Health, Nutrition, Education and Equity

Jere R. Behrman

University of Pennsylvania

World Bank Conference "Equity, Development and Policy:

Evidence, New Ideas & Future Directions" 10 June 2011

This paper reviews selected relatively recent evidence on:

1. Short-run policy impacts on human capital investments

2. Longer-run impacts of human capital investments and some benefit/cost ratios

3. Impact of targeted policies on inequality and on poverty

1. Short-run policy impacts on human capital investments

1. Short-run policy impacts on human capital investments

1A. Early Childhood Development (ECD) Programs1B. Food for Education (FFE) Programs1C. Conditional Cash Transfers (CCTs)1D. Performance Incentives and Vouchers1E. Conclusions

1A. Early Childhood Development (ECD) Programs

ECD has multiple interacting components: Cognitive-language skills, Interpersonal skills, Social-emotional skills and Physical development (nutrition, sensory-motor)

Large numbers of children in developing world, estimated 200+ million, fail to reach their development potential -- four major risks: stunting, iron deficiency, iodine deficiency, and lack of cognitive and social-emotional stimulation*

*Grantham-McGregor, SM., YB Cheung, S Cueto, P Glewwe, LM Richter, BJ Strupp, 2007, “Over Two Hundred Million Children Fail to Reach Their Developmental Potential in the First Five Years in Developing Countries,” Lancet 369 (January): 60–70.

Age (months)

Z

-2

-1.5

-1

-0.5

0 0-5 6-11 12-17 18-23 24-29 30-35 36-41 42-47 48-53 54-59

Mean Z-scores for height-for-age relative to the new WHO standards for Peru, 2000

ECD Enrollment Rates for 3 & 4 y Olds by Income Quintile

(Engle et al 2011 Lancet)

No. of Mothers’ Activities in Last 3 Days that Support Child Learning by Income Quintile (Engle et al 2011 Lancet)

Evidence on impacts of ECD programs

What interventions have worked at scale to reduce the loss of developmental potential from the four major risks: stunting, iron deficiency, iodine deficiency, and lack of cognitive and social-emotional stimulation?

• Engle, Patrice L., Maureen M. Black, Jere R. Behrman, Meena Cabral de Mello, Paul J. Gertler, Lydia Kapiriri, Reynaldo Martorell, Mary Eming Young, International Child Development Steering Committee, 2007, “Strategies to Avoid the Loss of Potential Among 240 Million Children in the Developing World,” Lancet 369 (January), 229-242.

Effects of interventions on cognitive and social-emotional development

Type of intervention

Significant evaluations out of total

Effect sizes

Mainly centre-based

8 of 8 0.23 to 1.40

Mainly parent-child and parenting

5 of 6 0.45 to 0.8

Comprehensive 5 of 6 0.37 to 1.80

Effects of combined improved nutrition and environment and age

85

90

95

100

105

110

115

IQ

Severelymalnourished

Moderatelymalnourished

Wellnourished

<24 mos>24 mos

Adapted from Winick M, Meyer K, Harris R. Malnutrition and environmental enrichment and early adoption. Science 1975: 190: 1173-75 and Lien N, Meyer K, Winick M. Early malnutrition and “late” adoption: a study of their effects on the development of Korean orphans adopted into American families. Am J Clin Nutr 1977: 30: 1734–39.

Philippines ECD Program Effects: Age and duration (marginal PSM)

Armecin, G, JR Behrman, P Duazo, S Ghuman, S Gultiano, EM King, N Lee, and The Office of Population Studies, University of San Carlos ECD Team, 2006. “Early Childhood Development through Integrated Programs: Evidence

from the Philippines,”, 2006.

