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Out of Africa: Human Capital Consequences of In Utero Conditions
Victor Lavy University of Warwick and Hebrew University
Analia SchlosserTel Aviv University
Adi ShanyHebrew University
November 2014
Some Salient Facts About Micronutrient Deficiencies
During Pregnancy in Developing Countries
Iron Deficiency
• Half of pregnant women in developing countries are anemic (WHO
2014).
• More than half of this anemia burden is due to Iron deficiency, the
rest partly due to deficiency of folic acid, vitamin B12, vitamin A,
and due to parasitic infections.
• Health consequences include poor pregnancy outcome, in
particular impaired physical, brain and cognitive development.
• If iron supplementation starts after the first trimester of pregnancy it
will not help prevent these poor birth outcomes.
Folic Acid Deficiency • Recent review by WHO suggest that deficiencies of folic acid is a
public health problem that affect many millions of people throughout
the developing world.
• Folic acid deficiency in early pregnancy increases dramatically the
chance of a spinal cord problem (Neural Tube Defect) or brain
development problems. A NTD is an opening in the spinal cord or
brain that occurs very early in gestation.
• Therefore FEolic acid supplement (folate) is advised for at least the first
12 weeks of pregnancy for all women - even if they are healthy and
have a good diet. If Folic acid supplementation starts after the first
trimester of pregnancy it will not help prevent these poor birth
outcomes.
Iodine Deficiency (IDD) • IDD during pregnancy is world’s most prevalent cause of brain damage (WHO
2014). Thought to Matter most at time of fetal brain development.
• It is estimated that 1 billion people are at risk of brain damage from IDD worldwide.
• Comprehensive Handbook of Iodine (2009):
“Iodine deficiency is now recognized by WHO as the most common preventable cause of brain damage in the world today, with excess of 2 billion at risk from 130 counties.”
• Iodine deficiency reduces intellectual capacity and cognitive development, with
larger effect on girls. • “Humans require iodine for biosynthesis of thyroid hormone. In utero
development of the central nervous system required for intellectual functioning depends critically on adequate supply of thyroid hormone, which influences the density of neural networks established in the developing of the brain” (Bror-Axel Lamberg 1991)..
Micronutrient Deficiencies in India
• The prevalence of micronutrient deficiencies amongst pregnant women of New Delhi slum communities is high (Umesh et al, Indian Pediatrics 1999; 36: 991-998). Prevalence of anemia and Iodine deficiency was 78.8% and 22.9%, respectively.
• A 2000-2001 survey in a sample of rural villages in Haryana State show that 73.4, 26.3, and 6.4 percent of pregnant women were deficient in iron, folic acid and iodine, respectively (Pathak et al, Indian J Pediatrics. 2004 Nov).
• Padam Singh (2007): over all anemia among pregnant women in India is 85%.
Rresearch Question
• What will be the human capital and economic consequences of
eliminating these Micronutrient Deficiencies among pregnant
women, for example, bringing them to the level in developed
countries?
• More general question, how would improvement of in utero
environmental conditions affect later life cognitive and human
capital outcomes?
• The challenge: Identify the casual effect of in utero conditions
where children’s family background correlate with in utero
conditions.
Literature• Medical
• The fetal origin hypothesis (Braker 1992): certain chronic conditions
later in life can be traced to the course of fetal development.
• Evidence on the effect of malnutrition during pregnancy:
• Dutch famine - Neugebauer et al. (1999), Rooij et al. (2010) - severe
maternal nutritional deficiency early in gestation is associated with
inferior brain and cognitive development of off-springs.
• Evidence on effect of radiation exposure:
• Relatively short pulse of exposure to radioactive fallout between 8
and 25 weeks of gestation has long term impact on cognitive abilities
of off-springs later in life. This is plausible given the nature of the
developmental events occurring in the brain during this period of
gestation (Nowakowski and Hayes (2008)).
Literature• Economic
• Studies that use changes in local environment caused by negative in utero
shocks and look at effect on health and education outcomes (review by Almond
and Currie, 2011)
• Radiation shock (Almond et al. 2009 Chernobyl), Nutrition shocks (Almond et
al. 2007 china famine),
• Economic shocks (Banerjee et al. 2010 19th century blight in French vineyards,
Baten et al. food prices in Britain 18th century). Variation in infectious disease
(Almond 2006 Influenza, Barreca 2009 malaria)
• Positive and policy driven events in early childhood:
• Food stamps program in USA that increasing family resources ((Hoynes et al.
