Lecture 9 and 10: Health, nutrition, education, and ...vojtechbartos.net/wp-content/uploads/2017DevEcon/Lectures/LMU_devecon... · 3/47 Nutrition Hidden hunger Why education Challenges

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Nutrition Hidden hunger Why education Challenges

Development economicsLecture 9 and 10: Health, nutrition, education, and

development (human capital)

Vojtech Bartos

LMU, June 1, 2017

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Health: Nutrition and development

Health: Hidden hunger

Education: Why does education matter for development?

Education: Challenges for education in developing countries

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Nutrition Statistics (mostly IFPRI 2014)

I 842 million people in the world do not have enough to eat.I Majority of hungry people (827 million) live in developing

countries, where 14.3 percent of the population isundernourished;

I Poor nutrition linked to nearly half (45%) of deaths inchildren under five (50% due to poor immunity)

I One in six children in developing countries is underweightI One in four of the world’s children are stuntedI 66 million primary school-age children attend classes hungry

across the developing worldI Large increase in food prices in 2006-2008, and again in 2010.

(What impact on the poor?)

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Can hunger be the cause of persistent poverty in the world?I Poverty trap?

I Model: Productivity 1 → Income 1 → Food 1 → Productivity2 → Income 2 . . .

I Q: Policy recommendation for very poor?

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Can hunger be the cause of persistent poverty in the world?

I Or no poverty trap?

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Poverty trap model

I We assume the following model:I Productivity 1 → Income 1 → Food 1 → Productivity 2 →

Income 2 . . .

I We have to establish following links:I ↑ Productivity ⇒ ↑ Income (basic micro)I ↑ Income ⇒ ↑ Food (?)I ↑ Food ⇒ ↑ Productivity (?)

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↑ Income ⇒ ↑ Food (?)

I How should a budget of a very poor person look like in casethe nutrition based poverty trap exists?

I Given the nutrition based poverty trap is true:I Is food for the poorest a normal, an inferior, or a luxury good?I Is food for the poorest an ordinary or a Giffen good?I What is the relationship between food consumption and

productivity of work?

I How to answer questions above empirically?I Jensen and Miller (2008): subsidized rice and wheat in Hunan

and Gansu, China, respectively.

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↑ Income ⇒ ↑ Food (?)

I Recall Banerjee and Duflo (2006): Economic lives of the poorI over 30% of resources spent on items other than food among

the very poorestI 5% annually on alcohol & tobacco, 10% on festivalsI 5% sugar and salt, 5% cooking oilI Poor can increase the levels of calories by switching from rice

to millets without increasing expenditures (Subramaniand andDeaton, 1996)

I Downward trend in calorie expenditures over timeI Maharashtra, India: 70% in 1983 to 62% 2000. Why?

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↑ Income ⇒ ↑ Food (?) (Income Engel curves)

I Subramanian and Deaton (1996): The demand for food andcalories (Maharashtra, India)

I Increasing spending ⇒ purchasing more expensive caloriesI Food expenditures spending elasticity: 0.7I Calorie intake spending elasticity: 0.35I ⇒ 50% of additional unit of income to food, 50% to better

tasting foodI Additional 600 calories to reach calorie levels required for work

in tropics can be purchased for 4% of daily income (coarsegrains)

I ”If nutrition is a trap, it is one from which there is a readyescape.”

I Higher income for very poor people ⇒ positive, but not hugeimpact on calories consumed

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↑ Food ⇒ ↑ Productivity (?)

Source: Strauss (1984)

I Strauss (1984)I Consumption 1%↑, work

productivity 0.35%↑ amonglow-income workers, but up to1%↑ for very poor

I Kenya similar (1%↑ ⇒ 0.5%↑)

I Schoefield (2014)I Experimentally providing

rickshaw drivers in Delhi 700additional calories (2200 caloriesbaseline for Muslim population)

I Labor supply and income 10 % ↑after five weeks.

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Nutrition based poverty trap?

I . . . poor people do not behave as if there was one.I They do not eat as much as they could and they do not

consume as much calories as they couldI Eating more calories brings benefits, but definitely not in 1:1

ratioI For example, if the income of the poor increased by 10%,

consumption would increase by 3.5% only and the productivityeven less so

I Isn’t it too little for the poverty trap?

