(although insignificant) would bias us against finding a decline in under-5 EFM because, in the post-ultrasound cohorts, the marginal survivors of the neonatal period are negatively selected (i.e., in the pre-ultrasound period they would have succumbed to neonatal mortality, but now they “just survive”).

Larger reductions in under-5 than in neonatal mortality are consistent with the increases in postnatal investments that we document below, given that neonatal survival is less dependent upon postnatal investments and is more closely linked to maternal health and delivery conditions. Our findings are also congruous with previous work; for instance, The Million Deaths Study (2010) in India shows that only 3.2 percent of neonatal deaths were caused by diarrhea—a function of clean water and nutrition—in contrast to 22.2 percent of post-neonatal deaths. The significance of our results is enhanced by the fact that reductions in post-neonatal mortality also improve later life circumstances, predicting adult height, a marker of health (Bozzoli et al. (2009)) and cognitive performance (Chay et al. (2009)).

**Results by birth order.** Estimates by birth order are in Table A.9. The only statistically significant reductions in under-5 EFM are among second births; although there are sizable but less precisely estimated reductions among third births too. This may reflect the common finding that parents are particularly averse to having more than two girls (which applies at order three and above),<sup>36</sup> so there remains a girl-boy differential in under-5 mortality at higher orders.

**Equalization of inheritance rights by gender.** We also test if our results are biased by state-level legislative changes during our sample period that equalized inheritance of ancestral property between men and women. Recent work shows that this led to an increase in sex-selection (Bhalotra et al. (2018a)). We find that our results hold even if we restrict the sample to states that did not experience changes in inheritance rights, i.e., when we exclude Kerala, Andhra Pradesh, Tamil Nadu, Maharashtra, and Karnataka. These results are available on request.

**Gendered recall bias.** As we combine fertility histories of mothers interviewed in three DHS waves, recall of birth year varies within the sample but is, for some women, as long as 20 years. For the analysis in this paper, it is relevant to consider whether accuracy of recall of the year of birth or death of a child varies with the gender of the child. The firm gathering the NFHS data was alert to recall bias, and they report that the data were subject to several probes designed to address it. We, nevertheless, check for the presence of recall bias—if women are more likely to have forgotten girl deaths and if this error is increasing in distance of birth year from survey year, then this could, in principle, bias our findings. On the other hand, if families with firstborn girls had stronger gender bias in recall in the pre-ultrasound period then our EFM estimates will be conservative.

We examine gendered recall bias by exploiting the fact that a range of birth years is available in more than one NFHS round and that distance between a given year and the survey date varies by

> 36Almond and Edlund (2008) show that Indian, Chinese, and Korean families with no previous sons exhibit male-biased sex ratios at third parity but not before in the 2000 US Census and Bhalotra and Cochrane (2010)) show that the male-bias in the sex ratio at birth in India is increasing in birth order.

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