 2007).
  33
     While the association between fertility behavior and anemia status is widely documented in the medical literature,
BMI is not among the outcomes mentioned in a review of the literature on the effects of short spacing (Conde-Agudelo,
Rosas-Bermdez, and Kafury-Goeta, 2007). Evidence that mother’s malnutrition at conception might affect the sex
ratio is discussed in Section 6.1.



                                                          14
relatively young. The randomness of the sex of the first-born is in fact widely supported. First,
as previously noted, several studies document that sex-selective abortion is much more common
among higher-order births. Second, the vast majority of Indian parents want at least one daughter.
Third, data from the NFHS indicate that the sex ratio for first births during ten years before the
time of each survey is in the normal range. The sex ratio for first births after 1990 (timing of the
diffusion of ultrasound testing) is 0.514, which is in the biological range.34 It is in the normal range
even for educated women (known to practice more sex-selection): among educated (uneducated)
women the sex ratio for first births is 0.515 (0.513). Section 6.3 provides additional evidence that
sex-selection is not practiced at first-birth.
      Given possible selective mortality (most visible in the subsample of older women in panel (c)
of table 2), the empirical strategy relies on the assumption of conditional exogeneity of the sex
of the first-born child. All the regressions for women’s fertility behavior control for a vast set of
observable characteristics. The analysis of women’s health status additionally focuses on women
who recently had their first birth and are therefore not yet selected.
      It is important to note that selective mortality would lead to underestimate the effect of a
first-born girl on fertility. This is because women who did not survive (and therefore do not appear
in the data) are probably the ones who suffered the most the consequences of an ‘extreme’ fertility
behavior due to son preference (both because of poorer health and access to maternal care).


5.2      Mechanism: Fertility behavior and sex of the first-born child

5.2.1      Fertility regressions

Although most Indian women want more than two children, the sex of the first-born still affects the
fraction of male children they can have through their lifetime. In fact, as previously noted, more
than a third of women want more sons than daughters and more than 40 percent want at least
two sons. To examine desired and realized fertility as well as other outcomes that are likely to be
affected in contexts with son preference, I estimate the following regression under the assumption
of conditional exogeneity of the sex of the first-born.


                                              ∗
               yi,s,b,r = β1 f gi + β2 f gi       edui + β3 edui + γXi,s,b,r + αs + µb + δr +       i,s,b,r   (1)

      with woman i, resident in state s, born in year b, surveyed in round r. yi,s,b,r is the dependent
variable, alternatively a dummy for whether the woman currently reports the desire to have more
children, a dummy for whether she has been sterilized, whether she has undergone ultrasound
 34
      The sex ratio for all births occurred after 1990, including those of higher-order is 0.519.




                                                            15
testing, whether she has ever had an abortion, and the number of children ever born.35 f gi
indicates whether the first child ever born is a girl, edui is a dummy variable equal to one if the
                                                                                   ∗ edu tests
woman completed at least one year of education, zero if she has completed none, f gi    i

whether the effect is heterogeneous between educated and uneducated women, Xi,s,b,r is the set
of covariates including: age of the woman and her partner (and age squared), seven five-year age
groups, age at first marriage, age at first birth, whether the woman’s partner completed one or
more years of education, woman’s religion and caste, a wealth index, and a urban dummy.36 , 37 αs ,
γb , δr are state, birth year, and survey round fixed effects, respectively. All the regressions (except
that for the number of children ever born) also include the number of live births. Since most of the
younger women in the sample have not completed their fertility, I restrict the sample to women who
have been sterilized or who report they do not want more children when estimating the regression
for the number of children ever born. Regression 1 is estimated using a probit model for binary
outcomes, and a linear model for the other dependent variable.
       If women’s fertility behavior is affected by the sex of the first-born and this is due to son
preference, β1 is expected to be positive in the regressions for desired (and realized) fertility, ultra-
sound testing, and abortion, while β1 should be negative for the use of sterilization. In terms of
heterogeneous effects, predictions are as follows.38 Women’s desire for having more children after
the birth of a first girl should not differ much between educated or not as they both have strong
incentives to try to conceive again for a boy. All women are expected to seek sterilization when the
desired sex composition of children is reached. The use of sterilization is in fact widespread among
all women irrespective of their education (often women in rural areas have access to ‘sterilization
camps’). The use of ultrasound testing is instead part of the routine antenatal care for most edu-
cated women (especially those with high education: 74 percent of women with more than 10 years
of education in NFHS-III performed the test), but is only rarely undergone among the uneducated.
Given their high access to prenatal maternal care, educated women are not expected to resort more
to ultrasound testing in response to a first-born girl than the uneducated (since most educated do
  35
       The number of children ever born includes all live births to each woman, including dead children and children
living elsewhere. Compared to the number of surviving children, this is a more pertinent measure of fertility as it is
not affected by differential mortality potentially affected by son preference.
  36
     The caste and religion variables are from the woman dataset. Caste includes Scheduled Caste, and Scheduled
Tribe (other backward classes (OBC) and other castes are the omitted category). Religion includes Hindu, Sikh,
Muslims, Christian (Buddhist, Jain, and other religions are the omitted category).
 37
    The wealth index is a principal component index of services and durable goods owned by the household, including
electricity, radio, television, refrigerator, bicycle, motorcycle, and car.
   38
      Average values of the independent variables for educated and uneducated women are as follows: 21 and 24 percent
for the desire to want more children, 38 and 35 percent for female sterilization, 40 and 10 percent for ultrasound
testing, 21 and 18 percent for terminated pregnancy, and 2.9 and 4.2 children ever born (the latter calculated on the
sample of women who have been sterilized or do not want to have more children), respectively.



                                                          16
it irrespective of the sex of the child).39 In turn, the educated are expected to be more likely to
selectively abort after a first-born girl, consistent with existing evidence. The uneducated may still
practice abortion but, being generally poorer, it is plausible to think that they might seek illegal
abortion, probably underreported. The sign of the differential effect on the number of children is a
priori ambiguous. The uneducated have higher ideal and realized family size so, given the number
of children, they have higher chances to have a son, and the educated will have more children too
if they do not practice sex selection at low birth-order. At the same time, the uneducated can keep
having children if they have no sons, or have an abortion performed.
       Table 3 reports the results. The first column shows the unconditional estimates for each of the
outcomes studied. Column (1) shows that, compared to women with a first-born boy, women with
a first-born girl are 4.9 percentage points more likely to desire more children (the effect is significant
at 1% level). Column (2) shows that the effect is slightly higher at 5.1 percentage points (equivalent
to a 25 percent effect relative to the average for women with a first-born boy) after conditioning
for all the observables and fixed effects. Column (3) explores heterogeneous effects: women with at
least one year of education are on average less likely to say they want more children, but the effect of
a first-born girl is not statistically different than for uneducated women (who have a higher desired
number of children to start with). A first-born girl substantially decreases the probability that a
woman is sterilized (columns 4–6). The effect is of 6.8 percentage points (column (5), equivalent
to a 18 percent effect). The effect on sterilization does not appear to differ significantly for women
with education. Column (8) shows that women with a first-born girl are 2.5 percentage points more
likely to have had an ultrasound test for their most recent births. This effect is significant at 1%
level and equivalent to a 9.5 percent effect. Educated women are more likely to have undergone
ultrasound testing as part of their antenatal care. This reflects their higher access to health care
relative to poorer uneducated women. As expected, the increase in the probability of an ultrasound
test after a first-born girl does not differ between educated and uneducated women. As can be seen
in column (11), an abortion is 1.1 percentage points (significant at 1% level) more likely for women
with first-born girls (equivalent to a 5.8% percent effect). Column (12) shows that education is
positively associated with the probability of having ever had a terminated pregnancy, and that this
effect is stronger for women with a girl as first-born child (the estimate for the interaction term is
1.4 percentage points, significant at 1% level). Although uneducated women are also more likely
–thought to a smaller extent– to have had an abortion after a first-born girl, this result confirms
findings from the existing literature documenting that sex-selective abortion is more common among
the educated. A nonparametric plot of the likelihood to have ever had a terminated pregnancy by
sex of the first-born and age reveals that, among the uneducated, a first-born girl has an effect only
  39
       The use of ultrasound testing seems to be motivated by the early detection of abnormalities for first-born children,
and by sex-selection for higher-order births (Bath and Zavier, 2007).



                                                            17
after age 30 (while among the educated an effect is visible also among younger women) (appendix
figure A.3). This is consistent with poorer women selectively aborting a female fetus later in
life, probably when the costs of having an additional daughter become unsustainable (i.e., dowry
costs).40 However, as the variable for terminated pregnancy does not distinguish among the reasons
for termination (e.g., miscarriage, abortion, or stillbirth), it is important to consider this evidence
as only indicative of higher recourse to induced abortion for sex selection.41 Column (13) shows
that women with first-born girls unconditionally have 0.301 more children ever born, 0.295 after
including all the controls (both significant at 1% level). The latter estimate implies a 8.7 percent
effect. As expected, the effect is statistically different for educated women for whom the effect of
a first-born girl on fertility is attenuated. Appendix table A.1 additionally estimates the effect of
the sex of the first two or three children on fertility outcomes of women who had at least two or
three live births. Consistent with increasing pressure for giving birth to a male child, additional
daughters after the first substantially increase the effects on all the examined outcomes.
       Altogether, these results suggest that the sex of the first-born strongly affects women’s fertility
behavior, and that educated women tend to rely more on sex-selective abortion, while uneducated
women rely on son-preferring fertility behavior.


5.2.2       Birth spacing regressions

The NFHS reports the entire fertility history of each woman. I exploit information on the length
of the interval between successive births. The idea is to test whether women with a first-born girl
try to conceive the following child sooner than women with a first-born boy.
       In a first step, I estimate whether the spacing between first and second child is affected by the
sex of the first child, as well as whether the interval between second and third child is affected
by the sex of the second child (conditional on the first child being a girl). To do this, I use a
regression similar to equation 1, in which the dependent variable is either the number of months
or the probability of an interval shorter than 15 months. To evaluate the effect of the sex of the
first-born, I first restrict the sample to women with at least two children ever born (who report at
least one birth interval), and then to the sample of women with at least three children ever born
for the effect of the sex of the second child.
       The availability of birth histories allows a second empirical strategy that exploits the variation
in the length of the interval and the sex of the child within the reported history of each woman.
This is done with mother fixed effects. However, this methodology does not allow the estimation
  40
       It is also consistent with a higher probability of miscarriage for women engaging in son-preferring behavior.
  41
       Only NFHS-II provides some more details on whether the abortion was spontaneous or induced. Evidence suggests
that at least some of the abortions reported as spontaneous are instead induced (due to misreporting) (Arnold, Kishor
and Roy, 2002).