2012) leads to reduction in incidence of obesity, high blood pressure, heart
disease, diabetes, as well as an increase in reporting to be in good health.
• Migration to Sweden (Van Den Berg et al. 2012) at early childhood leads to
improved outcomes at adulthood.
Literature
• Economic
• Field et al "Iodine Deficiency and Schooling Attainment in Tanzania." AEJ Applied (2009).
“Our findings suggest a large effect of in utero iodine on cognition and
human capital: treated children attain an estimated 0.35-0.56 years of
additional schooling relative to siblings and older and younger peers.
Furthermore, the effect appears to be substantially larger for girls,
consistent with laboratory evidence indicating greater cognitive
sensitivity of female fetuses to maternal thyroid deprivation.”
In This Research Project
We use the immigration from a poor African country (Ethiopia) to a developed economy (Israel) in May 1991:
• Quasi-experimental variation• Immigration was unexpected, in a short time and not self selected• Random variation in the timing of pregnancy and birth
• Different environmental conditions during pregnancy
• Pregnant women experienced different environmental conditions because of immigration, especially in terms of micronutrient deficiencies.
• Natural Regression discontinuity Design
• Comparing cognitive and high school achievements of children who faced dramatic differences in prenatal conditions in utero based on their gestational age upon arrival to Israel in May 1991.
Unique in this Study
• Using unique identification based on a positive event of environmental differences caused by immigration.
• Investigating the effects of environmental conditions in utero in different stages of pregnancy on cognitive outcomes.
• Policy implications for developed and developing countries.
• Understanding of intergenerational effects of immigration
The immigration from Ethiopia to Israel
• In 1975 the Ethiopian Jews were recognized as Jewish by the state of Israel and allowed to immigrate to Israel under the Law of Return.
The immigration from Ethiopia to Israel
• “Operation Moses” - 6,000 immigrant airlifted from Sudan secretly between end of 1984 and 1985.
The immigration from Ethiopia to Israel
• "Operation Solomon" - On May 24th 1991 the Israeli government
brought to Israel more than 14,000 Ethiopians Jews within 36 hours.
“Operation Solomon” – May 24th 1991
Why is it Natural Experiment?
• Unexpected • Organized by the Israeli government as a rescue operation following
unstable political situation in Ethiopia
• Completed in short time • Airlift by Israeli aircrafts within 36 hours
• Not self selected• Included almost all the Jews living in Ethiopia
The quasi-experimental variation properties:The timing of immigration uncorrelated with the timing of
the pregnancy and birth The decision to immigrate uncorrelated with unobserved
factors like family background
Analysis Sample
Students born in Israel between June 1991 and February
1992 to mothers who immigrated to Israel in "Operation
Solomon“:
• Their pregnancy incepted in Ethiopia but they were born in Israel
• Experienced the same conditions at birth and at later life
• Faced dramatic differences in prenatal conditions in utero based on their gestational age upon arrival to Israel in May 1991
Analysis Sample
The birth distribution of all the "Operation Solomon" offspring:
Large environmental differences between Ethiopia and Israel that may have affected pregnant mothers
• Micro Nutrient Supplements:• Ethiopia: No vitamins consumption (less then 1% of pregnant women age
15-49 took iron supplements for 90+ days – DHS 2011).• Israel: use of vitamins during pregnancy, mainly iron and Folid Acid
(Granot et al. (1996)).• Iodine: Ethiopia remains severely iodine deficient. Children in Northern
Ethiopia are Iodine Deficient (Girma et al. 2014). Iodine level in Israel is adequate.
• Health Care and Pregnancy Monitoring:• Ethiopia: Little or no medical care during pregnancy. In Israel: modern
health care and medicine, regular monitoring.
• Leaving Conditions and Nutrition• Income per capita in Israel 60 times higher, nutritional level and quality in
Israel better than in Ethiopia. Probably not much difference in short term.
Environmental Differences
Source Ethiopia Israel Indicator
Israel (CBS 1993)Ethiopia (IFPRI 1993)
1,516 3,089 Calorie Supply Per Capita
The world bank (1990/1) 120 10 Mortality rate, infant (per 1,000 live births)
The world bank (1990/1) 202 12 Mortality rate, under-5 (per 1,000 live births)
The world bank (2000/1) 15 8 Low birth-weight babies (% of births)
The world bank (2000) 27 100 Pregnant women receiving prenatal care (%)
Data
Israeli Ministry of Education Database 2007-2011:
• Students administrative records
• Birth date, Own and parental country of origin, Immigration date.