I What to take of it?I There may be other reasonsI Things may also be very different for childrenI How households redistribute income shocks?

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”Hidden hunger”

I Not enough nutrients (malnourished)I ”Malnourished person finds that their body has difficulty doing

normal things such as growing and resisting disease. Physicalwork becomes problematic and even learning abilities can bediminished. For women, pregnancy becomes risky and theycannot be sure of producing nourishing breast milk.” (WFP)

I Not enough to eat (undernourished)I ”Under-nutrition affects school performance and studies have

shown it often leads to a lower income as an adult. It alsocauses women to give birth to low birth-weight babies.” (WFP)

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Intermezzo: Selection issues and randomized control trialsI Treatment as a binary random variable: Di = {0, 1}I Outcome of interest:

Yi ={

Y0i if Di = 0Y1i if Di = 1

I Causal effect of treatment on the outcome is: Y1i − Y0iI Problem: No within individual Y1i and Y0i simultaneously.I We thus have to compare average outcome of those treated

and of those not treated (large N assumed):

E [Y1i |Di = 1]− E [Y0i |Di = 0]︸︷︷︸Observed difference in outcome

=Observed︷︸︸︷

E [Y1i |Di = 1]−Unobserved︷︸︸︷

E [Y0i |Di = 1]︸︷︷︸Average treatment effect on the treated

+Unobserved︷︸︸︷

E [Y0i |Di = 1]−Observed︷︸︸︷

E [Y0i |Di = 0]︸︷︷︸Selection bias

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Intermezzo: Selection issues and randomized control trials


= E [Y1i |Di = 1]− E [Y0i |Di = 1]︸︷︷︸Average treatment effect on the treated

+ E [Y0i |Di = 1]− E [Y0i |Di = 0]︸︷︷︸Selection bias

I Treatment Di randomly assigned to a subset of the populationindependent of outcome Yi

I Thus, we can treat E [Y0i |Di = 1] and E [Y0i |Di = 0] asequivalent. Selection term is cancelled and we end up withaverage treatment effect on treated, a causal effect of thetreatment.

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Intermezzo: Selection issues and randomized control trials


= E [Y1i |Di = 1]− E [Y0i |Di = 1]︸︷︷︸Average treatment effect on the treated

+ E [Y0i |Di = 1]− E [Y0i |Di = 0]︸︷︷︸Selection bias

I Selection bias makes treatment effect look larger: say,effect of textbooks in schools on educational outcomes andparents in schools with textbooks take education moreseriously, i.e. E [Y1i |Di = 0] > E [Y0i |Di = 0]

I Selection bias makes treatment effect look larger: say,textbooks have been provided to schools that were mostlagging behind and were compared to schools withouttextbooks, but where parents care more about education, i.e.E [Y1i |Di = 1] > E [Y0i |Di = 1]

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”Hidden hunger”

I Thomas et al. (2006): A randomized experiment in Indonesia(Work and Iron Status Evaluation):

I Provision of iron supplement to 50% and placebo to 50%I Reduction in anemia . . .I . . . and increase in yearly earnings for self-employed workers

who got the supplement and were anemic at baseline: $40I Cost of fortified Fish sauce for one year: $6I Cost-benefit analysis. (Why?)

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Children and nutrients

I Nutrients most important before birth and during childhoodI Pre-natal: children in-utero during (Ramadan/famine) tend to

perform worse in life (Schultz-Nielsen et al., 2014; Meng andQian, 2009)

I Better nutrition for children: long term investmentI Improved learning (⇒ higher incomes)I Improved health (⇒ further improved learning)

I Fighting for nutritients with intestinal parasites (more on thatin the tutorial: Miguel and Kremer 2004)

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Why does education matter for development?

I Macroeconomic benefits: education increases economicgrowth

I Micro-level benefits: education improves multiple dimensionsof life quality (income, health, fertility, etc.)

I Examples of education and growth miracles:I Germany and Japan after WW II: destruction of physical

capital, human capital remained → economic boomI South Korea: heavy investment in education preceded

industrial boom (Miracle on the Han River)I Importance of education after war. Literacy at 22% in 1945,

88% in 1970s.I University enrollment 0.4 mil in 1980 and 1.4 mil in 1989.

