Tracking how mortality a¤ects fertility along the
demographic transtition
Luis Angeles
July 20, 2015
Abstract
The importance of reductions in mortality as a driver of fertility
change is not …rmly established among economists as the experience
of European countries over the 19th century seems to contradict it.
This paper shows how a small e¤ect of mortality on fertility is to be
expected during the early stages of the demographic transition - and
does not preclude a major role for mortality later on. The underlying
mechanism makes use of an important empirical regularity uncovered
by demographers but seldom discussed in economics: the absence of
parity-speci…c fertility control prior to the transition in fertility rates.
After discussing the mechanism, I present empirical evidence using
three distinct datasets which strongly supports the existence of a nonhomogenous e¤ect of mortality on fertility.
1
Introduction
A certain degree of confusion exists within economics regarding the role of
reductions in mortality rates as a driver of fertility transitions. On the one
hand, mortality rates have been found to be a statistically signi…cant predictor of fertility rates in panel data analyses covering long time periods.
Angeles (2010) …nds this in a panel of up to 118 countries over the period
Adam Smith Business School (Economics), University of Glasgow. Glasgow G12 8QQ,
UK. Email: [email protected]
1
1960-2005, and the same is true of Herzer et al. (2012), who analyze 20
countries over the whole 20th century, and Murtin (2013), covering 70 countries over the period 1870-2000. In all cases the e¤ect is positive - reductions
in mortality leading to reductions in fertility - and the concept of fertility
being referred to is gross fertility - the total number of births per woman.
On the other hand, non-statistical analyses of the fertility transition in
Europe are often interpreted as evidence against the importance of mortality
as a driver of fertility change. In particular, Oded Galor has pointed out
repeatedly that mortality rates started falling in most European countries
long before any decreasing trend in fertility could be detected (Galor 2005a,
2005b, 2012). Furthermore, a clear break in the time trend of fertility rates
can be observed in most European countries between the 1880s and the
early 1900s - from long-term stagnation to rapidly falling fertility. No such
change can be observed for mortality rates, which are falling more or less
steadily throughout this period. Being the …rst and most heavily studied of
all demographic transitions, the European case cannot possibly be brushed
aside.
This paper argues that the European experience and the outcomes of
panel data analyses should not be seen as contradictory. Far from it, I
believe the two sets of results …t comfortably together once we use the correct
theoretical framework to interpret them. The central message of this paper
is that the e¤ect of mortality rates on fertility is di¤erent at di¤erent stages
of the demographic transition. The absence of an e¤ect during the early
stages of the European transition should not surprise us, as it is exactly in
accordance with the adequate framework.
While I am not the …rst to make this point, the analysis in this paper
improves over previous e¤orts both on the theoretical and on the empirical side. On the theory side, Cervellati and Sunde (2015) and Strulik and
Weisdorf (2014) have explored potential mechanisms able to explain how
the e¤ect of mortality on fertility may change as the demographic transition progresses. While ingenious, neither of these two papers engage with
2
all the empirical evidence collected by demographers on the subject of the
demographic transition - a criticism which, to be fair, applies to the vast
majority of economic papers in this area. The mechanism I put forward corrects this, and has the added bene…t of being far simpler than those already
in existence.
On the empirical side, I present new evidence showing that, as a rule,
reductions in mortality rates have a non-homogenous e¤ect on fertility along
the demographic transition. The e¤ect is small and potentially di¢ cult to
detect in the early stages, turning much larger and unequivocally positive
later on. Cervellati and Sunde (2015) began to build the empirical case
for this pattern by using cross-sectional analysis of long-run changes for 47
countries over the period 1940-2000. Here I provide much wider evidence
using panel data analysis over three di¤erent datasets. The …rst one covers
only European countries and tracks them from as early as the year 1750
up until 1949, when their demographic transition was arguably at a very
advanced stage. The second one uses the dataset of Murtin (2013), which
covers 70 developed and developing countries since 1870, and extends the
time coverage up to the year 2010. The third one, …nally, tracks the vast
majority of countries in the world over the period 1960-2010. In all cases
the results corroborate my theoretical analysis and the insights from the
demographic literature.