Characteristics of Successful Program According to Engle et al(2007)

• Comprehensive • Target disadvantaged children• Begin with younger children • Sufficient intensity and duration • Quality

– Training of staff, – Initiative and exploration in learning environment, – Partnership with families– Blend traditional child rearing with evidence-based

approaches

1B. Food for Education Programs (FFE)*• FFE programs aim to increase enrolment,

attendance and performance in school.– School feeding programs (SFP) –subsidy to school

attendance and increase in real income for family.– Take home rations (THR)-can be resold unlike SFP

programs. • Long history of FFE programs, e.g. World Food

Program operating for > 45 years. *For more details, see Behrman, JR, SW Parker, & PE Todd (BPT), 2011, “Incentives for Students and Parents”, in P Glewwe, ed. Education Policy in Developing Countries: What Do We Know, and What Should We Do to Understand What We Don’t Know? (in preparation)

Large Scale FFE Programs

• Global Food for Education pilot: USDA donated surplus U.S. agricultural commodities for use in school feeding and pre-school nutrition programs in 4000 schools in 38 developing countries between 2001 and 2003.

• World Food Program: operated by United Nations, 22.6 million beneficiaries in school feeding programs in 2008.

FFE Program Evaluations

• Large number of studies but few rigorous evaluations of Global Food for Education and World Food Program interventions.

• BPT focus on recent individual level school feeding projects with rigorous evaluations (mostly randomized).

• Bangladesh (5 studies), Burkino Faso (2) and Uganda (2), Jamaica (1) and Peru (1).

FFE Programs: Conclusions

• Generally positive impacts of FFE programs on enrollment and attendance.

• More limited results on performance in school including repetition rates and achievement tests.

• Few estimates of real resource costs and relationship to benefits.

1C. Conditional Cash Transfers (CCTs)

• Monetary transfers to poor families conditional on human capital investment, principally regular school attendance of children in beneficiary families.

• Over 30 countries in 5 continents with CCTs, around half with rigorous evaluations.

• Rigorous randomized large-scale evaluation accompanied initial Mexican PROGRESA/Oportunidades program in late 90s. – Implementation of many similar programs.– Impact evaluations implemented in initial program stages.

Literature on CCTs

• Substantial literature on short-run impacts in different contexts.

• Number of reviews of CCTs, most prominent probably 2009 WB PRR (Fiszbein & Schady).

• Behrman, Parker & Todd (2011) focuses mainly on studies carried out since WB 2009.

WB (2009) on CCTs

• Focus on results for short-run educational indicators for 10 countries with CCTs and rigorous evaluations (mostly randomized).

• Significant impacts on enrollment in all contexts with exception of Turkey.

• Impacts range from 2 to 13 percentage points in Latin American countries and 11 to 31 percentage points for countries outside the region (Bangladesh, Pakistan, Cambodia).

WB (2009) on CCTs

• Enrollment impacts higher in countries and contexts with lower levels of schooling.

• Impacts higher for poorer families than for less poor families.

• Evidence on achievement scores and longer-term education indicators “disappointing.” – Few available studies show no impacts on achievement

tests. • But only 2 based on achievement tests applied in the

household.

BPT (2011) on CCT Conditionality• Sig impacts on attendance/enrollment for Malawian girls 13-

22 y old randomized to conditional transfers but not to unconditional transfers vs. control group (Baird, McIntosh & Ozler 2010, WB Working Paper).

• Impacts 5-10 percentage points higher for Mexican Oportunidades families who received enrollment forms vs. those not receiving enrollment forms (unconditioned) (DeBrauw and Hoddinott 2010 JDE).

• Morrocan J-PAL study (in process)• Appears conditionality plays main role in generating

educational impacts, but conditionality has costs:– Individual compliance costs.– Program enforcement costs.

BPT (2011) onCCTs in Urban Areas• Colombia (Bogota): Randomized (1) traditional

CCTs for attendance, (2) some benefits delayed to beginning of next year & (3) some benefits linked to graduation and reenrollment in next level. Sig impacts on attendance in all 3 but higher impacts on reenrollment under (2) and (3). (Barrera-Osorio, Bertrand, Linden and Perez, 2011. American Economic Journal: Applied Economics).

• Matched control Mexican urban evaluation: enrollment impacts on children 6 to 20, about 3 percentage points, 0.1 grades of schooling. (Behrman, Gallardo, Parker, Todd and Velez, 2010)

BPT on Other Recent CCT Results• Gender: Impacts in some cases sig higher for boys (but

schooling attainment conditional on some enrollment for girls >= for boys) (Grant and Behrman 2010 Population Development Review)

• Spillovers on non-beneficiary children a priori could be either direction but in Mexican rural program are positive (Lalive and Cattaneo, 2009 ReStat and Bobonis and Finan, 2009 ReStat)

• Sig impact on achievement tests in math and English for girls in Malawi (Baird et al 2010 WB Working Paper).