• Family characteristics – parents schooling, number of siblings.
• High School data
• Completion of 12th grade.
• Obtaining matriculation certificate by age 18.
• matriculation certificate is required for admission for academic post secondary schooling and for some jobs.
• Credit units of matriculation exams.
• Measure the quality of the matriculation program.
• Units in English and math, measures of inetability
Background Characteristics by Treatmetment
First Trimester Second
Trimester
Third
Trimester
Mother's age at birth 30.76 30.91 30.59(9.281) (8.516) (8.788)
Parents's age gap 10.49 11.29 11.11(7.143) (7.749) (6.987)
Birth order 2.789 2.703 2.866(1.966) (1.883) (1.895)
Father's years of schooling 2.183 2.415 1.838(3.675) (4.079) (3.552)
Mother's years of schooling 1.972 2.415 2.317(3.539) (3.906) (3.823)
Definition of Treatment
1. Treatment Definition by Trimester• First trimester constitute the most critical time for negative effects of
deficiencies in micro nutrients and iodine. Evidence from effect of famine on cognitive abilities later in life (Von Hinke Kessler Scholder et al. (2014), Neugebauer et al. (1999), Rooij et al. (2010)).
2. Treatment Definition by the critical period for fetus brain Development:• Week 8 to week 25 is viewed as the critical period of pregnancy for fetus
brain and cognitive development (Nowakowski and Hayes (2008), Loganovskaja and Loganovsky (1999). E.X. damage caused by radiation to human fetus in this period can result in cognitive deficits that still manifest 16-18 years after birth it is the major neuron genetic period of the developing human neocortex.
The key variable: The gestational age of the student at immigration (measured by weeks)
Balancing Tests
Testing the correlation between observable characteristics and timing of pregnancy based treatment definition by Trimesters:
Treatment Period
Mother age at birth
Parents age gap
Number of
sibiling
Birth order
Indictor for
twins
Mother schooling
trimester_1 0.165 -0.628 0.000-0.078-0.079 0.006 -0.454 0.239 -0.020(0.776) (0.690) (0.246)(0.164)(0.197) (0.033) (0.384) (0.325) (0.055)
trimester_2 0.323 0.192 -0.016-0.159-0.162 -0.017 -0.048 0.438 0.020(0.826) (0.674) (0.205)(0.213)(0.206) (0.027) (0.381) (0.295) (0.051)
Observations 624 624 624 2473624 624 624 624 572
Father schooling
SES of first
locality of
Mean Outcomes by Treatment First Trimester Second Trimester Third Trimester
Birth weight 3076.0 3087.4 3021.4(491.2) (487.2) (468.8)
Did not repeat 6th-12th grade 0.829 0.809 0.754(0.377) (0.394) (0.432)
Matriculation diploma 0.346 0.199 0.197(0.477) (0.400) (0.399)
Matriculation units 12.91 12.26 8.972(11.35) (11.38) (10.15)
Math units 1.476 1.347 0.915(1.538) (1.549) (1.355)
English units 2.224 2.025 1.620(1.900) (1.899) (1.817)
Math 5 units 0.0163 0.0127 0(0.127) (0.112) (0)
The Baseline Model• Treatment definition by trimesters:
(1)
• - Student school outcome
• - Vector of student characteristic
• The omitted category is Third trimester
• Treatment definition by weeks:
(1)
We expect that
• Shortcomings:• Not include cohort and month of birth effects.• Estimates may be confounded by unobserved cohort effects or substantial
seasonality in school performance by month of birth.
Controlling for Cohort and Month of Birth Effects
(1) Adding a respective older cohort:
(2) Adding two comparison groups for the two cohorts:
“Before Treatment” – Pre cohort “Post Treatment” – Primary sample
June 1990 to February 1991 cohort June 1991 to February 1992 cohort
Control for cohort effects and seasonality in the timing of birth inIsrael.
Conception and birth In Israel
Second-generation immigrants from "Operation Moses“(parents immigrated before 1989)
Group A
Control for cohort effects and seasonality in the timing of conception inEthiopia.
