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Journal of Health Economics 69 (2020) 102247
Contents lists available at ScienceDirect
Journal of Health Economics
journal homepage: www.elsevier.com/locate/econbase
Neonatal health of parents and cognitive development
of children*
Claus Thustrup Kreiner a , Hans Henrik Sievertsen b
a
b
University of Copenhagen, CEBI and CEPR, Denmark
University of Bristol and VIVE, United Kingdom
a r t i c l e
i n f o
Article history:
Received 19 November 2018
Received in revised form 13 August 2019
Accepted 9 October 2019
Available online 30 November 2019
JEL classi?cation:
I12
J13
J24
Keywords:
Neonatal health
Human capital formation
Intergenerational dependency
a b s t r a c t
It is well-established that neonatal health is a strong predictor of socioeconomic outcomes
later in life, but does neonatal health also predict key outcomes of the next generation?
This paper documents a surprisingly strong relationship between birth weight of parents
and school test scores of their children. The association between maternal birth weight and
child test scores corresponds to 50–80 percent of the association between the child’s own
birth weight and test scores across various empirical speci?cations, for example including
grandmother ?xed effects that isolate within-family differences between mothers. Paternal
and maternal birth weights are equally important in predicting child test scores. Our intergenerational results suggest that inequality in neonatal health is important for inequality
in key outcomes of the next generation.
© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC
BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
Today, it is a stylized fact that inequality in birth
endowments is related to inequality in key socioeconomic outcomes later in life (Currie, 2011). For example,
many studies have documented a relationship between
birth weight and measures of cognitive development
(Almond and Currie, 2010), and this relationship exists
within siblings, thereby holding family background ?xed
* *We thank Douglas Almond, Heather Royer and numerous seminar
participants for helpful comments and discussions. We are also thankful
for improvements suggested by two anonymous referees. We are grateful to the Danish Ministry for Education for providing access to data on
school grades. Sievertsen acknowledges support from The Danish Council for Strategic Research, Grant DSF-09-070295. The activities of Center
for Economic Behavior and Inequality (CEBI) are funded by the Danish
National Research Foundation.
E-mail addresses: ctk@econ.ku.dk (C.T. Kreiner),
h.h.sievertsen@bristol.ac.uk (H.H. Sievertsen).
(Currie and Moretti, 2007; Black et al., 2007), and it exists
when measuring performance of children early in school
(Figlio et al., 2014).
We ask whether neonatal health of one generation
(birth weights of parents) is important for the cognitive
development of the next generation (early school performance of children)? The intergenerational literature has
established a strong correlation across generations for a
huge set of socioeconomic outcomes (Solon, 1999; Black
and Devereux, 2011; Chetty et al., 2017; Boserup et al.,
2018; Landersø et al., 2017), including birth weight (Currie
and Moretti, 2007; Royer, 2009). As a result, it is natural to
expect that differences in birth weight within a generation
are associated with differences in cognitive development
of the next generation. Based on estimates of the intergenerational correlation in birth weight and the correlation
between birth weight and school test scores, we may form
a conjecture about the importance of parental birth weight
for child test scores. Estimates for the US (Currie and
https://doi.org/10.1016/j.jhealeco.2019.102247
0167-6296/© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/
licenses/by-nc-nd/4.0/).
2
C.T. Kreiner and H.H. Sievertsen / Journal of Health Economics 69 (2020) 102247
Moretti, 2007) and for Denmark (this study) show that a
one percent higher birth weight of the mother is associated with a 0.2 percent higher birth weight of the child.
Estimates for the US (Figlio et al., 2014) and for Denmark
(this study) show that a one percent higher birth weight of
the child is associated with higher test scores in elementary
school of 0.3 percent of a standard deviation (SD percent).
From these (partial) estimates, we may expect that a one
percent higher birth weight of the mother is associated
with a 0.05 SD percent higher test score of the child (i.e.
0.2 * 0.3 ˜ 0.05).1
This conjecture would be correct if neonatal health of
children is a ‘suf?cient statistic’ incorporating maternal
neonatal health. We ?nd that maternal neonatal health
plays a much larger role. A one percent higher maternal
birth weight is associated with a 0.25 SD percent higher
child test score. This is around ?ve times larger than the
conjecture, and it is 80 percent of the association between
the child’s own birth weight and test score. When running a multivariate regression that includes birth weights
of both the child and the mother, we ?nd a coef?cient on
the mother equal to 0.2 SD percent and, again, close to
80 percent of the child coef?cient. We also provide nonparametric evidence showing a strong association between
maternal birth weight and child test scores, conditional on
the birth weight of the child, throughout the child birth
weight distribution.
A key question is whether the estimated relationship between maternal birth weight and child test scores
re?ects a causal effect or a selection effect. A selection effect
can occur because family background of the mothers affects
both maternal birth weight and child school performance.