• Longer-term impacts for initially 9 to 12 y olds after 6 y of benefits in rural Mexico: Boys 1 additional grade, girls 0.8; some evidence of increased work and substitution to non-agricultural work (Behrman, Parker & Todd, 2011 JHR).

Conclusions on CCTs• Popular program, new efforts likely to continue.

Evaluation challenging given bundle of goals including both current and long-run poverty alleviation

• Substantial evidence on enrollment impacts.• Some evidence on nutritional and other health–

related impacts.• Very limited evidence that improve learning and

achievement.• Evidence on longer-term impacts limited.

1D. Performance Incentives & Vouchers• Randomized cash grants for performance on

matriculation exams in 40 Israeli secondary schools. Students in treatment schools were 6 to 8 percentage points more likely to pass high school matriculation exam after one year (Angrist and Lavy, 2009 AER).

• Randomized scholarships for 15% highest scoring girls per district on standardized test in Kenya led to improvements of 0.2 standard deviations on achievement tests. Though students lower in the distribution had little chance of obtaining scholarship, they also showed significant impacts. (Kremer, Miguel and Thornton, 2009 ReStat)

• Aligning learning incentives (ALI) with randomization among 88 Mexican high schools of alternative monetary incentive payments based on level and improvement in curriculum-based math test scores: students only, teachers only, both students and teachers with own and group components. After two years if students receive incentives improvement of 0.4 to 0.7 SD, but no significant effect if teachers alone receive incentives. (Behrman, Parker, Todd & Wolpin, 2011).

• Randomized teacher incentive program in 500 government rural primary schools in Andhra Pradesh, India. Bonus payments (mean 3% of annual pay) based on average improvement of students' test scores. After two years students in incentive schools had significantly higher test scores by 0.28 and 0.16 SD in math and language, as well on subjects for which no incentives. Incentive schools performed significantly better than other randomly-chosen schools that received additional schooling inputs of a similar value. (Muralidharan, Karthik and Venkatesh Sundararaman, 2008, “Teacher Performance Pay: Experimental Evidence from India,: San Diego, CA: U. of CA and Washington, DC: World Bank )

School Vouchers• Most evaluations of vouchers in developing

countries focus on Chile, with universal program introduced in 1981; limited impact on student achievement even in communities where private schools expanded most (Mizala and Romaguera, JHR 2000; MacEwan Ed Ec 2001; Hsieh and Urquiola JPubEc 2006)

• Colombia used lotteries to distribute vouchers subsidizing cost of private secondary school (PACES); lottery winners 10 percentage points more likely to finish 8th grade and with significantly higher achievement tests cores (0.2 SD). (Angrist, Bettinger, Bloom, King and Kremer, 2000 AER)

1E. Conclusions

• Apparently substantial short-run impact of ECD programs.

• FFE and CCT incentive programs to students and parents do seem to get kids to go to school more.

• But effects on learning via standardized tests more elusive.

• Perhaps most promising intervention is direct linking of incentives to achievement and other desirable indicators such as graduation.

Caveat: One size does not fit all

• Differences in:–Program objectives– Initial conditions–Prices and other policies

• Resource costs, NOT governmental budgets• Therefore search for “best practices” needs to

be calibrated for such differences

Country Net Primary School Enrollments in 2000

Madagascar 68%

Kenya 65%

India 79%

Mexico 97%

For Such Reasons:

1. At minimum such a table must include some of characteristics of key relevance, such as prevalence of worms, misinformation and enrollments. Still may be quite misleading.

2. But perhaps most important lesson of PROGRESA/Oportunidades and subsequent J-PAL and other studies is the importance of systematic evaluation of programs on significant scale, NOT that the program should or should not be applied in other contexts that may vary in important dimensions.

2. Longer-run impacts of human capital

investments and some benefit/cost ratios

2A. Better early life nutrition 2B. Expanded ECD programs2C. School programs

2A. Better early life nutrition

2008 Lancet review* of existing studies and new estimates based on five cohort studies (Brazil, Guatemala, India, Philippines, South Africa) suggests longer-run positive effects.