Conception and birth In Ethiopia
Ethiopian born students who immigrated between 1992 and 2000
Group B
Students born in Ethiopia between June 1990 and February 1991 andimmigrated to Israel on "Operation Solomon":
Controlling for Cohort and Month of Birth Effects• Treatment definition by weeks:
(2)
• - Month of birth fixed effects
• - Students born between June 1990 and February 1991
• - Students born in Ethiopia
• - Students born in Israel to “Operation Moses” immigrants
• - Students born Ethiopia and immigrated after 1991
Effect on Schooling Attainment
Effect on Repetition and Matriculation OLS Baseline
Treatment
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 0.078** 0.068 0.151*** 0.137**(0.037) (0.041) (0.052) (0.057)
Trimester_2 0.054 0.051 -0.000 -0.005(0.038) (0.039) (0.049) (0.053)
Did not repeat 6th-12th
grade
Matriculation
diploma
Effect on Repetition and Matriculation Two Years Cohorts Sample
Treatment
Wit
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 0.411***0.073*** 0.072*** 0.097** 0.094*(0.108)(0.020) (0.022) (0.045) (0.047)
Trimester_2 0.135 0.058 0.054 0.026 0.023(0.094)(0.035) (0.035) (0.032) (0.030)
Observations 2473 2473 2473 2473 2473
Did not repeat 6th-12th
grade
Att
Matriculation
diploma
Effect on Quality of the Matriculation Program OLS Baseline
Treatment
With
Controls
No
Controls
Wit
No
Controls
With
Controls
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 3.387*** 3.129***3.096***0.444*** 0.426** 0.555*** 0.472** 0.016** 0.013**(1.034) (1.065)(0.950)(0.152) (0.163) (0.201) (0.199) (0.007) (0.006)
Trimester_2 2.613** 2.677**2.161**0.249 0.243 0.420* 0.401* 0.009 0.006(1.077) (1.088)(0.759)(0.156) (0.163) (0.210) (0.203) (0.006) (0.006)
Observations 624 624 2473 624 624 624 624 624 624
Matriculation units Math 5 unitsMath units English units
Effect on Quality of the Matriculation Program Two Years Cohorts Sample
Treatment
With
Controls
No
Controls
Wit
No
Controls
With
Controls
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 3.154*** 3.096***3.096***0.468*** 0.463*** 0.455* 0.436* 0.021** 0.020**(1.008) (0.950)(0.950)(0.118) (0.116) (0.249) (0.250) (0.009) (0.009)
Trimester_2 2.177** 2.161**2.161**0.194** 0.192** 0.328 0.311 0.015* 0.015*(0.861) (0.759)(0.759)(0.092) (0.085) (0.203) (0.194) (0.008) (0.008)
Observations 2473 2473 24732473 2473 2473 2473 2473 2473
Matriculation units Math 5 unitsMath units English units
Effect Size
Effect on Matriculation diploma is about twice the effect of attending a high quality primary school versus a low quality primary school
Gould, Lavy and Paserman, QJE May 2004:“Immigrating tp Opportunity: Estimating the Effect of School
quality Using A Natural Experiment on Ethiopians In Israel ”
Additional Results• Heterogeneity Effect by Gender:
• Large and significant effect for girls.• Small and insignificant effect for boys.
• Heterogeneity Effect by Family Education:
• Much larger and significant effect among the "high education" group.• Negligible effect for the low education group.
• Robustness Checks:
• Results are similar when dropping from the sample students who born in the last two weeks of February.
• Placebo test: Estimating equation (2) for the comparison groups only.