Some …nal remarks are in order regarding the e¤ects of mortality reductions on net fertility - the number of children surviving to adulthood per
woman. Angeles (2010) estimates this relationship directly and …nds that
lower mortality rates decrease net fertility after a lag of 10 to 20 years. On
the other hand, the results of Herzer et al. (2012) suggest the opposite.
These authors do not consider net fertility rates directly, but their estimated e¤ect on gross fertility is not large enough to produce decreasing net
fertility when mortality falls.1 Some authors have focused on the ambiguity
surrounding the e¤ect on net fertility to challenge the importance of falling
1
Indeed, ceteris paribus, lower mortality increases net fertility as more children survive
to adulthood. For net fertility to fall, gross fertility needs to fall by a large enough margin.
3
mortality rates, under the argument that "it is the reduction in net fertility
and thus population growth that is most relevant from the viewpoint of the
theory of economic growth" (Galor 2012, p. 7).
In this paper I will also delve into the question of how mortality rates
a¤ect net fertility. While the question is obviously of interest, I do not
subscribe to the view that the e¤ect on net fertility is of larger importance
for economists than the e¤ect on gross fertility. If standard growth models
have a place for net fertility, and not for gross fertility, that is only because
of the simplifying assumptions that the creators of these models have judged
adequate to make. Even if we are only interested in economic growth, it is
not di¢ cult to argue that a society where women give birth to six children,
and four of them die, is quite di¤erent from one where women give birth to
two children and none of them dies - despite them having the same rate of
net fertility. In the …rst case women may be forced to abandon the labour
market, they will be less motivated to accumulate human capital, and less
resources will be available per child - important socioeconomic phenomena
which will not fail to have an impact on growth. Thus, how many children
each woman gives birth to is a question of comparable importance to how
fast the population grows or how many adult children each woman brings
about.
2
The fertility transition and parity-speci…c fertility control
The demographic transition is de…ned as the passage from a regime of high
mortality and high gross fertility to one of low mortality and low gross
fertility. Net fertility is typically low both at the beginning of the process and
towards its end, but tends to be high in the middle as declines in mortality
often predate those in fertility.
The analysis of fertility change has dominated the agenda for the two
social sciences most involved in the study of the demographic transition,
4
demography and economics. The reasons for this are many. First, there is
considerable agreement over the forces that led to mortality decline, with
medical advances, improvements in public sanitation, and general economic
development (leading to gains in nutrition and improved hygiene) all playing a prominent role (Kirk 1996, Guinnane 2011). Second, and of especial
relevance for economists, the forces leading to mortality reductions appear
exogenous to individual control. As the study of individual choice is the
most frequent mode of economic analysis, mortality rates tend to be taken
as given. Finally, mortality rates tend to behave quite predictably over time;
falling steadily rather than experiencing sudden changes.2
None of the above is true when it comes to fertility. The forces leading to
its decline are not well understood and still hotly debated, and it seems clear
that fertility behavior lies squarely within the realm of individual choice.
Furthermore, the most remarkable aspect of time series of gross fertility
is their sudden transition from a long-standing period of high and stable
fertility rates towards a period of rapidly declining ones. The pattern is
present in practically all countries, and researchers in the …eld refer to it as
the fertility transition.3
While all of the above is well-known to economists, considerable less
attention has been paid to an additional empirical regularity uncovered by
demographers and which will be at the heart of the arguments in this paper:
the appearance of parity-speci…c fertility control.
In demography, a woman’s parity is the number of children she has
birthed at a given moment in time. An empirical regularity much-discussed
among demographers has been the absence of any relationship between parity and age-speci…c fertility rates before the onset of the fertility transition
2
The adoption of antibiotics, vaccines and methods of malaria prevention around the
world starting in the 1940s would be the main exception to this, as they brought about
a major decline of mortality rates throughout the developing world (see Acemoglu and
Johnson 2007).
3
To avoid any ambiguity, from this point onwards all uses of the terms ‘pre-transition’
and ‘post-transition’will refer to the fertility transition (not the demographic transition).