*Victora, CG, L Adair, C Fall, PC Hallal, R Martorell, L Richter, HS Sachdev, 2008, “Maternal and Child Undernutrition: Consequences for Adult Health and Human Capital,” The Lancet 371 (Issue 9609), 340-357.

Summary of Selected Associations between Maternal and Infant Anthropometric Measures and Adult Outcomes based on Victora et al. (2008) Adult height 3.2 cm for 1 HAZ at age 2 0.7-1.0 cm for 1 cm at birth 0.5 cm for 1 cm of maternal height Schooling attainment 0.5 grades for 1 HAZ at age 2 (?) 0.5 grades for 1 WAZ at age 2 (?) 0.3 grades for 1 kg at birth Labor income 8% for 1 HAZ at age 2(?) males 8-25% for 1 HAZ at age 2 (?) females Birth weight of offspring 208g for 1 kg for mother at birth 70-80 g for 1 HAZ or 1 WAZ of mother at age 2(?) *HAZ refers to height-for-age Z scores (i.e., number of standard deviations in the international reference population. WAZ is the weight-for-age Z score.

Long-term effects of a nutrition intervention in early childhood: Guatemalan INCAP studies

• Better (atole) and less good (fresco) nutritional supplements randomly available across small number of villages in 1969-77; follow-up surveys in 2002-4 and 2006-7 of children (0-7y) in 1969-77 after about 35 years and their children.

Impact on education of exposure to improved nutrition from 0–3 y of age*

Schooling attainment: Effects found for women only– Improved by 1.2 grades (0.36 SD)

Reading: For men and women (25-42y), improved Inter-American Reading scores by 0.28 SD

Cognition: For men and women (25-42y), improved Raven’s Progressive Matrices scores by 0.24 SD

*Maluccio J, Hoddinott J, Behrman JR, Martorell R, Quisumbing A, and Stein A. 2009 “The impact of improving nutrition during early childhood on education among Guatemalan adults ,” Economic Journal 119 (April), 734–763.

Improved nutrition in early childhood and adult economic activity*

Exposure to improved nutrition before, but not after 3 years, improved wage rates (income/hour) for men but not women. Exposure from 0–2 years had the greatest impact: Wages increased by US $ 0.67 (CI: 0.16,1.17) or 0.45 SD

*Hoddinott J, Maluccio JA, Behrman JR, Flores R, and Martorell R. Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults. Lancet 2008; 371:411-16.

0.670.62

0.22

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0-24 0-36 36-72

P = 0.009P = 0.007

P = 0.406

US$/hr

Window of exposure (months)

*Hoddinott J, Maluccio JA, Behrman JR, Flores R, and Martorell R. Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults. Lancet 2008; 371:411-16.

Exposure to improved nutrition in early childhood and income (in US$) earned per hour; n=602 men; age 25-42 y*

Exposure to early childhood nutritional supplements & intergenerational effects*

Exposure for females, but not for males, affected their children 0-12 y. Significant increases in:• Birth weight of 116 g (CI: 17 g to 215 g)• Height 1.3 cm (CI 0.4 cm to 2.2 cm)• Head circumference 0.63 cm (CI 0.37 cm to 0.89 cm)• But NOT in weight, BMI, arm circumference, triceps and

subscapular skinfold thicknesses(Estimates robust to alternative treatments of standard errors and attrition.)

*Behrman JR, Calderon MC, Preston S, Hoddinott J, Martorell R and Stein A. 2009. “Nutritional Supplementation of Girls Influences the Growth of their Children: Prospective Study in Guatemala,” American Journal of Clinical Nutrition .

Cognitive skills (brain) production functionsBehrman, JR, J Hoddinott, JA Maluccio, E Soler-Hampejsek, EL Behrman, R Martorell, M Ramirez and AD Stein, 2008, “What Determines Adult Cognitive Skills? Impacts of Pre-School, School-Years and Post-

School Experiences in Guatemala”, Washington, DC: IFPRI Discussion Paper No. 826.

Informative about whether schooling dominant or possibly exclusive determinant of adult cognitive skills , as often (implicitly) assumed.

