era is a question of considerable importance (see next section). There is a growing awareness in the field of economics of the importance of replication (Kane (1984), Card and Krueger (1995), Hammermesh (2007), Anderson and Kichkha (2017)), and that this may entail changes in design (Rosenblum (2001)).

Our investigations suggest that an important source of the difference is that we leverage the systematic pre- versus post-ultrasound difference between the behavior of families with firstborn girls versus firstborn boys, whereas HS pool these families and lose that identifying variation. In their specification, the independent variable is a 7-year moving average of the state-year average of the male-female sex ratio at birth, _MFRst_ . The summary statistics in Table 1 and estimates of a double-difference model displayed in Table A.6 show that pre-ultrasound EFM and the postultrasound decline in EFM were both concentrated in firstborn-girl families. The pre-ultrasound girlboy differential in under-5 mortality was 2.87 p.p. for births preceded by a firstborn girl in contrast to -0.08 p.p. for births preceded by a firstborn boy. This is an enormous difference, so a specification forcing equal coefficients for the two groups is likely to veil relevant changes. The _MFRst_ variable in HS essentially pools a treated group with an untreated group that is roughly as large. It is useful to observe here that a number of other studies resemble ours in using quasi-experimental variation in the sex of the first born child and showing that it predicts son-preferring behaviors (e.g., Dahl and Moretti (2008), Rosenblum (2013), Milazzo (2018), Bhalotra et al. (2018a)).

To demonstrate the empirical relevance of this difference, we start with the HS specification<sup>54</sup> and make one change—we calculate the state-year averaged female-male sex ratio at birth separately for firstborn-girl ( _FMRst_<sup>_FG_) and firstborn-boy families (</sup><sup>_FMR_</sup> _st_<sup>_FB_), and then compute the difference</sup> between the two, calling it the “ _excess_ female-male sex ratio at birth” ( _EFMRst_ = _FMRst_<sup>_FG_</sup> _− FMRst_<sup>_FB_).Wethenreplace</sup><sup>_FMRst_inequation(4)with</sup><sup>_EFMRst_asfollows:</sup> Table A.24 presents the results for specification (5). Columns (1)-(5) use the same sample as HS. Columns (6)-(8) expand the sample to include children who were born within 20 years of interview to make the estimates comparable to ours. This simple change to the HS specification uncovers a significant narrowing of the girl-boy difference in mortality, in line with the findings in our paper.<sup>55</sup>

> 54In our paper, unlike HS, we define _mortality_ rather than survival as the outcome and we define the sex ratio at birth as the share of _females_ at birth instead of the share of males at birth. To ensure comparability with our estimates, we rewrite HS’ specification as follows:

_′ Yist_ = _αs_ 0 + _αs_ 1 _femalei_ + _δt_ 0 + _δt_ 1 _femalei_ + _xi_<sup>_β_+</sup><sup>_π_0</sup><sup>_FMRst_+</sup><sup>_π_1(</sup><sup>_FMRst∗femalei_) +</sup><sup>_εist_</sup> (4) where _Yist_ is a mortality indicator for child _i_ .

> 55We find similar results when we merge our _EFMRst_ variable with the HS data published on the EJ webpage, and use their program to estimate their specification except for replacing _MFRst_ with _EFMRst_ . This exercise eliminates all differences in sample construction and the estimation method, so the only remaining difference is that we replace MFR with EFMR.

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