5
(that is, during the period of high and stable fertility rates). In a typical
post-transition society, women who have given birth to, say, three children
are far less likely to become pregnant than women of the same age who have
given birth to one child. In other words, the probability of pregnancy falls
with a woman’s parity once age is controlled for (since women at higher
parities tend to be older and natural fertility falls with age). This is not the
case among pre-transition societies, where women with six children are as
likely to become pregnant as women with one child provided they are of the
same age. Thus, the onset of the fertility transition brings about not just
a quantitative change in fertility but also a qualitative one. Women do not
start having less children at all stages of their lives; they tend to keep high
fertility rates at low parities and adopt much lower fertility rates at high
parities.
Table 1 below illustrates the situation by comparing parity-speci…c fertility rates for women aged between 30 and 35 years old in a society that
most likely quali…es as pre-transition (Nigeria in the year 1990) and a society that can be safely described as post-transition (the United States in the
years 1985-1990). As can be seen, Nigerian women have a yearly chance of
giving birth to a child of about 25% in this age bracket, and the probability
is the same at all parities. American women are about as likely to give birth
as Nigerian ones if they have no children or one child, but the probability
falls from 25% to 11-12% once they reach their second child. The natural
interpretation would be that many American women regard two children as
an ideal or target family size, and actively reduce their fertility after their
second childbirth.
[Table 1]
Faced with the above evidence, a popular explanation among demographers has been to claim that pre-transition couples had no target level of
fertility in mind. In their view, fertility control was not a culturally accepted
mode of behavior in these societies, and couples were expected to give birth
to as many children as God or nature was willing to send them. In the
6
words of Francine van de Walle, before the onset of the fertility transition,
“fertility is not within the calculus of conscious choice”(van de Walle 1986,
p. 202).4
While not implausible, this interpretation may well be the reason why
economists never seriously engaged with the evidence on parity-speci…c fertility control. After all, it runs in the face of economics’central organizing
principle: that people’s behavior is determined by conscious and rational
choice. According to demographers, pre-transition societies simply don’t
consider fertility as a choice variable in an optimization problem.
While demographers may be right or wrong in their theoretical interpretation, the empirical evidence regarding the existence or absence of parityspeci…c fertility control should not be ignored. Economics arguably su¤ers
from an excessive richness of theoretical explanations for the demographic
transition, and only additional evidence will help us narrow down the relevant options.
In this spirit, a …rst contribution of this paper will be to argue that
the evidence on the appearance of parity-speci…c fertility control does not
need to come at the expense of rational fertility behavior (in the economists’
sense) among pre-transition societies. I hereby o¤er an alternative explanation: that absence of parity-speci…c fertility control is also compatible with a
setting in which families optimize fertility decisions and have a target family
size, but this target is never reached due to an upper limit in gross fertility
rates and a high mortality environment. In other words, families would not
4
We should note that the empirical evidence sustaining this claim is not without problems. The calculation of partity-speci…c fertility rates requirest data on the parity of each
woman giving birth. Such data is available for recent periods (as in table 1), so we may
con…dently state that today’s post-transition countries feature parity-speci…c fertility control while today’s pre-transition countries do not. On the other hand, it is less certain
that today’s post-transition countries did not present parity-speci…c fertility control before their fertility transition as the data for that period is less rich. Demographers have
argued in favour of this view using data on the age of women giving birth (but not their
parity) - see Coale (1986). This type of analysis has been in‡uential, but can be called
into question (Friedlander et al. 1999).
7
reduce their fertility at high parities because they have not reached (or do
not expect to reach) their target.
To elaborate a bit, recall that in the economists’ standard formulation
of fertility behavior it is the number of children surviving to adulthood (in
other words, net fertility) which enters into the couples’ utility function.
Families target a certain level of net fertility, and gross fertility derives from
this choice and the mortality environment. While it is commonly assumed
that this desired target is reached, such may not be the case in pre-transition
times and that for at least two reasons.