Given wage function estimates below, informative of whether cognitive skills a channel through which early-life nutrition works.

Also informative about other topics, ranging from cross-country regressions to “Flynn effect” (increasing ability measures over time).

(Estimation IV or 2SLS with good diagnostics & robust to alternative treatment of standard errors/attrition.)

Results—Reading Comp Scores (SDs)

Set 1A Set 1B Set 2 Set 3

Life stage Representation OLS IV OLS IV OLS IV OLS IV

RCS z scores E1 Not Stunted at age six 0.270 0.153 0.13 0.51 0.13 0.48

(0.060) (0.284) (0.04) (0.22) (0.04) (0.23) E2 Schooling attainment 0.22 0.11 0.22 0.13 0.22 0.11

(0.01) (0.03) (0.01) (0.03) (0.01) (0.03) E3a Skilled job tenure -0.0002 0.02

(0.004) (0.01) E3b Age at interview in 2002–4 0.19 0.20 0.08 0.11 0.11 0.23 0.11 0.20

(0.09) (0.11) (0.06) (0.07) (0.06) (0.08) (0.06) (0.09) Age at interview squared 100 -0.33 -0.35 -0.12 -0.20 -0.17 -0.37 -0.17 -0.33 (0.13) (0.17) (0.09) (0.10) (0.09) (0.13) (0.09) (0.13) Constant -2.70 -2.88 -2.16 -2.01 -2.71 -4.38 -2.71 -3.80 (1.41) (1.92) (0.93) (1.07) (0.93) (1.45) (0.94) (1.56)

Results – Non Verbal Skills (SDs) NVS z scores

Life stage Representation OLS IV OLS IV OLS IV OLS IV

E1 Not Stunted at age six 0.22 0.366 0.13 0.90 0.13 0.72 (0.06) (0.263) (0.05) (0.28) (0.05) (0.29)

E2 Schooling attainment 0.15 0.13 0.14 0.17 0.14 0.04 (0.01) (0.03) (0.01) (0.03) (0.01) (0.04)

E3a Skilled job tenure 0.02 0.13 (0.01) (0.02)

E3b Age at interview in 2002–4 0.20 0.288 0.12 0.14 0.15 0.31 0.12 0.10 (0.09) (0.108) (0.08) (0.08) (0.08) (0.11) (0.08) (0.12) Age at interview squared 100 -0.36 -0.49 -0.21 -0.25 -0.26 -0.49 -0.22 -0.21 (0.14) (0.16) (0.12) (0.12) (0.12) (0.16) (0.12) (0.18)

Conclusions for Cognitive Skills Production Function Estimates

Most previous empirical investigations of importance of and determinants of adult cognitive skills assume that (1) cognitive skills produced primarily by schooling (2) schooling predetermined in statistical sense

But may lead to misleading inferences about impact of schooling & also about importance of pre-schooling and post-schooling experiences on what adults know.

Brain versus brawn in wage functionsBehrman, Jere R., John Hoddinott, John A. Maluccio and Reynaldo Martorell, 2009, “Brains versus Brawn: Labor Market Returns to Intellectual and Physical Human Capital in a Poor Developing Country,” Philadelphia, PA: University of Pennsylvania, mimeo.

Vast literature assessing “return” to intellectual human capital (typically schooling) in labor market (Psacharopoulos & Patrinos 2004)

Some of it incorporates physical human capital (short-term measures or height), often for developing countries (Strauss 1986; Thomas & Strauss 1997)

Other studies incorporate more proximate measures, particularly for intellectual human capital (Boissiere, Knight & Sabot 1985; Murnane, Willet & Levy 1995; Alderman et al. 1996; Glewwe et al. 1996)

Here endogenize proximate measures of two HC types

OLS IV OLS IV

0.084 0.1140.228 0.404

2.117 -1.7651.079 -0.553

Male 0.207 0.484 0.102 0.524Age 0.014 0.016 0.012 0.018

0.19 0.16 0.16 0.1111.71 8.348.42 7.96

p-value [0.39] [0.44]

Significance 0.01 0.05

Table 4: Ln hourly wage rate production functions (N=962)

(I1) Completed grades of schooling(I2) Adult RCS Z score(H1) Ln adult height(H2) Ln adult fat-free body mass

R2/Centered R2

Kleibergen-Paap testHansen J test

Notes: Instrumental variables GMM estimates using instruments and second stage controls indicated in Table 3. Standard errors calculated allowing for clustering at the birth year-village cohort level (64 clusters)s.

