Although the NFHS contain fairly rich data on investments in children, these questions are asked only for children born in a few years preceding each survey and there are no pre-ultrasound data on investments.<sup>20</sup> For this reason, we utilize the 1999 round of the Rural Economic and Demographic Survey (REDS) that reports data on health investments for all children alive at the time of survey to analyze effects on health investments.<sup>21</sup> For the mortality and postnatal health specifications (presented in the next section), we pool all births of the surveyed women to create a child-level data set. The birth hazard sample is a retrospective mother-year panel that we create from women’s retrospective birth histories; women enter this panel in the year of marriage and exit in the year of survey. The sample used for the fertility stock estimates simply pools all surveyed women to form a woman-level data set. Summary statistics for mortality, (actual) fertility, and child health investments are in Table 1. In Section 5.1.1, we examine the robustness of our results to data-related issues, including gendered recall bias. The maximum recall period is 20 years in our NFHS sample and is 26 years in our REDS sample.

# **4 Empirical Strategy**

The hypothesis we test in this paper is that the availability of prenatal sex-detection technology (in particular, ultrasound), which led to large-scale selective abortion of female fetuses, also modified conception and investment decisions in a gendered manner, with implications for excess female mortality (EFM).

As discussed in Section 1, we exploit exogenous variation in the supply of ultrasound scanners. The first supply shock was the first imports of ultrasound scanners in the early stages of India’s import liberalization (tariff reduction), and the second was initiation of local production following industrial delicensing policies.<sup>22</sup> However, the wave of economic liberalization in India that led risk, and more so among families with firstborn girls (who are more treated). However, maternal mortality is numerically small and the share of maternal mortality associated with abortion even smaller; so, any resulting bias is unlikely to drive our findings. We, nevertheless, considered the direction of any such bias. If, as observed in Jha et al. (2006) and Bhalotra and Cochrane (2010), high-SES women are more likely to commit sex-selection then, given that their children face lower mortality risks, our estimates of EFM decline will tend to be conservative. However, this downward bias may be somewhat offset if low-SES women, even with lower take up of abortion, are more likely to die of abortion.

20NFHS-1, 2, and 3 collected health investments for, respectively, the last three children born after January 1988, the last two children born after January 1995, and all children born after January 2001.

> 21REDS is restricted to rural women from 16 major states. To the extent that deceased children are likely to have received lower health investments than surviving children and (as we show) excess girl mortality was higher during the pre-ultrasound period than in the post-ultrasound years, the exclusion of deceased children will tend to bias the estimated effects downward. In this sense, the estimates we present are conservative. Since REDS data does not report the year of birth or death for children that did not survive until the year of survey, we cannot perform a bounding exercise for this bias. However, our results for postnatal health investments using NFHS data, that does not suffer from this issue, are broadly similar.

> 22We do not use measures of state-specific penetration or adoption as they would be endogenous; see Jayachandran et al. (2010) for a similar argument pertaining to the introduction of antibiotics in the United States. Bhalotra and Cochrane (2010) document that access to ultrasound in India was widespread and that

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