Effect By Gender
Effect on Repetition and Matriculation Two Years Cohorts Sample, GIRLS
Treatment
Wit
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 0.411***0.137*** 0.126*** 0.164* 0.157*(0.108)(0.037) (0.038) (0.081) (0.079)
Trimester_2 0.1350.098** 0.089* 0.093 0.089(0.094)(0.045) (0.047) (0.090) (0.091)
Observations 2473 1201 1201 1201 1201
Matriculation
diploma
Did not repeat 6th-12th
grade
Att
Effect on Repetition and Matriculation Two Years Cohorts Sample, BOYS
Treatment
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 0.011 0.013 0.064 0.063(0.043) (0.044) (0.052) (0.055)
Trimester_2 0.015 0.012 0.037 0.035(0.035) (0.036) (0.041) (0.041)
Observations 1272 1272 1272 1272
Matriculation
diploma
Did not repeat 6th-12th
grade
Effect on Quality of the Matriculation Program Two Years Cohorts Sample, GIRLS
Treatment
With
Controls
No
Controls
Wit
No
Controls
With
Controls
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 4.366*** 4.112***3.096***0.590*** 0.585*** 0.661* 0.626* 0.007 0.008(1.441) (1.407)(0.950)(0.163) (0.163) (0.333) (0.346) (0.011) (0.011)
Trimester_2 2.899* 2.699*2.161**0.118 0.111 0.516 0.478 0.016 0.016(1.498) (1.440)(0.759)(0.179) (0.170) (0.312) (0.338) (0.011) (0.011)
Observations 1201 1201 24731201 1201 1201 1201 1201 1201
Math 5 unitsMath units English unitsMatriculation units
Effect on Quality of the Matriculation Program Two Years Cohorts Sample, BOYS
Treatment
With
Controls
No
Controls
Wit
No
Controls
With
Controls
No
Controls
With
Controls
No
Controls
With
Controls
Trimester_1 2.191* 2.088*3.096***0.370* 0.359 0.307 0.259 0.036*** 0.033**(1.086) (1.078)(0.950)(0.206) (0.208) (0.260) (0.245) (0.012) (0.012)
Trimester_2 1.599* 1.581**2.161**0.271* 0.253 0.172 0.141 0.014 0.013(0.782) (0.680)(0.759)(0.152) (0.149) (0.234) (0.207) (0.009) (0.009)
Observations 1272 1272 24731272 1272 1272 1272 1272 1272
Math 5 unitsMath units English unitsMatriculation units
Why larger effect on girls?
Evidence of larger impact for girls is consistent with related literature.
1. Baird et al (2011) find that in DC girls infant mortality is significantly more
sensitive to aggregate economic shocks during pregnancy.
2. Field et al. (2009) find that delays in resupply of iodine for pregnant
women in Tanzania has larger educational improvements for girls.
3. Oreopoulos et al. (2008) show that effects of infant health on reaching
grade 12 by age 17 appear to be stronger for females than males.
4. Hoynes et al. (2012) find that increasing family resources during early
childhood improve health at adulthood for both men and women but have
positive significant effect on economic self-sufficiency only for women.
5. Gould et al. (2011) find that early childhood living conditions affected only
girls short and long term outcomes (until age sixty).
Why larger effect on girls?Other studies, suggest that from conception and during pregnancy, males are
more vulnerable than females.
1. Ravelli et al. (1999) show that in the Dutch famine during the Second World
War the number of boys born fell in relation to the number of girls.
2. Eriksson et al. (2010) suggests that in the womb boys have a more dangerous
growth strategy than girls. They grow more rapidly and invest less in placental
growth, which puts them at greater risk of becoming undernourished.
3. Kraemer (2000) discusses how the human male is, on most measures, more
vulnerable than the female, a vulnerability that is attributed in part to the biological
fragility of the male fetus and argues that girls are more likely to survive adverse
in utero health conditions.
Why larger effect on girls?
If there are more spontaneous abortions of boys in utero during adverse
conditions, as suggested in the literature, one possible explanation for our
findings could then be that better environmental conditions early in utero
enabled marginal boys to be born.
This could explain the absence of an effect of early exposure to better
environmental conditions among boys since we compare between
relatively stronger boys born to mothers who immigrated during weeks
25+ and marginal boys born to mothers who immigrated during weeks 1-
7.