Economic Benefits (not sufficient to guide policies) Relative to Economic Costs

Benefits• Recognize benefits over life cycle and across generations,

conditional on survival probabilities, but avoid double counting

• Estimate benefits, not associations, given behavioral choices• Monetary value on each benefit (challenge, e.g. survival)• Obtain present discounted value of benefits by discountingCosts• Include private and public resource costs, including distortion

costs of raising public resources but not transfers• Obtain present discounted value of costs by discounting

Behrman JR, Alderman H and Hoddinott J. “Hunger and Malnutrition” in ed. Bjørn Lomborg, Global Crises, Global Solutions, Cambridge, UK: Cambridge University Press, 2004, 363-420.

Multiple impacts over life cycle, evaluation (e.g., survival), no double counting (e.g., schooling), discount rates (e.g., table)

Alderman H and Behrman JR. Reducing the Incidence of Low Birth Weight In Low-Income Countries has Substantial Economic Benefits, World Bank Research Observer 21(1): 25–48, 2006.

Estimates of Present Discounted Values of Seven Major Benefits of Moving One Infant Out of Low Birth Weight Status in Low-Income Country (U.S. Dollars) Annual discount rate Benefit 3% 5% 10% 1. Reduced infant mortality $95 $99 $89 2. Reduced neonatal care $42 $42 $42 3. Reduced costs of infant and child illness $36 $35 $34 4. Productivity gain from reduced stunting $152 $85 $25 5. Productivity gain from increased cognitive ability $367 $205 $60 6. Reduced costs of chronic diseases $49 $15 $1 7. Intergenerational benefits $92 $35 $6 Total $832 $510 $257 Share of total at 5 percent discount rate (percent) 163 100 50

Combining Benefits and Costs (Copenhagen Consensus)

Behrman JR, Alderman H and Hoddinott J. “Hunger and Malnutrition” in ed. Bjørn Lomborg, Global Crises, Global Solutions, Cambridge, UK: Cambridge University Press, 2004, 363-420.

Opportunities and targeted populations Benefits/

Costs Size of Targeted Populations

1. Reducing LBW for pregnancies with high probabilities LBW (particularly in South Asia)

12 million LBW births per year

1a. Treatments for women with asymptomatic bacterial infections 0.6-4.9

1b. Treatment for women with presumptive STD 1.3-10.7 1c. Drugs for pregnant women with poor obstretic history 4.1-35.2 2. Improving infant and child nutrition in populations with high prevalence of child malnutrition (fairly widespread in poor populations)

162 million stunted children

2a. Breastfeeding promotion in hospitals in which norm has been promotion of use of infant formula

4.8-7.4 0-5 years old

2b. Integrated child care programs 9.4-16.2 2c. Intensive pre-school program with considerable nutrition for poor families

1.4-2.9

3. Reducing micro nutrient deficiencies in populations in which they are prevalent

3a. Iodine (per woman of child bearing age)cc 15-520 2 billion people with iodine deficiencies 3b Vitamin A (pre child under six years) 4.3-43 128 million pre-school children 3c. Iron (per capita) 176-200 3.5 billion people, incl. est. 67 million

pregnant women 3d Iron (pregnant women)c 6.1-14

2B. Expanded ECD programs

• Benefit/cost of eliminating preschool enrollment gaps among income quintiles for 73 developing countries with 2.69 billion people (Engle et al. 2011 Lancet)

• For every percentage point increase in preschool enrollment, the schooling gap for 15-19 year olds declines 0.026 grades [5% -95% CI = -0.14, -0.38], controlling for countries’ GDP and inequality (GINI index) (robust to using country fixed-effects).

• Economic benefit PDV of added wage productivity for real discount rates of 3% and 6% under assumption that earnings are 0 for first 12 y after preschool & equal to yearly average earnings incremented by average rates of return to schooling (8.3% for urban areas, 7.5% for rural areas) for following 45 y.