I But: In many countries education still strikingly low

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Returns to education: model

Source: Psacharopoulos (1994)

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Returns to education

I Measuring returns/benefits (Mincer wage regression):I S . . . schoolingI X . . . experienceI Dp,Ds ,Dt . . . dummies for attending primary, secondary,

tertiaryI Normal: ln(wi ) = α + β1Si + β2Xi + β3X 2

i + εiI Extended:

ln(wi ) = γ + δpDpi + δsDsi + δtDti + δ1Xi + δ2X 2i + µi

I Returns to specific types of schooling (excluding direct andindirect costs of education):

rp = (δp)/(Sp) rs = (δs−δp)/(Ss−Sp) rt = (δt−δs)/(St−Ss)

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I Consistent findings in Psacharopoulos (1994) andpredecessors:

1. Returns positive2. Cross-economy average return: 10% annually3. Returns highest in low/middle income economies4. Returns declining modestly over time; schooling attainment

rising (supply chasing demand)5. Returns highest at the primary level and declining at the

secondary and tertiary levels of schooling. → Not today!Highest benefits to university (theoretical justification?)

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Source: Montenegro and Patrinos (2014)

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Problems with measuring returns to educationI Overestimation of returns to education. Why?

I Simple OLS estimates cannot distinguish betweenunobservable differences in innate quality of students (i.e.,what if those who go to school are better).

I Natural experiment to overcome the problem: Duflo (2001):Evidence from Indonesian school reform

I Between 1974 and 1978 over 61,000 primary schoolsconstructed in Indonesia (doubling stock).

I Exogenous shock to educationI Exploiting discontinuity in exposure to program in younger and

older kids and differences in rate at which schools constructed.I Returns to education roughly 8% for each extra year of

schooling (smaller but not that far from Psacharopoulos’)I (you might read Duflo (2004) to see the displacement effect

on older workers)

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Problems with measuring returns to education

I Underestimation of (social) returns to education. Why?I People learn from each other, collaboration easier in educated

society (spillovers)I Spillovers → technology adoptionI But careful: some displacement effects on uneducated.

I Duflo (2004) finds that increase of 10 percentage points inproportion of primary school graduates on labor marketreduced wages of older cohorts in Indonesia not affected byschooling expansion by 3.8% to 10% (although formal laborforce participation increased by about 7% to 10%).

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Wider effects of education

I Education affects other outcomes apart from income(directly). Which?

I Higher literacy level → lower transaction costs. Why?I Education increases opportunity costs for women and their

participation on the labor market. Why?I Literate electorate puts more pressure on governments →

autocracy less likely

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Wider effects of education

I Significant correlation between education and healthoutcomes:

I Mirowski and Ross (2000): correlation between literacy andlife expectancy higher than correlation between income and lifeexpectancy

I Chou et al. (2007): A school construction program in Taiwandecreased child mortality due to higher parental education

I Education decreases fertility through decrease in desiredfertility and higher use of contraceptives

I Malawi: girls staying longer in school due to conditional cashtransfer program less likely to become pregnant (Baird et al.,2010)

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Costs and benefits of education

I Costs of education:I Private: foregone earnings while studying, tuition fees and

other direct costsI Social: subsidies

I Benefits of educationI Private: Wages, private non-market effectsI Social: Shifting technological frontiers, social non-market

effects, spillovers in worker productivity

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Challenges for education in developing countries

I Although there are many, we’ll discuss four:1. Basic school inputs missing2. Absenteeism in schools3. Parents and students having imprecise beliefs about returns to

education4. Discrimination of children in school

I Distinguish between supply and demand challenges.I Which of the above supply, which demand?I What should be a response to a supply problem? And to a

demand problem?I Education interventionists (Sachs, 2005) vs. aid pessimists

(Easterly, 2006)

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Basic inputs missing

I Schools lacking:I A building: 8% in IndiaI Textbooks: 80% primary students in KenyaI Blackboards: 40% in rural northern VietnamI Enough teachers: primary school pupil to teacher ratio in

high-income countries is 16, in low-income countries is 32(Sub-Saharan Africa 43)

I Will availability of textbooks increase test scores? → Glewwe,Kremer, and Moulin (2009)

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Glewwe, Kremer, and Moulin (2009): Many Children LeftBehind? Textbooks and Test Scores in Kenya

I Economic rationale: spending on nonteacher inputs will raisestudent performance much more than increased spending onteachers where governance poor (Pritchett and Filmer, 1999)

I Why can’t you use the following OLS model?

test scoreijks = α + β textbookijks + ujks + εijks

I RCT in Kenya (baseline: 80% students without textbooks).I Result: Provision of textbooks on average did not increase

test scores (only helped the brightest students)I Why no effect?

