Presented by Halsey Rogers and Kathleen Beegle World Bank June 4, 2009

1. Fertility, Reproductive Health and Economic Development:Preliminary results of the World Bank research program supported by the William and Flora Hewlett Foundation Presented byHalsey Rogers and Kathleen Beegle World Bank June 4, 2009

2. Thematic areas • Fertility and investments in child quality • 4 studies • Fertility, poverty, and family welfare in the time of HIV/AIDS • 2 studies • Fertility and female labor supply • 2 studies

3. Thematic Area 1: Fertility and investments in child quality • 4 research projects in this category • Family size • Family size and early childhood development: evidence from Ecuador • Declining fertility and rising household investment in education in Vietnam • Gender preference • Development, modernization, and childbearing: The role of family gender composition • Financial incentives for female births and parental investments in daughters in North India

4. Motivating question: How do fertility choices affect investments in children? • A large literature documents associations between family size and children’s outcomes: • In developed countries, many studies have documented a negative association between family size and educational attainment • Research in developing countries has documented negative associations between children’s health nutritional outcomes and family size • Negative associations between family size and child outcomes could be due to a number of factors: • Resource dilution (both financial and parental) produces “quality-quantity” tradeoffs. Son preference adds another dimension to resource dilution, as parents prefer to invest in sons than in daughters • Changes in family dynamics—larger families may have lower “average maturity” of household members • Omitted variables or selection: characteristics of families that result in larger family size also result in poorer child outcomes • This set of studies documents determinants of family size and tests quantity-quality hypothesis in ways that control for selection/omitted variables

5. Family size and early child development: evidence from Ecuador Christina Paxson (Princeton University) and Norbert Schady (World Bank)

6. Questions and data • Research questions: • Part 1: What is the association between (1)cognitive and nutrition outcomes in early childhood and (2) family size? • Part 2: Do children in families that grow between baseline and follow-up experience (relative) declines in their cognitive and nutritional outcomes? • Use detailed information on maternal characteristics, including cognitive ability, mental health and parenting behaviors • Information on multiple children in the households permits within-family estimates, and longitudinal information makes it possible to examine how the presence of “new” children influences the outcomes of their older siblings • Sample • 4200 low-income families with about 6700 children aged 0-6 at baseline • From rural and urban areas of 6 provinces in Ecuador • Longitudinal data on families, with two interviews spaced approximately 18 months apart, with 1,124 births between baseline and the 1st follow-up

7. Test of family-size effect • If family size merely reflects family-specific unobservables, we expect that children of families that are going to grow will fare worse • If family size has a negative effect on children, we expect that children in families that grow will experience declines in outcomes relative to children in families that remain the same size

8. Result 1: Cognitive and nutritional outcomes are strongly associated with family size (1)

9. Result 1: Cognitive and nutritional outcomes are strongly associated with family size (2)

10. Result 2 • However, there are large differences in the characteristics of large and small families • Select one- and two- child families at baseline • Examine outcomes that were measured at both waves: TVIP score, hemoglobin and height • Use panel data to: • Examine whether the children in families that grow between baseline and follow-up have worse outcomes at baseline • Examine whether children in families that grow between baseline and follow-up experience declines in their cognitive and nutritional outcomes

11. Table 5a – Child outcomes at baseline and changes in outcomes between baseline and follow-upOne-child families

12. Table 5a – Child outcomes at baseline and changes in outcomes between baseline and follow-upOne-child families

13. Table 5b – Child outcomes at baseline and changes in outcomes between baseline and follow-upTwo-child families

14. Summary and conclusions • Large negative associations between family size and children’s cognitive and nutritional outcomes • These results indicate that associations documented later in life, for education and earnings, are evident in early life • However, little evidence of deterioration in children’s outcomes or in parenting quality with the addition of a new child • Children in families that are going to become larger have poorer outcomes (Table 5) • This evidence is consistent with selection stories--common factors drive family size and child outcomes • Current analysis (still preliminary) analyzes outcomes using a third round of data • Do negative causal effects of family size manifest themselves after a longer time period? • Are they more likely at larger family sizes than the ones we observe in waves 1 and 2 of our data?