• With 3% discount rate, benefits from $10.6 billion with an increase of all children in each country to 25% enrollment for preschool to $33.7 billion with increase to 50% preschool enrollment. With a 6% discount rate benefits are $4.7 billion (for 25%) to $14.9 billion (for 50%).

• Imply benefit/cost ratios respectively from 6.4 to 17.6

2C. School Programs

• CCTs• Vouchers

Benefit/Cost Ratios: Schooling in Mexican Rural PROGRESA/Oportunidades Program

Discount Rate

Rate of Return to Schooling

6% 8% 10%

3% 3.60 5.36 7.115% 1.70 2.77 3.84

Behrman, Jere R., Susan W. Parker, and Petra E. Todd, 2011, “Do Conditional Cash Transfers for Schooling Generate Lasting Benefits? A Five-Year Follow-Up of

Oportunidades Participants, Journal of Human Resources 46:1 (Winter), 93-122.

Chilean vouchers and labor market outcomes

Structural model to identify impacts from differences in schooling and work choices made and wage returns received by individuals differentially exposed to program and find: vouchers induced higher attendance at private subsidized schools, higher schooling attainment, higher wages and higher labor force participation (all more for non-poor). Returns to both public and private schools increased. (Bravo, David, Sankar Mukhopadhyay and Petra E. Todd, 2010, “Effects of a Universal School Voucher System on Educational and Labor Market Outcomes: Evidence from Chile,” Quantitative Economics )

• Colombian vouchers allocated by lottery in cities with excess demand (PACES): no significant impact on enrollment or drop-out, 15 percent more likely to attend private school, 0.12-0.16 more grades of schooling (primarily due to lower repetition rates), ~10 percentage points more likely to complete 8th grade, 0.2 standard deviations higher on standardized tests, worked 1.2 hours per week less, less likely to be either married or cohabiting as teenagers, 15-20% higher secondary school completion rates; benefit-cost ratios of 3.8 with a discount rate of 3%, 2.7 with a discount rate of 5%, and 1.4 with a discount rate of 10% (Angrist et al. 2002, Angrist, Bettinger & Kremer 2004, Knowles & Behrman 2005).

3. Impact of targeted policies on

inequality and on poverty

• Low Birth Weight• Schooling

• India has 22.6% low birth weights vs. 8.9% for US. Closing gap by increased all birth weights < median in India would increase earnings by estimated 9.2%. But closing gaps for all countries for which relevant data would reduce world income inequality by < 1%. (Behrman, Jere R. and Mark R. Rosenzweig, 2004, “Returns to Birthweight,” Review of Economics and Statistics 86:2 (May), 586-601.)

Targeted Schooling and Earnings Distribution – Illustration with 2004 Chilean SPS

(Behrman, Jere R., 2011, “How Much Might Human Capital Policies Affect Earnings Inequalities and Poverty?” Estudios de Economia (June))

• Given qualified, but definitely positive assessment of a number of HR-related interventions, of interest to ask what would be impacts on income distribution were there some targeted increases in human capital

• Simulate impacts of hypothetical changes in schooling attainment; focus on schooling attainment because it is most-emphasized among possible human capital investments -- indeed many studies empirically seem to equate schooling attainment with human capital

Basic description of inequality and “poverty” in the 2004 Chilean SPS:

Conclusions• HR targeted towards lower part of distributions often

thought to be major means to reduce inequality and poverty, increased knowledge of policy effects.

• B/C estimates for range of HR interventions, though with caveats (e.g., due to sensitivity to discount rate, value of life), suggest opportunities for range of HRs (not just schooling)

• Will targeted HR substantially reduce inequality? Simulations of schooling suggest (a) significant effects, (b) relevance of targeting, (c) range of possible effects on poverty – but (d) magnitudes of effects on inequality not all that great

Extra Slides

Introduction• High persistent inequalities in many

developing countries well-known

• Separate but related question is wide-spread poverty

• Human resource policies thought possibly important tool for both (e.g., early childhood development programs, conditional cash transfers, food for education)

ECD: Low priority for donors

Aid to ECCE as % of aid to primary education

0 5 10 15

J apanEC

United KingdomGermany

FranceNetherlands

DenmarkUNDPItaly

CanadaIreland

BelgiumLuxembourg

PortugalNorway

New ZealandUNICEF

AustraliaFinland

Spain

Almost all donors allocate to pre-primary less than 10% of

what they give to primary

Bilateral donors give priority to center-based program for

children from age 3.