First, the level of gross fertility will be bounded from above not just by
biological constraints, but also by social and cultural factors. The importance of this last element is worth emphasizing as it is not always su¢ ciently
appreciated within economics. In the absence of any inhibiting social or cultural factors, the highest number of births per woman recorded for a population of substantial size is about 12.5 In the vast majority of pre-transition
societies, however, births per woman typically average between one half and
two-thirds of this maximum, and that despite the fact that couples do not
reduce their chances of pregnancy at any parity level. The reason is the
existence of social and cultural factors that reduce gross fertility in di¤erent
ways. In the European case, this was mainly driven by restrictions for entry
into marriage, as fertility rates for unmarried women have always been extremely low. Pre-transition women in Europe married in their mid-twenties
(instead of their mid-teens, as in most parts of Asia), cutting their potential
fertility by more than a third. An alternative method, common for instance
in India, would be to allow early entrance into marriage but to forbid the
remarriage of widows - thus ending the fertile life of many women early. In
addition to this, cultural norms would also limit fertility within marriage, for
instance by prescribing extended periods of breast-feeding or sexual abstinence following a birth. In all these cases fertility rates diminish uniformly
5
The canonical case would be that of the Hutterites, an Anabaptist Christian community used as a standard for high fertility levels in demographic research.
8
across all parities, and women would experience an average of between 6
and 8 births over their reproductive lifetime..
Add to this the second factor, namely that mortality rates in pre-transition
societies could often be as high as 50% between birth and adulthood. As
an example, during the second half of the 18th century only 49% of French
newborns reached aged 15 (Livi-Bacci 1991, p. 74). Even as late as the period 1950-1955, survival rates to age 15 averaged only 63% in Sub-Saharan
Africa (United Nations 2013). Under these conditions, families could expect
an average number of children surviving to adulthood of between 3 and 4
- and considerably less if the objective was for the children not just reaching adulthood but taking care of their parents when old. For early modern
England, Clark and Hamilton (2006) have shown that, on average, only 2.79
children survive the death of their father over the period 1585-1638. The
…gure over-estimates survival rates among the general population, as it is
obtained from a sample of people leaving a will at death - that is, the relatively well-o¤. With such poor prospects of surviving, it seems plausible
that families would …nd it hard to reach their target number of surviving
children - even when this target was a modest 3 or 4 - and rationally decide
to give birth to as many children as they possibly can.
To summarize, absence of parity-speci…c fertility control is compatible
with rational fertility choice as long as the upper bound on gross fertility is
binding. The evidence presented in the last two paragraphs suggests that,
during the pre-transition period, such was probably the case. On the other
hand, the constraint on gross fertility would cease to bind as the demographic
transition advances - both because the target number of children declines
and because mortality rates are falling. Once families are able to reach their
desired family size, parity-speci…c fertility control would appear. Below I
discuss how the relationship between mortality rates and fertility would be
a¤ected by these considerations.
9
3
Mortality and fertility
Mortality has always been regarded as one of the major determinants of gross
fertility rates in demographic research. The idea that in a lower mortality
environment parents would need to give birth to fewer children in order to
reach a target family size was present in demography since the beginning
of its development as an academic discipline, following World War II.6 This
mechanism, known today as the replacement e¤ ect, advances that parents
who su¤er the death of a child take steps to give birth to one additional
child than otherwise planned, as they search to compensate for the lost one.
The mechanism is typically incorporated in most economic models of
fertility choice in a reduced form. In the economists’standard formulation
families decide on the number of children they give birth to at a single
moment in time (instead of sequentially) in order to maximize a utility
function where the number of children surviving to adulthood enters as an
argument. Higher mortality rates would thus require a larger number of
births for any chosen level of net fertility.
Worthy of notice, within this framework the target level of net fertility
may or may not be itself related to mortality rates. In a number of economic
models it is factors such as technological change, income levels or labour
market characteristics which determine the net fertility target, and mortality
rates only play a role in determining the required number of births to reach
this target (see Galor 2012 for an overview of this literature). On the other
hand, economists have also explored models where mortality rates have an
e¤ect on net fertility - for instance because parents "hoard" children in order
to protect themselves against the possibility of high mortality scenarios (Sah
1991, Kalemli-Ozcan 2002), or because lower mortality increases the return
6
See Guinnane (2011, 598-99). For an account of the development of demography and
"Demographic Transition Theory" see Kirk (1996) and Friedlander et al. (1999). Other
factors emphasized by Demographic Transition Theory as drivers of fertility rates are
the educational level of the population (especially females), urbanization rates, economic
development and cultural di¤usion.