                                                          18
of the effect of the sex of a child at a specific birth order and identification requires restricting the
sample to all women with at least three children ever born. I estimate the following regression:



                            yi,j,(k−1,k) = β1 girli,j,k−1 +       γk bi,j,k + χj +   i,j,k−1                   (2)
                                                              k

       with child i, mother j , birth order k . yi,j,(k−1,k) is the time interval (between birth of child k − 1
and k ), expressed in number of months or as a dummy variable equal to one if the interval is shorter
than 15 months. girli,j,k−1 is a dummy equal to one if the sex of the child k − 1 is female. bi,j,k
are k dummies for each birth order. χj denote mother fixed effects. I exclude births of birth order
four and higher to evaluate the effect of the sex of earlier-born girls on spacing. This regression
is estimated using the entire sample, and the subsamples of uneducated and educated women. If
there is son preference, the birth interval is expected to be shorter (β1 < 0) after a girl is born
compared to a boy. This regression is estimated using a linear model for the number of months,
and a probit model for the probability of having an interval shorter than 15 months.
       A potential source of bias in the regressions for birth spacing is represented by the practice of
sex-selective abortion. This is because female fetuses are especially likely to be selectively aborted
after a first-born girl. It is important to note that this would generate downward biased estimates
of the (negative) effect of a first-born girl on the length of the birth interval since more time will
be needed to have a completed pregnancy following an abortion. This is especially the case for
educated women who are much more likely to have had a terminated pregnancy after a first-born
girl than the uneducated.42
       Table 4 shows the results of the regression without mother fixed effects (number of months
in columns (1)–(2), and probability of a short interval in columns (3)–(4)). Panel (a) shows the
effect of a first-born girl on the time to the next birth. Conditional on the covariates, women
with a first-born girl wait 0.8 months less compared to women with a first-born boy (significant
at 1% level, and equivalent to a 2.4 percent effect). Column (2) explores heterogeneous effects. A
first-born girl reduces the interval particularly for uneducated women, while among the educated
the effect is significantly attenuated. This is consistent with educated women with a first-born girl
aborting if the next fetus is detected to be a female. Columns (3)–(4) show that, while education
is on average significantly and negatively associated with the probability of a short birth intervals,
a first girl increases the probability of a short interval by 0.5 percentage points (significant at 1%
level, and equal to a large 5.7 percent effect), and this effect is not different between educated and
  42
       As a check, I added the variable for having ever had a terminated pregnancy as a control in the regressions
(without mother fixed effects) and the results for birth spacing are consistently stronger. However, as previously
noted, this variable probably underestimates the prevalence of induced abortions, due to under-reporting especially
if performed illegally.


                                                         19
uneducated women. The effect of a second-born girl on the birth interval conditional on having a
first-born girl is shown in panel (b). Again, the time interval is significantly reduced after the birth
of a second girl (column (1)), and now the effect is only found among uneducated women (column
(2)). Moreover, the birth of two consecutive girls increases the probability of a short interval by
0.8 percentage points (significant at 1% level) (column (3)). This effect implies a 8.7 percent effect.
Similar to the result in column (2), the effect on short spacing is almost doubled in magnitude (1.5
percentage points and significant at 1% level) for uneducated women (column (4)). The net effect
is instead negative for women with at least one year of education.
   Table 5 shows the estimates including fixed effects at the mother-level. The first column shows
the estimated effect of having a girl at first or second order on the length of the interval to next
birth. The coefficient is -0.60 months (significant at 1% level) for all women, -0.63 and -0.50 for
uneducated and educated women, respectively (columns (2) and (3)). Columns (4)–(6) show that
the birth of a girl increases the likelihood of a short interval by 0.5 percentage points (significant
at 1% level), which is equal to the estimate obtained without mother fixed effects (column (3) of
table 4). As expected and consistent with estimates in table 4, an effect (equal to 0.6 percentage
points) is found only in the subsample of uneducated women.
   This evidence is again consistent with educated women being more likely to turn to sex-selective
abortion while uneducated ones to son-preferring fertility behavior with associated health risks.


5.3     Outcomes: Age structure and women’s health outcomes

5.3.1    Age structure

To confirm the nonparametric evidence shown in figure 4, I estimate an ordered logit model in
which the dependent variable is a categorical variable with seven five-year age groups (from 15–19
to 45–49). The controls are the same as in regression 1. After estimating the ordered logit model, I
compute changes in the predicted outcome probabilities when the independent variable ‘first-born
girl’ changes from 0 to 1, with all the other independent variables set at their mean value. Changes
are reported with 95% confidence intervals computed with the delta method. Column (1) and (2) in
table 6 show the changes in the predicted probabilities and the 95% confidence bands, respectively.
The results confirm that the age distribution for women who had a first-born girl lies to the left
of the distribution for women with a first-born boy, conditional on the number of children and all
other covariates (set at their mean).


5.3.2    Health outcomes

Next, I estimate the effect of the sex of the first-born on anemia status and other health indicators
for women in different age groups with the following regression:


                                                 20
                                              ∗
               yi,s,b,r = β1 f gi + β2 f gi       over30i + γXi,s,b,r + αs + µb + δr +   i,s,b,r    (3)

   with woman i, resident in state s, born in year b, surveyed in round r. yi,s,b,r is a dummy
variable equal to one if the woman is anemic, zero otherwise. f gi indicates whether the first child
ever born is a girl, which is also interacted with a dummy equal to one if the woman is aged 30
or older (over30i ). The cutoff at age 30 is chosen based on the nonparametric evidence previously
presented (section 4) and the age at which the conditional age distribution for women with first-
born girls shifts to the left of the distribution of those with a first-born boy (table 6). αs , µb , δr
are state, cohort of birth, and survey round fixed effects, respectively. In addition to the set of
covariates and fixed effects as in regression 1, Xi,s,b,r also includes dummies for whether the woman
is currently pregnant or breastfeeding. These women are in fact more likely to be anemic and their
status might be correlated with the error term. Another potential concern is whether past health
(predetermined to first-birth) affects both the probability of having a first-born girl and current
anemia status (further discussed in the next section). For this reason, I also control for height,
a proxy for women’s health status during childhood. Regression 3 is estimated using a probit
model. Again, identification relies on the assumption that the sex of the first-born is exogenous
(uncorrelated with the error term) after conditioning for the observable characteristics.
   Table 7 shows the results. Column (1) shows the unconditional estimates. Women with a first-
born girl are 1.1 percentage points more likely to be anemic (significant at 1% level). Columns (2)-
(3) include most covariates as well as the controls for women’s current pregnancy and breastfeeding
status and the coefficient of a first-born girl is slighly reduced (as expected). Height is included in
column (4) and does not affect the estimated coefficient for a first-born girl. This allows me to rule
out the possibility that past health conditions are correlated with the sex ratio and with current
anemia status. Column (5) controls for the number of children ever born and the coefficient of
interest is slightly reduced. The patterns shown in figure 7 are consistent with the result in column
(6) indicating that a first-born girl significantly increases the incidence of anemia for women below
age 30 (the increase is 1.4 percentage points or a 2.5 percent effect), while this effect is significantly
reduced for older women. A further decrease in the incidence of anemia for women aged 45 and
older is suggested by estimates in column (7), though it is not significant. Columns (8)-(9) split
the sample into women by education and shows that the effect is found only among women with
no education. This is consistent with increased health risks associated with risky son-preferring
fertility behavior that is most common among them. The last two columns check whether the age
pattern of anemia is purely reflecting higher fertility. The estimates of the interactions between the
number of children ever born and the older age groups show that, as expected, a higher number
of live births significanlty increases the prevalence of anemia among younger women. However, as

                                                        21
opposed to the effect of a first-born girl, this effect is not offset among those aged 30 and older.
This suggests that anemia persists among women with more children (irrespective of their gender)
over the years, while the impact of a first-born girl is more complex in that it also leads to ‘riskier’
pregnancies that further increase their risk of mortality (and selection).
    To check how the sex of the first-born affects the intensity of anemia, I estimate an ordered
logit model in which the dependent variable is a categorical variable with four ordered categories:
severely anemic, moderately anemic, mildly anemic, and not anemic. Table 8 shows the changes
in predicted probabilities computed using the estimates for the entire sample of women, and the
subsample of younger (aged 15–29) and older women (aged 30–49). It can be seen that, conditional
on the covariates, a first-born girl is associated with a significant increase in the probability of
suffering from any level of anemia, and a decrease in the probability of not being anemic (implied
percent effects indicate that women aged 15–29 are 4.3, 3.3, and 1.1 more likely to be severely,
moderately and mildly anemic, respectively).
    Finally, table 9 considers other indicators of women’s nutritional status, including BMI (and
undernourishment), and height (and shortness) as the dependent variables of regression 3. The
estimates for BMI and chronic energy deficiency show a similar pattern: women above the age of
30 exhibit significantly better nutritional conditions, controlling for height. The results for height
are not significant, but in the same direction as the other indicators (women 45 and older with a
first-born girl appear slightly taller).
    In sum, these estimates support the hypothesis that a first-born girl drives women into a fer-
tility behavior that significantly jeopardizes their health and can have fatal effects during their
reproductive years and cause long-term disabilities. They also support the hypothesis of selective
mortality in light of better health conditions of living older women with first-born girls.


6     Alternative interpretations and robustness
Next, I turn to the plausibility of four alternative interpretations of the results.


6.1    Biological differences

There is evidence that maternal diet and poor nutrition around the time of conception are associated
with a female birth (Mathews, Johnson, and Neil, 2008; Almond and Mazumder, 2011). This is
because male fetuses are more fragile (Waldron, 1983; Kraemer, 2000) and susceptible to death in
utero than females. Therefore selective mortality may be the result of biological and genetic factors
rather than behavioral. To rule out this possibility, I perform several checks.
    First, as previously noted, all the regressions for health outcomes control for height, an indicator
of nutritional status in childhood. The estimates with and without the inclusion of height are


                                                  22
similar, indicating that past health does not seem to be associated with the sex of the first-born.43
       Second, this interpretation would not be compatible with a pattern in which differential inci-
dence of anemia between women with a first-born girl or boy is not present at the time of birth and
arises only some time after first birth. To understand the timing of the emergence of differences
in anemia status, I plot the prevalence of anemia among women by the sex of their first-born child
and the time since their first birth (using Kernel-weighted local polynomial smoothing). Figure 10
shows that there is no differential incidence of anemia at the time of first birth, and that women with
a first-born girl start developing anemia approximately 16 months after the birth of their daughter
and that differences increase over time.44 I also estimate a probit regression for the probability of
being anemic on ‘first-born girl’ and its interaction with the interval of time since birth (controlling
for height and other covariates). Column (1) of table 10 shows that from the time of birth until the
11th month there is no differential anemia status, while differences seem to develop gradually over
time, though not significantly. As expected, differential incidence of anemia develops much faster
among uneducated women, for which the increase becomes significant about three years after the
birth of the first child. No similar pattern is found for educated women (columns (2)–(3)).
       A third check explores whether there is differential incidence of anemia at the time of each birth
from birth order 1 to 3. This is to make sure that anemia status does not affect the sex of the
child at any birth. I run a probit regression for the probability of a female birth at birth order 1
to 3 on whether the mother is anemic (and the different levels of anemia severity) restricting the
dataset to women who gave birth less than a year before the time of the survey. Table 11 shows
no association between anemia status and the sex of the child at any birth order.45
       None of these results is consistent with explanations based on biological differences.


6.2       Reporting bias

Another concern is that, as they are based on self-reported retrospective information, birth histories
in the NFHS might suffer from misreporting and recall bias especially in relation to births (and
deaths) occurred many years before the time of the survey (Smith, 1994; Byass et al., 2007).
  43
       The results of the regressions for fertility behavior are robust to the inclusion of height (including height implies
restricting the sample to second and third surveys in which measurements were taken). Results shown in table A.2.
  44
     The timing of emergence of anemia is consistent with higher iron requirements particularly in the third trimester
of pregnancy. Iron stores are especially depleted for women who had a short interval. Therefore, women with a
first-born girl (found to be more likely to have a short interval) appear to develop anemia towards the end of their
second pregnancy and these anemia differences seem to persist over time.
  45
     No association (from birth order 1 to 3) is found even when using other nutritional indicators such as BMI (and
the two cutoffs for underweight and obesity) and shortness. This is in contrast with Andersson and Bergstrom (1998)
who find that short maternal stature and obesity are independently related to low sex ratio at birth using data for
684 women from the Central African Republic.




