1. Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

2. Why study RH/poverty links: Financing of the "Cairo" agenda has fallen far short of changing needs. Changed funding modes: poverty- reduction credits, with MDG focus, guided by evidence about social sector investments and poverty reduction. How strong is the evidence that poor RH outcomes undermine poverty reduction?

3. Macro evidence that fertility decline helps economies grow Rapid fertility declines in East Asia created a demographic bonus—a temporary bulge in working ages that enabled greater investment. Cashing in on bonus required "good" economic policies: open economies, job creation, investments in health and education, gender equity. Is there a parallel household-level story?

4. Poor women get less care Poorest 20% Richest 20% Source: World Bank/DHS 1999 Summary of data for 10 countries % of population reached by services But does this, in turn, make them poorer?

6. Do poor RH outcomes keep households poor? Poverty analyses by others suggests: Not much direct impact of RH outcomes (early childbearing, unintended pregnancy, maternal mortality) on poverty in households. Linkages are indirect—via health, education, consumption—see chart 

7. Adapted from work by Ruger, Jamison and Bloom 2001 Conceptual framework: early childbearing and poverty

8. Poverty measurement, concepts Income poverty Expenditure and consumption Capabilities (Sen): Education Health Social and economic inclusion

9. Our review focused on three sets of RH outcomes 1. Early childbearing 2. Maternal mortality and morbidity 3. Unintended, mistimed pregnancy & large family size

10. Adverse effects of poor RH: quick summary Health: strong evidence on obstetric complications, unsafe abortion, low birth weight, lasting health problems affecting productivity, well-being. Schooling: evidence is good, includes debate on intergenerational transmission of poverty via early childbearing and school drop out. Well-being (consumption, productivity): evidence harder to find, impact affected by welfare and educational policies, labor market conditions.

11. Common threads: Context matters (fosterage, labor market conditions, stage of demographic transition). Causality is very difficult to demonstrate (many feedbacks). Scarcity of information on maternal deaths in survey data.

12. Context Child rearing customs: fosterage mitigates impact of early childbearing, maternal mortality in Africa Labor market conditions in Latin America affect link between women’s work and fertility Effects are more pronounced when conditions are changing (an echo of the macro story)

13. The causality problem Reproductive Health Outcome Poverty Indicator Possible third causal variable

14. For a stronger evidence base: Apply analytical techniques that can overcome the problems of mutual causality ("natural experiments"). Make more use of longitudinal data that enable tracking of effects over time (our work with Progresa/Oportunidades data). Get more mileage out of existing data sources (DHS, LSMS). Address knowledge gaps: for example, effects of morbidity associated with poorly managed obstetric complications.

15. Country-level work is needed: Research on P/RH consequences suggests that impacts affected by context: stage of demographic and epidemiological transition, political, economic and social contexts, including gender, so we need country studies It's not always necessary to have "gold standard” causal research to make the case in each country. It is important to link country evidence to relevant international evidence.

16. Using panel data from Mexico’s Oportunidades (Progresa) to study RH & Poverty Links Conditional cash transfers (CCTs) to poor households for education, health, nutrition Evaluation: baseline in 1997-98, follow- on surveys in 1999, 2000, 2003 Initially controlled experiment, but controls lost as more localities included in program Survey covers some aspects of RH, but limited information in baseline; there’s an RH module in 2003

17. Our research objectives: See whether a panel survey can help us study RH- Poverty link Initial focus on early childbearing: Do kids of early-CB mothers have worse educational outcomes (progression to secondary school—attendance by kids who’ve completed six grades) Existing evaluations (Schultz 2000) of CCTs showed improvements in secondary enrollments, especially girls Could CCTs have reduced enrollment gap relative to kids of later CBers Hypothesis is of interest because welfare and GED helped adolescent mothers (and their kids) in the USA

18. Percent of kids who progress to secondary school (1997 baseline) Mother’s age* at first birth 18 & under19 & over All kids41%49% Boys50%54% Girls33%44% (*mothers 25-39 in ’97)

19. Percent of kids who progress to secondary school (2003 follow-up) Mother’s age* at first birth 18 & under19 & over All kids56%65% Boys58%67% Girls54%63% (*mothers who were 25-39 in 1997)

20. What we’re learning Enrollment gap existed in 1997-98, eight percentage points, large for girls Overall enrollments improve by 2003, probably because of CCTs (control problem in 2003, also issues of supply side) Early childbearing gap persists, but girls catch up a lot more than boys Difficult to show that early CB “caused” gap (endogeneity, trying to disentangle) May be able to attribute narrowing of gap to CCTs (of interest because of possibility of better targeting) Using existing panel surveys is very challenging