15. The decision to invest in child quality over quantity: Declining fertility and rising household investment in education in Vietnam Hai-Anh Dang and Halsey Rogers (World Bank)

16. Methodology and data • Approach: Use data from Vietnam to investigate the hypothesized child quantity-quality tradeoff: • Question: Are lower fertility levels making it possible for households to invest more in their children’s human capital? • IV approach, using instruments from different sources, incl. our own survey • One innovation: Good data on private tutoring expenditures, so we’re not just relying on (e.g.) enrollment or attainment as indicator of parental investment in education • Why Vietnam? Very rapid fertility decline and educational advances • Data sources • 2006 household survey (VHLSS) • DHS 2002 • New survey focused on private tutoring (2008)

17. Correlation between quantity and quality (Tutoring)

21. Summary of findings • Larger number of siblings predicts lower educational investment in Vietnam, in un-instrumented regressions • Result holds for both school enrolment and use of private tutoring • IV analysis partially confirms this quality-quantity tradeoff • Impact of sibship size on school enrolment is strongly negative (from -0.5 to -1.0 per sibling) and significant across instruments • Impact on tutoring investment is not robustly significant, though always negative • Distance to family planning center seems the most promising instrument; other instruments yield mixed results, perhaps due to small N and data issues • Coefficients are generally larger in IV than in un-instrumented regressions • Implications • Better availability of family planning may increase investment in education • Two-child policy may have led to more education in Vietnam

22. Development, modernization, and childbearing: The role of family gender composition Deon Filmer, Jed Friedman, and Norbert Schady (all World Bank)

23. Research question and methodology • Research question: What is the relationship between continuing fertility and the gender make-up of existing children? • Focusing on one indicator of preference for sons over daughters: son preference in fertility decisions • Note that differential gender-related behavior could be the result of “taste-based” gender discrimination, but also other causes • Focus here is on measuring the extent of son-preferred differential stopping behavior (DSB), regardless of its causes • Methodology • Calculate probability of additional birth if zero sons vs. zero daughters in family already • Data: 158 DHS surveys, covering 1.3m women from 64 countries

24. DSB Where and when do we see the greatest differentials in stopping behavior? Results: • Differential Stopping Behavior largest in • Central Asia (9.4 percentage points) • South Asia (7.8 percentage points) • Middle East/North Africa (5.8 percentage points) • No clear evidence of DSB in • Sub-Saharan Africa • Latin America and the Caribbean Probability of an additional birth

25. Where and when do we see the greatest differentials in stopping behavior? • Son preference increases at higher birth orders • Mean number of children per family is 4.1 in Eastern Europe and Central Asia (ECA), and 4.9 in South Asia. • In such high-fertility settings, the gender composition of lower-parity children is less important in determining future fertility. • But once parents are closer to achieving their total desired number of children, the gender composition of children already born becomes an important determinant of whether parents have another child. • For example, families with 4 or 5 children in South Asia are approximately 14 percentage points more likely to add another child if all of the children up to this point are girls rather than boys.

26. Does “modernization” reduce differential stopping behavior? Differential Stopping Behavior Urbanization and female education are often associated with higher, not lower, son preference in continuing fertility • For example, in South Asian countries, son preference is significantly greater for women in urban areas or with more education--and this pattern seems to have increased over time. • It’s possible that latent son preference manifests itself when fertility levels are low—that is, when families are closer to desired fertility at low parity—and indeed fertility has fallen among women in urban areas or with more education.

27. Possible implications of DSB for investment in girls • Differential stopping behavior driven by son preference is likely to exacerbate other forms of gender discrimination • Mean number of siblings of girls exceeds boys’ in regions where DSB is high (sons are preferred). • Girls in South Asia have about 0.13 more siblings than boys • in the Central Asian countries, the comparable number is 0.10 • in Sub-Saharan Africa, boys and girls have the same number of siblings • Studies on the association between family size and child outcomes usually show that more siblings dilute household and parental resources devoted to each child, a “quantity-quality” tradeoff. • If this association is causal, son preference, as manifested in gender-specific fertility choices is likely to have adverse consequences for girls since they will grow up in larger families.

28. Long-Term Financial Incentives And Investment In Daughters: Evidence From Conditional Cash Transfers In North India Nistha Sinha (World Bank) and Joanne Yoong (RAND)

29. Background and Program DescriptionGender Bias in Haryana State, North India One of India’s richest states, but among the worst in terms of female disadvantage 1990s: evidence of consistent gender gap in sex ratios at birth (Sudha and Rajan,1999) early childhood mortality (Filmer, King and Pritchett,1998) school enrollment for 6-14 year olds (Filmer and Pritchett, 1998) October 1994: Haryana State Government introduced Apni Beti Apna Dhan (ABAD), a conditional cash transfer program to address these issues Upon the birth of a daughter, families receive Immediate cash grant of Rs. 500 to cover post-delivery needs Government savings bond in daughter’s name, redeemable for Rs 25,000 (about $550) only on 18th birthday if still unmarried Additional bonuses for completed education or claim deferral Subject to belonging to poor or low caste households Sinha and Yoong (2009)