I Textbooks in English, while main language Kiswahili (notunique)

I School curricula way above qualityI Often absent teachers do not help students to improve

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Glewwe, Kremer, and Moulin (2009)

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Absenteeism in schools

Source: Chaudhury et al. (2006)

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Banerjee and Duflo (2006): Addressing Absence

I How to fight absenteeism? Ideas?I External control

I More intensive monitoring → Duflo and Hanna (2005)I Monitoring by camera (bonus for presentce / fine for absence)I Results: absence rate of (treatment) teachers cut by halfI Monitoring by headmasters not working (Kremer and Chen,

2001) – side with the teachers

I Incentives (rewards / punishments; monetary / shame–praise)based on measured performance

I Glewwe, Ilias and Kremer (2010): In-kind incentives (≈20% ofsalary) for top and best improving schools in district examtest-scores

I Improved test-score results, but no effect on absenteeism.How did they manage?

I More test preparation (no effect on long-term learning)

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Banerjee and Duflo (2006): Addressing AbsenceI Beneficiary control over providers

I Why don’t parents do the monitoring?I World Bank Development Report (2004): ”Services can work

when poor people stand at the center of service provision—when they can avoid poor providers, while rewarding goodproviders with their clientele, and when their voices are heardby politicians — that is, when service providers have incentivesto serve the poor.”

I Two important components for beneficiary control:I Beneficiaries must have a real demand for the serviceI Beneficiaries must have a mechanism for affecting providers

I Experiments on community monitoring show no effects.I Punishment mechanisms rather limited in many developing

countriesI Maybe the parents value education too little. Rational or

imprecise beliefs?

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Jensen (2010): The (perceived) returns to education andthe demand for schooling

I US students guess returns to education precisely (Smith andPowell, 1990). What about developing countries?

I Survey data for eighth-grade boys in the Dominican Republic(non-rural population, representative sample, 2250 students)

I Now, we would like you to think about adult men who areabout 30 to 40 years old and who have completed only[primary school/secondary school/university]. Think not justabout the ones you know personally, but all men like thisthroughout the country. How much do you think they earn ina typical week, month or year?

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Jensen (2010): The (perceived) returns to education

Source: Jensen (2010)

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Jensen (2010): The (perceived) returns to educationI Results: perceived returns to secondary school are extremely

low, despite high measured returnsI Similar results also in Nguyen (2008) for Madagascar, only

with parentsI RCT on giving information to students:

I Students at randomly selected (urban) schools giveninformation on the higher measured returns

I ”We found that the average earnings of a man 30 to 40 yearsold with only a primary school education was about 3,200pesos per month, [...] of a man [...] who completed secondaryschool [...] was about 4,500 pesos per month [...]. And peoplewho go to university earn about 5,900 pesos per month.”

I Students given the information completed on average0.20-0.35 more years of school over the next four years thanthose who were not.

I Demand side problem!

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Discrimination of children in school

I Stereotype threat: stereotyped-based expectations affectindividual performance in the domain of the stereotype

I Stone et al. (1999): Students asked to perform a taskdescribed as testing ”natural athletic ability,” and the exactlysame test, only described as testing ”sports intelligence”. Whoperformed better: Blacks or whites?

I Whites did worse than blacks in ”athletic ability test”I Blacks did worse than whites in ”sports intelligence test”I Change in self-confidence a culprit

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Hoff and Pandey (2006): Discrimination, Social Identity,and Durable Inequalities

I Experiment in which indian students invited to solve 15 mazes

I Students either of low or high caste invited in groups of 6I Some in mixed sessions (H/L), some in homogenousI In some groups this information revealed at the beginning:

I Name, village, father’s name, paternal grandfather’s name,caste

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Hoff and Pandey (2006): Results

Source: Hoff and Pandey (2006)

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Lecture 9 and 10: Health, nutrition, education, and ...vojtechbartos.net/wp-content/uploads/2017DevEcon/Lectures/LMU_devecon... · 3/47 Nutrition Hidden hunger Why education Challenges