10
to investments in children’s education and shift their choices towards more
child "quality" (Becker et al. 1990, Ehrlich and Liu 1991).
While most theoretical analysis in economics have focused on net fertility
choice, it is interesting to note that empirical studies in both economics and
demography typically use measures of gross fertility as their dependent variable. A …rst reason for this is the traditional de…nition of fertility transitions
as the period when gross fertility rates begin to fall, while the larger availability of data on gross fertility provides a second, more practical, rationale.
With gross fertility rates as the dependent variable, the standard replacement e¤ect described above would predict a positive relationship between
mortality and fertility at all times (and regardless of whether net fertility
is also being a¤ected). The absence of a positive e¤ect during much of the
19th century in Europe may then be regarded as a rejection of the theory.
This rationale, however, ceases to apply as soon as we consider couples
not reaching their target net fertility due to an upper limit on gross fertility
rates. In this case, couples do not change their fertility behavior following
the death of a child as this behavior is constant throughout their fertile
lifetime: couples plan, from the beginning, to have as many children as
possible (having arguably internalized the fact that many of these children
will not reach adulthood). In a nutshell, there is no replacement e¤ect.
But this is not the end of the story. While the absence of a replacement
e¤ect clearly weakens the link between mortality rates and gross fertility,
it does not eliminate it altogether. An additional channel for mortality to
a¤ect fertility will still remain in place when couples are having as many
births as they possibly can. This is because of the existence of what is
known as the physiological e¤ ect.
As demographers and other social scientists have long discussed, the
period following the birth of an infant is characterized by a very reduced
pregnancy risk due to the universal practice of breast-feeding and the resulting lactational amenorrhea. For as long as a mother breast-feeds her
11
child, the pregnancy risk remains low.7 This, however, introduces a positive
link between infant mortality and fertility as the death of a lactating infant
cuts short this low pregnancy-risk environment. As we have described them,
couples for whom the upper limit on gross fertility is binding will have as
many pregnancies as possible during the time period when such an event is
possible. The death of an infant increases the length of this time period.
The existence of the physiological e¤ect implies that mortality rates
would have a positive e¤ect on fertility even during the early stages of the
demographic transition. The e¤ect, however, would turn larger once the
upper bound on gross fertility is no longer binding and the replacement effect kicks in. In short, incorporating the evidence on parity-speci…c fertility
control into our analysis points towards a non-homogeneous e¤ect of mortality on gross fertility as the demographic transition advances. The e¤ect
would be small and positive during the early stages, when the upper limit
on gross fertility is binding, and large and positive later on. This rejects the
common assumption of a constant-size e¤ect of mortality on fertility that
characterizes linear regression models, and explains why the e¤ect may be
di¢ cult to capture in 19th century Europe.
The analysis so far has not discussed when along the demographic transition will the upper bound on gross fertility cease to bind. Being largely
determined by social and cultural norms, this upper bound takes di¤erent
values for di¤erent societies. Under such conditions, and following the usual
practice in demography, I assume the society-speci…c upper bound on gross
fertility equals the (relatively constant) gross fertility rate observed before
the fertility transition.8 It follows that the onset of the fertility transition
separates the period when the upper bound on gross fertility is binding from
the period when it is not, which in turn determines the empirical strategy
7
Besides the purely hormonal changes induced by breastfeeding, mothers will often
sleep with their babies and must care for them - thus reducing the chances of sexual
intercourse.
8
Assuming otherwise implies that fertility could have been higher in pre-transition
times, but couples chose not to have more children. I regard this as unlikely not so much
because pre-transition fertility is very high, but because it is very stable.
12
for testing the above hypotheses.