30. Program Evaluation Strategy and Empirical Challenges Full evaluation some years away: first beneficiaries turn 18 in 2012 Empirical challenge 1: No systematic data collection; uniformly implemented across Haryana in October 1994 without piloting Solution: Use data from India’s National Family Health Surveys (NFHS); repeated cross-sections Empirical challenge 2: No measures of actual participation in NFHS Solution:Program evaluation is limited at best to an intent-to-treat analysis (measuring effects of being eligible ); use data on eligibility criteria to identify “eligible individuals” among poor households or households belong to certain castes Empirical method: Basic Difference in Difference Specification (i.e. before and after program, eligible non-eligible girls or households) 1992 NFHS 1 Before program 1998/9 NFHS 2 2005-06 NFHS 3 1994 Program rolled out statewide Sinha and Yoong (2009)

31. Results: Impact of the program (but recall the challenges of the program evaluation) • Increased girl child survival • Positive, significant estimated effects on sex ratio of living children for individual women • Perhaps due to less sex-selective abortion, since insignificant (but consistently positive) estimated effects on survival rates in early childhood • However, no effects on expressed preferences for girls • Increased health investment in children • Positive, significant effects on childhood vaccinations • Effects on education and marriage are limited by time horizon of data, but early results for education suggest positive relationship

32. Thematic Area 2: Fertility, Poverty and Family Welfare in the time of HIV/AIDS • HIV/AIDS is the leading cause of prime-age death in Africa. Early sexual initiation, early marriage, risky sexual practices, and commercial sex work have all contributed to the transmission of the pandemic—with consequences for the wellbeing not only of the person who has AIDS, but also for others in their household. • These studies seek to understand the socio-economic consequences of early marriage and non-marital sexual relations, and of efforts to reduce premature adult mortality through the use of anti-retroviral therapy • 2 research projects in this category which are entail longitudinal surveys: • Marriage Transitions and HIV/AIDS in Malawi • HIV/AIDS and the impact of treatment on family and individual welfare

33. Marriage Transitions and HIV/AIDS in Malawi Kathleen Beegle (World Bank), Berk Ozler (World Bank) and Michelle Poulin (Brown University)

34. Research question and methodology • Research question: What is the relationship between socioeconomic characteristics of young people, economic shocks they experience, their partnership choices, sexual behavior, and risk of HIV infection? • To explore in detail young people’s transition into marriage and the effect of these transitions on their subsequent outcomes, such as health, fertility, labor market participation and important outcomes for their young children, such as anthropometrics, nutrition, cognitive ability, etc • Methodology: new data collection effort • Surveys integrated over topics not normally covered in traditional household surveys. • Specific sample of young adults. The study is following an initially never-married sample of 1,185 young Malawians for at least 3 years, using an array of panel data collection methods.

35. Details of the data effort • Annual household survey started in summer 2007. Modified LSMS-style household questionnaire, accompanied by a detailed individual component on marital aspirations and sexual behavior . • Interim in-depth partnership interviews (PIs) collected from Feb-March between rounds of the annual household survey. • HIV testing introduced in summer 2008 on a random sub-sample (to address concerns of the influence of testing itself on subsequent behaviors/outcomes). • Tracking individuals who move: This is a highly mobile population. • Last round of data planned for summer 2009.

36. Preliminary findings • 28 of the 596 young women, aged 14-21 in our sample (5%) have ever given birth and all of them have given birth only once. • The mean (and median) age at birth for these young women is 17 (youngest 14 and oldest 20). • 35 of the 583 men, aged 17-25 in our sample (6%) reported than a women has given birth to their child at least once. • The mean (and median) age for these young men when the at the time of the first birth was 19 (youngest 16 and oldest 22). • Approximately, one third of the women and three quarters of the men reported ever having sex.