Currie and Moretti (2007) and Figlio et al. (2014) show that
the aforementioned relationships between birth weights
of two generations and between an individual’s own birth
weight and school test scores also exist when looking at the
variation within siblings. Using a similar strategy, we keep
family background ?xed by estimating the effect of differences in birth weight between sisters on the test scores of
their offspring. When repeating the univariate and multivariate regressions with ?xed effects, we ?nd in both cases
that a one percent higher maternal birth weight is associated with a 0.1–0.15 SD percent higher child test score,
corresponding to approximately 50 percent of the coef?cient on the child’s own birth weight. These results point
to the existence of a signi?cant causal effect of maternal
birth weight on child test scores.
The signi?cant coef?cient on the birth weight of the
mother, when including the birth weight of the child in the
?xed effect regressions, may re?ect a causal effect of maternal birth weight conditional on child birth weight, but this
is not necessarily the case. We show theoretically that an
alternative explanation can be that variation in child birth
weight related to maternal birth weight is more impor-
1
We are not aware of other countries where there exist estimates of
both the intergenerational correlation in birth weight and the correlation
between birth weight and early school performance of children. We obtain
the same conjecture based on estimates for Norway reported in Black et al.
(2007) if we use their estimates of the correlation between birth weight
and IQ measured for males at age 18.
tant for child cognitive development than the variation in
child birth weight unrelated to maternal birth weight. In
this case, the causal effect of maternal birth weight can
run entirely through child birth weight. However, independent of the causal mechanism at play, the conclusion is that
inequalities in birth endowments of mothers have signi?cant consequences for individuals in the next generation.
For a smaller subsample, we also have information
about the birth weight of the father. Non-parametric evidence for this subsample reveals that child test scores are
also strongly associated with paternal birth weight, conditional on the birth weight of the child, throughout the
child birth weight distribution. When repeating the basic
regression analysis with birth weights of both mothers and
fathers, we ?nd that the two birth weight coef?cients are of
nearly the same size across all speci?cations. For example,
when running multivariate regressions with birth weights
of both children and parents, we ?nd a coef?cient of around
0.2 SD percent for both parents and close to 80 percent
of the child coef?cient. Thus, maternal and paternal birth
endowments are strong and equally good predictors of
child school performance.
We provide three sensitivity analyses to address
potential concerns about model misspeci?cation, sample
selection bias and external validity. First, we show that our
results are robust to model speci?cation. For example, the
results become similar if we, instead of using a standard
speci?cation with the logarithm of birth weight, use a low
birth weight indicator, de?ned conventionally as a birth
weight below 2500 g (Chaikind and Corman, 1991). Second, to address concerns about sample selection, we redo
the basic analysis on another sample of births and reach
the same conclusions. This sample is smaller and has only
survey information on maternal birth weight, but the survey population is representative of all births, unlike the
administrative data where mothers on average are younger
because of lack of birth weight information for older mothers. Third, to address concerns about external validity, we
replicate recent evidence for the US by Figlio et al. (2014)
on the relationship between the birth weight of an individual and school test performance in elementary school. This
suggests that our main results on the relationship between
neonatal health of parents and cognitive development of
children are also relevant for the US and probably other
countries. The similar results for Denmark and the US are
also interesting because of the very different institutional
settings, with Denmark having publicly provided universal
health care (including pre-natal and post-natal care) and
a tax-?nanced school system, with a very limited role of
privately ?nanced supplementary spending on health care
and education.
The results in this paper complement recent ?ndings
demonstrating a long run impact of neonatal health on
individual outcomes (Bharadwaj et al., 2018, 2019). Several studies show that endowments at birth are affected by
external factors such as nutritional shocks, health shocks,
tobacco policies, stress and environmental factors (Almond
and Currie, 2011; Almond and Mazumder, 2011; Currie and
Schwandt, 2013, 2016; Harris et al., 2015; Carlson, 2015;
Black et al., 2016; Persson and Rossin-Slater, 2018). Our
?nding that inequalities in endowments at birth persist
C.T. Kreiner and H.H. Sievertsen / Journal of Health Economics 69 (2020) 102247
into the next generation indicates that external factors,
as well as health innovations and policies, affecting birth
endowments can have signi?cant effects on the next generation.
The rest of the paper proceeds as follows: Section 2
describes our data. Section 3 presents the main empirical results on the relationship between parental neonatal
health and child school performance. Section 4 assesses the
generalizability of the ?ndings. Section 5 provides concluding remarks.
2. Data
2.1. Sources
The information on each individual is based on three
data sources linked together through a unique personal
identi?er. The ?rst data source is The Medical Birth Registry, which contains information on all births in Denmark
for the period 1973–2014. The registry includes information on birth outcomes (birth weight, child height,
gestational age), date of birth, parity, gender and birth
place, as well as personal identi?ers for the child, the
mother and the father. Information on births in hospitals is
based on data from the hospital registry while information
on home births comes from reports by the midwife.
