compare it with savings afterwards. However, 2006 REDS only reports cross-sectional information on savings. Note, however, that REDS is a panel survey, and the same households were also surveyed in 1999. Unfortunately, the survey questions were not exactly the same in both rounds, making it difficult to use the 1999 round for a panel-specification without significant measurement error.

To investigate whether FG parents save more than FB parents due to expected future dowry payments, we estimate the following specification for mother _i_ from caste _c_ in state _s_ and whose first child was born in year _t_ : where _Savingicst_<sup>2008denotes various measures of household saving last year reported in 2008;</sup><sup>_FirstGirli_</sup> indicates that the firstborn child is female; _Dowrycst_ is expected dowry defined as the average dowry paid by brides from caste _c_ in state _s_<sup>30</sup> who were married during the year of the child’s birth or the prior four years (i.e., during _t, t −_ 1 _, t −_ 2 _, t −_ 3 _, t −_ 4);<sup>31</sup> **X** _i_ is a vector of covariates comprising parents’ years of schooling and ages at the time of survey, and indicators for religion and month of survey. We report unweighted regressions in the main set of tables. However, our results remain the same when we use weights.<sup>32</sup> Standard errors are clustered at the state level. We also compute standard errors that are wild-cluster bootstrapped by state as a robustness check.

The coefficient _β_ 2 captures how savings in FB families respond to expected dowry receipts. The coefficient of primary interest is _β_ 1 which captures the differential response of FG families to expected dowry, relative to the response of FB families. To exclude other confounding factors related to the caste, state, gender, and year of birth of the firstborn child, we control for all main and interaction fixed effects for these factors. For instance, if certain castes are richer and therefore save more, the caste fixed effects ( _ωc_ ) would capture this confounding variation. If there is state or time variation in wealth status of various castes that can explain the differential saving behavior, it would be captured by the state-caste and caste-year fixed effects ( _φct_ and _ψsc_ ). The state-year fixed effects ( _πst_ ) take into account any differential trends across states in economic prosperity. If the fertility response to a firstborn girl differs across castes or states or time due to differential son

> 30State reflects the state of residence at the time of survey, and not necessarily the state of marriage or the state of first birth. However, this is unlikely to be a major source of measurement error due to low inter-state migration in India, especially after marriage.

> 31The robustness checks using alternate definition of dowry expectation are provided in Section 7.

> 32The 2006 REDS data do not provide sampling weights; hence we construct them in the following manner, based on Andrew Foster’s suggestion. Using the village listing data which includes all households in REDS villages, we create an indicator for the households that are actually sampled and regress it on the observables in the listing data. These inverted predicted probabilities serve as weights, assuming that the observables capture differential reasons for being surveyed. The observables in the listing sheet data used to construct weight are household size, number of earners in the household, head’s age, head’s years of schooling, indicators of head’s caste (SC, ST, OBC, upper caste), religion (Muslim), and gender, and state fixed effects.

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