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The unintended effects of cash transfers on fertility: evidence from the Safe Motherhood Scheme in India

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India launched the Safe Motherhood Scheme (Janani Suraksha Yojana or JSY) in 2005 in response to persistently high maternal and child mortality rates. JSY provides a cash incentive to socioeconomically disadvantaged women for childbirth at health facilities. This study explores some unintended consequences of JSY. Using data from two large household surveys, we examine a policy variation that exploits the differential incentive structure under JSY across states and population subgroups. We find that JSY may have resulted in a 2.5–3.5 percentage point rise in the probability of childbirth or pregnancy over a 3-year period in states already experiencing high population growth.

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  1. For example, the infant mortality rates of India, Nepal, Bangladesh, and Sri Lanka were 47, 39, 37, and 11 per 1000 live births in 2011, respectively. Source: Level and Trends in Child Mortality. Report 2011. Estimates Developed by the UN Inter-agency Group for Child Estimation (UNICEF, WHO, World Bank, UN DESA, UNPD).

  2. Source: MDGMonitor, United Nations Development Programme,

  3. Assuming US$1 = INR 60, approximately. The annual budget of JSY in 2010–11 was INR 16.18 billion. INR = Indian rupees.

  4. Randive et al. (2013) also find a positive association between JSY and institutional deliveries.

  5. The phrases “low-performing states” and “high-performing states” are official JSY terms for describing these two groups of states.

  6. See Hotz et al. (1993) for a review of the literature on economics of fertility. Del Boca (2002) finds that the availability of publicly funded child care increased fertility in Italy. Milligan (2005) finds that pronatalist tax benefits may have increased childbirth probability in Canada, while Laroque and Salanié (2013) estimate that child benefits might increase total fertility in France. Cohen et al. (2007) and Mörk et al. (2013) find similar effects of fiscal benefits on fertility in Israel and Sweden respectively.

  7. The Honduran Programa de Asignación Familiar (PRAF-II) CCT provides two different cash incentives for schooling and health. One of them is a US$48 cash incentive, per person per year, provided for health care and nutrition of pregnant and nursing mothers, and young children (Moore 2008).

  8. Except Jammu & Kashmir and Assam, the rest are EAG states.

  9. Before 2013, the BPL women in HPS needed to be at least 19 years old to be eligible for JSY. This restriction has been now abolished.

  10. In DLHS 2007–2008 data, 41, 12.9, and 19 % of villages in India had a primary health sub-center, a primary health center, and a private clinic, respectively. The availability of other types of facilities, such as community health center or private hospital, was even lower. The average distance from a village to a primary health center and a private clinic was 9 and 10 km respectively (IIPS 2014).

  11. The state of Nagaland was not surveyed in DLHS-3.

  12. Our results are robust to the inclusion of births during 2004 and 2005 in our analysis, as discussed later (also see Table 8).

  13. In the absence of a below-poverty-line indicator in DLHS-2, we use an approximate measure for poverty. First, we use principal-component analysis to create an household-level wealth index following Filmer and Pritchett (2001). Only variables that are common to both DLHS rounds are considered in this index—for example, the possession of a radio, sewing machine, TV, bicycle, car, and so on—and indicators of housing condition such as construction quality, availability of toilets, sources of drinking water, and the type of cooking fuel used. Then, we consider households on or below the 30th percentile of the wealth index distribution, separately in DLHS-2 and DLHS-3, as approximately poor. For comparison, the national poverty headcount rate was 33.8 % in India in 2009 (Source: World Bank data,, accessed May 5, 2015)

  14. We use maps from the 2001 Indian census, and the GADM ( database, to identify the districts along state borders. There are several extra districts in the DLHS-3 data. A new district in DLHS-3 was typically created by carving out from a parent district in DLHS-2. In such cases, we mapped the DLHS-3 district back to the parent district. However, one particular border district in DLHS-3, Mewat in the state of Haryana, was created from more than one parent DLHS-2 districts. We exclude these parent districts and Mewat from our analysis. Also excluded from analysis is the state of Nagaland which was surveyed in DLHS-2 but not in DLHS-3. Figures 1 and 2 in the appendix present the district maps.

  15. For example, pregnant women may visit or temporarily live at their natal home for the purpose of childbirth. However, DLHS-3 data show that less than 1 % of pregnant women who reported receiving antenatal care did so at their natal homes, and only 3.75 % of the most recent child deliveries took place in natal homes.

  16. 17 We include 26 indicators of household asset ownership and housing condition in the pre-JSY (2001–2003) propensity score estimation, and 46 such indicators in the post-JSY (2006–2008) propensity score estimation. The difference is a result of DLHS-3 collecting data on more such indicators as compared with DLHS-2.

  17. The availability of a dai may be associated with the rollout of JSY in a village. According to official JSY documents, traditional birth attendants are often trained and converted into ASHAs. Anganwadi centers operate under the Integrated Child Development Services (ICDS) of India, a large national program providing supplemental nutrition, immunization, health check-up and education, and preschool education to over 90 million women and children. See, accessed April 29, 2015.

  18. Powell-Jackson et al. (2015) use a different way of estimating the coverage of JSY. They consider the proportion of women giving birth at a public facility who receive the cash benefit as an indicator of coverage. This method ignores births at accredited private health facilities. In addition, the inconsistencies in JSY uptake and usage data at the level of the mother from DLHS-3 have been already pointed out by Das et al. (2011).

  19. Past experience from India’s coercive fertility control policy (abolished in 1996) show that minorities and the poor were disproportionately targeted by health workers seeking to meet contraceptive targets mandated by the government (Sangwan and Maru 1999). These groups may be similarly vulnerable to coercion by health workers under JSY.

  20. One possible confounding factor for the fertility effect of JSY seen in our results is a change in the family planning policy. If the family planning policy was relaxed in LPS at the same time as the introduction of JSY, the effect of JSY will be overestimated. However, both the National Population Policy of 2000 and the Working Group on Population Stabilization for the Eleventh Year Plan (2007–2012) of India vigorously emphasized the need for family planning particularly in LPS states (GoI 2006). Therefore, any concurrent relaxation of family planning policies is highly unlikely.

  21. In additional analyses, we examined the space between two most recent births during the study period for women with multiple births in the data. We do not find any statistically significant effect of JSY on birth spacing. This could be either due to the small sample size of women with multiple births during the 3-year study period, or an indication of JSY’s positive effect on total fertility. Powell-Jackson et al. (2015) also suggest that the fertility effect of JSY may not be temporary, as it increased with the program’s age. However, longer-term data are required for more research on such effect.


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We thank the two anonymous reviewers for their very helpful comments, and Ashvin Ashok, Nikolay Braykov, and Nestor Mojica for their research assistance.

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Correspondence to Arindam Nandi.

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Nandi, A., Laxminarayan, R. The unintended effects of cash transfers on fertility: evidence from the Safe Motherhood Scheme in India. J Popul Econ 29, 457–491 (2016).

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