The second data source is provided by the Danish Ministry of Education and contains information on test results
for the Danish National Tests in public schools. The test
program was introduced in 2010. All children in compulsory schooling have to take a reading test in grades 2, 4,
6, and 8, a math test in grads 3 and 6, and a test in each
of the subjects English, Geography, Physics/Chemistry and
Biology during grades 7–8. Three cognitive domains are
tested simultaneously in each test. The math tests assess
numbers and algebra, geometry and applied mathematics.
The reading tests assess language comprehension, decoding and reading comprehension. The tests are IT-based and
teachers are not involved in test design or in assessment of
the test results. The purpose of the national test program is
to provide teachers with an instrument for assessment and
feedback. The program and tests are described in greater
detail in Beuchert and Nandrup (2018), which also shows
that the test results are highly predictive of the exam grades
of the students at the end of compulsory schooling. Data
from the National Tests has been used for research before
by Andersen et al. (2016) and Sievertsen et al. (2016). Our
dataset contains all tests for the period 2010–2016, giving more than three million test results. The data contains
information on the raw test results, the test date and time,
a school identi?er, the test subject and the child’s grade.
The third data source is administrative data from Statistics Denmark. This data contains information about income
and education (degree completed). The income measures
of Statistics Denmark are based on third-party reports from
employers to the tax authorities who use it for tax assessment and selection for audit, and the data is therefore of
high quality (Kleven et al., 2011).
In Denmark, each individual is given a unique personal
identi?er at birth (the so-called CPR number) and this is
registered together with the personal identi?ers of the par-
3
ents. We use the personal identi?er from the CPR-Registry
to obtain an exact link across the three datasets and across
generations: for each child we ?rst merge information from
the birth registry with information on test outcomes and
background characteristics using the personal identi?er.
We then merge the child data with data on parental background (income, education, etc.) using the unique identi?er
from the CPR-Registry.
To complement the study based on administrative registers, we further use data from the Danish National Birth
Cohort (DNBC), which is a nationwide survey of almost
100,000 pregnant women in Denmark between 1997 and
2004, in which the mother was interviewed during pregnancy and at the beginning of the child’s life. The survey
contains self-reported information about the birth weight
of the mothers, which enables us to assess our ?ndings on
a smaller, but more representative, sample of mothers and
children.
2.2. Sample selection
The point of departure for our sample selection is the
927,805 children born in Denmark from 1995 to 2007. The
tests are only mandatory in public schools, which enables
us to match 740,769 of the children to test results in primary school.2 Our sample is reduced to 226,304 (31 percent
of the matched child birth weight and child test score data)
when we merge the child records with the information
on maternal birth weight. This reduction in sample size
is caused by the fact that the mother has to be born in
1973 or later in order to be included in the Medical Birth
Registry. The two sources of sample selection could lead
to non-representative samples. However, as Fig. 1 shows,
the samples have remarkably similar birth weight distributions (Panel A) and test score distributions (Panel B). In
addition, we replicate our main results on the smaller, but
more representative DNBC survey sample in a robustness
analysis in Section 4.
2.3. Variable de?nitions
2.3.1. Birth weight
Data accuracy in the Medical Birth Registry is very
high as the information is provided directly from hospital
records for births in hospitals, comprising about 99 percent
of all births, and by midwives for all home births. Moreover,
the birth outcomes (including birth weight) are recorded by
health professionals (i.e. not self-reported). However, from
1973 to 1978, birth weight was recorded in 500-g intervals, and from 1979 to 1989 birth weight was recorded in
10-g intervals, and as of 1990, birth weight is recorded in
1-g units. For the births between 1973 and 1989, we use
the midpoints of the bins. This may result in attenuation
bias and work against ?nding a relationship. Therefore, we
2
In 2007, public schools accounted for 81.4 percent of all students,
boarding schools (Danish: “Efterskoler”) account for 3.6 percent, private
schools (Danish: “Friskoler og private grundskoler”) for 12.9 percent and
the remaining two percent are in schools for children with special needs
and other schools (Danish: specialskoler, behandlingshjem, kommunale
ungdomsskoler, etc.).
4
C.T. Kreiner and H.H. Sievertsen / Journal of Health Economics 69 (2020) 102247
Fig. 1. Birth weight and test score distributions for each step of the sample selection. Notes: Based on all children born in Denmark from 1995 to 2007.
Test scores are standardized to have mean zero and unit standard deviation by test year, test subject and grade. The densities are estimated using an
Epanechnikov kernel with the “optimal” bandwidth.
assess the robustness of our results by using an indicator
speci?cation, where we estimate the impact of a low birth
weight, de?ned as a birth weight below 2500 g. Furthermore, we replicate our main ?ndings using the continuous,
self-reported, measure of maternal birth weight in the survey data from the DNBC.
2.3.2. Test scores and child variables
We use all tests from all subjects (Math, Reading,
English, Geography, Biology …
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