Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know?

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 % of population reached by services Richest 20% Poorest 20% Source: World Bank/DHS 1999 Summary of data for 10 countries 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. Conceptual framework: early childbearing and poverty Adapted from work by Ruger, Jamison and Bloom 2001

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 Possible third causal variable Reproductive Health Outcome Poverty Indicator

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) (*mothers 25-39 in ’97)

19. Percent of kids who progress to secondary school (2003 follow-up) (*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