                                                             23
However, to affect the findings, recall bias would have to be systematically gender-biased and
specific to first-births. In societies with strong son preference women might deliberately under-
report female births (even though there is no reason they should misreport those that occurred
at first birth only).46 If this is the case, age at first birth should be negatively associated with a
first female birth. This is because women who do not report their first-born daughters and instead
report a later born boy will appear as if they had a first-born boy, but later. I test for this possibility
by estimating a probit model for the probability of a female at first birth regressed on age at first
birth and other controls. Results instead indicate that age at first birth positively and significantly
predicts a first female birth (marginal effect of 0.001, with a standard error of 0.000, equally for all
women and those aged 30 and older separately).47 This result is not consistent with gender-biased
recall bias but instead supports selective mortality.
       As a further check, it is useful to note that gender-biased recall bias (arguably motivated by
strong preferences for male children), if it exists, should not be decreasing over time in line with
nondecreasing son preference in India (if anything, Census data report increasing male-biased sex-
ratios at birth). Since both selective mortality and gender-biased recall bias imply that women
with a first-born girl appear younger on average (older women might have died or be more likely to
under-report a first-born girl, respectively), I check the age distribution of women with a first-born
girl across the three NFHS rounds. Specifically, I regress women’s age at the time of the survey
on the variable ‘first-born girl’ and its interaction with the survey round dummies. The dependent
variable is expressed in terms of seven age groups (in this case the regression is an ordered logit
model), or as age in years (estimated with a linear model). As can be seen in column (1) table 12,
women with a first-born girl are on average younger than those with a first-born boy in the first
wave of the NFHS and this effect is attenuated for women in the last two survey rounds. Column
(2) shows a similar pattern, although it is not significant. This pattern is not consistent with
sex-selective recall bias but instead with the reduction in maternal mortality that has been taking
place over the last decades in India.


6.3       Selective mortality or selective abortion?

One could argue that figure 5 can be interpreted as evidence of selective abortion of female children
(at first pregnancy) among older and uneducated women. However, as discussed in the previous
sections, there is vast evidence in the literature that sex selection is instead common at higher-
  46
       Gender-biased recall bias is not compatible with the state-wise patterns presented in section 4.1. If women do
not want to report a first female birth because of son preference, then the decreasing share of women with a first-born
girl as a function of women’s age should also be found in states with the highest sex ratios, i.e. Punjab and Haryana.
  47
     Covariates include state fixed effects, urban dummy, birth year fixed effects, 7 five-year age groups dummies,
survey round fixed effects, whether she and her partner have completed one or more years of education, a durables
index, religion and caste. Result available upon request.


                                                            24
order births and among women with higher education and from more prosperous families (who
have access to the technologies for sex detection of the fetus).
       As an additional check, figure 11 plots the sex ratio for first and higher-order births by birth
year of the child and women’s education. Panel (a) shows that, for educated women, the sex ratio
for first births is constant over time (and in the normal range). As expected, the sex ratio for
higher-order births shows a steep increase after 1990 most likely due to the spread of prenatal sex
diagnostic technologies. This evidence clearly suggests that sex selective abortion is not practiced at
first-birth among the educated. Among the uneducated (panel b), it is the sex ratio for first births
only that is decreasing over time (while it is decreasing only slightly for higher order births).48 This
pattern cannot be the result of sex-selective abortion as the period in which the sex ratio for first
birth is found to be abnormally high is prior to the diffusion of ultrasound testing. It is instead
consistent with selective mortality due to the association between sex of the first-born and risky
fertility behavior or unsafe abortion.


6.4       Direct punishment (mistreatment)

There is evidence that domestic violence is associated with malnutrition (after controlling for so-
cioeconomic variables) potentially through withholding of food or psychological stress (Ackerson
and Subramanian, 2008). This section tests whether women with a first-born girl are more likely
to suffer overt discrimination in the allocation of food (or nutritional supplements) or through do-
mestic violence and discusses their possible contribution to selective mortality.


       Food consumption and iron supplementation. To test whether women are ‘punished’
for having given birth to a girl through withholding of food, I estimate a probit model for the
probability of consuming certain types of food at least once a week on the sex of the first-born.
The dependent variables are dummies based on whether women self-report consuming specific food
items daily or weekly. These include milk, pulses, green vegetables, fruits, and eggs or meat or
fish. The independent variables of interest are ‘first-born girl’ and its interaction with the dummy
for education level. All the regressions include height, current pregnancy or breastfeeding status as
well as the standard set of covariates. The regression is estimated using three samples: women who
had their first birth less than a year before the time of the survey, women aged 15–29, and 30–49.
       To explain the anemia pattern, lower consumption of nutritious food (in particular eggs/meat/fish
and green vegetables, that are rich in iron) should be found among younger women with a first-born
girl, especially among the uneducated. Table 13 shows that there is no differential consumption of
  48
       The pattern of the sex ratio for higher order births among the uneducated might be explained partly by selective
mortality of women with female children at low birth order back in time, and to the practice of sex selective abortion
in the period after 1990 (although much less common than among the educated– compare panel (a) and (b)).


                                                           25
food between younger women with a first-born girl or boy (also by education level) (panel (a) and
(b)). Among older women, those with a first-born girl appear to have a slightly higher consumption
of milk, green vegetables, and fruits (panel (b)). This can be partly explained by selective mortality.
   Table 14 further checks whether women are differentially likely to receive iron and folic acid
(IFA) supplements during pregnancy. It can be seen that a first-born girl is not associated with
having received more supplements during the first (columns (1)-(2)) or second (columns (3)-(4))
pregnancies. The results also indicate that consumption of food or iron supplementation does not
increase after the birth of a girl to compensate for higher nutritional needs.


   Domestic violence. Next, I test whether self-reported experience of physical, emotional or
sexual violence perpetrated by the husband (collected in NFHS-III) differs between women by the
sex of their first-born. Table 15 presents the results. Panel (a) considers the subsample of women
who had their first birth less than a year before the time of the survey. As can be seen in columns
(1)-(2), women with a first-born girl do not appear to be more likely to have suffered any forms
of physical violence. It is only when the variable for physical violence is disaggregated between
severe and less severe that an effect is visible. Columns (4) in fact shows that among uneducated
women, those with a first-born girl are 3.6 percentage points more likely to have been the victims
of severe violence (including strangling or burning, or threatening with a gun or knife). This effect
is in accord with Bloch and Rao (2002) who find that the number of male children reduces the
probability of violence consistent with increased husband’s satisfaction with the marriage in a male-
dominated society that greatly values males. The effect on severe violence is specific to the period
immediately after the birth of the child (11 months or less) seemingly as a form of immediate
punishment inflicted on women (panel (b) and (c) indicate no effect on women aged 15–29 and 30–
49). It is also specific to uneducated women (who are generally more likely to experience spousal
violence). No effect is found for the other forms of violence.
   Domestic violence thus appears to be another channel (complementary to or potentially exacer-
bating fertility behavior) that contributes to explaining excess mortality of women with first-born
girls around the time of the first-birth. As for extreme fertility behavior, this is also motivated by
strong son preference. However, even though it is consistent with selective mortality (the weakest
are more likely die), the fact that it is only specific to the time of birth does not reflect the dif-
ferential age patterns of anemia status (higher among women with a first girl during their entire
reproductive years or below age 30, as shown in figure 7). The anemia patterns are instead more
consistent with the explanation based on son-preferring fertility behavior.




                                                  26
7         Implied effect on women’s excess mortality
Next, I turn to calculating the implied impact of son preference on mortality among adult women
from the observed sex ratios for first births in the data.49 The observed sex ratio (so ) can be
                              sn
expressed as: so =         1−m(1−sn ) ;   where sn is the biologically normal sex ratio, and m is the mortality
rate among women with first-born girls due to son preference (i.e., with no son preference: m = 0
                                            so −sn
and so = sn ). Therefore, m =              so (1−sn ) .   Table 16 reports the observed sex ratios by age group in
the entire sample and the subsample of uneducated women. Figure 12 shows the implied values of
m (for each age group) among women with first-born girls assuming a normal sex ratio of 0.514.
As expected, the inferred mortality rates increase with age, ranging from 2.2 to 8.4% for women
aged 30 to 49 (3.7 to 13% among uneducated women).


8         Conclusions
This paper examines the phenomenon of excess mortality among women of reproductive and adult
ages in India. It is the first to show that strong preferences for male children are partly driving
female mortality in adulthood. In settings with son preference, there are two main ways for parents
to ensure the desired sex composition of children. They can have repeated and closely spaced
pregnancies until the ideal number of sons has been reached, a behavior medically known to increase
the risk of maternal mortality and morbidity. Parents can also selectively abort female fetuses.
In India, the latter appears to be more common among well-off, educated women, and the former
among the poor and uneducated. Therefore, differential access to prenatal care as well as differences
in initial health status between women from different socioeconomic strata can lead to differential
mortality due to son preference.
         I explore this issue by using three rounds of the National Family Health Survey for India.
The main results can be summarized as follows. First, there are no systematic differences among
women with a first-born girl or boy close to the time of birth. Second, women with first-born
daughters are more likely to desire more children, to have performed an ultrasound test, to have
had a terminated pregnancy, to have given birth to more children, and less likely to be sterilized.
The effect on abortion is significantly larger for educated women (who also exhibit an attenuated
effect on fertility), which confirms existing evidence that sex selection is more common among them.
Third, women with a first-born girl are more likely to develop anemia more than a year after birth.
Fourth, differential incidence of anemia disappears in the subsample of older women. This age
pattern of anemia is stronger for women with no education. Fifth, the share of living women with
    49
         This approach is adapted from Abrevaya (2009) who estimates the prevalence of sex-selective abortions from the
observed sex ratios.



                                                                27
a first-born girl decreases with the women’s age at the time of the survey, and this is again specific
to uneducated women. These results are consistent with a model in which son preference induces
women into a fertility behavior that increases their risk of death and morbidity. Women with first-
born daughters, especially the poor and uneducated among them, are in fact more likely to develop
anemia and appear to suffer higher maternal and adult mortality. Higher mortality can also be
partly attributed to increased domestic violence close to the time of birth for these women. The
findings also indicate that neither women’s food consumption nor iron supplementation is affected
by the sex of their first-born. This can inform targeted interventions aiming to compensate higher
nutritional needs of women with first-born girls.
   Altogether, the findings of this paper vividly emphasize how vulnerable women are in certain
contexts and help to understand the factors exacerbating the burden of maternal mortality. Al-
though progress in reducing maternal mortality has been made over the last decades, many women
continue not to receive adequate maternal care, especially among the poorest. To ensure further
progress, it is crucial to guarantee access and availability of maternal care services to all strata of
the population. This is of foremost importance in the context of the fifth Millennium Development
Goal that aims to reduce by three-quarters the maternal mortality ratio and achieve universal
access to reproductive health care by 2015.
   Finally, the paper highlights once again how deeply rooted son preference is in Indian society
and its potential for hindering safe motherhood and better child health.




                                                  28
                                              Data appendix

    Demographic, fertility and education variables. “eduyrs ” is the number of completed years of
education. “eduyrs>0 ” is a dummy equal to one if the woman completed at least one year of education,
zero otherwise. “wants more children ” is a dummy equal to one if the woman wants more children at the
time of the survey, zero otherwise. “sterilized ” is a dummy equal to one if the woman has undergone female
sterilization, zero otherwise (or if she is using another method of contraception). “ultrasound ” is a dummy
equal to one if the woman has undergone an ultrasound test (zero otherwise), asked only with reference to
the two most recent births in the last three years preceding the survey (NFHS 1998), and to any pregnancy
in the last five years preceding the survey (NFHS 2005) (not asked in NFHS 1992). “ever had terminated
pregnancy ” is a dummy equal to one if the woman ever had a pregnancy that terminated in a miscarriage,
abortion, or still birth, zero otherwise. “spacing ” refers to the time interval between first and second birth
and it is therefore available only for women who had at least two births.


