with error, it is notable that the coefficients of interest are not discernibly changed with the inclusion of these controls (Table A.10). In column (2) of Table A.10, we control for a different (also imperfect) measure of preferences that reflects actual choices rather than stated preferences —the state-year gender school enrollment ratio at ages 6-11 and 11-14—and, again, the results are stable. The coefficients of these additional terms are interesting in their own right, and are consistent with our expectations. The coefficients of _Ideal fraction of sons * Female_ is positive and that of _Girl-boy enrollment rate 6-11 ∗ Female_ is negative, implying that EFM is higher in families with _*_ a stronger preference for sons. The coefficient on _Ideal number of children Female_ is negative, implying that, conditional on son preference, a declining trend in fertility leads to higher EFM, a finding that is consistent with Jayachandran (2016).

We also estimated equations in which son preference (measured as the mother’s reported ideal fraction of sons) is the dependent variable with a view to testing if it evolved differently between families with firstborn girls and firstborn boys; see Table A.11. This is not straightforward because we do not have longitudinal data on son preference. Instead, we have son preference recorded at the time of the survey in three cross-sections. The survey dates for the NFHS are 1991-92, 199899, and 2005-06, which are all post-ultrasound, but they span 15 years, allowing us to investigate preference decline during this period. For each wave, we keep women who had their first birth within a calendar year from their survey date, so that their preferences at the survey date reflect their preferences around the birth of their first child. We find a trend decline in son preference but no significant difference in the trend decline between firstborn-girl and firstborn-boy families.

As discussed earlier, Table A.3 suggests that there was no change in the composition of firstborngirl families post-ultrasound. To the extent that son preference is systematically associated with observables, this contributes to showing that preferences did not change post-ultrasound in firstborngirl relative to firstborn-boy families.<sup>39</sup> Overall, using different approaches, we find no evidence that our finding of post-ultrasound declines in EFM in families with firstborn girls was driven by changes in son preference specific to this group. Instead, the mechanism appears to be that parents use selective abortion to align the timing, number, and sex of births to their preferences. We substantiate this by analyzing four additional sets of outcomes—parental investments, son-biased fertility stopping, the gap between actual and desired fertility, and birth spacing.

# **6 Mechanisms**

In the following sub-sections, we investigate proximate mechanisms, i.e., the behaviors that operate in the treated (firstborn-girl) families that have daughters post-ultrasound. The hypothesis is that,

> 39As an indirect test of whether preferences changed, we considered exploiting the random variation in firstborn sex to look at whether EFM among firstborn children also changed post-ultrasound. However, this is not a clean test because the outcomes of firstborn children in firstborn-girl versus firstborn-boy families may have changed post-ultrasound because of spillovers to firstborns, for example, from fertility decline which relaxes resource constraints.

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