The majority of treated women understood how the vouchers worked: at endline, 81 percent reported knowing about the transportation reimbursement; 67 percent knew about the free FP consultation; 76 percent knew about discounted FP services at the ADC; and only 4 percent of women incorrectly thought that child health services were covered by our intervention. To cross-check whether women understood the differences between vouchers, we asked treated women if the program enabled them to offer their friend(s) a voucher if they visited the ADC with them. While 74 percent of women in the BAF arm positively responded to this question, only 6 percent in the Own group did the same.<sup>24</sup>

# **2.4 Data**

Our survey instruments collected data on household demographics and women’s socioeconomic background, birth history, contraceptive use, marriage and sexual activity, fertility preferences, autonomy, social networks, and utilization of health services, including FP services. To map the social network of our sample, we asked each woman to name up to five individuals in the study area, besides her husband and mother-in-law, with whom she converses most often about any issue (e.g., financial support, health, child health, and schooling) that is important to her; we call these individuals her “general peers”. In addition, we asked each woman to name up to five individuals in the study area, besides her husband and mother-in-law, with whom she discusses issues related to FP and reproductive health; we denote these individuals as her “close peers”.<sup>25</sup> We then collected socioeconomic, demographic, FP-related, and networkrelated information (e.g., measures of trust and closeness) from the surveyed woman for each of her identified close peers. Since a woman’s FP decisions may also be shaped by her husband, mother-in-law, and relatives outside the study area, we asked about her interactions related to FP with these key individuals and documented her beliefs about their attitudes towards fertility and FP. In this manner, we sought to capture each respondent’s immediate social neighborhood and the network characteristics through which attitudes about fertility and FP are most likely to be shaped and spread. In the module on health services utilization, we asked each woman about her access to FP clinics, such as, whether she has visited an FP clinic and whether she goes to the FP clinic alone or with other individuals.

Tables 1 and A.1 provide context for the types of women included in our experiment. Our sample is comprised of young married women who, on average, were 25 years old and had nine years of schooling and 1.9 children at baseline. The sample is predominantly Hindu and comprises women from Scheduled Castes (SC), Other Backward Classes (OBC), and general

> an increase in contraceptive use if they were already using an FP method at baseline.

> 24All results in this paper are robust to the exclusion of treated women who did not understand how their voucher worked from the estimation sample. These results are available upon request.

> 25In both baseline and endline surveys, all participants reported fewer than five close peers. Thus, five appears to be an effective upper limit on network size in our sample and is unlikely to introduce downward bias due to top-coding (Chandrasekhar and Lewis, 2012).

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