37. HIV/AIDS and the impact of treatment on family and individual welfare Damien de Walque (World Bank), Harounan Kazianga (World Bank) and Mead Over (CGD)

38. Research question and methodology • Research question: What is the impact of HIV treatment on… • Lives saved and health outcomes • Labor supply of patient and family members • Schooling and welfare of children • Other welfare indicators • Methodology: new data collection effort • Biomedical follow-up including data on treatment regimen and treatment success (CD4 counts) • Household surveys (HIV patients and general population) including health, schooling, labor force. • 7 countries: Burkina Faso, Ghana, Kenya, India, Mozambique, Rwanda and, South Africa

39. Methodological challenges • It is not possible to randomize ARV treatment! • But in some countries, can evaluate some experiments on the conditions of ARV delivery. • Rwanda: performance-based contracting for HIV/AIDS services in health facilities • South Africa: food and counseling intervention as adherence support. • Kenya: text messaging intervention as reminders for adherence

40. Preliminary findings from baseline surveys • Access to pediatric ART appears limited (evidence from Mozambique and Ghana) • Parents and family might not identify weak or sick children as suffering from HIV/AIDS • HIV/AIDS affects not only the mental health of persons with AIDS but also affects the mental health of family members in these households (evidence from Ghana) • Compared to other patients, HIV/AIDS patients seem to receive better health services (evidence from Burkina Faso): • They wait less • They receive higher quality care

41. Thematic Area 3: Fertility and female labor supply • Motivating question: What is the relationship between fertility outcomes and women’s labor market participation? • 2 research projects using household survey data • Fertility and women’s labor force participation (96 DHS surveys) • Fertility and Women’s Labor Supply in A Low Income Rural Economy (the case of Matlab, Bangladesh)

42. Fertility and women’s labor force participation Elizabeth King (World Bank) and Maria Porter (University of Chicago)

43. Research question and methodology • Research question: This study focuses on the relationship between fertility outcomes and women’s labor market behavior. • As fertility declines around the world, childbearing patterns change in three ways: women may delay their first birth, space their births, or stop having children at an earlier age than previous cohorts. Each of these changes is likely to have a different impact on the ability of women to work outside the home and on the decisions they make regarding work and child-bearing • Methodology: • Analysis of 96 Demographic & Health Surveys in 59 countries

44. Methodological challenges • Endogeneity between fertility and labor market behaviors of women. • Most previous studies of the relationship between fertility and labor force participation have relied on cross-sectional data, but with cross-sectional data, it is difficult to correct for both the endogeneity of fertility and the impact of unobserved heterogeneity among women. • In the absence of natural experiments that may affect fertility choice but not otherwise affect other behaviors such as child outcomes, an econometric approach is needed in order to identify and quantify such an effect • Using exogenous shocks to fertility (twins in first birth and sex of first two births), we estimate how fertility affects women’s labor force participation decisions across different regions of the developing world

45. Effect of Sex at 1st Birth on Women’s LFP in Sub-Saharan Africa

46. Summary of Findings • Women are more likely to have worked in the past year if they have more children in sub-Saharan Africa, and for some older women in South Asia. • Younger women in South Asia face the tradeoff between more children or work in the labor force. These women are less likely to have worked in the past two years as a consequence of having more children.

47. Summary of Findings for Sub-Saharan Africa, where the income effect dominate • Women have more children if they had twins in the first birth, if the first two births were the same sex, or if the first two births were girls. • Women have fewer surviving children if their first or second child was a boy. • Positive effects on the number of surviving children are strongest for women who have completed secondary schooling or higher. • More educated women are also more likely to work when they have twins in the first birth. • Any effect of the sex of first birth(s) does not vary much by education.

48. Fertility and Women’s Labor Supply in A Low Income Rural Economy: the case of Matlab, Bangladesh Mattias Lundberg (World Bank), Nistha Sinha (World Bank) and Joanne Yoong (RAND)

49. Study Objectives & Context Explore effect of children on women’s labor force participation using data from rural Bangladesh Rural labor market characterized by Low female participation in wage labor Cultural practice of female seclusion Home based production by women Women’s work in rural Bangladesh: Based on a question about primary activity, 58% of women and 82% of men aged 20-55 are “working”: Among those who report earnings (1995), Men’s mean earnings were 21,370 Takas Women’s mean earnings were 3,005 Takas Most women’s (87%) location of work is home Women report activities such processing rice, raising poultry and livestock

50. Data and methodology Data: Matlab Health and Socioeconomic Survey 1996 Survey of 4,363 households in a demographic surveillance area in rural Bangladesh. Surveillance area is site of a family planning program experiment Survey covered 142 villages in treatment and control areas Methodology: Identify causal effect of children on women’s labor supply Unobservables influence both women’s decision to work and their family size Standard methodology finds a variable that influences fertility but not labor-force participation (Literature: twins, sex of first-born) This paper exploits women’s exposure to a family planning program experiment