thIn
Utero Exposure to Maternal Stress: Effects of the September 11
Terrorist Attacks in New York City on Birth and Early Schooling
Outcomes
Melissa
Eccleston October 11,
2011
PRELIMINARY
DRAFT
Abstract
growing body of primarily observational research finds that exposure to maternal
psychological stress while in utero may have substantial effects on physical and mental health, as
well as cognitive ability. This paper estimates the causal effect of exposure to the stress of the
September 11th, 2001 terrorist attacks on the cohort in utero that day using birth data from the
National Vital Statistics System and New York City public school student records. The analysis
finds that cohorts exposed during first or second trimester in New York City were 1-1.5 days
younger, weighed 8-19 grams less, and had a 0.1% lower five-minute Apgar score at birth.
Male and female newborns were affected similarly. Births in the rest of the United States were
not affected. Initial educational attainment in New York City also suffered: at the age of six,
boys were 7-9% more likely to be in special education and 15-18% more likely to be in
kindergarten rather than first grade, with no effect on girls. The analysis accounts for
alternative causal channels, namely air pollution and economic recession. Effects estimated
outside the area of air pollution are very similar to estimates within it. Outcomes for a cohort
exposed in utero to a period of high unemployment following September 11, but not to the
terrorist attacks themselves, are not adversely impacted. The results suggest that psychological
stress is an important channel through which adverse conditions experienced by pregnant women
negatively impact the early life outcomes of in utero cohorts. JEL Codes: I14, I15, J13, O15.
thA
I. Introduction
Chronic psychological stress contributes to a broad range of adverse health and cognitive
outcomes. A growing body of research finds that stress may have substantial impacts even
before birth. In animal experiments, maternal exposure to temporary psychological stressors
during pregnancy results in offspring with impaired physical health and diminished cognitive,
emotional, and behavioral abilities (Kaiser and Sachser 2005).
However, our understanding of the nature and magnitude of effects for humans remains
limited due to the difficulties of causal estimation. Omitted variables bias, in particular the direct
effect of stressors on outcomes, makes the results of observational studies difficult to interpret.
Studies that do utilize exogenous variation are limited by the small number of relevant outcomes
measured.
The terrorist attacks of September 11 th, 2001 created a substantial and widespread
psychological shock, providing an opportunity to estimate the causal effects of stress exposure in
utero on early life outcomes. The analysis focuses on New York City, where the destruction and
psychological impact were greatest. Using Vital Statistics birth records from 1995 through 2004
and New York City public school student records from the 2003 through 2009 school years, I
estimate the effects of in utero exposure to the attacks on maternal health in pregnancy, health at
birth, and early schooling performance.
In line with the human and animal literature, I define the cohort first or second trimester
thin
utero on September 11, and therefore conceived in the spring or summer of 2001, as exposed.
The unexpected nature of the attacks and the limited duration of the psychological impact allow
causal estimation by comparing outcomes of the exposed cohort to those of cohorts conceived
1
prior to the spring of 2001 and to cohorts conceived after the attacks.1
thPregnant
women exposed to September 11 during first or second trimester were 2-5% more
likely to suffer from a medical risk and 2% more likely to experience a complication during labor.
Newborns were 1-1.5 days younger, weighed 8-19 grams less, and had a 0.1% lower five-minute
Apgar score at birth.2 Male and female newborns were affected similarly. Analysis of national birth
records finds neither effects in geographies proximate to the attacks nor a national impact.
Diminished health at birth has long-term effects on health and socioeconomic status, mediated
in part by childhood health and educational attainment (Case, Fertig and Paxson 2005; Oreopoulous
et al. 2008). Additionally, results from the animal experimental literature suggest that in utero
exposure may have cognitive, emotional, or behavioral effects which are not manifested or measured
at birth. I find evidence of such effects for boys at the onset of their education. At the age of six, boys
were 7-9% more likely to be in special education and 15-18% more likely to be in kindergarten rather
than first grade, with no effect on girls.
thFeatures
of September 11’s economic and environmental consequences in New York
City allow for assessment of their impacts on in utero cohorts. Air pollution was highly
geographically concentrated in lower Manhattan and western Brooklyn, and estimation
excluding these areas finds effects of similar magnitudes and significance. The economic
thdownturn
thcohort
attributed to September 11 was prolonged, and examination of the outcomes of a
conceived well after September 11 but exposed to poor economic conditions in utero
finds no effects.
1 Cohorts conceived prior to the
spring of 2001 were either third trimester in utero or already born on September 112th. Five-minute Apgar score is a
“summary measure of the infant’s condition” rating five aspects of newborn’s health five minutes after birth (NCHS
Technical Appendix 2004).
2
These results shed light on a difficult to measure mechanism through which a range of
adverse shocks in utero affect individual outcomes.3 Psychological stress may be a particularly
important channel in explaining the significant impacts of in utero exposure to relatively mild
adversities, such as severe storms (King and LaPlante 2005; Simeonova 2009), temporary income
shocks (Burlando 2010), and cold weather (Stoecker 2011).4 In addition, the estimates
contribute to our understanding of the long-term effects and full costs of the attacks of
thSeptember
11.
The remainder of the paper is organized as follows. Section II describes the primary
theffects
of September 11 in New York City and their implications for the cohort in utero.
Section III describes the data sources and construction. Section IV presents the main results,
followed by investigations of the potential for selective migration, heterogeneous effects, and
alternative causal channels. Section V concludes.
II. Background
II.A. September 11 th, 2001 in New York City
great loss of human life and physical
thThe
terrorist attacks of September 11 caused
property. The unprecedented scale and method of attack, vividly captured in film and photos,
elicited shock, sadness, and other feelings associated with trauma in onlookers around the world.
The most dramatic destruction and over 90% of the casualties occurred in New York City, which
experienced substantial environmental, economic, and psychological fallout over the ensuing
months and years.
3 See Almond and Currie (2011a;
2011b) for overviews of the long-run effects of in utero exposures and early life shocks. 4 With the exception of
Stoecker (2011), these papers find that adverse exposures in first and/or second trimester affect outcomes.
3
Environmental effects
September 11th created “an acute environmental disaster” in parts of New York City
(Landrigan et al. 2004). The collision of the airliners with the towers and the towers’ subsequent
collapse generated thousands of tons of airborne pollutants, including glass fiber, cement dust,
and a range of chemical compounds (Clark et al. 2001). Much of the particulate matter settled in
the vicinity immediately surrounding the site of the World Trade Center, leading to elevated
levels of respiratory illness among rescue workers and nearby residents (Farfel et al. 2008). A
large dust cloud also formed, spreading the airborne pollution across lower Manhattan, New York
Harbor, and western Brooklyn in the days following the attack before dispersing (Clark et al.
2001).
The effects of prenatal exposure to environmental toxins have been well documented. Air
pollution has been linked to infant mortality (Currie and Neidell 2005), lead exposure to low
birth weight (Reyes 2005), and radioactive fallout to diminished cognitive ability (Almond,
thEdlund
and Palme 2009). After September 11, two studies of pregnant women who were near
the World Trade Center towers during the attacks found a higher incidence of small-forgestational age births compared to other births at the same hospital (Landrigan et al. 2004).5
thBased
on satellite imagery from existing monitors and samples collected after September 11,
the Environmental Protection Agency concluded that levels of particulate matter in the air only
exceeded thresholds for health problems in the immediate vicinity of the World Trade Center in
the weeks following the attack (Lorber et al. 2007). I will use this spatial concentration to assess
if the effects of exposure could have been caused by pollution rather than stress.
th
percentile of weight for gestational age. One study
Small-for-gestational age is defined as being below the
10
found an effect on gestational age, but neither found an effect on birth weight. A limitation of these studies is that the
control group was likely affected as well.
5
4
Economic effects
Employment in New York City had been slowly declining since the beginning of 2001,
and dropped off sharply in the months after the attacks. Approximately 92,000 (or 2% of) private
sector jobs were lost in the city from September 2001 to March 2002, and 50-75% of these losses
were estimated to be a direct consequence of the attacks (Bram, Orr and Rapaport 2002). After
peaking in the second quarter of 2002, the unemployment rate declined modestly, but then rose
again in early 2003 before steadily declining, aided in part by $10 billion in federal economic
redevelopment assistance (Makinen 2002; U.S. Department of Labor 2011).
Poor economic conditions while in utero have been found to affect a range of outcomes.
In the extreme, prenatal famine exposure has been shown to increase the rate of schizophrenia in
adulthood, a link thought to be caused by a lack of micronutrients causing fetal genetic mutations
(Neugebauer, Hoek and Susser 1999 ). Common economic cycles have also been shown to
matter. Van den Berg, Lindeboom and Portrait (2006) find that cohorts in utero during recessions
in the Netherlands had higher mortality rates than their counterparts in utero immediately before
recessions began. Several channels could account for this effect. Reduced income could, for
example, push a pregnant woman to reduce her consumption of healthcare or significantly
increase her work effort. In contrast, Dehejia and Lleras-Muney (2004) find that birth outcomes
during times of high unemployment improve due to healthier behaviors and, for some subgroups,
positive selection into birth. I will assess the effect of in utero exposure to the economic
thslowdown
by examining the outcomes of a cohort conceived after September 11, when the
unemployment rate was high and rising, but the psychological shock had faded for most.
5
Psychological effects
The purpose of terrorism is “to intimidate a watching popular audience by harming only a
few”, and the dramatic violence of the attacks affected the mental health and behavior of millions
with no direct connection to the victims (Crenshaw 2000). A national phone survey conducted
ththree
to five days after September 11 (a weekend) found that 61% of respondents living within
100 miles of New York City, and 42% living farther away, were suffering from at least one
substantial stress symptom such as repeated disturbing thoughts or dreams about the attacks, or
feeling very upset when reminded of the attacks (Schuster et al. 2001).6
Additional evidence suggests that the psychological effects were both concentrated in
New York City and limited in duration. In the three month period following the attacks,
emergency room visits for mental or behavioral disorders rose 10% and the number of
psychiatric medication prescriptions rose 18% among Medicaid enrollees resident in the City
relative to enrollees in the rest of New York State (DiMaggio, Galea and Richardson 2007;
DiMaggio, Galea and Madrid 2007). Self-reports from phone surveys suggest that these rates
had declined back to long-run averages by four to five months after the attacks (Boscarino et al.
2004). More broadly, one month after the attacks, the rates of probable post-traumatic stress
disorder (PTSD) and depression among New York City residents were estimated to be over two
times higher than the national average, which itself was unaffected by the attacks (Galea et al.
2002; Schlenger et al. 2002).7
These rates had returned to national averages within five months
6 There are limited data with which
to compare these results, as few studies report “the prevalence of trauma-related symptoms of stress in people who do not
necessarily meet criteria for a psychiatric disorder” (Schuster et al. 2001). A study of the 1980-81 Epidemiological
Catchment Area survey provides evidence consistent with a point-in-time trauma-related stress symptom prevalence rate
among the general population of roughly half that found in Schuster et al. (Helzer, Robins and McEvoy 1987). 7 The
surveys in these studies were conducted through random-digit telephone dialing for Manhattan residents below 110th
street.
6
(Galea et al.
2003).
8
Behaviors were
also affected.
Surveys found
increased
alcohol,
tobacco, and
marijuana use among
New York City
residents who were prior
consumers in the
months after
thSeptember
11 (Vlahov
et al. 2004). Becker
and Rubinstein (2008)
find evidence of
avoidance
of commercial flights:
national passenger
volumes, relative to
cargo, declined 10
percentage
thpoints
after
Septembe
r 11, and
attack-rel
ated
routes
were
particularl
y
affected.9
While there is no
clear theory to
guide the
investigation of
in utero impacts
across
thgeographies,
the
evidence from
September 11 suggests
that both physical and
social proximity
are associated with larger
psychological effects.10
In particular, the
surrounding suburbs of
New
Jersey and New York
State, as well as the
Washington, D.C.
metropolitan area, may
have been
affected.11
National
and
area-specifi
c effects
will be
investigated
in Section
IV.C.
II.B. Prenatal effects of
psychological stress
According to the
American
Psychiatric
Association’s
Diagnostic and
Statistical
Manual
of Mental Disorders
(Fourth Edition),
psychosocial stressors
include difficult or
negative events
and situations related to
one’s family, friends,
work, or community.
Stressors prompt
cognitive
and emotional reactions,
and activate a
physiological stress
response. This
physiological
response is remarkably
consistent across
imminent external
stressors as well as
thoughts or
feelings regarding past
or potential stressors
(Sapolsky 2004).
A woman’s
physiological
stress response is
thought to affect
pregnancy
through three
interrelated biological
channels. A primary
component of the body’s
complex stress response
is
Among rescue workers
and those directly exposed to
the attack, rates of PTSD have
actually risen over time
(Thorpe 2009). Becker and
Rubinstein (2003) find that
the NYC-London route
suffered a substantial decline
in passenger volume
compared to the
Chicago-Paris route. 10 I
define social proximity as the
likelihood of knowing
someone affected by the
attacks.
The third crash
site, near Shanksville,
Pennsylvania, is less likely to
have been affected, given that
nearby residents were
unlikely to have known the
victims on the flight, no one
on the ground was injured or
killed, and the area was not
the intended target.
1198
7
the production of hormones, including corticotropin-releasing hormone (CRH) and cortisol.
CRH plays important roles in fetal maturation and in the process of parturition (Wadhwa et al.
2001). Observational medical studies consistently find strong correlations between maternal
psychosocial stressors, CRH levels in early to middle pregnancy, and risk of preterm birth and
delivery complications (Paarlberg et al. 1995; Dunkel-Schetter et al. 2000). These studies utilize
women’s self-assessments of stress or self-reported incidents of stressful events. For example,
Da Costa et al. (2000) find that women who report facing stressful incidents were more likely to
have a complication in labor or delivery, and the newborns of women who were dissatisfied with
their social support weighed less.
In addition to regulating fetal maturation, hormones produced in response to stress play
an epigenetic role in fetal development of nervous, endocrine, and immune systems, thereby
affecting future cognitive, behavioral, and emotional abilities, as well as health (Meaney and
Seckl 2004; Van den Bergh et al. 2005). Excess exposure to cortisol has been correlated with
impaired development of the brain and spinal cord, as well as diminished mental and motor skills
of infants (Yu et al. 2004; Huizink et al. 2003). Several observational studies have also found
negative correlations between women’s blood cortisol or self-assessed level of stress during
pregnancy and the emotional and mental health of their children through middle school age (de
Weerth and Buitelaar 2005; Malaspina et al. 2008). Effects on health outcomes are just
beginning to be studied in humans; for example, Li et al. (2010) find that in utero exposure to
maternal stress increases the risk of being overweight starting at age 10.
Thirdly, chronic stress has a well-established correlation with disease and deterioration of
bodily systems. The theory of allostatic load posits that this is a causal relationship, by which
frequent stimulation of the body’s stress response causes harm over time (McEwen and Stellar
8
1993). Some of the conditions correlated with chronic stress are known to directly affect
pregnancy; for example, hypertension increases the risk of labor complications and preterm birth
(Warren, Gurewitsch and Goland 1995). In addition to the biological channels, maternal stress
may also affect pregnancy through behavior. Patterns of eating, sleeping, and drug use can all be
altered by psychological stress, and directly affect the health of a pregnancy.
While the relationships between and relative importance of these channels continues to be
studied, the current evidence suggests that stress is most strongly correlated with negative
outcomes when experienced in the first two trimesters of pregnancy (Wadhwa 1998; Glynn et al.
2001). This may be driven by the range of vulnerable developmental processes that occur early
in pregnancy; in addition, women may become less reactive to stressors in the third trimester as a
protective mechanism (Kammerer et al. 2002). However, because these observational studies
lack sources of exogenous variation in stress, the concern remains that measures of stress are
correlated with other determinants of fetal health, including stressors that directly affect health
and relevant maternal characteristics, such as the ability to cope with difficulties.
In medical research, randomized experiments with animals ranging from rats to primates
have provided causal estimates of the effects of temporary stress on pregnancies. Exposure of
pregnant females to a range of stressors, including unstable social groupings, unexpected stimuli,
or physical discomfort, results in offspring with lower birth weight, impaired cognitive ability, or
diminished behavioral skills (Kaiser and Sachser 2005). The form and severity of impairment, as
well as differences by offspring gender, vary with the species, the type and severity of stressor
imposed, and the timing of exposure.
For humans, plausibly exogenous shocks to stress are rare, but a small number have been
used to identify causal impacts of stressful events on birth outcomes. Hansen, Lou and Olsen
9
(2000) examine the effects of a deadly diagnosis or death of a loved one during first trimester of
pregnancy in a sample of Danish women, finding a marked increase in the rate of cranial neural
crest malformations.12 With an approach similar to this paper, Camacho (2008) utilizes the
unexpected timing of terrorist landmine explosions in Colombia and finds that cohorts in utero
first trimester when a landmine exploded in the municipality of their birth weighed
approximately 9 grams, or 0.3%, less than average.
However, birth weight is the only outcome
Camacho is able to examine, leaving unanswered the potential for effects on the health of a
pregnancy, other measures of health at birth, and later life outcomes.
While the existing literature does not include the use of exogenous shocks to measure
effects beyond birth, Aizer, Stroud and Buka (2009) reduce the scope for bias from unobserved
maternal characteristics by utilizing variation in blood cortisol across pregnancies for siblings.
They find that childhood health, IQ, and ultimate educational attainment are negatively impacted
by high maternal blood cortisol during pregnancy.13
Recent medical findings suggest that female fetuses may be less susceptible or better able
to adapt to changes in their uterine environment, and therefore potentially less likely to be
impacted by maternal stress (Stark, Wright and Clifton 2009; Charil et al. 2010). However,
evidence of gender differences in susceptibility to the effects of stress is mixed. After negative
shocks such as economic recessions and natural disasters, which cause both psychological and
physical stress, the sex ratio at birth is often found to shift towards females (Catalano et al.
2006). Some studies, including Aizer, Stroud and Buka (2009), find no differences across
gender in the magnitude and type of effects.
12 Cranial neural crest are precursor
cells responsible for the formation of most structures of the head and face. These cells are known to be sensitive to a
range of environmental signals, and resulting defects include cleft lip and
cleft palate. 13 Aizer, Stroud and Buka (2009) find weak evidence for effects on birth outcomes, which they believe may
be due to the way in which their sample was constructed (see pgs. 18 and 24).
10
thII.C.
Psychological effects of September 11 on pregnancy outcomes
thA
handful of studies have examined September 11’s psychological effects on a narrow
range of pregnancy outcomes, and most have found negative impacts. In New York City and
surrounding New York State suburbs, Eskenazi et al. (2007) find an increase in the rate of very
low birth weight (<1500 grams) births for pregnancies that were first or second trimester on
thSeptember
11.14 Catalano et al. (2005; 2006) find that the sex ratio at birth dipped in January
2002 in both California and New York City, which the authors suggest is due to increased rates
of spontaneous abortion of male fetuses caused by the psychological trauma of the attacks.
thThe
spike in incidents of discrimination and hate crimes following September 11 was
itself a source of stress for the targeted population. Lauderdale (2006) estimates the effect of
increased discrimination on the birth outcomes of Arabic women in California. She finds that
births to women with distinctly Arabic names were two times more likely to be low birth weight
in the six calendar months after the attacks. Results from other studies of births after September
11th vary, potentially because they have focused on populations less likely to have been affected.
In a sample of Dutch infants, Smits et al. (2006) find a 48-gram reduction in birth weight for
ththose
in utero on September 11, but Rich-Edwards et al. (2005) find that a sample of women in
thBoston
who were in their first trimester of pregnancy on September 11 were less likely to
deliver preterm (Rich-Edwards et al. 2005). Endara et al. (2009) find no effect on birth
outcomes for a sample of active-duty military families residing across the U.S.
By utilizing the full range of relevant outcomes available in the Vital Statistics birth data,
I provide evidence of the effects of psychological stress on health at birth and one potential
causal channel, maternal health in pregnancy. In addition, the evidence from early schooling
14 Eskenazi et al. (2007) use data
from 1996 through 2002 and therefore have a limited post-September 11th sample. The authors also consider the rate of
pre-term birth, finding no evidence of impact. Effects on birth weight in the suburbs are weaker than those in New York
City.
11
records provides the first estimate of effects beyond birth using plausibly exogenous variation in
stress.
III. Data
III.A. Pregnancy outcomes
Data on pregnancy outcomes come from the National Center for Health Statistics’ Vital
Statistics public use data files.15 The birth data files contain the information recorded on every
birth certificate issued in the United States. I combine this data with the fetal death data files,
which contain information recorded on all reported fetal deaths. I limit the sample to live births
and fetal deaths occurring to women whose residence is listed as one of the five counties,
equivalent to the five boroughs, of New York City.
I pool the data between 1995 and 2004,
resulting in almost 1.2 million observations.16
The data report month and year of birth, as well as estimated weeks of gestation at birth.
Using this information, I determine whether a pregnancy was in progress, and if so, in which
thtrimester,
on September 11, 2001. I first assign all births in a given month to a birthdate equal
to the midpoint of that month. I subtract from this assigned birthdate the gestation estimate to
arrive at a conception date.
thI then count the number of weeks from the conception date to September 11, 2001.
t , 2001 were 0-13 weeks in utero on
thBirths conceived between June 18 and September
h
10
thSeptember
, and therefore defined as exposed during first trimester. Births
11
conceived
thbetween March
th and June 17, 2001 were 14-27 weeks in utero and therefore defined as
12
exposed during second trimester.17
15 These files are available
online at http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm The sample ends in 2004 because public Vital
Statistics do not report geographic information in subsequent years. There may be error in birth certificate measures of
gestation length (Wier 2007). I present an alternate version of specification (1), ignoring gestation estimates entirely, in
Appendix Table I. Results are very similar.
1716
12
III.A.i. Following the medical literature, I identify six outcomes that may be affected by maternal
stress.
1) For live births, I consider two indicators of the health of a pregnancy.
18a.
Any maternal medical risk factors: An indicator variable for the presence of one
or more factor. These factors are a set of diseases and health conditions that a
pregnant woman might enter pregnancy with or develop over its course, and that can
negatively impact a pregnancy’s outcome. Factors that have been shown to be
induced by stress are hypertension, eclampsia, and genital herpes, although other
factors may be related to stress (Higgins et al. 2002; Chida and Mao 2009).
b. Any complication of labor or delivery: An indicator variable for the presence of
one or more complication. These complications include placental abnormalities and
precipitously fast or excessively prolonged labor. Complications of labor and delivery
are more likely in women with high levels of stress and in women with certain
medical risks, including eclampsia (NCHS Technical Appendix 2004).
2) For live births, I consider three indicators of the health of a newborn.
a. Birth
weight: Weight immediately after birth, measured in grams. b. Gestational age: Estimated
in weeks from the date of mother’s last menstrual period (when unknown, a clinical estimate
is used). c. Five minute Apgar score (scaled from 0 to 10): A “summary measure of the
19infant’s condition” rating five aspects of newborn’s health (NCHS Technical Appendix
2004).
203) Fetal Death: An indicator variable for a pregnancy resulting in a fetal death rather than a live
birth. While New York requires the reporting of fetal deaths at all stages of pregnancy, the majority
of states do not require reporting under 20 weeks gestation.
Fetal death is consistently
underreported and gestation length measured with error. Underreporting and errors are most severe
at the earliest gestational lengths (Goldhaber 1989). I therefore consider only fetal deaths occurring
at 20 weeks gestation or later, and utilize only month and year of delivery data.
18 Appendix Table II presents
results for stress-related and other medical risk factors separately. The five aspects are heart rate, respiratory effort,
muscle tone, reflex irritability, and color. Each aspect is scored from 0 to 2, and the scores are totaled across aspects,
with a score of 10 considered optimal. The score is named after its inventor, Dr. Virginia Apgar. 20 Including fetal
deaths at all gestation lengths yields very similar results.
19
13
III.A.ii. Characteristics of the birth and mother recorded on birth certificates serve as control
variables.21
1) Gender of the newborn.
2) Indicator of plural birth (twins or higher order).
3) Age: Mother’s age at time of delivery.
4) Race: Mother’s self-identified affiliation, for which I construct five indicator
variables (Black, White, Hispanic, Asian, and Other).
5) Marital status: An indicator of whether or not mother is married at time of delivery.
6) Years of schooling: Mother’s educational attainment, for which I construct four
indicator variables (0-8 years, 8-12 years, 12-16 years, 16 or more years).
7) Parity: Number of live births mother has had prior to the current one. 8)
Mother’s borough of residence. III.B. Schooling outcomes
Data on schooling comes from the administrative records of the New York City
Department of Education for the 2003/4 through 2009/10 academic years.22 In order to
thseparately
identify the effect of exposure to September 11 from school year and grade effects, I
limit the sample in each academic year to children who turn six in the calendar year in which that
academic year begins. This allows me to observe children born before and after the exposed
cohort, and to use grade level as an outcome measure, because New York City allows children to
stenter
first grade if their sixth birthday occurs by December 31 of the calendar year in which the
21 Other recorded characteristics,
such as tobacco and alcohol use, may be partially determined by the effects of stress and are omitted. Tobacco and
alcohol use, on both extensive and intensive margins, were examined as behavioral outcomes of September 11 22th
exposure, and no results were found. Based on comparisons of enrollment numbers with population counts in the
American Community Survey, approximately 65-80% of elementary school-aged children (K-8 grades) in New York
City are in public school. Selective sorting out of public school by unaffected children in the exposed cohort would create
bias in the direction of the results.
14
academic year begins.
The administrative records do not include data on student’s place of birth or parents’
former places of residence. I exclude all children identified as English language learners, as their
mothers are relatively less likely to have been residing in New York City when pregnant.23
With this exclusion, the sample consists of slightly more than 410K observations of six year old
students across academic years.
The data report exact date of birth, which I use to define the affected cohort as children
thborn March
th to June
th, 2002 (27-40 weeks later) and December 11, 2001 to March 19th,
20
19
2002 (13-26 weeks later). If gestation for all children had been approximately 40 weeks, these
definitions would correspond directly to first and second trimester in utero exposure. If gestation
is shortened by exposure, using date of birth to identify exposure will incorrectly identify some
children as having been exposed one trimester later than they actually were. These errors may
attenuate the estimated effect of exposure in first trimester.24
III.B.i. Although the cohort exposed to September 11th in utero is still very young, I am able to
construct five measures of children’s educational performance.25
1) Attendance: A count of the number of days a student is recorded absent from school. At
the age of six, absence may be a plausible indicator for child health (rather than an indicator
of skipping school).
2) Behavior: An indicator equal to one if a student has one or more behavioral incidents
during a school year. Incidents are recorded and punished on a scale of one to four. For
children aged six, commonly reported incidents include “being insubordinate” and
“fighting/engaging in physically aggressive behavior”.
3) Special education: An indicator equal to one if a student is enrolled in a special
23 Over 50% of English
Language Learners are immigrants, and a significant additional share is believed to have parents who are immigrants
(NYC Department of Education 2007). 24 Because these errors may assign some first trimester exposures to second
trimester, and some second trimester exposures to third trimester (and therefore non-exposure), their net effect on the
estimate of exposure in second trimester is indeterminate. 25 Public school students in New York City begin taking
state standardized tests in grade three.
15
education program. Enrollment is highly correlated with both cognitive impairments and
behavioral issues (NYCLU 2011).
4) Held back: An indicator equal to one if a student is in kindergarten rather than first
grade in the calendar year in which he or she turns six.
5) Average grade per course: For kindergartners through fifth graders, courses are graded
on a scale of one to four. This data is available only for a 10% subsample, and is not
representative of the full sample.
III.B.ii. Students’ demographic and residential information is used to construct control
variables.26
1) Student’s gender
2) Student’s race: grouped into five categories (White, Black, Hispanic, Asian, and
Other)
3) Student’s current home zip code
IV. Econometric Specifications and Results
IV.A. Pregnancy outcomes
Live births
th
This section presents evidence of the effect of in utero exposure to September 11 for births
to women residing in New York City. I begin by comparing mean outcomes of live births across
years, grouped by estimated time of conception in order to account for seasonality in birth
thcharacteristics. As detailed in Section III.A., pregnancies in first trimester on September 11 are
thconceived approximately 0-13 weeks prior, between June
th and September 10, and
18
pregnancies in second trimester are conceived approximately 14-27 weeks prior, between March
12t th and June 17.
h
26 Student’s free lunch status is also
recorded, but is missing for nearly one quarter of the sample. Therefore I do not include it as a covariate but do examine it
as an outcome when assessing selection in Section IV.D.
16
Figure I displays the mean values of the five outcomes of interest for live births conceived
during these two windows annually from 1995 to 2003.27 While there is substantial annual
variation, pregnancies exposed to the attacks in 2001 deviate negatively from trends across the
five outcomes. As a falsification exercise, Figure II displays the same mean outcomes for births
thconceived between December
th and March 11, which are approximately third trimester in
27
, and for which studies predict limited effects of exposure to stres
t
h
Similar
annual variation is apparent, but the cohort’s outcomes are in line with neighbori
u
t
years.
e
r Regression analysis of live births exploits the limited nature of the exposure, and mea
o
ththe extent to which outcomes for children in utero on September 11 differ from the outc
o
children
born immediately before and after:
n
S
e
p
t
e
m
b
e
r
1
1
(1)
� �
=
� 1
2
* � ( � 𝑛� � � � 2� ) +
+
+
+� �
�
�
� �
are the five measures of the health of a pregnancy
�
birth is estimated to be first or second trimester in utero on September 11thand of a newborn
graphed in Figure I. The binary variables inutero1 and inutero2 indicate if a , 2001. Xiof
covariates: newborn’s gender; indicator of plural birth; mother’s parity, age, race, marital status,
and educational attainment. d and γ are month and year of birth indicators, capturing both
within-year seasonality and trends across years in birth outcomes. The parameters � 1 and
� 2therefore identified from differences in outcomes between births occurring in the same year, are
2001 or 2002, which were and were not exposed in utero.
27 Conceptions in 2004 are
omitted because the sample ends in 2004 and thus does not include those conceived in 2004 and born in 2005.
17
The outcome variables of interest * � ( � 𝑛� � � � 1� )
�
+�
�
�
� �
𝑦�
is a vector
Table I, Panel A presents the results of this specification. The effects are similar for the first
and second trimester cohorts, ranging from 0.1% to 5% at sample means.28 Pregnant women
thexposed
to September 11 in their first two trimesters were 2-5% more likely to have a medical
risk factor and were about 2% more likely to suffer from a complication of labor.29 Their
newborns were 1-1.5 days younger, 8-19 grams lighter, and had a 0.01 point lower Apgar score.
The magnitude of effects is similar to other estimates of the effect of stress (Camacho 2008).
However, compared to direct harmful exposures, the effects are relatively small. For example, in
the sample, the newborns of mothers who smoke are 240 grams lighter, 4 days younger, and
have a 0.08 point lower Apgar score.
Table I, Panels B and C present the results of this specification fully interacted with gender to
examine potential differences in the magnitude of effects between males and females. The
majority of the coefficient estimates are statistically equivalent for males and females, suggesting
that effects of exposure are similar across genders.30
Because the timing of birth is endogenous, Table II presents an alternative specification
utilizing month and year of conception indicators, rather than month and year of birth indicators.
The magnitude and statistical significance of the estimates are very similar to those in Table I,
Panel A.
Selection into live birth
thIn
addition to negatively affecting the outcomes of live births, exposure to September 11
may have increased the risk of fetal death. I examine the rate of fetal deaths relative to live
28 Significant differences exist
between trimester effects for three of the outcomes. Medical risks increase more for inutero2 exposure, gestation length
decreases more for inutero1 exposure, and birth weight decreases more for inutero2 exposure. 29 Specifications using
separate outcome indicators for stress-related and other medical risk factors are presented in Appendix Table II. Effects
are significant only for stress-related factors. 30 Of the 10 coefficient comparisons, two are significantly different across
gender. Pregnancies carrying females exposed in inutero2 have a larger increase in medical risks than those carrying
males. Males exposed inutero1 have a larger reduction in Apgar score than females.
18
birt
hs,
for
the
sam
ple
as a
who
le
and
by
gen
der,
mot
ivat
ed
by
the
evid
ence
of a
shift
ed
sex
ratio
at
birt
h in
Cat
alan
o et
al.
(20
06).
Bec
aus
e of
the
limi
ted
acc
urac
y of
feta
l
deat
h
data
,I
use
onl
y
the
mo
st
basi
c
info
rma
tion
to
esti
mat
e
the
effe
ct
of
exp
osu
re –
the
mo
nth
and
yea
r in
whi
ch
the
fe
tu
s
w
as
de
li
ve
re
d
fo
r
th
e
si
x
m
on
th
s
fo
ll
o
wi
ng
th
e
att
ac
ks
:
(2)
� � 𝑎 h�
=
*
�
�
1
+
(
�
+
𝑏
�
�
𝑛
�
�
2
0
0
1
4
7
�
)
+
�
*
�
(
�
�
𝑟
�
thwindows
18
a
�
)
*
+
�
)
*
�
(
�
𝑏
(
�
𝑛
�
�
�
𝑟
𝐹
�
6
2
0
0
1
�
2
0
0
2
�
)
Results of this specification, presented in
Appendix Table III, show no effect on the
fetal
thdeath
11.
rate in the months following September
However, it is possible that systematic
underreporting of miscarriages could mask a real
effect. I therefore use specification (2) with
male gender as the outcome in the sample of live
births. Results, which show no significant
31,32effect on the sex ratio at
birth, are presented in
Appendix Table IV.
In addition, while the nature of the attacks
strictly limits the scope for selection into
(June
pregnancy, there may have been migration
following the attacks that would affect the sample.
Table III presents means by year for live births
conceived in the first and second trimester
to September th th and March 12 to June 17th). These means do not
10
present
cl
ea
r
pa
tte
rn
,
bu
tI
wi
ll
ex
pl
or
e
th
is
is
su
e
fu
rt
he
r
in
Se
cti
on
I
V.
D.
31
The
samp
le
used
in
Catal
ano
et
al.
(200
6)
ends
in
June
2002
.
Omit
ting
birth
s
after
June
2002
prod
uces
resul
ts in
line
with
Catal
ano
et al.
Usin
g
male
sex
as
the
outc
ome
in
speci
ficati
on
(1)
with
only
year
and
mont
h of
birth
as
cova
riates
also
yield
s no
signi
fican
t
effec
ts. 32
Relat
edly,
predi
ction
s in
the
popu
lar
press
of a
“bab
y
boo
m”
follo
wing
Sept
embe
r 11th
find
no
supp
ort in
the
data.
In
fact,
the
coho
rt
born
9-12
mont
hs
later
(July
-Sept
embe
r
2002
) was
one
of
the
small
est
JulySept
embe
r
coho
rts
born
from
1995
throu
gh
2004
.
Ruth
er
(201
0)
finds
evide
nce
of
incre
ased
fertil
ity
rates
two
to
three
years
later,
but it
is not
clear
that
this
incre
ase is
relat
ed to
the
attac
ks.
19
IV.B. Schooling outcomes
The preceding results show that exposure to September 11th in New York City negatively
impacted the health at birth of the cohorts that were exposed first or second trimester in utero.
While I am unable to track individual children, I can examine the schooling outcomes of the
cohort that was exposed in utero. Diminished health at birth may lead to diminished childhood
outcomes, and there may be additional negative effects of in utero stress exposure not manifested
or measured at birth.
=
� 1
* � ( 𝑏� � � 𝑎20� � 𝐽� �
18
The outcome variables of interest �
)+�
+
+
+
�
�
�
� �
* � ( 𝑏� � � � � 11𝑡� 𝑎19� ) +
� 2
�
(
3
Boys
) who were born 3-9 months after September 11
�
�
underlying health and personality variation.
33
are the four schooling outcomes defined in Section
I
I gender, race, and home zip code. Table IV, Panel A
includes the indicators of child’s
I
presents the results of this specification
. for the full sample of six-year-old public school children.
thThe
outcomes are largely unaffectedXby in utero exposure to September 11. However, when
d
u
r
i
n
g
i
fully interacted with gender in Table IV, Panels B and C, there is clearly an effect among boys.
th
(and therefore exposed approximately
f
i
rst or cant effects for absences
secon
and behavioral incidents suggests that the impact of exposure, at least at age six, may be
d
trimes
ter) primarily cognitive. However, it may be that these outcomes do not adequately capture
were
33
7-9%
more
likely
to be Aizer, Stroud and Buka (2009) do find childhood health effects of mother’s cortisol during pregnancy with data
from doctor’s visits.
in
20
specia
l
educa
tion
and
15-18
%
more
likely
to be
in
kinder
garten
rather
than
first
grade
at age
six.
The
effect
s of
expos
ure in
first
and
second
trimest
er are
statisti
cally
equival
ent.
The
lack of
signifi
�
In contrast to boys, there are no significant effects for girls across the four outcomes.34
However, I cannot conclude from identifying effects solely for boys that there are no effects for
girls. In the sample, 2.6 times as many boys are in special education, and boys are held back 1.7
times more often. It may therefore be that more boys than girls are at the margin of the cognitive
and behavioral outcomes measured in the data.
Appendix Table V displays the estimated
coefficients using average grade as the outcome in the limited available sample. While there is
no discernible impact of exposure, this may be due to the small sample.
When considering these results, it is worth noting that the majority of the unaffected
children (74%) were exposed to the shock as young children, having been between birth and age
thfour
on September 11. Children with direct experience of the attacks or whose mothers’
experienced the attacks displayed elevated rates of behavioral problems in the years after
thSeptember
11 (Chemtob et al. 2010). To the extent that children across the city were affected, I
may be underestimating the true effect of in utero exposure to maternal stress.35,36
IV.C. Broader geographical analysis
thAlthough
the effects of September 11 were most substantial for the residents of New
York City, there may have also been impacts on geographically and socially proximate
populations. In particular, the six suburban counties of New York City home to the highest
number of attack victims and the largest share of lower Manhattan workers outside of New York
City, as well as the Washington D.C. metropolitan area, are natural candidates.37,38
34 Tests of the equality of
coefficients across genders are easily rejected for the special education and held back outcomes.
35th found no significant effects of this
Specifications including an indicator for children who were one year old or
younger (the cohort most likely to be breastfeeding and thus exposed to maternal stress hormones) on September 11
The majority of research into the effects of September 11 36indicator. The coefficients on the main indicators were
unchanged. th on children focused on those of school age. See, for
example, Hoven 2005. 37 Five of these counties (Nassau, Westchester, Suffolk, Hudson, and Bergen) are home to a
total of 18% of lower Manhattan workers. In each, less than 2% of the county labor force works in lower Manhattan.
Each county,
21
To investigate this possibility on birth outcomes, I expand the sample to include all births
occurring in the United States, and add geographic indicators and their interactions with the
indicators of in utero timing to specification (1):
�
*
) + * � ( � 𝑛�
* � ( � 𝑛� � � � 2� )
� �
� +� � � � 1
5
= � 1 * � ( � 𝑛�
) ++ � �
+� � +� �
4) + � � �* � ( � 𝑛� � � � 1�
𝑚
�
=2�
� �
� � � 18+ � � �
=6� � * � �
𝑦�
(4)
� �
39
t
o
�
and � 6to �
8
�
and � 5
Only three of the five birth outcomes are comparable across states over time due to
1
revisions of birth certificate content implemented in some states in 2003. In particular, the list of
maternal medical risks and the list of complications of labor and delivery were altered such that it is
not possible to compare them across revised and unrevised data. Therefore, the outcomes � are
gestational age, birth weight, and Apgar score.The three � � indicators capture fixed differences
between New York City, its suburbs, the Washington D.C. area, and the rest of the nation. The
month and year of birth indicators flexibly thcapture national time trends. Estimates of � exposure to
September 11 measure the national effect of in utero . Because the psychological impact of the
attacks was felt broadly, it is plausible that national birth outcomes were affected. Estimates of
� 24measure the extent to which outcomes of exposed in utero cohorts in the three specified areas
including the sixth (Monmouth) lost at least 80 residents in the attacks. Approximately 70% of lower Manhattan workers
live in one of the five New York City boroughs (US Census Bureau 2008). 38 The area is defined as the Washington
Metropolitan Statistical Area. Victims at the Pentagon lived throughout the MSA. Specifications using only Arlington
County (where the Pentagon is located) or only the counties that lost the
highest number of residents (Fairfax, Prince William, and Prince Georges – each lost at least 20 residents) do not alter
the results. 39 California and Texas did not record the five-minute Apgar score on birth certificates during the sample
period, reducing the sample size for this outcome by 22%.
22
differ from the outcomes of those exposed in utero in the rest of the nation. Table V reports the
results of this specification. Across outcomes, only � 2 and � 6, the estimated effect of in utero
exposure in New York City, are consistently negative and statistically
significant. While these results suggest that the effects were not widespread or substantial
enough to be detected in broad geographies outside New York City, there are likely several
groups across the country that were significantly affected but not identifiable in standard data
sets, including those who knew someone killed in the attacks and, as Lauderdale (2006) finds in
California, those subject to increased discrimination.
IV.D. Selection
IV.D.i. Birth outcomes
thAs
the attacks of September 11 were entirely unforeseen, and no other major event
followed closely in timing, there is a limited role for selection into pregnancy.40 However,
thmigration
in response to September 11 may have been selective. To generate the estimates of
exposure found in the previous sections, negative selection through migration would have had to
thoccur
particularly among women pregnant on September 11. For example, if higher
socioeconomic status residents were more likely to move out the city after the attacks, and if
pregnant women were more likely to move than other women, the resident population that gave
birth in the months following September 11th may have had worse outcomes due to lower
average socioeconomic status, rather than to the effect of exposure to the attacks.
To investigate the possibility of selective migration, I treat covariates indicative of
maternal socioeconomic status as outcome variables:
40
with an economic recession, the implications of which are explored in section IV.F.
23
September 11th did coincide
outcome variables are mother’s race, marital status, and educational attainment.
Results in Table VI, Panel A suggest that selection into New York City residence was indeed
occurring among pregnant women. Those in their first or second trimester of pregnancy on
thSeptember
11 were approximately 3-5% less likely to be White, 2% less likely to be married,
and 4% less likely to have 16 or more years of education. To informally assess the importance
of selection on the observed covariates, I present specification (1) without the vector of covariates
� � in Appendix Table VI. The estimated effects are very similar to the results with covariates.
In addition, the lower share of married mothers may directly reflect the increase in
thdivorce
rates observed in the year following September 11 (Cohan, Cole and Schoen 2009).
However, there may be selection on unmeasured characteristics as well.
To formally assess the potential bias, Altonji, Elder and Taber (2005) develop a method
that utilizes the amount of selection on observables as a guide to selection on unobservables.
However, the method is not informative in this case due to the low explanatory power of the few
measured covariates. Across specifications, R-squared values range from 0.01 to 0.11, and the
variance of residuals ranges from seven to 47 times greater than the variance of the index of
covariates.41 Because the covariates are correlated with indicators of in utero exposure (as
shown in Table VI) and explain relatively little of the variation in outcomes, if unobserved
characteristics are similarly correlated with exposure, bias from these unobservables could
account for the estimated effects.
This possibility is tempered by the fact that bias from unobservables in the estimated
41 The index is constructed as the
sum of every explanatory variable (other than in utero indicators) multiplied by its coefficient estimate.
24
The � ( 5 )
� ��
=
� 1
* � ( � 𝑛� � � � 1� ) * � ( � 𝑛� � � � 2� ) + + �
+� 2
� 𝑚�
𝑦�
+
� �
effects of exposure is related to outcome variance across conception windows (the dimension of
exposure) and not to variance within windows. Depending on the outcome measure, variance
within a conception window is five to 100 times greater than variance across windows.
Although the timing of conception accounts for relatively little variance in outcomes, there may
have been a unique period of selective migration out of New York City in response to September
11th.
While conclusive assessments are not possible, qualitatively, two countervailing types of
unobserved selection seem plausible. Pregnant women who were economically able to move
may have been more likely to leave the city, shifting the distribution of unobservable maternal
characteristics such that birth outcomes worsened, therefore biasing estimates towards finding
theffects
of September 11 exposure. On the other hand, pregnant women who were particularly
affected by the attacks may have been more likely to migrate, removing the more negatively
impacted pregnancies from the sample and attenuating the estimated effects. Unfortunately, data
regarding either mechanism is not available.
IV.D.ii. Schooling outcomes
For schooling outcomes, there are two additional channels for potential selection:
migration out of the city after birth and private school attendance. Each could plausibly lead to
theither
over or underestimates of the effect of September 11 in utero exposure. If families with
the most severely affected children were more likely to move out of the city, or to enroll their
children in private school, the main results would be underestimates of in utero exposure’s
effects on schooling outcomes. However, if such families were more likely to stay in the city or
to utilize public schools, the results would be overestimates.
To investigate these possibilities, I follow the same initial approach of the previous
25
se
cti
on
,
an
d
tr
ea
t
co
va
ri
at
es
in
di
ca
ti
ve
of
a
ch
il
d’
s
so
ci
oe
co
no
m
ic
st
at
us
as
ou
tc
o
m
e
va
ri
ab
le
s:
1
* � ( � � � 𝑛 � � 11� � �
� � 19� ) + � 2
� �
�
+
�
+
�
As with the birth
data, students’ characteristics suggest some selection into New York City
4
2
residence
in Table VI,
Panels B and C. Students are approximately 4% less likely to be White, and 3% more likely to
be Black. The similarity of these estimates to those at birth suggests that selective migration
between birth and school, as well as selective public school attendance, was limited, at least for
race. To informally assess the importance of selection on the observed covariates, I present
specification (3) without the vector of covariates � � in Appendix Table VII. The estimated
effects are again very similar to the results with covariates. The same challenge of limited
covariates makes the Altonji, Elder and Taber (2005) method uninformative in the schooling
data.
Given the robustness of the estimates to the inclusion of covariates, as well as the potential
for either positive or negative selection on unobservables, migration does not appear to fully
account for the effects of in utero exposure found in Sections IV.A. and IV.B.
IV.E. Heterogeneity of effects
Because the experience of stress is personalized, there may have been variation in its
severity across subgroups within New York City. Baseline levels of stress, access to coping
resources, and the ability to compensate for bad shocks could all affect the extent to which
Students are eligible for free or reduced price meals according to federal guidelines. For the 2009-10 school year,
household income at 185% of the poverty line qualifies students for reduced price meals; at 130% qualifies students
for free meals (http://www.fns.usda.gov/cnd/governance/notices/iegs/iegs.htm ). Approximately 63% of the total
sample is listed as eligible (22% have no eligibility status listed).
42
26
( 6 ) The
� �
� �
=
outcome variables are student’s race and free lunch
� eligibility.
* � ( � � � 𝑛 𝑎20� � 𝐽𝑢 19� ) +
�
𝑚�
�
thexposure
to September 11 translated to experienced stress, poor birth outcomes, and eventually
poor schooling outcomes. Suggestive evidence finds that Manhattan residents with prior
stressors in their lives, lower household income, and lower levels of education were all more
likely to be suffering from attack-related PTSD or depression in the weeks after the attacks
(Galea et al. 2002).
To explore the possibility that socioeconomic status and the impact of the attacks may be
negatively correlated, I fully interact specifications (2) and (3) with indicators of status.
In the birth data, I use an indicator for maternal education being 16 years or more. Table VII
displays the results. The negative effects of exposure on birth outcomes appear to be largely
mitigated for highly educated mothers. For these mothers, first trimester exposure had a more
substantial impact on their rate of labor complications, but effects on gestation length are about
half those of less educated mothers, while effects on medical risks, birth weight, and Apgar
score on indistinguishable from zero.43
In the schooling data, I approximate a student’s socioeconomic background with the
mean household income of his or her home zip code and then divide the sample into income
quartiles. Table VIII reports these results for the two affected schooling outcomes, special
education and held back status. While many of the coefficients are insignificant for boys, a
pattern is readily discernible: the most affected income quartile appears to be the second.
These results are in line with a growing literature which finds that children in families of
lower socioeconomic status suffer larger effects of adverse health shocks, possibly because their
parents take fewer compensatory actions or because they are more likely to face additional
negative shocks (Currie and Hyson 1999; Currie and Stabile 2003; Almond, Edlund and Palme
43 Specifications by maternal race
find attenuated (but still significant) effects for White mothers compared to Black and Hispanic mothers.
27
2009). Heterogeneity of effects may also be explained by selective migration. For example, if
thall
pregnant women were adversely affected by September 11, but only those of high
socioeconomic status could respond by moving, larger or more significant negative impacts
would be measured for lower socioeconomic status groups.
IV.F. Channels: Environmental or Economic instead of Stress?
The environmental impact of the World Trade Center attack was substantial but highly
localized: the dust cloud did not move north beyond Canal Street, and after traveling over
western Brooklyn, dispersed (Landrigan et al. 2004). Among Medicaid enrollees, only residents
of areas where the dust cloud passed over were more likely to receive medical care for asthma in
the weeks after the attacks (Wagner 2005). To assess the extent to which the results are
capturing the effects of air pollution, I would like to exclude the areas affected by the dust cloud
from my analysis. This is a conservative approach, because people in the most environmentally
damaged geographies may also have suffered the most psychologically.
The birth data is only identified at the borough level, so I divide the five boroughs into
two groups: environmentally affected (Manhattan, Brooklyn) and unaffected (Staten Island,
Queens, the Bronx). Table IX presents the results of specification (1) fully interacted with an
indicator for residence in one of the three environmentally unaffected boroughs, Staten Island,
Queens, and the Bronx. The two environmentally affected boroughs, Manhattan and Brooklyn,
are the omitted group. Equality of effects across the two borough groups cannot be rejected for
medical risks, labor complications, birth weight, and Apgar score. For gestation length, equality
of effects is rejected for both inutero1 and inutero2, however the estimates for the
environmentally unaffected boroughs are still significantly different from zero.
Overall, the
estimates are somewhat smaller for Staten Island, Queens, and the Bronx compared to Manhattan
28
and Brooklyn, suggesting that part of the measured effects may be due to air pollution.44
In the schooling data, records identify children’s current place of residence at the zip code
level. Due to mobility, current residence is a measure of residence in utero with error. I
construct one indicator for residence in a Manhattan zip code south of Canal Street and a second
indicator for residence in a western Brooklyn zip code.45 Table X presents the results of
specification (3) fully interacted with the two indicators. The effects of in utero exposure appear
to be the same for children living in and out of the environmentally affected area. However, the
error in this measure of residence may obscure real differences, particularly if mobility after
thSeptember
11 was selective such that more affected women moved. Across both data sets, the
limited impact of location within New York City on the estimates suggests that air pollution is
not the sole driver of the estimated effects.
thIn
addition to its environmental consequences, September 11 had a substantial negative
impact on the New York City economy. It is plausible that the effects I am measuring may be
due to economic deprivation rather than psychological stress. Pregnant women who lost their
jobs or whose partners lost their jobs might have struggled to meet their needs for food, shelter,
or medical care, which may have adversely impacted their pregnancy.
While I cannot separately identify the economic effect from the effect of stress, I can look
for evidence of its magnitude and direction. If this were a primary channel through which in
utero exposure affected outcomes, I would expect that pregnancies which began well after
thSeptember
11, when the psychological trauma had begun to fade but the economic effects
persisted, would also be negatively affected. I check this in both the birth and schooling data by
defining an affected cohort as the children who were born August to October 2002. These
44 In addition, specifications with
the maternal medical risk factor most likely to indicate air pollution, acute or chronic lung disease (including asthma and
tuberculosis), as an outcome find no effects of September 1145th exposure. Western Brooklyn is defined as the zip codes
adjacent to Manhattan by way of the harbor (Wagner 2005).
29
thchildren
were all conceived at least six weeks after September 11, 2001, but were in utero
during much of the same period of economic slowdown as the exposed cohort. I compare their
outcomes against cohorts born in the same months from 1995 through 2004, including a smooth
quadratic year of birth trend:
( 7 ) = * � ( 𝑏 � 𝑛 𝑢� � � � � 2002� ) + +
* � � 𝑎� � � 𝑖 + * � 𝑒𝑟 � � � 𝑟 +
� �
� 1 � � �
� 2 � h�
� 3 h� 2
� �
Results are presented in Table XI, Panel A for the birth outcomes and Panels B and C for
the schooling outcomes. There are no significantly negative effects for these later cohorts,
suggesting that the economic impact of the attack is not a primary driver of the results.46
V. Conclusion
thPregnancies
exposed to the September 11, 2001 attacks in New York City during first or
second trimester were 2-5% more likely to suffer from a medical risk and 2% more likely to
experience a complication during labor. Newborns were 1-1.5 days younger, weighed 8-19
grams less, and had a 0.1% lower five-minute Apgar score at birth. At the age of six, boys were
7-9% more likely to be in special education and 15-18% more likely to be in kindergarten rather
than first grade, with no effect on girls.
These results do not appear to be driven by
environmental or economic conditions, but rather provide evidence that psychological stress is an
important channel through which adverse events experienced by pregnant women negatively
impact the early life outcomes of in utero cohorts.
Moreover, because early life outcomes are good predictors of later health and
socioeconomic status, the results suggest that there may be substantial long-term effects of the
46 Note that the comparison
group includes part of the cohort that was third trimester in utero on September 11 th. Excluding this group does not
affect the results.
30
thSeptember
th11
11 attacks on the exposed cohort. To the extent that the stress induced by September
is similar to the stress created by more common experiences, the results provide support to
the hypothesis that unmeasured psychosocial stressors explain part of the differences observed in
birth outcomes and schooling performance across socioeconomic groups.
31
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39
F
i
g
u
r
e
1
Mean birth outcomes for New York
City resident women by estimated
time of conception
Share of mothers with 1+ labor complications
Share of mothers with 1+ medical risks
1995 1996 1997 1998 1999 2000 2001 2002 2003
18 - Sep 10 Conceived March 12 - June 17
1995 1996 1997 1998 1999 2000 2001 2002 2003
18 - Sep 10 Conceived March 12 - June 17
Year Conceived June
Year Conceived June
Mean birth weight (in grams)
Mean gestation length (in weeks)
1995 1996 1997 1998 1999 2000 2001 2002 2003
- Sep 10 Conceived March 12 - June 17
1995 1996 1997 1998 1999 2000 2001 2002 2003 Year Conceived
June 18 - Sep 10 Conceived March 12 - June 17
Mean five-minute Apgar score (scale 1-10)
Year Conceived June 18
1 arch 12 - June 17
9
9
5
estimated
to have been
Notes. The figures display
mean outcome values of births
conceived either March 12-June 17 or
June 18-September10 annually from1 1995 through 2003. The sample includes all live births to women residing in one
9
of the five boroughs of New York City
from 1995 through 2004.
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
Y
e
a
r
C
o
n
c
e
i
v
e
d
J
u
n
e
1
8
S
e
p
1
0
C
o
n
c
e
i
v
e
d
.38
.26 .27
M
F
i
g
u
r
e
2
Birth outcomes for cohort third
trimester in utero on September 11
(conceived December 27 to March
11)
Share of mothers with 1+ medical risks
Mean five-
1995 1996
1995 1996 1997 1998 1999 2000 2001 2002 2003 Year
Mean gestation length (in weeks)
1995 1996 1997 1998 1999 2000 2001 2002 2003 Year
Share of mothers with 1+ labor complications
1995 1996 1997 1998 1999 2000 2001 2002 2003 Year
8.94 8.96 8.98 9 9.02 9.04
.36 .37
3245 3250 3255 3260 3265
38.8 38.85 38.9 38.95
Notes. The figures display mean
outcome values of births estimated to
have been conceived December
27-March 11 annually from 1995
through 2003. The sample includes all
live births to women residing in one of
the five boroughs of New York City
from 1995 through 2004.
.34 .35
.2 .22 .24 .26 .28
Mean birth weight (in grams)
1995 1996 199
Table I Outcomes for births occurring to New York City women 1995-2004
Medical risk
Labor complication indicator Gestation Birthweight Apgar
indicator
Panel A: All births sample mean 0.248
3,253
8.995
0.360
38.8
inutero1 0.0056* 0.0072** -0.215*** -8.01* -0.012** [0.0032] [0.0035] [0.019] [4.23]
[0.0051]
inutero2 0.012*** 0.0057* -0.163*** -18.70*** -0.014*** [0.0029] [0.0033] [0.017]
[3.90] [0.0047]
2N
1,198,265
1,198,265
1,198,265
1,198,265
1,198,265
R0.02 0.01 0.07 0.11 0.02 Panel B: Males sample mean 0.248 0.367 38.7 3,307
8.989
inutero1 0.0024 0.0022 -0.231*** -11.495* -0.023*** [0.0044] [0.0049] [0.027] [6.030]
[0.0072]
inutero2 0.0056 0.0034 -0.156*** -13.145** -0.015** [0.0041] [0.0046] [0.025] [5.557]
[0.0066]
2N
614,024
R0.02
0.02
9.002
614,024
614,024
614,024
614,024
0.01
0.06
0.10
Panel C: Females sample mean 0.249 0.353 38.8 3,196
inutero1 0.0090** 0.012** -0.198*** -4.546 -0.00085 [0.0045] [0.0050] [0.027] [5.927]
[0.0071]
inutero2 0.018*** 0.0082* -0.171*** -24.490*** -0.012* [0.0042] [0.0046] [0.025]
[5.449] [0.0066]
2N
584,241
R and �
0.01
2
584,241
584,241
584,241
in specification (1). Panels B and C report estimates of � 1 and � 0.02
0.07
0.11
0.02
584,241
2
*Significant at 10%; **significant at 5%; ***significant at 1%.
Notes. Panel A reports estimates of
in specification (1) run separately by child’s gender. In all panels, the sample includes all liv
New York City from 1995 through 2004. Regressions include mother’s parity, age (and age squ
� 1
(5 categories – Black, White, Hispanic, Asian, Other) and marital status, as well as indicators of
year of birth, and month of birth. Indicators of missing values are also included for covariates.
Table II Outcomes for births occurring to New York City women 1995-2004
Medical risk
Labor complication indicator Gestation Birthweight Apgar
indicator
20.02
sample mean 0.248
0.360
38.8
3,253
8.995
inutero1 0.0072** 0.0083** -0.219*** -11.931*** -0.0067 [0.0033] [0.0036] [0.019]
[4.346] [0.0052]
inutero2 0.012*** 0.0078** -0.115*** -14.316*** -0.011** [0.0031] [0.0035] [0.019]
[4.175] [0.0050]
N 1,198,265 1,198,265 1,198,265 1,198,265 1,198,265 R1 Notes. The table
reports estimates of � and �
*Significant at 10%; **significant at 5%; ***significant at 1%.
0.02 0.07 0.11
residing in one of the five
education (4 levels), race
conception, and month of
Table III: Mean values of characteristics across cohorts of births
occurring to New York City women (by time of conception)
Mother's race Mother's education
White Black Hispanic Mother maried>12 years 16+ years Live births Sex ratio
First trimester on Septemer 11 (Conceived June 18 - September 10) 1995 27.1% 27.5% 33.2% 47.1% 36.6%
19.3% 28,442 0.517
1996 27.0% 27.8% 32.4% 55.8% 39.5% 20.1% 28,014 0.512
1997 27.5%
27.5% 33.0% 55.0% 39.3% 20.6% 28,500 0.516
1998 27.0% 27.6% 32.8% 53.9% 40.8% 22.3%
27,765 0.510
1999 27.0% 27.0% 33.2% 54.8% 43.0% 23.2% 27,952 0.512
2000 27.8% 26.7%
33.5% 54.7% 43.4% 23.6% 28,089 0.519
2001 27.3% 26.0% 33.7% 55.3% 43.8% 23.8% 28,119
0.513
2002 28.9% 24.7% 32.6% 57.2% 46.5% 26.7% 28,106 0.516
2003 29.3% 23.9% 33.1%
56.2% 43.4% 26.7% 28,152 0.514
Second trimester on September 11 (Conceived March 12 - June 17) 1995 25.3% 29.5% 33.3% 46.6% 34.8%
17.9% 35,011 0.512
1996 25.2% 29.2% 32.9% 52.8% 37.7% 18.5% 33,390 0.509
1997 26.8%
29.0% 32.4% 53.5% 38.7% 20.0% 33,839 0.511
1998 25.7% 28.4% 33.8% 53.0% 40.2% 20.7%
33,048 0.512
1999 26.0% 28.0% 33.4% 53.0% 40.6% 21.4% 34,078 0.515
2000 26.8% 27.8%
32.7% 53.4% 41.7% 22.0% 33,307 0.512
2001 26.5% 27.2% 33.6% 53.7% 42.8% 22.8% 33,073
0.509
2002 27.5% 25.5% 33.1% 55.0% 44.5% 25.3% 33,253 0.512
2003 27.6% 25.9% 33.0%
54.6% 42.8% 25.2% 33,654 0.510
Notes. The table reports mean values for all live births estimated to have been conceived in one of the two specified
windows to women residing in one of the five boroughs of New York City from 1995 through 2004.
Table IV Outcomes for New York City public school children 2003/4-2009/10
Days absent Behavior
Special
Held back
from school
incident
education
indicator
indicator
indicator
Panel A: all students sample mean 11 0.03
0.08
0.03
born Mar 20 to June 18, 2002 -0.054 0.0026 0.0047* 0.0026 [0.106] [0.0016] [0.0027] [0.0017]
born Dec 11 to Mar 19, 2002 0.085 4.7x10-5 0.0037 0.0028* [0.101] [0.0015] [0.0026] [0.0016]
2N
410,297
410,297
mean 11 0.04 0.12 0.04
410,297
410,297
R0.15 0.03 0.03 0.02 Panel B: Boys sample
born Mar 20 to June 18, 2002 -0.034 0.0049* 0.011** 0.0055** [0.153] [0.0028] [0.0045] [0.0026]
born Dec 11 to Mar 19, 2002 0.037 0.0020 0.0083* 0.0066*** [0.145] [0.0026] [0.0043] [0.0025]
2N
210,519
0.03
210,519
210,519
210,519
Panel C: Girls sample mean 11 0.01
R0.16
0.04
0.03
0.02
0.02
born Mar 20 to June 18, 2002 -0.074 0.00029 -0.0014 -0.00029 [0.148] [0.0014] [0.0030] [0.0021]
1
born Dec 11 to Mar 19, 2002 0.140 -0.0021 -0.0011 -0.00083 [0.140] [0.0014] [0.0028] [0.0020]
Notes. Panel A reports estimates of � and �
199,778
199,778
199,778
212
and �
2
in specification (3). Panels B and C report estimates of �
R0.15
0.01
0.01
N 199,778
0.02
in specification (3) run separately by child’s gender. In all panels, the sample includes all six-yearold public school students in New
York City who are not English Language Learners from the 2003 through 2009 school years. All regressions include indicators of
child’s gender (Panel A only), race (5 categories – Black, White, Hispanic, Asian, Other), home zip code, year of birth, and month of
birth. Indicators of missing values are also included for covariates. *Significant at 10%; **significant at 5%; ***significant at 1%.
Outcomes for births occurring to women resident in the United States 1995-2004
Table V
Gestation Birthweight Apgar
sample mean 38.8
3,311
8.915
inutero1 -0.035* 1.62 0.0033 [0.019] [4.45] [0.0041]
inutero1*NYC -0.18*** -8.81*** -0.016*** [0.0034] [0.78] [0.0057]
inutero1*NYsuburbs -0.0052 4.83 -0.013* [0.024] [5.46] [0.0069]
inutero1*DC 0.045* -2.33 -0.017** [0.026] [6.02] [0.0076]
inutero2 -0.024 -3.00 0.00025 [0.018] [4.10] [0.0010]
inutero2*NYC -0.14*** -17.16*** -0.015*** [0.0031] [0.72] [0.0052]
inutero2*NYsuburbs 0.0019 1.55 -0.0093 [0.022] [5.12] [0.0065]
inutero2*DC 0.011 5.75 0.0010 [0.024] [5.57] [0.0071]
38,672,662
38,672,662
29,980,978
R1 Notes. The table
reports estimates of � to � 0.01 0.05 0.018 in specification (4). The sample includes all live births to
2N
women residing in the United States from 1995 through 2004, except births in CA and TX for the third
column, as these states did not report Apgar score during the sample period. Regressions include mother’s
parity, age (and age squared), and indicators of mother’s education (4 levels), race (5 categories – Black,
White, Hispanic, Asian, Other), marital status, and indicators for residence in New York City, New York
suburbs, or the DC area, as well as indicators of child’s gender, plurality (twins or higher), year of birth, and
month of birth. Indicators of missing values are also included for covariates. *Significant at 10%;
**significant at 5%; ***significant at 1%.
Panel
A: Characteristics
of New York City
women giving birth
1995-2004
Mother's race white
Mother's race black
Mother's race
hispanic Mother married
Table VI Selection i
Data
sample mean 0.27
0.27
0.33
inutero1 -0.0144*** 0.0046 0.0067* -0.0086** -0.009
[0.0033] [0.0033
0.0053* 0.0053* -0.0116*** -0.0079***
[0.0030] [0.003
1,198,265
1,198,265
1,198,265
1,198,2
R20.001
0.001
0.0001
Characteristics of New York City public school child
White Black Hispanic Free Lunch Eligible Panel B: Boys sa
0.33
0.80
born Mar 20 to June 18, 2002 -0.0045 0.0056 0.000
[0.0057]
born Dec 11 to Mar 19, 2002 -0.0092** 0.010** 0.0
[0.0054]
2N
210,519
0.20
0.33
210,519
0.26
0.80
210,519
1
Panel C: Girls sa
born Mar 20 to June 18, 2002 -0.0017 0.0074 -0.008
[0.0058]
born Dec 11 to Mar 19, 2002 -0.0028 0.0052 0.0022
1 Notes. Panel A reports estimates of � and �
in specification (5). The sample includes all live births to women residing in one of the
five boroughs of New York City from 1995 through 2004. Panels B and C report estimates of � 12 and � 22N 199,778
199,778
199,778
157,320
R0.35
0.39
0.20
0.26
in specification (6) run separately by child’s gender. The sample includes all six-year-old public school students in New York City
who are not English Language Learners from the 2003 through 2009 school years. In all panels, regressions include month of birth and
year of birth indicators.
*Significant at 10%; **significant at 5%; ***significant at 1%.
Table VII Outcomes
M for births occurring to New York City
e
women 1995-2004
d
Labor complication indicator Gestation Birthweight
i
Apgar
c
a
sample
mean 0.248
0.360
38.8
3,253
8.995
l
inutero1 0.0075** 0.0037 -0.241*** -10.727** -0.018*** [0.0036] [0.0040] [0.022] [4.843] [0.0058]
r
i
inutero1*mother 16+ years of education -0.010 0.013 0.122*** 15.683 0.027**
s
[0.0075] [0.0083] [0.045] [9.985] [0.012]
k
inutero2
0.014*** 0.0050 -0.180*** -20.627*** -0.015*** [0.0033] [0.0037] [0.020] [4.430]
i
[0.0053]
n
d
inutero2*mother
16+ years of education -0.013* 0.0026 0.088** 14.456 0.0078
i
[0.0070] [0.0078] [0.042] [9.324] [0.011]
c
2N a1,198,265 1,198,265 1,198,265 1,198,265 1,198,265 R0.02
0.02
0.07
0.11
0.02
t
o
r
Notes. The table reports estimates from specification (1) fully interacted with an indicator of mother’s education 16+ years. The sample
includes all live births to women residing in one of the five boroughs of New York City from 1995 through 2004. Regressions include mother’s
parity, age (and age squared), and indicators of mother’s race (5 categories – Black, White, Hispanic, Asian, Other) and marital status, as well as
indicators of child’s gender, plurality (twins or higher), year of birth, and month of birth, and all interactions.
Indicators of missing values are also included for covariates.
*Significant at 10%; **significant at 5%; ***significant at 1%.
Table VIII (Part 1) Heterogeneity: Outcomes for
New York City public school children 2003/4-2009/10
Special education indicator Held back indicator
Boys:
born Mar 20 to June 18, 2002 0.011 0.0081 [0.0088] [0.0067]
born Mar 20 to June 18, 2002*quartile2 0.0029*** 0.021*** [0.00091] [0.0068]
born Mar 20 to June 18, 2002*quartile 3 0.0010 0.014* [0.013] [0.0066]
born Mar 20 to June 18, 2002*quartile4 -0.0049 -0.0050 [0.013] [0.0052]
born Dec 11 to Mar 19, 2002 0.0071 0.0074 [0.0083] [0.0051]
born Dec 11 to Mar 19, 2002*quartile2 0.007** 0.011* [0.0026] [0.0056]
born Dec 11 to Mar 19, 2002*quartile3 0.015 0.011 [0.012] [0.0071]
born Dec 11 to Mar 19, 2002*quartile4 -0.012 -0.0061 [0.012] [0.0072]
2N 210,519
210,519
R0.02
0.03
Table VIII (Part 2) Heterogeneity: Outcomes for
New York City public school children 2003/4-2009/10
Special education indicator Held back indicator
Girls: born Mar 20 to June 18, 2002 -0.0054 -0.0033
[0.0059] [0.0042] born Mar 20 to
June 18, 2002*quartile2 0.0065 0.0027
[0.0083] [0.0058] born Mar 20 to
June 18, 2002*quartile 3 0.0078 0.0084
[0.0085] [0.0059] born Mar 20 to
June 18, 2002*quartile4 0.0021 0.0017
[0.0084] [0.0059] born Dec 11 to
Mar 19, 2002 0.0008 -0.0062
[0.0055] [0.0039] born Dec 11 to
Mar 19, 2002*quartile2 0.0061 0.0063
[0.0079] [0.0055] born Dec 11 to
Mar 19, 2002*quartile3 -0.0026 0.011*
[0.0079] [0.0056] born Dec 11 to
Mar 19, 2002*quartile4 -0.0096 0.0045
R[0.0079] [0.0056] N 199,778
199,778
20.01
0.02
Notes. The table reports estimates from specification (3) run separately by child’s gender and fully interacted
with indicators of quartiles of child’s home zip code mean income. The sample includes all six-year-old public
school students in New York City who are not English Language Learners from the 2003 through 2009 school
years. Regressions include indicators of child’s race (5 categories – Black, White, Hispanic, Asian, Other),
home zip code, year of birth, and month of birth, and all interactions. Indicators of missing values are also
included for covariates. *Significant at 10%; **significant at 5%; ***significant at 1%.
Table IX Outcomes for births occurring to New York City women 1995-2004
Medical risk
Labor complication indicator Gestation Birthweight Apgar
indicator
sample mean 0.248
0.360
38.8
3,253
8.995
inutero1 0.0057 0.0095* -0.260*** -11.815** -0.015** [0.0045] [0.0050] [0.027] [5.987]
[0.0071]
inutero2 0.0057 0.0081* -0.192*** -22.184*** -0.014** [0.0041] [0.0046] [0.025] [5.500]
[0.0066]
2N
1,198,265
0.02
1,198,265
0.07
1,198,265
0.11
1,198,265
0.02
1,198,265
R0.02
Notes. The table reports estimates from specification (1) fully interacted with an indicator of
mother’s borough of residence being Staten Island, the Bronx, or Queens (omitted boroughs are
Manhattan and Brooklyn). The sample includes all live births to women residing in one of the
five boroughs of New York City from 1995 through 2004. Regressions include mother’s parity,
age (and age squared), mother’s education (4 levels), and indicators of mother’s race (5
categories – Black, White, Hispanic, Asian, Other) and marital status, as well as indicators of
child’s gender, plurality (twins or higher), year of birth, and month of birth, and all interactions.
Indicators of missing values are also included for covariates.