Effect by Parental Education
Effect on Repetition and Matriculation Two Years Cohorts Sample, By Education
TreatmentNo Controls With Controls No Controls With Controls
Trimester_1 0.102*** 0.097*** 0.034 0.029
(0.026) (0.026) (0.028) (0.031)
Trimester_2 0.088** 0.081** -0.019 -0.026
(0.031) (0.035) (0.041) (0.041)
Observations 1489 1489 1489 1489
Trimester_1 0.008 0.017 0.220** 0.203*
(0.066) (0.069) (0.099) (0.098)
Trimester_2 -0.020 -0.020 0.112* 0.098
(0.075) (0.077) (0.059) -0.058
Observations 984 984 984 984
Low Education
High Education
Did not repeat 6th-12th grade Matriculation diploma
Effect on Quality of the Matriculation Program Two Years Cohorts Sample, By Education
Treatment
With Controls No Controls Wi
No Controls With Controls No Controls With Controls No Controls With Controls
Trimester_1 2.815*** 2.823*** 3.096***0.457*** 0.448*** 0.391* 0.400** 0.036** 0.036**(0.954) (0.863) (0.950) (0.138) (0.132) (0.205) (0.189) (0.014) (0.014)
Trimester_2 2.019 2.035 2.161** 0.240 0.234 0.140 0.155 0.025** 0.025**(1.337) (1.311) (0.759) (0.204) (0.200) (0.226) (0.210) (0.012) (0.012)
Observations 1489 1489 2473 1489 1489 1489 1489 1489 1489
Trimester_1 5.115* 4.495 3.096***0.817*** 0.762** 0.729 0.661 0.003 0.002(2.676) (2.597) (0.950) (0.273) (0.275) (0.580) (0.590) (0.017) (0.015)
Trimester_2 4.109* 3.706* 2.161** 0.633** 0.595** 0.612 0.555 0.014 0.012(2.329) (2.066) (0.759) (0.254) (0.234) (0.527) (0.499) (0.011) (0.011)
Observations 984 984 984 984 984 984 984 984
Math 5 unitsMath units English units
Low Eduction
High Education
Matriculation units
Why larger effect in educated families?
These results are consistent with previews findings in the literature . Studies found that the negative impact of poor fetal health [Currie and Hyson (1999)] or exposure to negative shocks in utero [Almond, Edlund and Palme (2009)] on human capital accumulation is greater in low-education or low-income
families . The explanation given for this finding is that higher educated families tend to
compensate for negative shocks to fetal health or to poor birth health outcomes . Moreover, negative shocks have usually smaller effects on children in high
income families because they are less vulnerable . In our analysis we evaluate the effect of positive shock so obtain the opposite result. The explanation can be that mothers with some formal education are able to take more advantage of a positive environmental shock by accessing more better medical technologies and nutrition.
Effect on Birth Weight
Effect on Birth Weight
No Controls With Controls No Controls With Controls
trimester_1 55.097 45.474 23.378 22.342(64.204) (62.415) (70.271) (65.017)
trimester_2 68.656 62.457 1.283 -5.066(61.729) (58.122) (76.401) (70.150)
47.545 47.954(50.822) (54.760)
Observations 612 612 1082 1082
Treatment
Operation Moses
Only "Operation Solomon"
"Operation Solomon" & "Operation Moses"
Effect on Low Birth Weight (< 2500 gr)
No Controls With Controls No Controls With Controls
trimester_1 -0.013 -0.013 0.010 0.008(0.039) (0.036) (0.044) (0.043)
trimester_2 -0.023 -0.024 -0.017 -0.018(0.039) (0.038) (0.042) (0.039)
0.005 -0.002(0.032) (0.034)
Observations 612 612 1082 1082
Only "Operation Solomon"
"Operation Solomon" & "Operation Moses"
Treatment
Operation Moses
Effect on Very Low Birth Weight (< 1500 gr)
No Controls With Controls No Controls With Controls
trimester_1 -0.003 -0.001 -0.019 -0.014(0.008) (0.007) (0.013) (0.011)
trimester_2 0.001 0.002 -0.025* -0.021*(0.009) (0.008) (0.013) (0.011)
-0.005 -0.003(0.009) (0.009)
Observations 612 612 1082 1082
Treatment
Operation Moses
Only "Operation Solomon"
"Operation Solomon" & "Operation Moses"
Potential Longer Term Returns
Potential Longer Term Benefit Annual wage Post secondery
educationUniversity Years at University
Mean 52002.62 0.632 0.056 0.142
Explanatory variable
4782.43** 0.217*** 0.116*** 0.340***(2304.6) (0.026) (0.017) (0.056)
376.969*** 0.016*** 0.004*** 0.012***(105.64) (0.001) (0.001) (0.002)
204.845*** 0.007*** 0.002*** 0.006***(55.98) (0.001) (0.000) (0.001)
6824.714 0.171*** 0.134*** 0.184**(4636.27) (0.024) (0.039) (0.074)
Observation 1115 1115 1115 1115
Advance math
Matriculation diploma
Matriculation units
Matriculation average score
Conclusions• Exposure to better environmental conditions in utero during the first trimester
of gestation (before week 13 at the latest or week 8 at the earliest) is
associated with substantially better high stakes cognitive achievements by
end of high school.
