sex composition), and the subsample of women with three girls (and, separately, those with three boys, two boys and one girl, and two girls and one boy) as earlier-born children. As a further check, I also estimate regressions using the full sample of women and including interaction terms between _girl_ and the sex of earlier-born children.

Identification with fixed effects requires that women with at least three, four, or five children ever born are considered.<sup>27</sup> The prediction with son preference is that the birth intervals succeeding the birth of girls should be significantly shorter ( _β_ 1 _<_ 0) than for boys. This effect should be larger the more girls there are among earlier-born children, because of mounting pressure for a son.

# **5 Main results**

## **5.1 Fertility results**

Table 3 shows the estimates of the effect of a first-born girl on the number of children ever born. In column (1), the coefficient on _firstborngirl_ is positive but not significant. In column (2), age at first birth is added among the controls and the coefficient is now larger and significant at the 10% level. The number of years of education is included in column (3) and the coefficient of interest is very similar to column (2), probably because of the positive correlation between age at first birth and education. Column (4) additionally controls for husband’s characteristics, therefore restricting the sample to married women (with information on their husband’s age and education) and yields similar results. As expected, adding the controls for first-born child mortality in column (5) and restricting the sample to continuously married women (column 6) leads to a further increase in the coefficient of interest. Specifically, compared to women with a first-born son, women with a firstborn (surviving) daughter have 0 _._ 07 more children (column 6) (this effect is significant at the 1% level), which correspond to a 1.7 percent increase of the number of children ever born (considering that the average number of children born to women with a first-born son in this sample is 4.32).<sup>28</sup> The effect is 2 percent in the subsample of women age 30–49 (column 8), who have had more children and are closer to completed fertility.<sup>29</sup>

> 27The percentages of women with at least three, four, or five children ever born in this sample are the following: 70%, 55%, and 42%, respectively.

> 28The estimated effect obtained using a negative binomial regression model for over-dispersed count data is shown in appendix table A.1 and is consistent with the OLS estimates (region and ethnic trends are not included due to failed convergence of the model with all the controls). A poisson regression yields similar results (with all controls as in column 6 of table 3 including region and ethnic trends), but it is less appropriate than the negative binomial regression due to over-dispersion of the dependent variable (the Pearson test for goodness of fit of the poisson model rejects that the conditional variance of the variable ‘children ever born’ is equal to its conditional mean).

> 29For comparison, Dahl and Moretti (2008) use Census data for the Unites States and find that women aged 18–40 with a first-born girl have 0.3 percent more children than women with a first-born boy. Using data for India, I find that women aged 15–49 with a first-born girl have 0.295 more births (equivalent to a 9 percent increase).

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