    Health indicators. “anemic ” is a dummy equal to one if the measured hemoglobin count is less than
12 grams per deciliter (less than 11 grams for pregnant women). “mild ” anemia refers to hemoglobin count
between 10.0 and 11.9 grams per deciliter (10.0 and 10.9 for pregnant women). “moderate ” anemia refers to
hemoglobin count between 7.0 and 9.9 grams per deciliter. “severe ” anemia refers to hemoglobin count less
than 7.0 grams per deciliter. Appropriate adjustments in these cutoff points were made for women living at
altitudes above 1,000 meters and women who smoke (NFHS data). Hemoglobin measurement is available for
all women in NFHS 1998 and 2005 (not available in NFHS 1992). The body mass index (BMI) is calculated
as weight in kilograms divided by the square of height in meters and it is not available for currently pregnant
women and those who gave birth in the two months preceding the survey. A value of the BMI lower than 18.5
is used to define chronic energy deficiency. Height measurement is in centimeters and women whose height is
below 145 cm are considered to be of short stature. BMI and height are available only in NFHS 1998 and 2005.


    Spousal violence. Spousal violence variables are based on a module of NFHS 2005 that collected de-
tailed information on physical, sexual, and emotional violence perpetrated by husbands against their wives
(based on women’s self-report). “any severe violence ” includes whether the spouse ever tried to strangle or
burn, or ever threatened her with knife or gun. “any less severe violence ” includes whether the spouse ever
pushed, slapped, punched, kicked or dragged her. “any emotional violence ” includes whether the husband
ever said something to humiliate her in front of others, or threatened to hurt someone close to her, or insulted
her. “any sexual violence ” includes whether the husband forced her to perform any unwanted sexual acts.
Domestic violence variables available for all married women in NFHS 2005.


    Food consumption. Food consumption variables are based on NFHS questions on frequency of con-
sumption of certain food groups. The variables are dummies equal to one if the woman consumes the
indicated type of food at least once a week. Food consumption is available for all women in NFHS 1998 and
2005 (not available in NFHS 1992).




                                                      29
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                                                   33
Figures

              Figure 1: Sex ratio (% male births), by cohort of birth




      Figure 2: Sex ratio (% male births), by cohort of birth and NFHS round




      Figure 3: Sex ratio (% male births), by cohort of birth and birth order




                                        34
Figure 4: Share of women with a first-born girl by age and NFHS round




 Figure 5: Share of women with a first-born girl by age and education




                                 35
     Figure 6: Share of women with a first-born girl by age in selected Indian states


a) group 1 states: highest proportion missing at birth




b) group 2 states: highest proportion of missing women in India & the majority missing at adult ages (15+)




 c) benchmark: lowest proportion of missing women in India & lowest female excess mortality at all ages




                                                    36
           Figure 7: Share of anemic women by age and sex of the first-born child




            Figure 8: Body mass index (BMI) by age and sex of the first-born child




Notes : The BMI index excludes women who were pregnant at the time of the survey or women who had given birth during
the two months preceding the survey (NFHS).


                      Figure 9: Height by age and sex of the first-born child




                                                         37
          Figure 10: Share of anemic women by length of time since first birth




Figure 11: Sex ratio (% male births), by cohort of birth, birth order, and education level




    Figure 12: Inferred percent of missing women with first-born girls by age group




                                           38
Tables

               Table 1: Summary statistics for all ever-married women and by sex of the first-born child
                                                                  all women   first-born girl   first-born boy     diff         se       Obs

          a) Demographic, fertility and education variables
          eduyrs>0                                                 0.453          0.458            0.449        0.009***   (0.002)   239826
          husband eduyrs>0 (dummy)                                 0.698          0.699            0.697          0.002    (0.002)   238745
          eduyrs                                                   3.512          3.538            3.489        0.049**    (0.022)   239826
          husband eduyrs                                           6.087          6.102            6.073          0.029    (0.026)   238745
          age                                                      31.930        31.831           32.021       -0.190***   (0.042)   240112
          age at first birth                                        18.923        18.945           18.902        0.043**    (0.017)   240112
          age at first marriage                                     16.790        16.807           16.774        0.033**    (0.016)   240072
          wants more children                                      0.227          0.252            0.204        0.048***   (0.002)   230795
          # children ever born                                     3.203          3.300            3.114        0.186***   (0.009)   240112
          sterilized                                               0.361          0.336            0.385       -0.049***   (0.002)   240112
          currently use any contraceptives                         0.520          0.497            0.543       -0.046***   (0.003)   240112
          ultrasound                                               0.268          0.275            0.262        0.013***   (0.004)   60112
          ever had terminated pregnancy                            0.194          0.199            0.189        0.010***   (0.002)   240093
          spacing (bw first and second birth) (# months)            32.636        32.193           33.051       -0.858***   (0.105)   198208
          short spacing (bw first and second birth) (<15 months)    0.090          0.093            0.088        0.005***   (0.002)   198208
          currently pregnant                                       0.056          0.061            0.051        0.010***   (0.001)   240112
          currently breastfeeding                                  0.301          0.319            0.285        0.034***   (0.002)   240112

          b) Health indicators
          anemic                                                    0.541         0.547           0.536        0.011***    (0.003)   147427
          mildly anemic                                             0.372         0.375           0.370         0.005*     (0.003)   147427
          moderately anemic                                         0.151         0.154           0.148        0.006***    (0.002)   147427
          severely anemic                                           0.017         0.017           0.017         -0.000     (0.001)   147427
          height                                                   151.527       151.546         151.508         0.038     (0.037)   153864
          height<145cm                                              0.123         0.123           0.123         -0.000     (0.002)   153864
          body mass index (BMI)                                     20.581       20.593          20.570          0.023     (0.025)   144590
          BMI<18.5                                                  0.346         0.346           0.346         -0.000     (0.003)   144590

          c) Food consumption (at least once a week)
          consumes milk                                             0.550         0.549            0.552        -0.002     (0.003)   162661
          consumes pulses                                           0.887         0.887            0.886         0.000     (0.002)   162655
          consumes green vegetables                                 0.891         0.892            0.891         0.001     (0.002)   162642
          consumes fruits                                           0.354         0.355            0.354         0.001     (0.003)   162573
          consumes eggs or meat or fish                              0.413         0.412            0.413        -0.001     (0.003)   162628

          d) Spousal violence
          any severe physical violence                              0.124         0.126            0.124         0.002     (0.004)   62564
          any less severe physical violence                         0.365         0.365            0.366        -0.001     (0.005)   62564
          any emotional violence                                    0.162         0.164            0.159         0.005     (0.004)   62569
          any sexual violence                                       0.100         0.102            0.098         0.004     (0.003)   62569

Demographic, fertility and education variables. “eduyrs” is the number of completed years of education. “eduyrs>0” is a dummy equal to
one if the woman completed at least one year of education, zero otherwise. “wants more children” is a dummy equal to one if the woman wants
more children at the time of the survey, zero otherwise. “sterilized” is a dummy equal to one if the mother has undergone female sterilization,
zero otherwise (or if she is using another method of contraception). “ultrasound” is a dummy equal to one if the woman has undergone
ultrasound test (zero otherwise), asked only with reference to the two most recent births in the last three years preceding the survey (NFHS
1998), and to any pregnancy in the last five years preceding the survey (NFHS 2005) (not asked in NFHS 1992). “ever had terminated
pregnancy” is a dummy equal to one if the woman ever had a pregnancy that terminated in a miscarriage, abortion, or still birth, zero otherwise.
Spacing refers to the time interval between first and second birth and it is therefore available only for women who had at least two births.
Health indicators. “anemic” is a dummy equal to one if the measured hemoglobin count is less than 12 grams per deciliter (less than 11 grams
for pregnant women). “mild” anemia refers to hemoglobin count between 10.0 and 11.9 grams per deciliter (10.0 and 10.9 for pregnant women).
“moderate” anemia refers to hemoglobin count between 7.0 and 9.9 grams per deciliter. “severe” anemia refers to hemoglobin count less than 7.0
grams per deciliter. Appropriate adjustments in these cutoff points were made for women living at altitudes above 1,000 meters and women who
smoke (NFHS data). Hemoglobin measurement is available for all women in NFHS 1998 and 2005 (not available in NFHS 1992). The body mass
index (BMI) is calculated as weight in kilograms divided by the square of height in meters and it is not available for currently pregnant women
and those who gave birth in the two months preceding the survey. A value of the BMI lower than 18.5 is used to define chronic energy deficiency.
Height measurement is in centimeters and women whose height is below 145 cm are considered to be of short stature. BMI and height are
available only in NFHS 1998 and 2005. Spousal violence. Spousal violence variables are based on a module of NFHS 2005 that collected
detailed information on physical, sexual, and emotional violence perpetrated by husbands against their wives (based on women’s self-report).
“any severe violence” includes whether the spouse ever tried to strangle or burn, or ever threatened her with knife or gun. “any less severe
violence” includes whether the spouse ever pushed, slapped, punched, kicked or dragged her. “any emotional violence” includes whether the
husband ever said something to humiliate her in front of others, or threatened to hurt someone close to her, or insulted her. “any sexual
violence” includes whether the husband forced her to perform any unwanted sexual acts. Domestic violence variables available for all married
women in NFHS 2005. Food consumption. Food consumption variables are based on NFHS questions on frequency of consumption of certain
food groups. The variables are dummies equal to one if the woman consumes the indicated type of food at least once a week. Food consumption
is available for all women in NFHS 1998 and 2005 (not available in NFHS 1992). Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at
1%, 5% and 10% levels, respectively.




                                                                       39
 Table 2: Selected summary statistics by sex of the first-born child, time since first birth, and age group
                          a) Less than a year after first birth
                                                             first-born girl   first-born boy      diff         se      Obs
                          eduyrs>0                                0.604            0.593        0.011     (0.012)   10212
                          husband eduyrs>0                        0.785            0.791       -0.006     (0.010)   10169
                          eduyrs                                  5.186            5.133        0.053     (0.122)   10212
                          husband eduyrs                          7.419            7.382        0.037     (0.124)   10169
                          age                                    20.694           20.683        0.011     (0.083)   10217
                          age at first birth                      20.231           20.215        0.016     (0.083)   10217
                          age at first marriage                   18.014           18.016       -0.002     (0.080)   10217
                          wants more children                    0.894             0.861      0.033***    (0.008)   10126
                          # children ever born                   1.008             1.009       -0.001     (0.002)   10217
                          sterilized                              0.001            0.001        0.000     (0.001)   10217
                          ultrasound                               0.37            0.356        0.014     (0.015)    5979
                          ever had terminated pregnancy           0.101            0.093        0.008     (0.007)   10216
                          anemic                                  0.584             0.58        0.004     (0.016)    5958
                          bmi                                    19.576           19.644       -0.068     (0.103)   4747
                          height                                151.578          151.429        0.149     (0.187)    6252

