reproductive health and poverty reduction: what do (can, might, don’t)we know? tom merrick...

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

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

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

Tom MerrickHewlett/PRB London Research Conference ~ November, 2006

Page 2: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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?

Page 3: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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?

Page 4: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

Poor women get less care

20

30

40

50

60

70

80

90

100

Antenatal care Skilled attendant at delivery

Poorest 20% Richest 20%Source: World Bank/DHS 1999 Summary of data for 10 countries

% of populationreached by services

But does this, in turn, make them poorer?

Page 5: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006
Page 6: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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

Page 7: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

Adapted from work by Ruger, Jamison and Bloom 2001

Conceptual framework: early childbearing and poverty

Page 8: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

Poverty measurement, concepts

Income poverty Expenditure and consumption Capabilities (Sen):

Education Health Social and economic inclusion

Page 9: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

Our review focused on three sets of RH outcomes

1. Early childbearing 2. Maternal mortality and morbidity 3. Unintended, mistimed pregnancy &

large family size

Page 10: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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.

Page 11: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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.

Page 12: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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)

Page 13: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

The causality problem

ReproductiveHealth Outcome

PovertyIndicator

Possible third causal variable

Page 14: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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.

Page 15: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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.

Page 16: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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

Page 17: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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

Page 18: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

Percent of kids who progress to secondary school (1997 baseline)

Mother’s age* at first birth

18 & under 19 & over

All kids 41% 49%

Boys 50% 54%

Girls 33% 44%

(*mothers 25-39 in ’97)

Page 19: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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

Mother’s age* at first birth

18 & under 19 & over

All kids 56% 65%

Boys 58% 67%

Girls 54% 63%

(*mothers who were 25-39 in 1997)

Page 20: Reproductive Health and Poverty Reduction: What Do (can, might, don’t)We Know? Tom Merrick Hewlett/PRB London Research Conference ~ November, 2006

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