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ECON 980oHealth, Education and Development
Lecture 2September 25, 2008
Motivation: Preston curve
• 3 possible interpretations:
‐ Income leads to health
‐ Health leads to income
‐ Third factor behind both (geography, institutions, politics, etc)
→ Difficult to isolate causal effect of health on income
Income‐health gradient
Multiple potential health-to-wealth pathways:
Direct productivity outcomes:– Health/nutrition increases labor market productivity
(Thomas et al, 2004)– Child nutrition increases productivity of schooling
(investment effect)– Ill health has large externalities
Particularly true for infectious disease ….
Lower life expectancy :– Reduces investment in education– Reduces savings rates – Increases population growth
To test theory, need to isolate particular channel
This class, focus on second and third channels
Why is effect of health on schooling potentially even more important for growth than labor market effects?
• Child interventions thought to have investment effects, so benefits of health intervention multiply over lifetime
What do we mean by this?
- Human capital investments- Biological investments (cognitive development)
• Another motivation: What is education production function? Why don’t people invest more in education in developing countries?Is it purely credit constraints?
Intestinal helminth (worm) infectionsIntestinal helminths among most widespread diseases in less
developed countries• 1.3 billion people infected with roundworm• 1.3 billion with hookworm• 900 million with whipworm• 200 million with schistosomiasis
Disease features:• Particularly concentrated among school-age children & in
sub-Saharan Africa• Worm load (# of worms) matters for health
Health impact:• Light infections often asymptomatic• Severe infections frequently cause anemia, malnutrition,
stunting, wasting, listlessness, and abdominal pain
Non-health impact:Education
• What channels important?
• Sickness lowers school attendance
• Hypothesized that children with intense infections less attentive in school and thus show reduced educational achievement
Spillovers
• Transmitted through contact with infected fecal matter
• What do we mean by spillovers in this context?
→ For parasitic and infectious diseases, reducing number of worms in one person reduces rate of infection in others
Prevention and treatment• Transmitted through poor sanitation & hygiene, bathing in
infected water
Treatments: 1. Behavioral change (shoes, latrines, bath in clean water)2. De-worming drugs
Advantages:– Low-cost – Easy to administer (single-dose oral therapies)– Virtually no side effectsDisadvantages:– Reinfection (need to take every 6 months to stay clean) – Girls over 12 typically excluded because of embryotoxicity
School-based de-worming particularly cost-effective. WHY?
Kremer/Miguel hypotheses:
• Even small health effect could have important effect on educational attainment and returns to schooling
• Externalities are also likely to be large because of way they spread
(i.e. de-worming one kid equivalent to de-worming ?? kids)
Why Kremer/Miguel paper important:
Previously much debate over whether to spend money on de-worming drugs
• Clear estimate of prevalence, but health impact of worms thought to be low based on medical studies
→ Not viewed as high priority policy area given preventable diseases with higher morbidity and mortality
In influential Cochrane review published in the British Medical Journal, Dickson et al. (2000) claim that:
“The evidence of benefit for mass [deworming] treatment of children … is not convincing. In light of these data, we would be unwilling to recommend that countries invest in programs that routinely treat children with anthelmintic drugs.”
Randomized experiment: Kenyan primary school de-worming project• NGO-initiated program to administer de-worming drugs
(albendazole, praziquantel) to students in primary school
• 75 primary schools and 30,000 children in single region of Kenya (Busia)
• Health education component (preventive health behavior)
• Take-up rate approximately 70 percent
Evaluation: Track outcomes of participating students and a comparison
group after the experiment
Want to know effect of drugs on:
• Health• School Attendance• School Performance
Key feature of intervention: For political/ethical reasons, all schools in districts had to be treated
So how do they get a control group?
Experimental design:
De-worming phased in to schools in three stages, each school randomly assigned to one of three start dates
Group A (25 schools) in 1998-2001Group B (25 schools) in 1999-2001Group C (25 schools) in 2001
Phase-in most common form of randomized policy evaluation
Treatment Group 1998 1999 2000 2001 Group 1 (25 schools) T T T T Group 2 (25 schools) C T T T Group 3 (25 schools) C C C T
How that translates into a regression:(Note: data from 1998, 1999)
ijtiijtititijt euXTTY ++′+⋅+⋅+= δββα 2211
How do you interpret ?
How do you interpret ?
Average effects of de-worming treatment in years 1 and 2 of program.
What do you expect coefficient on T2 to look like?
1̂β
2β̂
Experimental complications:
1. Low take-up (what is this?)Many students don’t take drug, mainly because they’re absent
So who do we put in the treatment group?
Possible approaches : • Intent-to-treat: Follow all students in treatment schools regardless of take-up
• Treatment on treated: Estimate effect only among those who take medicine
Which approach is better? Why are they useful?What assumptions necessary?
Other experimental complications
1. Contamination (#1)
Untreated students can get outside treatment for worms
Why is this a problem?
Why not a big problem in Busia:
• Low willingness-to-pay for de-worming medication• Main remedies herbal treatments not thought to have
large effects• Gives conservative treatment effect. Why?• Effect of school de-worming over and above potential
influence of home remedies
Other experimental complications
2. Contamination (#2)
Students assigned to control schools may benefit from treatment of others
Why?