                          b) Women aged 15–29
                                                             first-born girl   first-born boy       diff        se      Obs
                          eduyrs>0                                0.476             0.48        -0.004    (0.004)   97834
                          husband eduyrs>0                        0.706            0.708        -0.002    (0.004)   97389
                          eduyrs                                  3.672            3.721        -0.049    (0.034)   97834
                          husband eduyrs                          6.167            6.205        -0.038    (0.039)   97389
                          age                                    24.014           23.998         0.016    (0.026)   97958
                          age at first birth                      18.287           18.276         0.011    (0.022)   97958
                          age at first marriage                    16.48           16.485        -0.005    (0.021)   97947
                          wants more children                    0.476             0.404       0.072***   (0.004)   96053
                          # children ever born                   2.382             2.255       0.127***   (0.010)   97958
                          sterilized                              0.195            0.252      -0.057***   (0.003)   97958
                          ultrasound                               0.28             0.27        0.010*    (0.005)   43087
                          ever had terminated pregnancy           0.166            0.158       0.008***   (0.003)   97951
                          anemic                                  0.575            0.556       0.019***   (0.005)   57747
                          bmi                                    19.604           19.627        -0.023    (0.032)   52790
                          height                                151.444          151.437         0.007    (0.057)   60368

                          c) Women aged 30–49
                                                             first-born girl   first-born boy       diff        se       Obs
                          eduyrs>0                                0.444            0.426       0.018***   (0.003)   141992
                          husband eduyrs>0                        0.693            0.688        0.005*    (0.003)   141356
                          eduyrs                                  3.435            3.316       0.119***   (0.029)   141992
                          husband eduyrs                          6.053            5.976       0.077**    (0.034)   141356
                          age                                    37.876           37.991      -0.115***   (0.037)   142154
                          age at first birth                      19.456           19.369       0.087***   (0.025)   142154
                          age at first marriage                   17.061           16.989      0.072***    (0.022)   142125
                          wants more children                    0.072              0.05       0.022***   (0.002)   134742
                          # children ever born                   4.008             3.752       0.256***   (0.012)   142154
                          sterilized                              0.445            0.484      -0.039***   (0.003)   142154
                          ultrasound                              0.262            0.236       0.026***   (0.008)    17025
                          ever had terminated pregnancy           0.225            0.213       0.012***   (0.003)   142142
                          anemic                                  0.526            0.521         0.005    (0.004)    89680
                          bmi                                    21.229           21.172         0.057    (0.035)    91800
                          height                                151.622          151.559         0.063    (0.048)    93496

Demographic, fertility and education variables. “eduyrs” is the number of completed years of education. “eduyrs>0” is a dummy equal to
one if the woman completed at least one year of education, zero otherwise. “wants more children” is a dummy equal to one if the woman wants
more children at the time of the survey, zero otherwise. “sterilized” is a dummy equal to one if the mother has undergone female sterilization,
zero otherwise (or if she is using another method of contraception). “ultrasound” is a dummy equal to one if the mother has undergone
ultrasound test (zero otherwise), asked only with reference to the two most recent births in the last three years preceding the survey (NFHS
1998), and to any pregnancy in the last five years preceding the survey (NFHS 2005) (not asked in NFHS 1992). “ever had terminated
pregnancy” is a dummy equal to one if the mother ever had a pregnancy that terminated in a miscarriage, abortion, or still birth, zero otherwise.
Health indicators. “anemic” is a dummy equal to one if the measured hemoglobin count is less than 12 grams per deciliter (less than 11 grams
for pregnant women). Appropriate adjustments in these cutoff points were made for women living at altitudes above 1,000 meters and women
who smoke (NFHS data). Hemoglobin measurement is available for all women in NFHS 1998 and 2005 (not available in NFHS 1992). The body
mass index (BMI) is calculated as weight in kilograms divided by the square of height in meters and it is not available for currently pregnant
women and those who gave birth in the two months preceding the survey. Height measurement is in centimeters. BMI and height are available
only in NFHS 1998 and 2005. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10% levels, respectively.




                                                                         40
                                                                     Table 3: Fertility outcomes by the sex of the first-born


                                             =1 if wants                            =1 if                        =1 if undergone               =1 if ever had terminated                  number of
       dep. var:                            more children                         sterilized                       ultrasound                          pregnancy                      children ever born
                                   (1)          (2)          (3)         (4)         (5)          (6)        (7)        (8)      (9)          (10)        (11)       (12)        (13)        (14)        (15)

       first-born girl            0.049***     0.051***    0.053***    -0.052***   -0.068***    -0.065***   0.012***   0.025***   0.025***   0.010***   0.011***      0.005*    0.301***   0.295***     0.324***
                                  (0.002)      (0.002)     (0.003)     (0.002)     (0.002)      (0.004)     (0.004)    (0.004)    (0.008)    (0.002)    (0.002)      (0.003)    (0.010)    (0.008)      (0.013)
       first-born girl*eduyrs>0                              -0.005                               -0.008                            0.000                           0.014***                           -0.058***
                                                           (0.004)                              (0.005)                           (0.010)                            (0.004)                            (0.015)
       eduyrs>0                              -0.046***   -0.043***                0.025***     0.028***               0.086***   0.085***              0.017***    0.010***               -0.334***   -0.307***
                                              (0.002)      (0.002)                 (0.003)      (0.004)                (0.005)    (0.008)                (0.003)     (0.003)                (0.011)     (0.013)
       urban                                 -0.018***   -0.018***                -0.024***    -0.024***              0.099***   0.099***              0.023***    0.023***               -0.098***   -0.098***
                                              (0.002)      (0.002)                 (0.004)      (0.004)                (0.006)    (0.006)                (0.003)     (0.003)                (0.010)     (0.010)
       husband eduyrs>0                      -0.021***   -0.021***                0.041***     0.041***               0.067***   0.067***              0.009***    0.009***               -0.111***   -0.111***
                                              (0.003)      (0.003)                 (0.004)      (0.004)                (0.005)    (0.005)                (0.003)     (0.003)                (0.011)     (0.011)
       age first birth                        0.023***    0.023***                 -0.034***    -0.034***              0.018***   0.018***              0.007***    0.007***               -0.153***   -0.153***
                                              (0.000)      (0.000)                 (0.001)      (0.001)                (0.001)    (0.001)                (0.001)     (0.001)                (0.002)     (0.002)




41
       age first marriage                     -0.004***   -0.004***                  0.001        0.001                  0.001      0.001               -0.009***   -0.009***               -0.006**    -0.006**
                                              (0.000)      (0.000)                 (0.001)      (0.001)                (0.001)    (0.001)                (0.001)     (0.001)                (0.003)     (0.003)
       durables index                        -0.010***   -0.010***                  0.001        0.001                0.061***   0.061***               0.002**     0.002**               -0.134***   -0.134***
                                              (0.001)      (0.001)                 (0.001)      (0.001)                (0.002)    (0.002)                (0.001)     (0.001)                (0.003)     (0.003)
       # children ever born                  -0.040***   -0.040***                0.017***     0.017***               -0.008**   -0.008**               -0.002**    -0.002**
                                              (0.001)      (0.001)                 (0.001)      (0.001)                (0.003)    (0.003)                (0.001)     (0.001)

       Observations              220087       220087        220087     220303      220234       220234      56669      56657      56657     220285      220275      220275     152291      152291      152291
       Pseudo R2 or R2            0.003        0.393         0.393      0.003       0.225        0.225      0.000      0.307      0.307      0.000      0.0278      0.0278      0.008       0.480       0.480

     Probit estimates in columns 1–12 (marginal effects reported). OLS estimates in columns 13–15. Robust standard errors adjusted for clustering at the household level in parentheses. “wants more
     children” is a dummy equal to one if the woman wants more children at the time of the survey, zero otherwise. “sterilized” is a dummy equal to one if the woman has undergone female sterilization,
     zero otherwise (or if she is using another method of contraception). “ultrasound” is a dummy equal to one if the woman has undergone ultrasound test (zero otherwise), asked only with reference to
     the two most recent births in the last three years preceding the survey (NFHS 1998), and to any pregnancy in the last five years preceding the survey (NFHS 2005) (not asked in NFHS 1992). “had
     terminated pregnancy” is a dummy equal to one if the woman ever had a pregnancy that terminated in a miscarriage, abortion, or still birth, zero otherwise. The regression for the number of
     children ever born is estimated on the subsample of women who have been sterilized or who do not want more children. Covariates include state fixed effects, urban dummy, birth year fixed effects,
     7 five-year age groups dummies, survey round fixed effects, age at first birth and marriage, her and partner’s current age (and square), whether she and her partner have completed one or more
     years of education, a durables index, religion and caste. The number of children ever born is included in columns 1–12. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and
     10% levels, respectively.
                                              Table 4: Birth spacing by sex of the child

                                       a) Time interval between first and second birth
                                       dep. var:                 number of months   interval < 15 months
                                                                  (1)        (2)       (3)         (4)

                                       first-born girl               -0.778***    -0.960***      0.005***    0.004**
                                                                     (0.102)      (0.133)        (0.002)     (0.002)
                                       first-born girl*eduyrs>0                    0.422**                     0.001
                                                                                  (0.199)                    (0.003)
                                       eduyrs>0                       0.143        -0.062       -0.005***   -0.006**
                                                                     (0.141)      (0.177)        (0.002)     (0.003)

                                       Observations                  182395       182395         182395       182395
                                       Pseudo R2 or R2                0.026        0.026          0.010        0.010


                                       b) Time interval between second and third birth
                                          (conditional on first-born girl)
                                       dep. var:                  number of months  interval < 15 months
                                                                    (1)       (2)      (3)         (4)

                                       second-born girl             -0.523***    -0.944***      0.008***    0.015***
                                                                     (0.158)      (0.211)        (0.002)     (0.003)
                                       second-born girl*eduyrs>0                 1.149***                   -0.019***
                                                                                  (0.386)                    (0.005)
                                       eduyrs>0                      0.483**       -0.102       -0.012***     -0.002
                                                                     (0.218)      (0.275)        (0.004)     (0.004)

                                       Observations                     63365        63365       63363         63363
                                       Pseudo R2 or R2                  0.024        0.024       0.010         0.010

OLS estimates in columns 1–2. Probit estimates in columns 3–4 (marginal effects reported). Robust standard errors adjusted for clustering at the
household level in parentheses. Spacing is the length of time between births and it’s expressed in number of months (columns 1–2), or as a
dummy variable equal to one if the interval is shorter than 15 months (or less than six months from birth to conception of the next child).
Covariates include state fixed effects, urban dummy, birth year fixed effects, 7 five-year age groups dummies, survey round fixed effects, age at
first birth and marriage, her and partner’s current age (and square), whether she and her partner have completed one or more years of education,
a durables index, religion and caste, and number of children ever born. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and
10% levels, respectively.




                          Table 5: Birth spacing by sex of the child, with mother fixed effects

                                dep. var:                   number of months                    interval < 15 months
                                Subsample:                     eduyrs=0 eduyrs>0                      eduyrs=0 eduyrs>0
                                                        (1)       (2)        (3)             (4)         (5)       (6)

                                girl              -0.597***   -0.632***    -0.496**     0.005***    0.006***       0.002
                                                   (0.113)     (0.129)      (0.229)      (0.002)     (0.002)      (0.004)

                                Observations       420703      243660       176488      420703       243660       176488
                                R-squared           0.593       0.556        0.658       0.506        0.484        0.548

OLS estimates. Robust standard errors adjusted for clustering at the household level in parentheses. The sample exclude births of birth order 4
and higher. Includes birth order fixed effects. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10% levels, respectively.




                                                                            42
Table 6: Differences in the conditional age distribution by sex of the first-born child from ordered logit
regression. Dep. variable: 5-year age groups.