• Large expected earnings gain at adulthood.
• Expected large effect on productivity and standard of living (ignoring general
equilibrium effects).
• Policy implications for developing countries: importance of pre-natal
nutritional supplement programs, gains outweigh cost
• Policy implications for developed countries with immigration from poor
African countries (ex., Israel, Italy, France, Spain): target prenatal nutritional
supplements
Definition of Treatment
By Weeks (by the critical period for fetus brain development):
By Trimester:
0-45-89-1213-1617-2021-2425-2829-3233-38-15.00
-10.00
-5.00
0.00
5.00
10.00
15.00
Figure 2: Coefficients of weeks (grouped by 4 weeks) of gestation at immigration on total matriculation units
Weeks of gestation at immigration (33-38 omitted)
Linear regression: searching for the critical period
Estimated Effect of In-Utero Environment on Schooling Outcomes by Age 18 -Linear effect
Dropped out of high school before
completing 12th grade
Obtained a matriculation diploma
after 12 years of schooling
Total matriculation units
Math matriculation units
English matriculation units
Dependent variable
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Week
0.001 -0.003 -0.005**
-0.021***
-0.175*** -0.323**
-0.022*** -0.054**
-0.029*** -0.073**
(0.002) (0.005) (0.002) (0.006) (0.046) (0.164) (0.006) (0.022) (0.007) (0.027)
Week^20.000 0.000 0.005 0.001 0.001*
(0.000) (0.000) (0.005) (0.001) (0.001)
Number of students
418
Effect on Attending a Regular School, Repetition and Matriculation Two Years Cohorts Sample, By Education and Gender
TreatmentNo Controls With Controls W
iNo Controls With Controls No Controls With Controls
Trimester_1 0.089 0.115 0.411*** -0.083 -0.044 0.063 0.092
(0.099) (0.114) (0.108) (0.112) (0.127) (0.066) (0.068)
Trimester_2 -0.072 -0.071 0.135 -0.080 -0.066 0.017 0.040
(0.083) (0.090) (0.094) (0.118) (0.143) (0.040) (0.036)
Observations 478 478 478 478 478 478
Trimester_1 0.592*** 0.540** 0.101* 0.097 0.385** 0.367***
(0.186) (0.189) (0.056) (0.061) (0.139) (0.124)
Trimester_2 0.146 0.100 0.044 0.049 0.214* 0.189
(0.154) (0.161) 2473 (0.076) (0.078) (0.107) (0.114)
Observations 506 506 506 506 506 506
High Education - Boys
High Education - Girls
Did not repeat 6th-12th gradeAttend regular school Matriculation diploma
Effect on Quality of the Matriculation Program Two Years Cohorts Sample, By Education and Gender
Treatment
With Controls No Controls Wi
No Controls With Controls No Controls With Controls No Controls With Controls
Trimester_1 -1.251 -1.345 3.096*** 0.432* 0.451 -0.352 -0.358 0.026 0.027(2.464) (2.729) (0.950) (0.240) (0.282) (0.502) (0.568) (0.024) (0.020)
Trimester_2 0.728 0.464 2.161** 0.406 0.384 -0.066 -0.120 0.002 0.004(2.471) (2.357) (0.759) (0.303) (0.292) (0.489) (0.495) (0.006) (0.007)
Observations 478 478 2473 478 478 478 478 478 478
Trimester_1 10.818*** 9.899*** 3.096***1.176*** 1.090*** 1.706*** 1.666** -0.019 -0.023(2.618) (2.660) (0.950) (0.325) (0.327) (0.576) (0.617) (0.019) (0.021)
Trimester_2 7.020*** 6.183** 2.161** 0.842*** 0.775** 1.173** 1.173* 0.022 0.020(1.954) (2.310) (0.759) (0.263) (0.305) (0.519) (0.579) (0.022) (0.023)
Observations 506 506 506 506 506 506 506 506
Math 5 unitsMath units English units
High Eduction - Boys
High Education - Girls
Matriculation units
Summary Statistics
• Background characteristics:• Comparing our primary sample to other students (Ethiopian origin and
Israeli natives) in the same cohort.
Summary Statistics
• Outcome variables:• Comparing our primary sample to other students (Ethiopian origin and
Israeli natives) in the same cohort.
Placebo TestEstimating equation (2) for the comparison groups only:
