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“Fear in the Womb”:The Effects of Terrorism on Birth Outcomes in Spain∗

Climent Quintana-DomequeUniversity of Oxford and IZA

Pedro RodenasUniversitat d’Alacant

February 2014

Preliminary and Incomplete

Abstract

We study the effects of terrorism in Spain on birth outcomes, focusing on terror-ism perpetrated by ETA (Euskadi ta Askatasuna or Basque Homeland and Freedom),combining information on the number of ETA casualties from The Victims of ETADataset with the individual birth records from the national registry of live births inSpain, elaborated by the Instituto Nacional de Estadıstica. We focus on live birthsconceived between January 1980 and February 2003 and find that in utero exposureto terrorism early in pregnancy (1st trimester), as measured by the number of ETA-bomb casualties, has detrimental effects on birth outcomes: in terms of average birthweight (lower), the prevalence of low birth weight (higher) and the fraction of normalbabies (lower). Our results are robust to a battery of robustness checks (e.g., measur-ing exposure to terrorism using date of birth instead of estimated conception date).Crucially, and in support of our identification strategy, the number of ETA-bomb ca-sualties after birth does not predict any of the birth outcomes under analysis, andvirtually the same estimates are obtained when controlling for economic conditions(as captured by total unemployment rates) in each of the trimester of pregnancy. Wedo not find evidence of migration responses (in terms of population responses to lastyear terrorist activity), but both the number of live births and the number of fetaldeaths increase with the number of ETA-bomb casualties. Given the increase in fetaldeaths, the estimated effects of terrorism on birth outcomes for live births are likelyto be downward biased (if anything) due to selective mortality.

JEL Classification Codes : I12, J13.Keywords : Stress, Pregnancy, Terrorism, Birth Weight, Spain.

∗Quintana-Domeque (corresponding author): University of Oxford, Department of Economics, Manor Road Building,Manor Road, Oxford OX1 3UQ, United Kingdom; [email protected]. The usual disclaimers apply.

“The ordinary textual meaning of “terrorism” refers to extreme fear”.

Ben Saul. The Challenge of Defining Terrorism, 2012.

1 Introduction

Terrorism and birth outcomes. According to Saul (2012), the best definition of

terrorism confines to violence committed to intimidate a population or coerce government

or international organizations in the name of a political, religious or ideological purpose.

Terrorism is one of today’s most important challenges faced by governments (and societies)

around the world. Terrorists seek to spread fear, influence public opinion, disrupt the econ-

omy, and change government policies in their target countries. Not surprisingly, several

United Nations resolutions acknowledge that terrorism seriously undermines human rights,

jeopardizes political order and peaceful, deliberative politics, and can threaten (interna-

tional) peace and security.

Terrorism has not escaped economists’ attention. Indeed, economists have been studying

the “economic” consequences of terrorism (as well as its causes) for several years (e.g.,

Krueger, 2007). More recently (health) economists have been inquiring about other “non-

economic” consequences of terrorism, such as its impact on birth outcomes (e.g., Brown,

2012), prompted by the existing and still growing research field on the role of prenatal

shocks in predicting not only birth but also long-term outcomes (e.g., Almond and Currie,

2011). But why birth outcomes should be affected by terrorism?

Terrorist violence involves stress and anxiety responses (e.g., Nijdam et al., 2010), and

one particular vulnerable group to stress responses is that of pregnant women.1 Women

who experience stress in the early stages of pregnancy are at increased risk of having a low

birth weight child (e.g., Beydoun and Saftlas, 2008).2

1These responses may lead to significant psychiatric disorders (e.g., Danieli, Brom and Sills, 2005; Whal-ley and Brewin, 2007).

2Stress during pregnancy could have negative effects on the fetus through neuroendocrine changes,changes in immune function, and/or through behavioral channels (Dunkel-Schetter, 2011).

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The connection between child health (or birth outcomes) and “terrorism” has been

investigated in very different contexts: landmine explosions in Colombia (Camacho, 2008),

the September 11 attacks in the United States (Brown, 2012; Eccleston, 2011), and armed

conflict in West Bank and Gaza (Mansour and Rees, 2012). Infants exposed to terrorist

attacks or armed conflict during the prenatal period tend to be smaller at birth, and low

birth-weight is a predictor of both child health (e.g., McCormick, 1985; Pollack and Divon,

1992) and long-term outcomes such as educational attainment, labor market outcomes,

and adult health (Behrman and Rosenzweig, 2004 ; Black, Devereux and Salvanes, 2007;

Currie and Hyson, 1999; Currie, Garces and Thomas, 2002; Case, Fertig, and Paxson, 2005;

Johnson and Schoeni, 2011).

This paper. We study the effects of terrorism in Spain on birth outcomes. In particular,

we focus on terrorism perpetrated by ETA (Euskadi ta Askatasuna or Basque Homeland and

Freedom), a terrorist organization who seeks to gain independence for a Basque homeland

in northern Spain and southern France, and who announced “the definitive cessation of

its armed activity” in October 2011. While no attack has been perpetrated by ETA since

then, the Barometro del CIS (2013) opinion polls show that ETA terrorism has been one

of the main worries of Spaniards during the last 30 years, only after unemployment and

sometimes ranking above it.

We combine information on the number of ETA casualties from The Victims of ETA

Dataset (2007), elaborated by de la Calle and Sanchez-Cuenca, with the individual birth

records from the national registry of live births in Spain, elaborated by the Instituto Nacional

de Estadıstica. We focus on live births conceived between January 1980 and February 2003,

a period characterized by attrition attacks3, and investigate the impact of ETA terrorism

(and in particular of the number of bomb casualties) in each trimester of pregnancy on a

3Attacks that took take place in more distant locations than the territory the terrorist group hopesto eventually govern and are aimed at exhausting the government economically, politically, and ultimatelypsychologically into agreeing to group demands (de la Calle and Sanchez-Cuenca, 2006; LaFree et al., 2012).Prior to 1980 the registry of live births does not provide information on birth weight. The upper limit avoidsMadrid train bombings (March 11 2004) interfering with our estimates.

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battery of birth outcomes: birth weight (in grams), low birth weight (1 if birth weight less

than 2500 grams), normality (absence of complications of labor and delivery) and gender of

the child.

Our identification is based on a difference-in-differences strategy across provinces (50

geographical regions) and time (more than 275 conception month-years). In addition, our

most complete econometric specification include several socio-demographic and maternal

controls (mother’s age, order of birth, mother’s marital status, mother’s occupation, father’s

occupation, municipality size, place of birth) and province-specific linear (month-by-year)

time trends. It is important to highlight that one crucial part of our analysis is to identify

the relevant trimesters of pregnancy (if any).4

Our contribution in perspective. Several studies in the United States have inves-

tigated the consequences of September 11 on birth outcomes. Perhaps, one of the most

carefully executed analyses has been conducted by Brown (2012). He finds that children ex-

posed while in utero to the terrorist attacks of September 11 were born significantly smaller

and earlier than previous cohorts. However, the external validity of estimates based on these

attacks is questionable on many different grounds. First, September 11 was just one shock

event, while the attacks of ETA (and many others terrorist groups) are spread over a long

time span (in our analysis, more than 20 years). Second, and perhaps more importantly,

September 11 was not only a source of acute maternal stress but also had negative pollution

and resource shocks (Bram, Orr and Rapaport, 2002; Landrigan, 2001), which are known

to have negative consequences on child health. While Brown excludes residents of the at-

tacked areas to remove these other influences, part of the relevant effect of stress on birth

outcomes is missed by using this approach. In our context, these other potential channels

are negligible.

4The medical literature provides mixed evidence on the relative importance of early versus late pregnancystress exposure (Schulte et al., 1990; de Weerth and Buitelaar, 2005; Hedegaard et al., 1993; Schneider etal., 1999). Economists tend to find that sources of acute maternal stress tend to affect birth outcomesnegatively when they occur early in pregnancy.

3

Another piece of relevant research for understanding the contribution of our paper is

the one by Mansour and Rees (2012), who provide perhaps the first study on the effect of

intrauterine exposure to armed conflict on pregnancy outcomes. Their evidence comes from

the al-Aqsa Intifada.5 Using data from the Palestinian Demographic Health Survey 2004,

they find that an additional conflict-related fatality 9-6 months before birth is associated

with a modest increase in the probability of having a child who weighed less than 2500g.

While this is a very relevant study, and the most comparable to ours in that they

try to estimate the impact of number of casualties per trimester of pregnancy on birth

outcomes, it suffers from certain limitations that we can overcome. First, their sample size

is very small (hundreds or thousands), while here we use administrative records (millions).

Second, different to us, they do not observe gestational length, so that they measure exposure

by counting backwards from the date of birth, which means that exposure in the first

trimester is likely going to be assigned with measurement error for pre-term babies (Currie

and Rossin-Slater, 2013). Third, while the al-Aqsa Intifada inflicted intense psychological

damage on noncombatants living in the West Bank and Gaza, Mansour and Rees recognize

that other channels apart from stress, namely, malnutrition, physical exertion and limited

access to prenatal care, due to curfews, border closures and road blocks, could affect birth

weight.6 These channels are certainly negligible in our context. Finally, they only have 10

administrative districts, which makes difficult to use “standard” clustering methods. We

have instead 50 provinces, not a very large number, but larger than 42, the rule of thumb

in Angrist and Pischke (2009).

Last but not least, our study is unique in that it is the first to assess the effects of

terrorism on birth outcomes in a developed country by using administrative records (more

than 6 million live births) and keeping track of a terrorist process (more than 20 years). In

5The name commonly used to describe a series of violent clashes between the Palestinians and Israel inthe time frame between 2000 and 2004.

6For instance, they note that many women of reproductive age living in the Occupied Territories werenot consuming sufficient meat, poultry and dairy products at the height of the al-Aqsa Intifada. They tryto assess the importance of these channels.

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addition, our study breaks new ground by extending the analysis of the effects of terrorism

in Spain to the realm of early life shocks, complementing the two main existing pieces

of research on the economic and political consequences of terrorism in Spanish soil: The

economic analysis of Abadie and Gardeazabal (2003) and the study by Montalvo (2011) on

the electoral consequences of the Madrid train bombings of March 11 of 2004.7

Findings. We find that in utero exposure to terrorism early in pregnancy (1st trimester),

as measured by the number of ETA-bomb casualties, has detrimental effects on birth out-

comes: in terms of average birth weight (lower), the prevalence of low birth weight (higher)

and the fraction of normal babies (lower). Our results are robust to measuring exposure

to terrorism using date of birth instead of estimated conception date. In support of our

identification strategy, the number of ETA-bomb casualties after birth does not predict any

of the birth outcomes under analysis, and virtually the same estimates are obtained when

controlling for economic conditions (as captured by total unemployment rates) in each of

the trimester of pregnancy. Excluding either the Basque Country (the region with the high-

est terrorist activity) or the “safe” provinces (regions without any ETA-bomb casualty), we

obtain similar results. Two other interesting results are: (i) the effects seem to be driven

by trimesters with intense terrorism (say 10 ETA-bomb casualties or more), rather than by

trimesters with some terrorism (say 1 ETA-bomb casualty or more), and (ii) the effects of

terrorism are more “intense” (albeit not statistically significant) for children born to moth-

ers whose husbands (partners) are members of the armed-forces. Finally, using aggregate

data, we investigate migration, fertility and (fetal) mortality responses. While we do not

find evidence of migration responses (in terms of population responses to last year terrorist

activity), we find that both the number of live births and the number of fetal deaths increase

with the number of ETA-bomb casualties. Given the increase in fetal deaths, the estimated

7Abadie and Gardeazabal find that, after the outbreak of ETA-terrorism, per capita GDP in the BasqueCountry declined about 10 percentage points relative to a region without terrorism, while Montalvo showsthat the Madrid train bombings of March 11 of 2004, the worst terrorist attack in Spain (with 191 deathsand more than 2000 injured), affected the electoral outcomes of the Spanish General Election celebrated 3days after.

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effects of terrorism on birth outcomes for live births are likely to be downward biased (if

anything) due to selective mortality.

The rest of the paper proceeds as follows. Section 2 describes the main data sources

and provide some descriptive statistics. Section 3 contains the empirical strategy. Section

4 presents the results of our analysis of live birth outcomes and a battery of extensions

and robustness checks. Section 5 studies the effects on fertility and (fetal) mortality and

migration responses. Section 6 provides a conceptual framework to measure the “trade-off”

between terrorism and unemployment in the production of child health and an estimate of

it. Finally, Section 7 concludes.

2 Data

2.1 Main Sources

The national registry of live births in Spain (Instituto Nacional de Estadıstica).8

The unit of observation in this dataset is the live birth. For each live birth, we have in-

formation on its date of occurrence (month and year), gender, weight, gestational length,

and normality (whether there were complications during the pregnancy or labor). How-

ever, there is no information on other child health metrics such as Apgar score or head

circumference. In addition, there is some demographic information on the mother of the

child (province of residence, age, parity history (number of births that she has had), mari-

tal status, and occupational status), but not on her risky behaviors (smoking or drinking),

prenatal visits, educational attainment or (family) income. When appropriate, there is also

information on his spouse: age and occupational status.

We use information on around 6.5 million births conceived between January 1980 and

February 2003.9 Following previous work on the determinants of birth weight, we focus on

8http://www.ine.es9Since conception length is not available for all live births, as a robustness check we also measure exposure

using date of birth. We have almost 10 million births born between January 1980 and December 2003.

6

mothers aged 15-49, exclude multiple births and those newborns whose weight was either

under 500 grams or above 9,000 grams. Moreover, following Currie and Rossin-Slater (2013),

those with gestational length below 26 weeks are also excluded.

The Victims of ETA Dataset (de la Calle and Sanchez-Cuenca).10 The unit of obser-

vation in this dataset is the ETA-victim casualty. It contains information on all casualties

caused by ETA during the period 1960-2006. For each casualty, there is information on

the name of the victim, the region of occurrence, time (day, month and year) and type

of attack (e.g., bomb or shooting). Our analysis will be focused on ETA-bomb casualties,

because from the point of view of the average mother in the population, she is more likely

to be concerned about attacks with (more) collateral victims (bombs) than about targeted

attacks (shooting).

2.2 Descriptive Statistics

We begin our empirical analysis presenting some descriptive statistics (averages) on birth

outcomes (panel A) and mother-pregnancy characteristics (panel B) by exposure to ETA-

bomb casualties during pregnancy in Table 1. This table has three columns. Column (1)

displays the average of the corresponding variable in each row for children unexposed to

ETA-bomb casualties during pregnancy, while column (2) focuses on children exposed to at

least one ETA-bomb casualty during pregnancy. Column (3) contains the (mean) difference

between the previous two columns (and its standard error).

[Insert Table 1 about here]

Panel A shows that children exposed to ETA-bomb casualties during pregnancy are on

average 36 grams (or 0.7 standard deviations) thinner; they are also 0.6 percentage points (or

6 per 1,000 live births) more likely to be low birth-weight babies and 2 percentage points (or

16 per 1,000 live births) less likely to be normally delivered; they are 1 percentage points (1

10http://www.march.es/ceacs/proyectos/dtv

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per 1,000 live births) less likely to be males. Note that neither the fraction of available birth

weights (non-missing values) nor the fraction of premature babies is related to exposure to

ETA-bomb casualties during pregnancy.

Taken at face value, the estimates from panel A are consistent with exposure to terrorism

while in utero affecting birth outcomes negatively. However, exposed and unexposed children

may be different in many other dimensions apart from their exposure to bomb-casualties.

This is confirmed in panel B. For instance, mothers of babies exposed to ETA-bomb casu-

alties are more than half a year older than mother of unexposed babies, and their order of

births are also different. In addition, these descriptive statistics are not informative about

the relative importance of the timing of exposure (trimester). It is then crucial to account

for the (precise) timing of exposure and to use a proper identification strategy in order to

identify the impact of terrorism on birth outcomes.

3 Empirical Strategy

3.1 Counting forward from date of conception

We use the number of ETA-bomb casualties as our measure of terrorism intensity and

estimate regressions of the form

Yi,p,t = α + β1Casualties1p,t + β2Casualties

2p,t + β3Casualties

3p,t

+δp + γt + (θp × t) + τXi,p,t + ui,p,t

(1)

where Yi,p,t is the birth outcome corresponding to newborn i, whose mother’s province

of residence is p, conceived in the year-month t, CasualtiesTp,t is the number of ETA-bomb

casualties in trimester T of pregnancy in province p, and ui,p,t is a random error term.

Year-month of conception is estimated using the approach in Brown (2012): month of birth

minus gestational age minus 2 weeks divided by 4, and increased by 12 if the difference is

8

less than 1. Conception year is then either the year of birth or the birth year less one if the

conception month is larger than the birth month.11

Our most naıve regressions include both mother’s province of residence fixed effects (δp)

and year-month of conception fixed effects (γt), while our most complete regressions include

a vector of control variables (Xi,p,t) –birth order (parity) categories, mother’s age categories,

mother’s marital status indicator, mother’s occupational categories, father’s occupational

categories (with one category if not father), indicator for delivery in a hospital or clinic,

and size of the municipality of residence categories– and province-specific linear time (year-

month of conception) trends. The vector of parameters of interest is β = (β1, β2, β3),

which measures the sensitivity of infant health to prenatal terrorist activity in each of the

trimesters of pregnancy. Standard errors are clustered at the province level (50 provinces).

3.2 Counting backward from date of birth

In addition, since gestational length is not available for all live births (it is missing for

32% of live births) and in many instances is not available to the researcher, we also follow the

standard approach of measuring exposure by counting backwards from month of birth (e.g.,

Bozzoli and Quintana-Domeque, 2014; Mansour and Rees, 2012). We estimate regressions

of the form

Yi,p,t = α + β8−6Casualties8−6p,t + β5−3Casualties

5−3p,t + β2−0Casualties

2−0p,t

+δp + γt + (θp × t) + τXi,p,t + εi,p,t

(2)

where Yi,p,t is the birth outcome corresponding to newborn i, whose mother’s province

of residence is p, born in the year-month t, CasualtiesC−Ap,t is the number of ETA-bomb

casualties in C to A months before birth in province p, and εi,p,t is a random error term.

112 weeks are subtracted because conception usually occurs 2 weeks after the last normal menstrualperiod.

9

Our most naıve regressions include both mother’s province of residence fixed effects (δp) and

year-month of birth fixed effects (γt), while our most complete regressions include a vector

of control variables (Xi,p,t) and province-specific linear time (year-month of birth) trends.

As before, the vector of parameters of interest is β = (β8−6, β5−3, β2−0), which measures

the sensitivity of infant health to prenatal terrorist activity in each of the “approximately

measured” trimesters of pregnancy.

4 Effects on Birth Outcomes for Live Births

4.1 Main Regressions

Table 2 displays the main results of this paper. It contains a series of regressions for

four different birth outcomes –birth weight (in grams), and low birth-weight, normal and

male (indicators)– on the number of ETA-bomb casualties in each trimester of pregnancy

grouped into three different panels (A, B, C). While birth weight and low birth-weight

are standard birth outcomes, as pointed out recently by Currie and Rossin-Slater (2013),

measured effects of stressful events on these measures may be sensitive to specification, and

it is preferable to use more sensitive indicators of newborn health, such as the probability

of abnormal conditions of the newborn (here we use normal). Finally, and following Brown

(2012), we also consider gender as a potential outcome of exposure to terrorism while in

utero, since maternal stress may impact the sex ratio by reducing male births (Catalano et

al., 2006).


Starting with panel A, which includes mother’s province of residence fixed effects and

year-month of conception fixed effects, we can see that an additional ETA-bomb casualty

in the first trimester of pregnancy (on average) decreases birth weight by around 0.7 grams,

increases the expected number of low birth-weights by around 0.2 per 1,000 live births,

10

and decreases the predicted number of normal deliveries (without pregnancy or labor com-

plications) by about 0.6 per 1,000 live births. In panel B we include socio-demographic

controls –mother’s age, birth order categories, mother’s occupational categories, father’s

occupational categories, mother’s marital status indicator, medical center/hospital delivery

indicator, and municipality size categories– and obtain similar results, both qualitatively

and quantitatively. Finally, to soak up any province-specific time trends, panel C adds the

interaction of mother’s province of residence fixed effects with a time trend (year-month

of conception). Remarkably enough, the statistical significance of our estimates survive

to this stringent adjustment.12 All point estimates remain in the same ballpark, but the

one concerning average birth weight, which gets reduced to almost one third of its original

magnitude.

The main takeaway of table 2 is that in utero exposure to terrorism early in pregnancy

(1st trimester) has detrimental effects on birth outcomes. According to our most conserva-

tive estimates, ten additional ETA-bomb casualties would decrease average birth weight by

about 3 grams (around 0.006 standard deviations) and increase low birth weight by about

1.5 per 1,000 live births. A more naıve picture would suggest instead effects of almost 7

grams (around 0.012 standard deviations) and about 1.9 per 1,000 live births. Both the

magnitudes of estimated effects and the fact that they are found for the first trimester

of pregnancy is consistent with the estimates available in the literature (Camacho, 2008;

Brown, 2012; Mansour and Rees, 2012).

Finally, since conception length is not available for all live births, in Table 3 we estimate

the same regressions but using only information on the date of birth as a robustness check.

The new point estimates are qualitatively very similar, which is quite reassuring given both

the different methodologies (date of birth versus date of conception) and the sample size

discrepancies. It seems that, if anything, using date of birth rather than conception date

results in attenuated estimated effects of terrorism on birth outcomes, something expected

12What is more, a new point estimate –the one corresponding to the number of fatalities in the 2ndtrimester of pregnancy– becomes statistically significant for the normal delivery outcome.

11

under (classical) measurement error in the trimester of pregnancy casualties variables.


4.2 Falsification Test: Does Terrorism After Birth predict Birth

Outcomes?

Table 4 presents our placebo or falsification tests. In this table we re-estimate our most

complete econometric specification in Table 2 (panel C) for each birth outcome adding

either the number of ETA-bomb casualties in the first trimester after birth or the number

of ETA-bomb casualties in the first nine months after birth. If we were identifying acute

maternal stress shocks due to (unexpected) terrorism casualties, we should not find that

casualties after birth affect birth outcomes. The results in Table 2 show basically the same

results as in Table 2 (panel C) and, reassuringly, none of the point estimates on the placebo

variables is statistically significant at any conventional level.


4.3 Confounding Economic Factors: In Utero Unemployment

Given that previous research has documented the negative economic consequences of

ETA-terrorism in Spain (Abadie and Gardeazabal, 2003), it may well be the case that our

trimester casualty variables are picking up the influence of resource (“economic”) shocks

rather than stress shocks. We assess such a possibility in Table 5, where we include the (to-

tal) unemployment rate corresponding to each trimester of pregnancy using data from the

Encuesta de Poblacion Activa.13 Two results stand out in this table. First, our estimates

are (almost) identical to those in Table 2 (panel C). Second, babies exposed to high unem-

ployment rates (in the first trimester of pregnancy) have a reduced incidence of low birth

13http://www.ine.es/inebaseDYN/epa30308

12

weight –a finding consistent with the empirical evidence in the US by Deheija and Lleras-

Muney (2004)–, tend to have a higher average birth weight, and are more likely to have

a normal delivery (without complications). This finding is consistent with an opportunity

cost of time selection story: High-educated (or more broadly, high socioeconomic status)

women are more likely to conceive during bad economic times than in good economic times

(and the opposite prevails for their low-educated counterparts).


4.4 Excluding either The Basque Country or “Safe” Provinces

One may wonder whether our estimates are driven by just one region (the Basque Coun-

try is the one with the highest level of terrorist activity) and its three provinces (Alava,

Guipuzcoa, Vizcaya), so that the other provinces do not play any role in our analysis.

Another observer could also raise the concern that “healthy people” (with better health

outcomes) may migrate in response to terrorism from the Basque Country to other regions,

so that those exposed to terrorism in the Basque Country would tend to be negatively se-

lected. If that were the case, we would be overestimating the effect of terrorism. Table

6 shows that none of these possibilities is borne out in the data. Excluding the Basque

Country, we still obtain the same empirical results as in Table 2 (Panel C).


By a similar token, we may inquire about what happens if we just focus on provinces

with at least one ETA-bomb casualty, so that we exclude “safe” provinces. This amounts

to excluding 35 out of 50 provinces. While clearly now clustered standard errors must be

taken with a grain of salt, the point estimates are similar to the ones reported in panel C

of Table 2.


13

4.5 Heterogeneous Effects: Armed-Forces

While terrorism is likely to stress mothers exposed to it, clearly, some mothers are

more likely to suffer or perceive higher risks from it, either because of individual or group

heterogeneity. Ceteris paribus, one group of mothers that should be expected to respond to

terrorism in a more intense way is that whose partners (husbands) are in the police forces.

Unfortunately, our dataset does not allow us to identify the occupation of the husband to

the police force category (or level). Still, it provides information on whether the husband is

a member of the armed forces (“profesionales de las fuerzas armadas”). In Table 8 we broke

down our sample by father’s armed-forces (occupation) status. The two subsamples are very

different in size (1 to 75), but the qualitative results are quite spectacular: 11 out of 12 point

estimates (albeit almost all of them very imprecisely estimated, and hence not statistically

significant) are much larger in magnitude for babies born to armed-forces fathers than their

counterparts. For example, the point estimates corresponding to ETA-bomb casualties in

the first trimester of pregnancy of birth weight is −1.2 for armed-forces fathers versus −0.25

for other fathers: a 5 to 1 difference. Although not statistically significant, the effects of

terrorism are more “intense” for children born to mothers whose husbands (partners) are

members of the armed-forces.


4.6 Non-linearities: Terrorism Intensity

So far we have been restricting the effect of ETA-bomb casualties to be linear. We now

explore the effects of terrorism by intensity in Table 9. We replace our count ETA-bomb

casualties’ variables with variables taking value 1 if the number of ETA-bomb casualties in

the trimester is equal or higher than 10 (and 0 otherwise) in panel A, and with variables

taking value 1 if the number of ETA-bomb casualties in the trimester is equal or higher than

1 (and 0 otherwise) in panel B. The results reveal that babies exposed in the first trimester

14

of pregnancy to 10 casualties or more are on average (almost) 10 grams thinner. Similarly,

the number of babies that are low birth-weight increase by (almost) 7 per 1,000 live births

when exposed to 10 casualties or more during the first trimester of pregnancy. The evidence

reported in this table indicates that intense terrorism is the responsible for the previously

estimated effects.


5 Effects on Mortality, Fertility and Migration

5.1 Effects on Mortality and Fertility Responses

The analysis conducted up to that point has investigated the impact of exposure to

terrorism on birth outcomes for live births. We now turn to the study the impact of

exposure to terrorism on mortality, and in particular, fetal deaths.14 We aggregate (count

the number of) fetal deaths at the year-month-province level, so that the total number of

observations is 13,900. The results are presented in Table 10.


The first column shows that one additional ETA-bomb casualty in the first trimester of

pregnancy increases fetal deaths by 0.2, while the increase is around 0.15 if the extra casualty

happens in the third trimester of pregnancy. We obtain virtually the same estimates if we

control for unemployment rates in each of trimester of pregnancy, and consistent with our

previous findings, higher unemployment rates are associated with a smaller number of fetal

deaths. Given the increase in fetal deaths, our previous estimates of the effects of terrorism

on birth outcomes are likely to be downward biased (if anything) due to selective mortality

14We investigate fetal deaths because is a natural extension in terms of linking them to in utero terrorismexposure. Note that neonatal deaths or post-neonatal deaths are likely to be affected by terrorist activityafter birth. Late Fetal Deaths Microdata available at http://www.ine.es/prodyser

15

(Bozzoli, Deaton, and Quintana-Domeque, 2009). In that sense, our previous estimates on

live birth outcomes can be understood as lower bounds.

While the first two columns look at mortality (fetal deaths), in columns (3) and (4) we

inquire into fertility responses. An additional casualty translates into 20 to 30 extra live

births, depending on the trimester of pregnancy. Interestingly, the effect is present for all

trimesters of pregnancy. The effects of terrorism on both fetal deaths and live birth are of

a similar order of magnitude: around 0.05 and 0.06 standard deviations.

5.2 Migration responses

Migration could be interfering with our identification strategy (and our estimates) if

residents (and in particular pregnant mothers) decided to migrate because of terrorism

from a region with terrorist activity (say the Basque Country) to one without terrorist

activity. While our results are robust to either excluding the Basque Country or “safe”

regions (provinces without any ETA-bomb casualty over 1980-2003), we have no way to

track mothers in our administrative records, so that we cannot study mothers’ migration

behavior. We can nevertheless investigate whether population sizes at the province level

for a given year can be predicted by the number of ETA-bomb casualties in the same

province one year before.15 The result of this analysis is presented in Table 11. For the

sake of comparison, in column (1) we replicate our regressions for live births using log(live

births), which gives a sense of how to compare the magnitudes for the estimates on the

log(population) dependent variables. Columns from (2) to (4), for the age-prime group,

age-prime females, and age-prime males, show that the number of ETA-bomb casualties

does not predict (log) population size for any of these groups (or any others).16


15Population data obtained from Estimaciones Intercensales de Poblacion (INE).16Results available upon request.

16

6 The trade-off between unemployment and terrorism

6.1 Conceptual Framework

(Child) health is a multidimensional concept. Suppose that we can classify babies as

being healthy (h = 1) or unhealthy (h = 0), and that h is a function of several (observable)

inputs, say x1 and x2, and several (unobservable to the econometrician) inputs, say η. In

other words, we postulate the following child health production function

h = f(x1, x2) + η (3)

While we do not observe h, we observe two measures of babies’ health, namely h1 (a binary

measure of non-low birth weight: 1 if normal weight, 0 if low-birth weight) and h2 (a binary

measure of normality: 1 if normal delivery/pregnancy, 0 if not), such that

h1 = g(h) + u1 (4)

h2 = v(h) + u2 (5)

Substituting (3) into (4) and (5), we obtain

h1 = g(f(x1, x2) + η) + u1 (6)

h2 = v(f(x1, x2) + η) + u2 (7)

So that, the marginal rate of technical substitution (MRTS) between inputs x1 and x2 (i.e.,

how much x1 have to decrease if x2 increases by one extra unit)

MRTS =

∂f∂x1

∂f∂x2

(8)

17

is overidentified, since∂h1

∂x1

∂h1

∂x2

=∂h2

∂x1

∂h2

∂x2

= MRTS (9)

6.2 Estimation

Under separability, conditional independence and linearity, the MRTS between

x1 and x2 can be consistently recovered. One can for instance simultaneously regress h1 (low

birth weight) and h2 (normality) on the main inputs at stake (i.e., terrorist intensity in each

trimester of pregnancy –Casualties1, Casualties2, Casualties3– and unemployment rate

in each trimester of pregnancy –Unemployment1, Unemployment2, Unemployment3) and

on the rest of control variables of panel C in Table 2 using seemingly unrelated regression

(SUR) and test for (9).


Table 12 shows that we cannot reject the equality of the ratios of the marginal effects of

terrorism and unemployment in the first trimester of pregnancy for h1 and h2, so that

the “marginal rate of technical substitution” between terrorism and unemployment in the

production of child health is identified.

7 Conclusion

We estimate the effect of in utero exposure to ETA-bomb casualties on a range of birth

outcomes: birth weight, low-birth weight, normality, and gender. We find detrimental effects

in terms of average birth weight (lower), the prevalence of low birth weight (higher) and the

fraction of normal babies (lower). Our results are robust to a battery of robustness checks

(e.g., measuring exposure to terrorism using date of birth instead of estimated conception

date).

Crucially, and in support of our identification strategy, the number of ETA-bomb casu-

alties after birth does not predict any of the birth outcomes under analysis, and virtually

18

the same estimates are obtained when controlling for economic conditions (as captured by

total unemployment rates) in each of the trimester of pregnancy. We do not find evidence

of migration responses (in terms of population responses to last year terrorist activity), but

both the number of live births and the number of fetal deaths increase with the number of

ETA-bomb casualties. Given the increase in fetal deaths, the estimated effects of terrorism

on birth outcomes for live births are likely to be downward biased (if anything) due to

selective mortality.

Results are driven by exposure to terrorism in the first trimester of pregnancy, indicating

that ETA-bomb casualties are acting as acute maternal stress shocks. That stress early in

pregnancy (rather than in other periods) is bad for the fetus is consistent with recent studies

on the effects of “violence”, from terrorist attacks in the United States (Brown, 2012) to

homicide rates in rural Brazil (Foureaux and Manacorda, 2013).

19

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23

Table 1. DESCRIPTIVE STATISTICS

Mean characteristics of live births for exposed and unexposed children (and their mothers) to ETA-bomb casualties during

pregnancy while in utero, and their difference.

No ETA-Bomb Casualty ETA-Bomb Casualties 1 Difference

A. Birth Outcomes

BW (Birth Weight: 500-6590 grams)

[N = 6,327,753] 3,291.64 3,255.78 35.86***

(8.28)

BW is available (per 1,000)

[N = 6,641,478] 953 953 0

(11)

LBW (Low Birth Weight) (per 1,000)

[N = 6,327,753] 51 57 6***

(1)

Premature (per 1,000)

[N = 6,641,478] 47 50 3

(4)

Normal (per 1,000)

[N = 6,641,478] 899 883 16*

(9)

Male (per 1,000)

[N = 6,641,478] 517 516 1*

(0.4)

B. Mother and Pregnancy Characteristics

Mother’s age (15-49 years old)

[N = 6,641,478] 28.8 29.4 0.6***

(0.2)

Mother is married (per 1,000)

[N = 6,641,478] 883 879 4

(9)

First pregnancy (per 1,000)

[N = 6,641,478] 519 508 11

(9)

Second pregnancy (per 1,000)

[N = 6,641,478] 364 347 17***

(6)

Note. Live births conceived between January 1980 and February 2003. Each difference is computed as the estimated coefficient on an indicator variable (1 if ETA-

bomb casualties during pregnancy 1, 0 otherwise) in a separate OLS regression (which includes a constant) for each variable. Low Birth Weight: 1 if BW 2,500

grams, 0 otherwise. Statistical significance associated to the t-test of the estimated coefficient on the indicator variable with standard errors clustered at the province level (50 clusters). *** p-value < 0.01, ** p-value < 0.05, * p-value < 0.1

Table 2. OLS Regressions of Birth Outcomes on ETA-Bomb casualties by trimester of in utero exposure

(counting forward from estimated date of conception)

BW

LBW Normal Male

(per 1,000) (per 1,000) (per 1,000)

A. Year-Month Fixed Effects & Province Fixed Effects

ETA-Bomb casualties 1st trimester of pregnancy 0.674*** 0.187** 0.631*** 0.138

(0.194) (0.834) (0.194) (0.123)

ETA-Bomb casualties 2nd trimester of pregnancy 0.504 0.118 0.287 0.379

(0.404) (0.148) (0.275) (0.230)

ETA-Bomb casualties 3rd trimester of pregnancy 0.392 0.017 0.252 0.276

(0.484) (0.105) (0.454) (0.212)

Number of live births 6,327,753 6,327,753 6,641,478 6,641,478

B. (A) & Socio-Demographic Controls

ETA-Bomb casualties 1st trimester of pregnancy 0.725*** 0.208** 0.571*** 0.130

(0.198) (0.088) (0.187) (0.126)

ETA-Bomb casualties 2nd trimester of pregnancy 0.489 0.119 0.173 0.376

(0.380) (0.154) (0.275) (0.232)


(0.460) (0.106) (0.434) (0.214)


C. (B) & Province-Specific Linear Year-Month Trends

ETA-Bomb casualties 1st trimester of pregnancy 0.278** 0.145** 0.671*** 0.093

(0.122) (0.061) (0.179) (0.120)

ETA-Bomb casualties 2nd trimester of pregnancy 0.055 0.179 0.272*** 0.337

(0.202) (0.144) (0.098) (0.236)


(0.250) (0.078) (0.174) (0.212)


Note. Live births conceived between January 1980 and February 2003. Year and month of conception. Province of mother’s residence. Socio-

demographic controls: mother’s age categories: 6 dummy variables; birth order categories: 3 dummy variables; mother’s occupational categories

(including non-labor market activities): 11 dummy variables; father’s occupational categories (including indicator NA): 12 dummy variables; mother’s marital status: 1 dummy variable (married or not); medical center/hospital delivery indicator: 1 dummy variable; municipality size categories: 5 dummy

variables. Standard errors clustered at the province level (50 clusters). *** p-value < 0.01, ** p-value < 0.05, * p-value < 0.1

Table 3. OLS Regressions of Birth Outcomes on ETA-Bomb casualties by in utero prenatal exposure period

(counting backwards from date of birth)

BW

LBW Normal Male

(per 1,000) (per 1,000) (per 1,000)

A. Year-Month Fixed Effects & Province Fixed Effects

ETA-Bomb casualties 6-8 months before birth –0.525** 0.075 –0.382*** –0.063

(0.227) (0.050) (0.130) (0.079)

ETA-Bomb casualties 3-5 months before birth –0.582* 0.038 0.155 –0.229

(0.309) (0.116) (0.263) (0.213)

ETA-Bomb casualties 0-2 months before birth –0.077 0.007 0.018 –0.226

(0.474) (0.117) (0.139) (0.207)


B. (A) & Socio-Demographic Controls

ETA-Bomb casualties 6-8 months before birth –0.607*** 0.113** –0.331** –0.063

(0.200) (0.053) (0.130) (0.080)

ETA-Bomb casualties 3-5 months before birth –0.618** 0.053 0.182 –0.225

(0.299) (0.119) (0.275) (0.215)

ETA-Bomb casualties 0-2 months before birth –0.094 0.022 0.079 –0.224

(0.452) (0.111) (0.145) (0.209)


C. (B) & Province-Specific Linear Year-Month Trends

ETA-Bomb casualties 6-8 months before birth –0.211* 0.067 –0.396* –0.040

(0.116) (0.058) (0.213) (0.088)

ETA-Bomb casualties 3-5 months before birth –0.193 –0.000 –0.018 –0.218

(0.149) (0.116) (0.180) (0.215)

ETA-Bomb casualties 0-2 months before birth 0.391 –0.034 –0.128 –0.210

(0.312) (0.104) (0.130) (0.203)


Note. Live births born between January 1980 and February 2003. Year and month of birth. Province of mother’s residence. See Table 2.

Table 4. PLACEBOS

OLS Regressions of Birth Outcomes on ETA-Bomb casualties by trimester of in utero exposure and placebos (after birth).

BW LBW

(per 1,000)

Normal

(per 1,000)

Male

(per 1,000)

(1) (2) (3) (4) (5) (6) (7) (8)

ETA-Bomb Casualties in the 1st trimester –0.271** –0.259** 0.142** 0.135** –0.671*** –0.660*** –0.090 –0.092

(0.119) (0.118) (0.063) (0.063) (0.182) (0.176) (0.120) (0.118)

ETA-Bomb Casualties in the 2nd trimester –0.054 –0.036 –0.179 –0.187 –0.272*** –0.261** –0.337 –0.337

(0.204) (0.216) (0.145) (0.149) (0.098) (0.105) (0.235) (0.240)

ETA-Bomb Casualties in the 3rd trimester 0.140 0.146 –0.053 –0.054 0.253 0.251 –0.232 –0.228

(0.242) (0.250) (0.076) (0.078) (0.175) (0.172) (0.211) (0.211)

Placebos

ETA-Bomb Casualties in the 1st trimester after birth 0.294 -- –0.087 -- 0.007 -- 0.103 --

(0.365) (0.132) (0.149) (0.069)

ETA-Bomb Casualties in the 1-9 months after birth -- 0.249 -- –0.119 -- 0.142 -- 0.004

(0.246) (0.085) (0.109) (0.078)

Number of live births 6,295,035 6,295,035 6,295,035 6,295,035 6,607,470 6,607,470 6,607,470 6,607,470

Mother’s Province of Residence Fixed Effects Yes Yes Yes Yes Yes Yes Yes Yes

Year-Month Fixed Effects Yes Yes Yes Yes Yes Yes Yes Yes

Socio-Demographic Controls Yes Yes Yes Yes Yes Yes Yes Yes

Province-Specific Linear Time (Y-M) Trends Yes Yes Yes Yes Yes Yes Yes Yes

Note. See Table 2.

Table 5. ACCOUNTING FOR THE RELATIONSHIP BETWEEN ECONOMIC CONDITIONS AND CHILD

HEALTH

OLS Regressions of Birth Outcomes on ETA-Bomb casualties and unemployment rates by trimester of in utero

exposure

BW

LBW Normal Male

(per 1,000) (per 1,000) (per 1,000)

ETA-Bomb casualties 1st trimester of pregnancy 0.251* 0.146** 0.618*** 0.090

(0.127) (0.059) (0.161) (0.120)

ETA-Bomb casualties 2nd trimester of pregnancy 0.038 0.181 0.246** 0.339

(0.188) (0.139) (0.108) (0.236)


(0.231) (0.076) (0.203) (0.217)

Unemployment rates

Unemployment rate 1st trimester of pregnancy 0.628* 0.209** 0.721* 0.001

(0.315) (0.093) (0.394) (0.155)

Unemployment rate 2nd trimester of pregnancy 0.013 0.138 0.283* 0.241

(0.240) (0.111) (0.158) (0.236)

Unemployment rate 3rd trimester of pregnancy 0.399 0.015 0.603 0.100

(0.325) (0.099) (0.566) (0.152)


Mother’s Province of Residence Fixed Effects Yes Yes Yes Yes

Year-Month Fixed Effects Yes Yes Yes Yes

Socio-Demographic Controls Yes Yes Yes Yes

Province-Specific Linear Time (Y-M) Trends Yes Yes Yes Yes

Note. See Table 2.

Table 6. EXCLUDING THE BASQUE COUNTRY

OLS Regressions of Birth Outcomes on ETA-Bomb casualties by trimester of in utero exposure

BW

LBW Normal Male

(per 1,000) (per 1,000) (per 1,000)

ETA-Bomb casualties 1st trimester of pregnancy 0.303* 0.136*** 0.662*** 0.042

(0.159) (0.049) (0.159) (0.118)

ETA-Bomb casualties 2nd trimester of pregnancy 0.113 0.131 0.280*** 0.353

(0.143) (0.091) (0.101) (0.217)


(0.168) (0.065) (0.186) (0.201)






Note. See Table 2. Number of provinces (clusters) is 47.

Table 7. EXCLUDING ALL PROVINCES WITHOUT ANY ETA-BOMB CASUALTY


BW

LBW Normal Male

(per 1,000) (per 1,000) (per 1,000)

ETA-Bomb casualties 1st trimester of pregnancy 0.348** 0.190** 0.541** 0.027

(0.125) (0.088) (0.228) (0.145)

ETA-Bomb casualties 2nd trimester of pregnancy 0.034 0.226 0.187 0.446*

(0.375) (0.183) (0.173) (0.222)


(0.476) (0.157) (0.187) (0.196)






Note. See Table 2. Number of provinces (clusters) is 15.

Table 8. HETEROGENEOUS EFFECTS: ARMED-FORCES FATHERS versus NON-ARMED-FORCES FATHERS

OLS Regressions of Birth Outcomes on ETA-Bomb casualties by trimester of in utero exposure.

BW LBW

(per 1,000)

Normal

(per 1,000)

Male

(per 1,000)

Armed-Force

Non-

Armed-

Force

Armed-Force

Non-

Armed-

Force

Armed-Force

Non-

Armed-

Force

Armed-Force

Non-

Armed-

Force

ETA-Bomb Casualties in the 1st trimester –1.20 –0.254** 0.377 0.142** –0.888 –0.662*** –0.458 –0.091

(1.11) (0.125) (0.670) (0.057) (1.34) (0.166) (1.0) (0.118)

ETA-Bomb Casualties in the 2nd trimester –0.109 –0.037 0.105 –0.186 –2.5*** –0.237** –2.6* –0.309

(0.739) (0.211) (0.258) (0.144) (0.63) (0.101) (1.5) (0.221)

ETA-Bomb Casualties in the 3rd trimester –1.04 0.173 0.875 –0.067 –2.7 0.296 2.3*** –0.259

(1.19) (0.254) (0.905) (0.724) (1.7) (0.180) (0.76) (0.226)

Number of live births 82,453 6,212,582 82,453 6,212,582 87,020 6,520,450 87,020 6,520,450

Mother’s Province of Residence Fixed Effects Yes Yes Yes Yes Yes Yes Yes Yes

Year-Month Fixed Effects Yes Yes Yes Yes Yes Yes Yes Yes

Socio-Demographic Controls Yes Yes Yes Yes Yes Yes Yes Yes

Province-Specific Linear Time (Y-M) Trends Yes Yes Yes Yes Yes Yes Yes Yes

Note. See Table 2.

Table 9. NON-LINEAR EFFECTS OF TERRORISM


BW

LBW Normal Male

(per 1,000) (per 1,000) (per 1,000)

A. Indicators for Trimesters with Intense Terrorism

1(ETA-Bomb casualties 1st trimester of pregnancy 10) 9.54*** 6.54*** 5.23** 0.29

(3.01) (0.87) (2.09) (4.66)

1(ETA-Bomb casualties 2nd trimester of pregnancy 10) 0.283 2.44 7.16** 7.77***

(3.71) (1.73) (3.28) (2.83)

1(ETA-Bomb casualties 3rd trimester of pregnancy 10) 2.65 2.65 11.16 5.02

(4.72) (2.87) (7.90) (3.03)

B. Indicators for Trimesters with Terrorism

1(ETA-Bomb casualties 1st trimester of pregnancy 1) 0.793 0.065 1.71 1.43

(0.996) (0.435) (1.03) (1.12)

1(ETA-Bomb casualties 2nd trimester of pregnancy 1) 1.36 1.10 2.30** 0.544

(1.64) (0.658) (1.09) (0.646)

1(ETA-Bomb casualties 3rd trimester of pregnancy 1) 2.06 0.787* 0.279 1.14

(1.47) (0.450) (1.30) (1.14)






Note. See Table 2. 1() equals 1 if the condition within parenthesis is satisfied, and 0 otherwise.

Table 10. MORTALITY AND FERTILITY RESPONSES TO TERRORISM

OLS Regressions of Fetal Deaths and Live Births on ETA-Bomb casualties (and unemployment rates) by

trimester of in utero exposure

Fetal Deaths Live Births

(1) (2) (3) (4)

ETA-Bomb casualties 1st trimester of pregnancy 0.190** 0.188** 29.01** 28.91**

(0.072) (0.071) (11.52) (11.51)

ETA-Bomb casualties 2nd trimester of pregnancy 0.093 0.093 30.21** 30.20**

(0.083) (0.083) (12.32) (12.30)

ETA-Bomb casualties 3rd trimester of pregnancy 0.151*** 0.150*** 20.22*** 20.25***

(0.037) (0.038) (3.71) (3.70)

Unemployment rates

Unemployment rate 1st trimester of pregnancy -- 0.001 -- 0.734

(0.017) (1.82)

Unemployment rate 2nd trimester of pregnancy -- 0.036*** -- 0.278

(0.013) (0.846)

Unemployment rate 3rd trimester of pregnancy -- 0.029* -- 2.22

(0.017) (2.41)

Number of observations 13,900 13,900 13,900 13,900




Mean of the dependent variable 2.10 477.8

SD of the dependent variable 2.96 620.4

Min of the dependent variable 0 2

Max of the dependent variable 25 5,899 Note. Each observation is the count of the dependent variable at the year-month-province cell. Standard errors clustered at the province level (50 clusters). *** p-value < 0.01, ** p-value < 0.05, * p-value < 0.1

Table 11. FERTILITY VERSUS MIGRATION RESPONSES TO TERRORISM

OLS Regressions of log (Live Births) and log(Population) on ETA-Bomb casualties (and unemployment rates) by


Log(Population at year t in province p)

Log(Live Births) Total

25-54

Female

25-54

Male

25-54

ETA-Bomb casualties 1st trimester of pregnancy 0.015*** -- -- --

(0.005)

ETA-Bomb casualties 2nd trimester of pregnancy 0.013** -- -- --

(0.006)

ETA-Bomb casualties 3rd trimester of pregnancy 0.013*** -- -- --

(0.004)

ETA-Bomb casualties at year t1 in province p -- 0.0002 0.0003 0.0002

(0.0019) (0.0018) (0.0020)

Number of observations 13,900 1,200 1,200 1,200


Year-Month Fixed Effects Yes No No No

Province-Specific Linear Time (Y-M) Trends Yes No No No

Year Fixed Effects -- Yes Yes Yes Note. For column (1) each observation is the count of the dependent variable at the year-month-province cell. For columns (2)-(4) each observation is the

count of the dependent variable at the year-province cell. Standard errors clustered at the province level (50 clusters). *** p-value < 0.01, ** p-value < 0.05,

* p-value < 0.1

Table 12. IDENTIFYING THE “MARGINAL RATE OF TECHNICAL SUBSTITUTION” BETWEEN

TERRORISM AND UNEMPLOYMENT IN THE 1ST TRIMESTER OF PREGNANCY

SUR Regressions of h1 (= 1 – LBW) and h2 (= Normal) on ETA-Bomb casualties and unemployment rates by


h1 h2

ETA-Bomb casualties 1st trimester of pregnancy (𝐓𝟏) 0.146*

(0.087)

0.392***

(0.118)

ETA-Bomb casualties 2nd trimester of pregnancy (𝐓𝟐) 0.181**

(0.087) 0.038

(0.118)

ETA-Bomb casualties 3rd trimester of pregnancy (𝐓𝟑) 0.055

(0.088)

0.515***

(0.119)

Unemployment rate 1st trimester of pregnancy (𝐔𝟏) 0.209***

(0.075)

0.799***

(0.102)

Unemployment rate 2nd trimester of pregnancy (𝐔𝟐) 0.138

(0.098)

0.231*

(0.133)

Unemployment rate 3rd trimester of pregnancy (𝐔𝟑) 0.015

(0.075)

0.486***

(0.101)

Ratio of Coefficients

𝐓𝟏

𝐔𝟏

0.697

(0.480)

0.491***

(0.159)

Wald Test 2(1) = 0.17

p-value=0.6777

Number of live births 6,295,035





Note. See Table 2. Standard errors (unadjusted) for clustering in parenthesis.

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