                                                     women with:                 at least one child ever born
                                                                               first-born girl vs first-born boy
                                                                               change             95% CI
                                                                                 (1)                (2)
                                                     P r(y = 15 − 19|x)        0.0000        [ 0.0000, 0.0001]
                                                     P r(y = 20 − 24|x)        0.0026        [ 0.0022, 0.0029]
                                                     P r(y = 25 − 29|x)        0.0283        [ 0.0247, 0.0318]
                                                     P r(y = 30 − 34|x)        -0.0093      [-0.0106, -0.0081]
                                                     P r(y = 35 − 39|x)        -0.0185      [-0.0208, -0.0161]
                                                     P r(y = 40 − 44|x)        -0.0027      [-0.0031, -0.0024]
                                                     P r(y = 45 − 49|x)        -0.0004      [-0.0004, -0.0003]
                                                     Observations                           220303
                                                     Pseudo R2                                0.456

Computed from the ordered logit estimates in which the dependent variable is a categorical variable for seven 5-year age groups and the
independent variable of interest is “first-born girl” (column 1), and “girl-girl” (column 2). Covariates include state fixed effects, urban dummy,
survey round fixed effects, age at first birth and marriage, partner’s age (and square), whether she and her partner have completed one or more
years of education, a durables index, religion and caste, and number of children ever born. Column 2 also includes dummies for whether the first
two born children are boy-girl or girl-boy. The values reported are the changes in predicted probabilities when “first-born girl” or “girl-girl”
change from 0 to 1, with all the other independent variables set at their mean value (for the regression in column 2, “girl-boy” and “boy-girl” are
set at zero). Changes are reported with 95% confidence intervals by the delta method in parentheses. Robust standard errors adjusted for
clustering at the household level in parentheses. All women aged 15–49. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and
10% levels, respectively.




              Table 7: Anemia status by sex of the first-born child (or number of children ever born)
 dep. var:                                                                                   =1 if anemic
 Subsample                                                                                                              eduyrs=0    eduyrs>0
                                 (1)         (2)          (3)         (4)          (5)           (6)           (7)         (8)         (9)        (10)        (11)

 first-born girl                0.011***   0.010***     0.009***    0.009***      0.008**      0.014***      0.014***    0.020***      0.009
                                (0.003)    (0.003)      (0.003)     (0.003)      (0.003)       (0.005)       (0.005)     (0.007)     (0.007)
 first-born girl*age≥30                                                                        -0.011**       -0.010*    -0.020**      -0.002
                                                                                               (0.006)       (0.006)     (0.009)     (0.010)
 first-born girl*age≥45                                                                                        -0.008      -0.006      -0.011
                                                                                                             (0.013)     (0.016)     (0.018)

 currently pregnant                                     0.016*       0.016*       0.015*        0.014*        0.014*      0.008      0.023**      0.016*      0.015*
                                                        (0.008)     (0.008)       (0.008)       (0.008)       (0.008)    (0.012)     (0.011)      (0.008)     (0.008)
 currently breastfeeding                               0.042***    0.042***     0.036***       0.036***      0.036***   0.038***    0.033***    0.036***    0.035***
                                                        (0.005)     (0.005)       (0.005)       (0.005)       (0.005)    (0.007)     (0.007)      (0.005)     (0.005)
 height                                                            -0.001***    -0.001***     -0.001***     -0.001***   -0.002***    -0.001*    -0.001***   -0.001***
                                                                    (0.000)       (0.000)       (0.000)       (0.000)    (0.000)     (0.000)      (0.000)     (0.000)
 eduyrs>0                                 -0.015***    -0.013***   -0.013***     -0.011**      -0.011**      -0.011**                            -0.011**    -0.011**
                                           (0.005)      (0.005)     (0.005)       (0.005)       (0.005)       (0.005)                             (0.004)     (0.005)
 husband eduyrs>0                         -0.013***    -0.012***   -0.012***     -0.011**      -0.011**      -0.011**    -0.011**     -0.008     -0.011**    -0.011**
                                           (0.005)      (0.005)     (0.005)       (0.005)       (0.005)       (0.005)     (0.005)    (0.010)      (0.005)     (0.005)
 durables index                           -0.021***    -0.020***   -0.020***    -0.019***     -0.019***     -0.019***   -0.022***   -0.017***   -0.019***   -0.019***
                                           (0.002)      (0.002)     (0.002)       (0.002)       (0.002)       (0.002)     (0.003)    (0.002)      (0.002)     (0.002)
 urban                                     -0.008*       -0.006     -0.007*        -0.007        -0.006        -0.006      -0.005     -0.006      -0.007*     -0.007*
                                           (0.004)      (0.004)     (0.004)       (0.004)       (0.004)       (0.004)     (0.006)    (0.006)      (0.004)     (0.004)
 # children ever born                                                           0.007***      0.007***      0.007***      0.003*    0.016***    0.011***    0.011***
                                                                                  (0.001)       (0.001)       (0.001)     (0.002)    (0.003)      (0.003)     (0.003)
 # children ever born*age≥30                                                                                                                       -0.004      -0.004
                                                                                                                                                  (0.003)     (0.003)
 # children ever born*age≥45                                                                                                                                   -0.001
                                                                                                                                                              (0.004)

 Covariates                       N          Y            Y           Y            Y             Y             Y           Y           Y            Y           Y
 Observations                  134132      134132       134132      134132       134132        134132        134132      59448       74681       134132      134132
 Pseudo R2                      0.000      0.0352       0.0358      0.0360       0.0361        0.0362        0.0362      0.0310      0.0354       0.036       0.036

Probit estimates (marginal effects reported). Robust standard errors adjusted for clustering at the household level in parentheses. “anemic” is a
dummy equal to one if the measured hemoglobin count is less than 12 grams per deciliter (less than 11 grams for pregnant women). Appropriate
adjustments in these cutoff points were made for women living at altitudes above 1,000 meters and women who smoke (NFHS data). Hemoglobin
measurement is available for all women in NFHS 1998 and 2005 (not available in NFHS 1992). Covariates include state fixed effects, urban
dummy, birth year fixed effects, 7 five-year age groups dummies, NFHS 2005 survey round fixed effect, age at first birth and marriage, her and
partner’s current age (and square), whether she and her partner have completed one or more years of education, a durables index, religion and
caste. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10% levels, respectively.




                                                                                43
Table 8: Levels of severity of anemia by sex of the first-born child - Changes in predicted probabilities
computed from ordered logit regression

                                                                all women                 women age 15–29                  women age 30–49
                                                      change          95% CI          change      95% CI               change      95% CI
                                                        (1)             (2)             (3)         (4)                  (5)         (6)

                    P r(y   =severely anemic|x)       0.0004      [ 0.0001, 0.0007]   0.0006       [ 0.0001, 0.0010]   0.0003     [-0.0002,   0.0007]
                    P r(y   =moderately anemic|x)     0.0032      [ 0.0005, 0.0060]   0.0049       [ 0.0005, 0.0093]   0.0020     [-0.0014,   0.0055]
                    P r(y   =mildly anemic|x)         0.0037      [ 0.0005, 0.0068]   0.0043       [ 0.0004, 0.0083]   0.0026     [-0.0019,   0.0072]
                    P r(y   =not anemic|x)            -0.0073    [-0.0136, -0.0010]   -0.0098     [-0.0186, -0.0010]   -0.0049    [-0.0133,   0.0035]

                    Observations                                 134060                           54328                           79732
                    Pseudo R-sq                                   0.023                           0.021                           0.024

Computed from the ordered logit estimates in which the dependent variable is a categorical variable with four categories for the levels of anemia
severity. “mild” anemia refers to hemoglobin count between 10.0 and 11.9 grams per deciliter (10.0 and 10.9 for pregnant women). “moderate”
anemia refers to hemoglobin count between 7.0 and 9.9 grams per deciliter. “severe” anemia refers to hemoglobin count less than 7.0 grams per
deciliter. Appropriate adjustments in these cutoff points were made for women living at altitudes above 1,000 meters and women who smoke
(NFHS data). Hemoglobin measurement is available for all women in NFHS 1998 and 2005 (not available in NFHS 1992). The independent
variable of interest is “first-born girl”. The values reported are the changes in predicted probabilities when “first-born girl” change from 0 to 1,
with all the other independent variables set at their mean value. Changes are reported with 95% confidence intervals by the delta method in
parentheses. Covariates include state fixed effects, urban dummy, 2005 NFHS survey round fixed effect, age at first birth and marriage, partner’s
age (and square), whether she and her partner have completed one or more years of education, a durables index, religion and caste, number of
children ever born, whether currently pregnant or breastfeeding, height. Column 1 also includes 7 five-year age groups dummies. Robust
standard errors adjusted for clustering at the household level in parentheses. All women aged 15–49. Using survey weights. ∗∗∗ , ∗∗ , and ∗
indicate significance at 1%, 5% and 10% levels, respectively.




                                   Table 9: Other health outcomes by sex of the first-born child

                                            BMI                               BMI< 18.5                         height                        height<145cm
                                   (1)       (2)         (3)         (4)         (5)        (6)         (7)      (8)        (9)        (10)        (11)    (12)

   first-born girl               0.090***     0.018      0.018      -0.007**      0.000      0.000      0.053     0.042     0.042      -0.000       0.001     0.001
                                 (0.023)    (0.033)    (0.033)      (0.003)     (0.005)   (0.005)     (0.036)   (0.053)   (0.053)    (0.002)     (0.003)   (0.003)
   first-born girl*age≥30                   0.120***    0.102**                 -0.013**   -0.011*                0.018     -0.009                 -0.001    0.000
                                            (0.044)    (0.047)                  (0.006)   (0.006)               (0.064)   (0.068)                (0.004)   (0.004)
   first-born girl*age≥45                                0.113                              -0.014                          0.171                            -0.008
                                                       (0.098)                            (0.012)                         (0.125)                          (0.007)

   Observations                  131262    131262      131262      131262       131262    131262      140196    140196    140196     140196       140196   140196
   R-squared                      0.258     0.258       0.258       0.089        0.089     0.089       0.079     0.079     0.079      0.037        0.037    0.037

OLS estimates (columns 1–3 and 7–9). Probit estimates (marginal effects reported) (columns 4–6 and 10–12). Robust standard errors adjusted
for clustering at the household level in parentheses. The body mass index (BMI) is calculated as weight in kilograms divided by the square of
height in meters and it is not available for currently pregnant women and those who gave birth in the two months preceding the survey. A value
of the BMI lower than 18.5 is used to define chronic energy deficiency. Height measurement is in centimeters and women whose height is below
145 cm are considered to be of short stature. BMI and height are available only in NFHS 1998 and 2005. Covariates include state fixed effects,
urban dummy, birth year fixed effects, 7 five-year age groups dummies, NFHS 2005 survey round fixed effect, age at first birth and marriage, her
and partner’s current age (and square), whether she and her partner have completed one or more years of education, a durables index, religion
and caste, number of children ever born, whether currently pregnant or breastfeeding. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance
at 1%, 5% and 10% levels, respectively.




                                                                                 44
                                        Table 10: Anemia status by time since first birth

                                    Sample:                                               all    eduyrs=0        eduyrs>0
                                                                                          (1)       (2)             (3)

                                    first-born girl                                    -0.005       -0.023           0.006
                                                                                     (0.017)      (0.031)         (0.021)
                                    first-born girl*12–23 months after first birth      -0.003       0.038           -0.025
                                                                                     (0.025)      (0.040)         (0.029)
                                    first-born girl*24–35 months after first birth      0.012        0.043           -0.001
                                                                                     (0.022)      (0.042)         (0.026)
                                    first-born girl*36–47 months after first birth      0.014       0.066*           -0.019
                                                                                     (0.024)      (0.039)         (0.030)

                                    Observations                                      22200           6584        15604
                                    Pseudo R2                                         0.050           0.050       0.052

Probit estimates (marginal effects reported). The sample is of all women who had their first birth less than 48 months before the time of the
survey. Robust standard errors adjusted for clustering at the household level in parentheses. “anemic” is a dummy equal to one if the measured
hemoglobin count is less than 12 grams per deciliter (less than 11 grams for pregnant women). Appropriate adjustments in these cutoff points
were made for women living at altitudes above 1,000 meters and women who smoke (NFHS data). Hemoglobin measurement is available for all
women in NFHS 1998 and 2005 (not available in NFHS 1992). Covariates include state fixed effects, urban dummy, birth year fixed effects, years
since first birth fixed effects, 7 five-year age groups dummies, NFHS 2005 survey round fixed effect, age at first birth and marriage, her and
partner’s current age (and square), whether she and her partner have completed one or more years of education, a durables index, religion and
caste, number of children ever born, whether currently pregnant or breastfeeding, height. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate
significance at 1%, 5% and 10% levels, respectively.




    Table 11: Probability of female child and anemia status less than a year after birth, by birth order

        dep. var:                                                     =1 if child birth order i is a female
               birth order:     1         2          3        1         2          3        1          2             3        1         2         3

        anemic (any level)     -0.007    0.005     -0.019
                              (0.018)   (0.018)   (0.024)
        mild anemic                                          -0.006    0.000     -0.002
                                                            (0.018)   (0.018)   (0.023)
        moderately anemic                                                                    -0.004     0.007      -0.030
                                                                                            (0.023)    (0.026)    (0.027)
        severely anemic                                                                                                      0.029     -0.007    0.036
                                                                                                                            (0.080)   (0.064)   (0.070)

        Observations           5691      4938       2946     5691      4938      2946        5691        4938      2946      5691      4938      2946
        Pseudo R2             0.0136    0.0162     0.0351   0.0136    0.0161    0.0349      0.0136      0.0162    0.0352    0.0136    0.0161    0.0349

Probit estimates (marginal effects reported). Robust standard errors adjusted for clustering at the household level in parentheses. “anemic” is a
dummy equal to one if the measured hemoglobin count is less than 12 grams per deciliter (less than 11 grams for pregnant women). Appropriate
adjustments in these cutoff points were made for women living at altitudes above 1,000 meters and women who smoke (NFHS data). Hemoglobin
measurement is available for all women in NFHS 1998 and 2005 (not available in NFHS 1992). Covariates include state fixed effects, urban
dummy, birth year fixed effects, 7 five-year age groups dummies, NFHS 2005 survey round fixed effect, age at first birth and marriage, her and
partner’s current age (and square), whether she and her partner have completed one or more years of education, a durables index, religion and
caste, number of children ever born, whether currently pregnant or breastfeeding, height. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate
significance at 1%, 5% and 10% levels, respectively.




                                                                           45
 Table 12: Women’s age at the time of the survey by sex of the first-born child and NFHS survey round

                                          dep. var:                  seven 5-year age groups     age
                                                                          ordered logit          OLS
                                                                               (1)               (2)

                                          first-born girl                    -0.180***          -0.287***
                                                                              (0.018)            (0.035)
                                          first-born girl*wave 1998             0.033              0.013
                                                                              (0.024)            (0.046)
                                          first-born girl*wave 2005            0.049*              0.068
                                                                              (0.027)            (0.042)
                                          wave 1998                          0.117***           0.229***
                                                                              (0.018)            (0.031)
                                          wave 2005                          0.447***           0.791***
                                                                              (0.017)            (0.029)

                                          Observations                       220303             220303
                                          Pseudo R2 or R2                     0.456              0.834

Ordered logit estimates in column (1), and OLS estimates in column (2). The dependent variable in column (1) is a categorical variable for 7
five-year age groups, and in column (2) it’s the woman’s age. Covariates include state fixed effects, urban dummy, survey round fixed effects, age
at first birth and marriage, partner’s age (and square), whether she and her partner have completed one or more years of education, a durables
index, religion and caste, and number of children ever born. Robust standard errors adjusted for clustering at the household level in parentheses.
All women aged 15–49. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10% levels, respectively.




                                                                       46
Table 13: Food consumption by sex of the first-born child (daily or weekly consumption of specific food
items)

      a) Less than a year since first birth
                                         milk                   pulses               green vegetables              fruits             eggs/meat/fish
                                    (1)       (2)         (3)            (4)          (5)        (6)        (7)              (8)      (9)       (10)

      first-born girl              -0.020      0.005      0.004       -0.014          0.002      -0.004     -0.001        0.024       -0.024     -0.027
                                 (0.016)     (0.028)    (0.007)     (0.013)         (0.009)    (0.014)    (0.018)       (0.028)     (0.017)    (0.031)
      first-born girl*eduyrs>0                 -0.039                0.029**                      0.010                   -0.035                 0.004
                                             (0.038)                (0.015)                    (0.018)                  (0.036)                (0.040)
      eduyrs>0                  0.109***    0.129***    0.022*        0.006         0.045***   0.040**    0.140***     0.156***      0.033      0.031
                                 (0.026)     (0.032)    (0.012)     (0.014)          (0.013)   (0.016)     (0.023)      (0.032)     (0.025)    (0.032)

      Observations               5972           5972     5961        5961            5959       5959       5973             5973     5977       5977
      Pseudo R2                  0.173          0.173    0.123       0.125           0.120      0.120      0.184            0.185    0.300      0.300


      b) Women age 15–29
                                         milk                   pulses               green vegetables              fruits             eggs/meat/fish

      first-born girl              -0.001      -0.003     -0.002       -0.005         0.000       -0.002    0.003          0.008      -0.003      -0.002
                                 (0.006)     (0.009)    (0.003)      (0.004)        (0.002)     (0.004)   (0.005)       (0.008)     (0.006)     (0.009)
      first-born girl*eduyrs>0                 0.004                   0.006                       0.005                  -0.008                  -0.002
                                             (0.011)                 (0.005)                    (0.005)                 (0.010)                 (0.011)
      eduyrs>0                  0.097***    0.095***    0.023***    0.019***        0.017***   0.014***   0.097***     0.101***     0.050***   0.051***
                                 (0.007)     (0.009)     (0.003)     (0.005)         (0.004)    (0.005)    (0.006)      (0.006)      (0.007)    (0.009)

      Observations               56940          56940    56940       56940           56937      56937      56921            56921    56930      56930
      Pseudo R2                  0.168          0.168    0.097       0.097           0.105      0.105      0.177            0.177    0.283      0.283


      c) Women age 30–49
                                         milk                   pulses               green vegetables              fruits             eggs/meat/fish

      first-born girl             0.008*       0.005      0.003        0.002         0.004*        0.005   0.008*         0.005       0.004       0.004
                                 (0.005)     (0.007)    (0.002)      (0.003)        (0.002)     (0.003)   (0.004)       (0.006)     (0.005)    (0.007)
      first-born girl*eduyrs>0                 0.005                   0.003                      -0.000                  0.007                  -0.001
                                             (0.011)                 (0.004)                    (0.005)                 (0.009)                (0.009)
      eduyrs>0                  0.081***    0.078***    0.017***    0.015***        0.017***   0.017***   0.096***     0.093***      0.010       0.010
                                 (0.006)     (0.008)     (0.003)     (0.004)         (0.003)    (0.004)    (0.006)      (0.007)     (0.006)    (0.008)

      Observations               83236          83236    83231       83231           83224      83224      83187            83187    83213      83213
      Pseudo R2                  0.171          0.171    0.109       0.109           0.125      0.125      0.202            0.202    0.293      0.293

Probit estimates (marginal effects reported). Robust standard errors adjusted for clustering at the household level in parentheses. Food
consumption variables are based on NFHS questions on frequency of consumption of certain food groups. The variables are dummies equal to one
if the woman consumes the indicated type of food at least once a week. Food consumption is available for all women in NFHS 1998 and 2005 (not
available in NFHS 1992). Covariates include state fixed effects, urban dummy, birth year fixed effects, 7 five-year age groups dummies, NFHS
2005 survey round fixed effect, age at first birth and marriage, her and partner’s current age (and square), whether she and her partner have
completed one or more years of education, a durables index, religion and caste, number of children ever born, whether currently pregnant or
breastfeeding, height. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10% levels, respectively.




                                                                               47
                              Table 14: Iron supplementation by sex of the first-born child

                                      dep. var:                         =1 if taken iron suppl. during:
                                                                   first pregnancy         second pregnancy
                                                                    (1)          (2)       (3)          (4)
                                      first-born girl              -0.008       -0.001     0.004       0.001
                                                                 (0.006)      (0.009)    (0.007)     (0.009)
                                      first-born girl*eduyrs>0                  -0.015                 0.005
                                                                              (0.013)                (0.014)
                                      eduyrs>0                  0.137*** 0.144*** 0.150*** 0.147***
                                                                 (0.009)      (0.012)    (0.010)     (0.012)

                                      currently pregnant          -0.000      -0.001     -0.014      -0.014
                                                                 (0.010)     (0.010)    (0.015)     (0.015)
                                      currently breastfeeding     0.005       0.005      0.004       0.004
                                                                 (0.008)     (0.008)    (0.009)     (0.009)
                                      # children ever born        -0.012      -0.012   -0.054***   -0.054***
                                                                 (0.010)     (0.010)    (0.010)     (0.009)
                                      husband eduyrs>0          0.056***    0.056***   0.048***    0.048***
                                                                 (0.009)     (0.009)    (0.009)     (0.009)
                                      durables index            0.043***    0.043***   0.043***    0.043***
                                                                 (0.003)     (0.003)    (0.003)     (0.003)
                                      urban                     0.033***    0.033***     0.015       0.015
                                                                 (0.009)     (0.009)    (0.009)     (0.009)

                                      Observations               32050       32050      30099       30099
                                      Pseudo R2                  0.231       0.231      0.212       0.212

Probit estimates (marginal effects reported). Robust standard errors adjusted for clustering at the household level in parentheses. NFHS 1992
asked women whether they received iron and folic acid (IFA) tablets or syrup during pregnancy for each birth during the four years preceding the
survey. NFHS 1998 asked the same question in relation to each birth during the last three years preceding the survey. NFHS 2005 asked the same
question in relation to the most recent birth during the five years preceding the survey. Covariates include state fixed effects, urban dummy,
birth year fixed effects, 7 five-year age groups dummies, survey round fixed effects, age at first birth and marriage, her and partner’s current age
(and square), whether she and her partner have completed one or more years of education, a durables index, religion and caste, number of
children ever born, whether currently pregnant or breastfeeding. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10%
levels, respectively.