Why is this a problem?
Recall necessary conditions for unbiased estimator:E[Net Effect]=E[YA
T=1-YBT=0 ] if and only if:
1. E[YBT=1]=E[YA
T=1] (both groups have the same response to treatment),
and
2. E[YAT=0]=E[YB
T=0] (both groups have same outcome if not treated)
Which condition violated by presence of externalities?
If untreated group affected by treatment, condition #2 violated
Why do externalities create complications with treatment estimation in randomized experiments?Untreated children benefit from treatment →Control group is contaminated
So instead of condition #2, we get: E[YAT=0]<E[YB
T=0]
How does this change the difference-in-difference estimate?
Does standard DID underestimate or overestimate the real benefit of the drugs?
Effect of de-worming treatment on worm infection:
0102030405060
Treated Students Comparablestudents incomparison
schools
Untreatedstudents intreatmentschools
Moderate-to-Heavy Helminth Infection Rates:
How do we correct for this?(1) Randomization happened at school level, so compare
treatment and control schools that are far apart
Does this give you an unbiased estimate of the benefit of the program?
Does it allow you to measure the size of the externality?
No! – you get the total effect only
(2) Make use of predictions about the expected size of externality
This solves two problems: (what?)• Can get unbiased estimate of effect on control group• Can separate treatment effect from externality
How do we predict size of externalities?What does size of externality depend on?
• Type of worm (life cycle, #eggs, how travels)• Mobility of children• Proximity, connectedness of water• Population density
How does this work?
If no externalities, rate of improvement among treatment and control groups should be independent of above factors
In practice?Interact above variable with treatment indicator and add to
OLS regression
Empirical SpecificationIdentification relies on the randomized design:
Yij is?health outcome of individual i in village j
Ti is ?indicator var for individual assignment to program
Xij is?a vector of village and individual characteristics
Nit is?total number of individuals at distance d from i
is?number of individuals distance d from i assigned to program
TitN
ijtiitTitijtititijt euNNXTTY ++⋅+⋅+′+⋅+⋅+= φγδββα 2211
Empirical Specification
Which parameter measures the externality?
What does this parameter measure in words?
Change in outcome with each additional treated person living d distance away
ijtiitTitijtititijt euNNXTTY ++⋅+⋅+′+⋅+⋅+= φγδββα 2211
Empirical Specification
How do we measure the average effect of de-worming on students in the treatment group in years 1 and 2?
ijtiitTitijtititijt euNNXTTY ++⋅+⋅+′+⋅+⋅+= φγδββα 2211
Empirical Specification
Average effect of de-worming on treatment group in year 1:
Average effect of de-worming on treatment group in year 2:
Are externalities ever likely to work in opposite direction?
ijtiitTitijtititijt euNNXTTY ++⋅+⋅+′+⋅+⋅+= φγδββα 2211
TitN⋅+ γβ1
TitN⋅+ γβ2
What additional sources of variation could be used to further isolate externalities?
Example:
NP=number of students with indoor plumbing within 3 km radius
Using both sources of variation:
Can you think of an experimental method of measuring externalities?
(what can be randomized to give a prediction about size of externality?)
2211 ijtiPit
TPitdit
Titijtititijt euNNNNXTTY ++⋅+⋅+⋅+⋅+′+⋅+⋅+= ϕλφγδββα
RESULTS
Health impact after 1st round of treatment:
• Prevalence of hookworm, roundworm, and schistosomiasissignificantly lower in Group 1
• Fewer Group 1 report having been sick
• Group 1 students have better height-for-age
• Worm prevention techniques education failed
Also bit impacts on health through externalities:
What are two types of externalities measured?
• Within-school and between school
Impacts on health through externalities:
• Cross-school externalities
– Infection rates 26 percentage points lower per 1000 pupils in Group 1 schools within 3 km
– Infection rates 14 percentage points lower per 1000 pupils between 3-6 km away
• Localized, within school externalities
– Rates of moderate-to-heavy infections substantially lower in Group 1 who did not receive medical treatment than among comparison students in Group 2 schools
Impacts on education:(Participation measured during quarterly unannounced visits)
Treatment associated with dramatic gains in school participation, large externalities:
• Baseline absence rate (30%) reduced by ¼
• Total effect: Increase in school participation ~0.14 yrs/ child
• What about impact on what is learned in classroom?– No significant impact on test scores (no evidence of
cognitive impact)– What do you make of this?
• Was it cost-effective?Very! $3.50 per additional year of schooling
Conclusions(1) Externalities important part of health effect
Over 2/3 of returns to de-worming from externalities
(2) Easy to conclude intervention has small effect when externalities:
Treatment very cost effective, but only meets strictest standard when externalities taken into account
• Cost: $20/DALY saved per person vs $5 per total DALYs• Externality benefits 75% of total DALY reduction
This means that must incorporate externalities into estimates whenever may be present – double bias in experimental estimates
Can externalities ever work in opposite direction?