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Evaluating the impact of conditional cash transfer programs on fertility: the case of the Red de Protección Social in Nicaragua


Evaluating the impact of poverty-reduction programs on fertility is complicated given that changes in incentives to have children take time to be incorporated into decision making and evaluation periods are usually quite brief. We explore the use of birth spacing as a short-run indicator of the impact of poverty-reduction programs on fertility. The data come from a Nicaraguan conditional cash transfer program that offers incentives for poor households to invest in children’s health, nutrition, and education. We estimate a stratified Cox proportional hazard model and find that the program decreased the hazard of a birth, indicating an increase in birth spacing.

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  1. Simulations were run to examine whether real changes in long-term fertility can be captured in the short run using spacing versus measures of birth. The results indicated that significant results are found for spacing and not number of births, particularly when the sample is small and when the time period is short. The results also indicated that increases in fertility are easier to identify as measured by births than are decreases in fertility. Thus, birth spacing measures are more valuable for these types of changes.

  2. The mortality rate for children born less than 2 years after another child is 60 per 1,000 live births, while that for children born 2 to 3 years after another child is 28 per 1,000 live births.

  3. In addition to the cash transfers for households, the program also included increased resources for schools and the contracting of a basic health care service package for program areas through NGOs.

  4. It is not exactly clear whether beneficiaries were explicitly told that the benefits would only last 3 years, however, they were informed that the program was not permanent.

  5. Although it is not possible to measure the start of the first risk period precisely, Pawloski et al. (2004) report the average age at menarche among a sample of girls in Managua to be 12. These data show that some women have their first birth as young age 12. The small number of women that reported a child was born before age 12 are not included in the sample.

  6. Since spacing measures the time between births, not conceptions, starting the next risk period 7 months after a birth allows for the possibility that a women conceives immediately after a birth and delivers prematurely. This is consistent with spacing reported from the Nicaragua DHS of 2001, where birth intervals are tabulated beginning at 7 months (INEC et al. 2002). Estimates were insensitive to whether we use an alternative minimum of 8 or 9 months between a birth and the start of the subsequent risk period.

  7. We assume a minimum of 7 months for a birth to occur after conception. Since transfers began in the control group in May of 2003, the earliest time at which a woman in the control group could have a birth that was influenced by the program is January 31, 2004.

  8. Only those children that died after the baseline survey or that were captured through the child mortality questions are observed. To be captured through the mortality questions, a child must have been the women’s most recent birth and have been born after 1996.

  9. When a woman’s reported number of live births equals the number of children observed (including those having died), it is assumed that all births are observed. When the reported number of live births is greater than the number of children observed, it is assumed that for women age 35 or younger, a missing birth is most likely to be an intermediate birth and not the first birth. For women over age 35, it is assumed that the first birth is not observed in the data when the earliest observed birth occurred when the women was 24 years old or older and that the children that are observed are the most recent births.

  10. Table 2 shows that nearly all of the median birth intervals are greater than 30 months. Since we find that the program decreases the probability of a birth, median birth intervals are likely to be longer. Given the small number of risk periods that begin after the program began and the short observation period, we are not able to estimate post-program median birth intervals.

  11. Adding age squared and its interaction with time at risk also does not change this result.

  12. A further test for pre-program differences in the hazard was conducted by limiting the observation period to only pre-program time and including a treatment group dummy. The coefficient on the treatment indicator was not significant, indicating that there were no differences in the hazard of birth between the two groups prior to the start of the program.


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The authors thank John Maluccio for access to the data as well as for providing valuable insights into the operation of the program. Eric Jensen, other participants at the 2008 Population Association of America Annual Meeting, Dean Jolliffe and two anonymous reviewers provided valuable feedback and suggestions.


The views expressed in this paper are those of the authors and do not necessarily reflect the views of the Economic Research Service or the US Department of Agriculture.

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Correspondence to Jessica E. Todd.

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Todd, J.E., Winters, P. & Stecklov, G. Evaluating the impact of conditional cash transfer programs on fertility: the case of the Red de Protección Social in Nicaragua. J Popul Econ 25, 267–290 (2012).

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  • Fertility
  • Conditional cash transfer programs
  • Hazard model

JEL Classification

  • J13
  • C41
  • H53