                                                                       48
                                    Table 15: Spousal violence by sex of the first-born child

         a) Less than a year since first birth
                                                            =1 if suffered physical violence                             =1 if suffered any    =1 if suffered any
                                                any                     severe                less severe               emotional violence    sexual violence
                                       (1)              (2)         (3)        (4)          (5)         (6)               (7)        (8)       (9)      (10)

         first-born girl               0.022            0.033          0.012      0.036**         0.024        0.037      0.012      -0.010    0.007     0.016
                                     (0.017)          (0.038)        (0.009)      (0.017)       (0.018)      (0.038)    (0.014)    (0.023)   (0.013)   (0.023)
         first-born girl*eduyrs>0                       -0.017                    -0.035**                     -0.020                 0.038              -0.014
                                                      (0.050)                     (0.017)                    (0.050)               (0.029)             (0.027)
         eduyrs>0                     -0.036           -0.026         -0.003       0.017         -0.031       -0.020     -0.021    -0.043*    -0.011    -0.002
                                     (0.033)          (0.040)        (0.011)      (0.015)       (0.031)      (0.039)    (0.019)    (0.023)   (0.016)   (0.019)

         Observations                 1867             1867           1492         1492          1867         1867       1843      1843      1677      1677
         Pseudo R2                    0.127            0.127          0.154        0.161         0.130        0.130      0.110     0.112     0.199     0.200


         b) Women age 15–29
                                                            =1 if suffered physical violence                             =1 if suffered any    =1 if suffered any
                                                any                     severe                      less severe         emotional violence    sexual violence

         first-born girl               -0.009             0.001        -0.008       -0.007        -0.007        0.003     0.001       0.004    0.001     0.008
                                     (0.010)           (0.016)       (0.016)      (0.009)       (0.010)      (0.016)    (0.005)    (0.008)   (0.006)   (0.008)
         first-born girl*eduyrs>0                        -0.018                     -0.002                     -0.020                -0.007             -0.014*
                                                       (0.019)                    (0.011)                    (0.019)               (0.012)             (0.008)
         eduyrs>0                   -0.039***         -0.031**      -0.017**     -0.016**      -0.038***     -0.029*     -0.013     -0.009    -0.005    0.002
                                     (0.010)           (0.015)       (0.007)      (0.008)       (0.010)      (0.015)    (0.008)    (0.009)   (0.006)   (0.007)

         Observations                21554             21554         21554        21554         21552        21552       21561     21561     21561     21561
         Pseudo R2                   0.091             0.091         0.067        0.067         0.091        0.092       0.042     0.042     0.099     0.099


         c) Women age 30–49
                                                          =1 if suffered any physical violence                           =1 if suffered any    =1 if suffered any
                                                any                     severe                less severe               emotional violence    sexual violence

         first-born girl              -0.013*        -0.013            0.005       0.004         -0.013*       -0.012     0.005       0.007    0.003     0.005
                                     (0.014)       (0.010)           (0.004)     (0.005)        (0.007)      (0.009)    (0.005)    (0.007)   (0.003)   (0.005)
         first-born girl*eduyrs>0                    0.001                         0.002                       -0.002                -0.003              -0.003
                                                   (0.013)                       (0.008)                     (0.013)               (0.009)             (0.007)
         eduyrs>0                   -0.053***     -0.053***         -0.024***   -0.025***      -0.052***    -0.051***   -0.013**   -0.011*   -0.008*    -0.007
                                     (0.009)       (0.009)           (0.007)     (0.008)        (0.009)      (0.009)     (0.006)   (0.006)   (0.005)   (0.006)

         Observations                32633             32633         32633        32633         32633        32633       32634     32634     32634     32634
         Pseudo R2                   0.087             0.087         0.069        0.069         0.087        0.087       0.043     0.043     0.099     0.099

Probit estimates (marginal effects reported). Robust standard errors adjusted for clustering at the household level in parentheses. The spousal
violence variables are based on a module of NFHS 2005 that collected detailed information on physical, sexual, and emotional violence
perpetrated by husbands against their wives (based on women’s self-report). “any severe violence” includes whether the spouse ever tried to
strangle or burn, or ever threatened her with knife or gun. “any less severe violence” includes whether the spouse ever pushed, slapped, punched,
kicked or dragged her. “any emotional violence” includes whether the husband ever said something to humiliate her in front of others, or
threatened to hurt someone close to her, or insulted her. “any sexual violence” includes whether the husband forced her to perform any unwanted
sexual acts. Domestic violence variables available for all married women in NFHS 2005. Covariates include state fixed effects, urban dummy,
birth year fixed effects, 7 five-year age groups dummies, NFHS 2005 survey round fixed effect, age at first birth and marriage, her and partner’s
current age (and square), whether she and her partner have completed one or more years of education, a durables index, religion and caste,
number of children ever born, whether currently pregnant or breastfeeding, height. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at
1%, 5% and 10% levels, respectively.




                                         Table 16: Sex ratios for first births by age group
                                                                      all women                     women   with no education
                                       age group        sex ratio           CI           n      sex ratio         CI         n
                                       20-24              0.515       [0.510; 0.520]   38544      0.513     [0.505; 0.520] 18050
                                       25-29              0.512       [0.508; 0.517]   50199      0.510     [0.504; 0.517] 22835
                                       30-34              0.520       [0.515; 0.524]   45878      0.523     [0.517; 0.530] 21637
                                       35-39              0.519       [0.514; 0.524]   40137      0.526     [0.519; 0.533] 19837
                                       40-44              0.524       [0.518; 0.530]   31674      0.534     [0.527; 0.542] 16419
                                       45-49              0.536       [0.529; 0.542]   24303      0.549     [0.540; 0.557] 13461

95% confidence intervals reported in square brackets. Using survey weights.




                                                                                       49
A    Appendix

    Figure A.1: Share of women with first-born girl by age and urban/rural location




                Figure A.2: Share of anemic women, by age (Subsamples)




Figure A.3: % of women who ever had a terminated pregnancy, by age and sex of the
first-born child




                                          50
                               Table A.1: Fertility outcomes by the sex of the earlier-born children
                                   =1 if wants                        =1 if                     =1 if undergone       =1 if ever had terminated           number of
                dep. var.         more children                     sterilized                     ultrasound                 pregnancy               children ever born
                                 (1)         (2)              (3)                (4)             (5)        (6)         (7)            (8)              (9)        (10)

                G,G            0.100***                    -0.158***                           0.049***               0.029***                      0.639***
                                (0.003)                     (0.004)                             (0.008)                (0.004)                       (0.011)
                G,B            0.009***                    -0.056***                           0.022***               0.013***                      0.147***
                                (0.002)                     (0.004)                             (0.007)                (0.003)                       (0.010)
                B,G            0.015***                    -0.054***                             0.005                0.015***                      0.155***
                                (0.002)                     (0.004)                             (0.008)                (0.003)                       (0.010)
                G,G,G                       0.107***                        -0.189***                      0.067***                   0.047***                 0.756***
                                             (0.005)                         (0.007)                        (0.013)                    (0.006)                  (0.018)
                G,G,B                       0.016***                        -0.077***                      0.046***                   0.017***                 0.207***
                                             (0.002)                         (0.007)                        (0.012)                    (0.005)                  (0.016)
                G,B,B                       -0.011***                       0.019***                       0.026**                      0.001                  -0.076***
                                             (0.002)                         (0.006)                        (0.012)                    (0.005)                  (0.017)
                G,B,G                       0.021***                        -0.052***                      0.023**                    0.024***                 0.236***
                                             (0.003)                         (0.007)                        (0.010)                    (0.005)                  (0.017)
                B,B,G                         -0.003                          0.002                        0.023**                      0.003                  -0.046***
                                             (0.002)                         (0.007)                        (0.011)                    (0.006)                  (0.016)
                B,G,B                       -0.008***                         0.003                          0.010                      0.009                  -0.067***
                                             (0.002)                         (0.007)                        (0.012)                    (0.006)                  (0.016)
                B,G,G                       0.028***                        -0.070***                        0.007                    0.026***                 0.264***
                                             (0.003)                         (0.007)                        (0.011)                    (0.006)                  (0.017)

                Observations    182582       126426         182752           126550             40236       23171     182724          126523          142863     103120
                Pseudo R2        0.325        0.296          0.184            0.180             0.291       0.250     0.0262          0.0255           0.455      0.346

Probit estimates in columns 1–8 (marginal effects reported). OLS estimates in columns 9–10. Robust standard errors adjusted for clustering at
the household level in parentheses. “wants more children” is a dummy equal to one if the woman wants more children at the time of the survey,
zero otherwise. “sterilized” is a dummy equal to one if the woman has undergone female sterilization, zero otherwise (or if she is using another
method of contraception). “ultrasound” is a dummy equal to one if the woman has undergone ultrasound test (zero otherwise), asked only with
reference to the two most recent births in the last three years preceding the survey (NFHS 1998), and to any pregnancy in the last five years
preceding the survey (NFHS 2005) (not asked in NFHS 1992). “had terminated pregnancy” is a dummy equal to one if the woman ever had a
pregnancy that terminated in a miscarriage, abortion, or still birth, zero otherwise. The regression for the number of children ever born is
estimated on the subsample of women who have been sterilized or who do not want more children. Covariates include state fixed effects, urban
dummy, birth year fixed effects, 7 five-year age groups dummies, survey round fixed effects, age at first birth and marriage, her and partner’s
current age (and square), whether she and her partner have completed one or more years of education, a durables index, religion and caste, and
number of children ever born. Height measurement (in centimeters) is available only in NFHS 1998 and 2005. The number of children ever born
is included in columns 1–8. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10% levels, respectively.



      Table A.2: Fertility outcomes by the sex of the first-born, robustness check (inclusion of height)
                                           =1 if wants                        =1 if                     =1 if undergone    =1 if ever had terminated           number of
       dep. var.                          more children                     sterilized                     ultrasound              pregnancy               children ever born
                                         (1)         (2)              (3)                (4)             (5)        (6)      (7)            (8)              (9)        (10)

       first-born girl              0.051***      0.051***       -0.072***          -0.072***        0.025***    0.025***     0.004          0.004         0.344***    0.344***
                                     (0.003)       (0.003)       (0.005)            (0.005)          (0.009)     (0.009)    (0.004)        (0.004)         (0.014)     (0.014)
       first-born girl*eduyrs>0      -0.009**      -0.009**        -0.009             -0.009           -0.001      -0.001   0.020***       0.020***        -0.063***   -0.063***
                                     (0.004)       (0.004)       (0.007)            (0.007)          (0.011)     (0.011)    (0.005)        (0.005)         (0.017)     (0.017)
       eduyrs>0                    -0.037***     -0.037***      0.037***           0.037***         0.074***    0.074***   0.011***       0.011***        -0.307***   -0.305***
                                     (0.003)       (0.003)       (0.005)            (0.005)          (0.009)     (0.009)    (0.004)        (0.004)         (0.015)     (0.015)
       height                                     -0.000**                           0.000                        0.000                   -0.001***                   -0.005***
                                                   (0.000)                          (0.000)                      (0.000)                   (0.000)                     (0.001)

       Observations                 140062         140062           140196             140196         54100       54100     140189         140189          104999      104999
       Pseudo R2 or R2               0.398          0.398            0.234              0.234         0.310       0.310     0.0302         0.0305           0.468       0.469

Probit estimates in columns 1–8 (marginal effects reported). OLS estimates in columns 9–10. Robust standard errors adjusted for clustering at
the household level in parentheses. “wants more children” is a dummy equal to one if the woman wants more children at the time of the survey,
zero otherwise. “sterilized” is a dummy equal to one if the woman has undergone female sterilization, zero otherwise (or if she is using another
method of contraception). “ultrasound” is a dummy equal to one if the woman has undergone ultrasound test (zero otherwise), asked only with
reference to the two most recent births in the last three years preceding the survey (NFHS 1998), and to any pregnancy in the last five years
preceding the survey (NFHS 2005) (not asked in NFHS 1992). “had terminated pregnancy” is a dummy equal to one if the woman ever had a
pregnancy that terminated in a miscarriage, abortion, or still birth, zero otherwise. The regression for the number of children ever born is
estimated on the subsample of women who have been sterilized or who do not want more children. Covariates include state fixed effects, urban
dummy, birth year fixed effects, 7 five-year age groups dummies, survey round fixed effects, age at first birth and marriage, her and partner’s
current age (and square), whether she and her partner have completed one or more years of education, a durables index, religion and caste, and
number of children ever born. Height measurement (in centimeters) is available only in NFHS 1998 and 2005. The number of children ever born
is included in columns 1–8. Using survey weights. ∗∗∗ , ∗∗ , and ∗ indicate significance at 1%, 5% and 10% levels, respectively.




                                                                                                 51