From EFA Report, UNESCO 2007

Criteria for program evaluations in Engle et al 2007:

• Conducted since 1990• Randomized controlled trial or matched groups (i.e. marginal

PSM)• Intervention before 6 years• Effectiveness or program evaluation (scale)• Child development assessed• Disadvantaged children• Developing country

20 studies located met these criteria

FFE Impacts: Enrollment & Attendance

• Generally significant impacts of FFEs on school enrollment: – effects range from 6 to 26 percentage points.

• Also significant positive effects on attendance in 5 of the 10 studies. – effects range from 2 to 15 percentage points.– But one study (Kazianga et al., 2009 for Burkina Faso)

finds negative effects on attendance, concentrated on households with low availability of child labor in the household.

FFE Impacts: Performance in school

• Mixed effects on progression and repetition indicators and test performance. – Bangladesh THR reduced dropout in 9% but Ugandan

THR did not.– Philippines SFP no effect on dropout rate, but

significant reductions of Ugandan SFP in reducing grade repetition for boys.

– Mixed pattern on achievement tests, at least 2 programs show some significantly negative effects on achievement.

• Large-scale non-linear incentive scheme for teachers in 950 schools in Pernambuco Brazil in 2008. Find differential response across subjects (0.3 SD for Portuguese > response for math) and grades (greater for 8th than 12th grade and non-linear contracts induce both positive and negative effects. Ferraz, Claudio and Barbara Bruns, 2011,” Incentives to Teach: The Effects of Non-Linear Incentive Contracts in Brazilian Schools”, Rio de Janeiro, PUC and Washington, World Bank.

Conclusions on ECD programs• Increasing body of evidence regarding substantial

impacts of life cycle of ECD – and some regarding benefits/costs

• What Nobel Laureate J. Heckman (2006) said for ECD in US also probably true for developing countries: “It is a rare public policy initiative that promotes fairness and social justice and at the same time promotes productivity in the economy and in society at large. Early interventions targeted to disadvantaged children have much higher returns than later investments. ”

Complete exposure to either supplement and birth year

1962 1969 1974 1977

Supplementation period

Too old for complete exposure for 0–36 m

Complete exposure for

0-36 m

Birth Year

Too young for complete

exposure for 0-36 m

Double-difference estimate

Average outcome for those exposed to atole 0–36 m

completely

Average outcome for those exposed to fresco 0–36 m

completely

–

Average outcome for those NOT

exposed to atole 0–36 m completely

–Average outcome

for those NOT exposed to fresco 0–36 m completely

–

Impact estimates: right-side behavioral variables and unobserved determinants

• For example, identifying impact of stunting at 36 m on subsequent outcomes if stunting proxies in part for unobserved family background, etc.

• Critical data attributes and estimation options Baseline and longitudinal follow-up (ideally for all impacts, many years) Representative of relevant population (e.g., not selected by clinic use) Sufficient sample size for power Treatment and control groups:

Random assignment and difference-in-difference estimates Propensity score matching Regression discontinuity Change in right-side behavioral variable (instruments for IV estimates)

Semilog earnings & wage rate functions based on the 2004 SPS

• Schooling inequality: Generally down (but sim1), about twice as much if targeted to low schooling, most if bring all up to 6 grades (norm Gini -0.08)

• Schooling “poverty” headcounts: Similar targeting point but with nuance (Sim 7); relatively effective compared to inequality (norm HC -0.-9 to -0.33)

• Earnings inequality: Targeting point reversed (1.5 to 3 times as effective) with drop in norm Gini -0.03– but how to do?

• Earnings poverty headcounts: first 4 simulations have same impact on norm Gini but very different on norm HC (-0.03 for sim 4 to -0.08 for sim 1)

• Wage rate inequality: Similar to earnings inequality but norm Gini drops a little more

• Wage rate poverty headcount: Relatively effective once again, but preferred simulation depends on what cutoff