*Significant at 10%; **significant at 5%; ***significant at 1%.
inutero2*
Staten/Bronx/Queens
residence
inutero1*
Staten/Bronx/Queens
residence
0.011* -0.0054 0.061* 6.918 0.0022 [0.0058] [0.0065] [0.035]
[7.809] [0.0093]
-0.00031 -0.0056 0.091** 5.818 0.0053 [0.0063] [0.0071] [0.038]
[8.487] [0.010]
Table X Outcomes for New York City
public school children 2003/4-2009/10
Special education indicatorHeld back indicator Boys:
sample mean 0.12
0.04
born Mar 20 to June 18, 2002 0.010** 0.0051* [0.0046] [0.0027]
born Mar 20 to June 18, 2002 * SouthCanal/Western Brooklyn 0.0048 0.0071 [0.019] [0.011]
born Dec 11 to Mar 19, 2002 0.032* 0.0069*** [0.018] [0.0025]
born D e c 11 to Ma r 19, 2002* SouthCa nal/We s te r n Br ooklyn 0.0063 -0.0071 [0.0047] [0.010]
2N
210,519
Girls: sample mean 0.04
210,519
R0.02
0.03
0.02
born Mar 20 to June 18, 2002 -0.0018 -0.000076 [0.0031] [0.00216]
born Mar 20 to June 18, 2002 * SouthCanal/Western Brooklyn 0.0072 -0.0014 [0.012] [0.0085]
born Dec 11 to Mar 19, 2002 -0.0012 -0.0013 [0.0029] [0.0020]
born D e c 11 to Ma r 19, 2002* SouthCa nal/We s te r n Br ooklyn 0.0011 0.0073 [0.012] [0.0082]
2N
199,778
199,778
R0.01
0.02
Notes. The table reports estimates from specification (3) run separately by child’s gender and fully interacted with an
indicator of child’s current home zip code (at the time of the school record) being located south of Canal St. or in
Western Brooklyn. The sample includes all six-year-old public school students in New York City who are not English
Language Learners from the 2003 through 2009 school years. Regressions include indicators of child’s race (5
categories – Black, White, Hispanic, Asian, Other), home zip code, year of birth, and month of birth, and all
interactions. Indicators of missing values are also included for covariates. *Significant at 10%; **significant at 5%;
***significant at 1%.
Table XI Economic
effects of September 11th
Panel A: Outcomes for births occurring to New York City women 1995-2004
Medical risk
Labor complication indicator Gestation Birthweight Apgar
indicator
sample mean 0.250
0.357
38.8
3,252
8.994
born Aug 1 to Oct 31, 2002 -0.018*** -0.0042 0.026 -4.494
0.0069
[0.0027] [0.0030] [0.016] [3.676] [0.0043] N
308,306
308,306
308,306
308,306
308,306
R20.02
0.02
0.06
0.11
0.02
Panels B and C: Outcomes for New York City public school children
2003/4-2009/10
Days absent
Behavior
Special
Held back
from school
incident
education
indicator
indicator
indicator
Panel B: Boys sample mean 11 0.04 0.13 0.04
born Aug 1 to Oct 31, 2002 0.145 0.050*** -0.0049 -0.0031
[0.470] [0.003] [0.0055] [0.0028]
2N
53,323
53,323
53,323
R0.15
0.03
0.02
Panel C: Girls sample mean 11
53,323
0.02
0.01 0.05 0.02
born Aug 1 to Oct 31, 2002 -0.258 0.0034 -0.0011 1.1x10-6
[0.172] [0.0061] [0.0044]
[0.0029] N 50,441
50,441
50,441
50,441
R20.15
0.01
0.01
0.01
Notes.
Panel A reports estimates from specification (7). The sample includes all live births to women
residing in
one of the five boroughs of New York City from 1995 through 2004 occurring between August
and October. Regressions include mother’s parity, age (and age squared), and indicators of
mother’s education (4 levels), race (5 categories – Black, White, Hispanic, Asian, Other) and
marital status, as well as indicators of child’s gender, plurality (twins or higher), and a quadratic
trend for year of birth. Indicators of missing values are also included for covariates. Panels B
and C report estimates from specification (7) run separately by child’s gender. The sample
includes all six-year-old public school students in New York City whose birthdates are between
August and October, and who are not English Language Learners, from the 2003 through 2009
school years. Regressions include indicators of child’s race (5 categories – Black, White,
Hispanic, Asian, Other), home zip code, year of birth, and a quadratic trend for year of birth.
Indicators of missing values are also included for covariates.
*Significant at 10%; **significant at 5%; ***significant at 1%.
(A-1)
�
�
=
� 1
*� (� � � 𝑛� � �
� � 𝑢� �
e
d
i
c
a
l
r
i
s
k
i
n
d
i
c
a
t
o
r
20.02
L
a
b
o
r
APPENDIX ) + � 2* � ( �
� � 𝑛𝐽� � � 𝑎� h � ) + � �
�
+�
𝑚�
+
� �
� �
+
� �
Appendix Table I Outcomes for births occurring to New York City
Mwomen 1995-2004
indicator Gestation Birthweight Apgar
sample mean 0.248
0.360
38.8
3,253
8.995
c
o
bornApriltoJune 2002 0.0070** 0.0092** -0.018* -6.136** -0.0091* [0.0032] [0.0036
m
[0.010] [2.602] [0.0051]
p
bornJantoMarch2002 0.010*** 0.011*** -0.027** -9.876*** -0.015*** [0.0032] [0.0
l
[0.011] [2.593] [0.0052]
i
c
a
t
i
o
n
0.01 0.07 0.11 0.02 in specification (A-1). The sample includes all live births to women residing in one
of the five boroughs of New York City from 1995 through 2004. Regressions include mother’s parity, age (and age
squared), and indicators of mother’s education (4 levels), race (5 categories – black, white, hispanic, asian, other) and
marital status, as well as indicators of child’s gender, plurality (twins or higher), year of birth, and month of birth.
Indicators of missing values are also included for covariates.
*Significant
at 10%; **significant at 5%; ***significant at 1%.
Notes. The table reports estimates of �
1,198,265
1,198,265
R
1
and �
N 1,198,265
2
1,198,265
1,198,265
Appendix Table II Outcomes for births occurring to New York City
women 1995-2004
Medical risk indicator:
Medical risk
stress related
indicator: other
sample mean 0.048
Notes. The table reports estimates of a1 and a2
inutero1 0.0050** 0.00082 [0.0020] [0.0029]
inutero2 0.0086*** 0.0020 [0.0019] [0.0027]
2N 1,198,265
1,198,265
0.02
in specification (1) with maternal medical risks as the outcomes. In the first column,
an indicator for having at least one stress-related medical risk (hypertension, eclampsia,
or genital herpes) is the outcome. In the second column, an indicator for having at least
one other medical risk (anemia, cardiac disease, diabetes, lung disease, hydramnios,
hemoglobinopathy, incompetent cervix, previous infant >4000 grams or preterm, renal
disease, Rh sensitization, uterine bleeding, or non-specified risk factor) is the outcome.
The sample includes all live births to women residing in one of the five boroughs of New
York City from 1995 through 2004. Regressions include mother’s parity, age (and age
squared), and indicators of mother’s education (4 levels), race (5 categories – Black,
White, Hispanic, Asian, Other) and marital status, as well as indicators of child’s gender
(Panel A only), plurality (twins or higher), year of birth, and month of birth. Indicators of
missing values are also included for covariates.
*Significant at 10%; **significant at 5%; ***significant at 1%.
0.231
1
Ap
Ci
Notes. The table reports estimates of � - �
sample
Born S
Born O
Born N
Born D
Born J
Born F
Born M
1,21
2N
reported
covariate
*Signific
Appendix Table
City women 19
Born Sep 2001 0.00
Born Oct 2001 0.00
Born Nov 2001 0.00
Born Dec 2001 0.00
Born Jan 2002 -0.00
Born Feb 2002 0.00
Born March 2002 -0
27N
1,198,265
includes all live births to
*Significant at 10%; **s
1
Notes. The table reports estimates of � - �
Appendix Table V Average grades for New
York City public school children 2003/4-2009/10
Average grade
Boys Girls
sample mean 2.85
3.05
born Mar 20 to June 18, 2002 -0.024 -0.018 [0.022]
[0.020]
born Dec 11 to Mar 19, 2002 -0.039* -0.0041 [0.021]
[0.019]
Notes. The table reports estimates of � and � 2N 24,566
24,259
R0.08
0.08
in specification (3) run separately
by child’s gender. The sample is a non-representative convenience sample of 6-year-old public school
students in New York City who are not English Language Learners from the 2003 through 2009 school
21
years. Regression includes indicators of child’s race (5 categories – black, white, Hispanic, Asian, other),
home zip code, year of birth, and month of birth. Indicators of missing values are also included for
covariates. *Significant at 10%; **significant at 5%; ***significant at 1%.
Outcomes for births occurring to New York City women 1995-2004 Appendix
Table VI
Medical risk
Labor complication indicator Gestation Birthweight Apgar
indicator
20.002 0.0003 0.001 0.0003 0.0032 in specification (1) with only indicators of year of birth
and month of birth included as covariates. The sample includes all live births to women residing in
one of the five boroughs of New York City from 1995 through 2004.
*Significant at 10%; **significant at 5%; ***significant at 1%.
sample mean 0.248
0.360
38.8
3,253
8.995
inutero1 0.0062* 0.0075** -0.220*** -9.832** -0.013*** [0.0032] [0.0035] [0.020]
[4.491] [0.0051]
inutero2 0.013*** 0.0063* -0.179*** -22.678*** -0.015*** [0.0029] [0.0033] [0.018]
[4.134] [0.0047]
N 1,198,265 1,198,265 1,198,265 1,198,265 1,198,265 R1
Notes.
The table reports estimates of � and �
Appendix Table VII Outcomes for New York City public school children 2003/4-2009/10
Behavior
Special
Held back
Days absent incident
education
indicator
from school indicator
indicator
Boys:
sample mean 11 0.04 0.12 0.04
born Mar 20 to June 18, 2002 -0.010 0.0052* 0.011** 0.0055** [0.158] [0.0028] [0.0044] [0.0026]
born Dec 11 to Mar 19, 2002 0.132 0.0032 0.0094** 0.0065*** [0.149] [0.0026] [0.0042] [0.0025]
2N
210,519
0.02
210,519
210,519
210,519
R0.10
0.01
0.003
Girls:
sample mean 11 0.01
0.04
0.02
born Mar 20 to June 18, 2002 -0.052 0.00042 -0.0013 -0.00017 [0.152] [0.0014] [0.0030] [0.0021]
born Dec 11 to Mar 19, 2002 0.164 -0.0019 -0.00069 -0.00081 [0.144] [0.0014] [0.0028] [0.0020]
Notes. The table reports estimates of � and � 2N 199,778
199,778
199,778
199,778
R0.10
0.001
0.01
in specification (3) run separately by child’s gender with only indicators of year of
birth and month of birth included as covariates. The sample includes all 6-year-old public school students in New York City who are not
English Language Learners from the 2003 through 2009 school years. *Significant at 10%; **significant at 5%; ***significant at 1%.
21
0.003