Finally, let us turn our attention to the e¤ect of mortality rates on net
fertility. When couples have as many births as possible this relationship
would certainly be negative, as a woman who loses its n-th born child would
need to invest twice the amount of time from her fertile years in order to
pass from n-1 to n surviving children.9 As women fully use all their available
fertile years, the total number of surviving children would diminish. Once
the fertility transition gets underway, however, women have some slack fertile
capacity which may be tapped into in the case of a child’s death. The e¤ect
of mortality on net fertility would then become at least less negative - and
potentially zero if enough slack capacity is available so that the replacement
e¤ect is complete. The e¤ect may even become positive if some additional
mechanism is in place, such as hoarding or the quantity-quality tradeo¤,
which would make net fertility directly a function of mortality rates.
The empirical section of this paper takes the preceding analysis to test
and looks for a change in the relationship between mortality and fertility
following the onset of the fertility transition. While the e¤ect on gross
fertility should remain positive and clearly increase in magnitude, the e¤ect
on net fertility would be expected to pass from negative to nil - or perhaps
even to positive. My preferred interpretation for such …ndings would be the
existence of an upper limit on gross fertility which is binding before the onset
of the fertility transition, but I note that the demographers’ hypothesis of
fertility decisions not being subject to individual rational choice in the pretransition period would be observationally equivalent with the data at hand.
Accordingly, my aim is not to establish which of these two explanations
is correct but rather to demonstrate the existence of a non-homogenous
e¤ect of mortality on fertility. It follows from that result that a small e¤ect
of mortality on fertility in the early stages of the demographic transition
is perfectly compatible with the claim that mortality reductions play an
9
To be more precise, the woman would need to invest twice the amount of time if the
child dies once brestfeeding is completed. If the child dies earlier, the amount of time
would increase but would not double, because of the physiological e¤ect discussed above.
13
important role as drivers of fertility decline once the fertility transition gets
underway.
4
Empirical analysis
I test the existence of a non-homogeneous e¤ect of mortality on fertility using
three separate panel datasets: 22 European countries over the period 17501949, 70 developed and developing countries over the period 1870-2010, and
as many as 187 developed and developing countries over the period 19602010. Sources and summary statistics are provided in the sections below.
The econometric speci…cation I use with all three datasets is as follows:
fi;t =
i
+ mi;t
1
+ Xi;t
1
+ "i;t
(1)
In equation (1) fi;t is a measure of gross fertility for country i during
period t, mi;t
1
is a corresponding measure of mortality and Xi;t
1
a set of
additional determinants of fertility. The equation includes country-speci…c
…xed e¤ects ( i ) in order to control for di¤erences in overall levels of fertility,
as the social and cultural aspects limiting fertility in pre-transition times
di¤er from country to country. Finally, a full set of time dummies is added
to equation (1) as a robustness check in all subsequent analyses. Time
dummies may capture unmeasurable aspects such as changes in cultural
norms, thus reducing the scope for omitted variable bias.
All determinants of fertility in equation (1) are used with a lag, with
the purpose of reducing endogeneity problems. The most visible source
of endogeneity bias would be reverse causality, for instance because high
levels of fertility may increase mortality as less resources are available per
child. Reverse causality is much less of a problem in equation (1) since
high fertility cannot a¤ect mortality rates (or other determinants of fertility)
retroactively. On the other hand, the possible existence of serially correlated
omitted factors still leaves scope for an endogeneity bias in (1), and the
results that follow ought to be interpreted with this in mind.
14
In order to capture the non-homogeneous e¤ect of mortality on fertility,
equation (1) is estimated, …rst, for all country-year observations taking place
before the onset of the fertility transition and, second, for all country-year
observations taking place afterwards. This approach allows not just for
coe¢ cient
to change freely between the two regimes; the e¤ect of all
other determinants of fertility is also allowed to change. As discussed below,
results clearly vindicate this procedure.
4.1
European countries, 1750-1949
As much of the suspicion regarding the importance of mortality as a determinant of fertility decline comes from observing the European case, it seems
adequate to start with it. Since many previous analyses have only covered a
handful of countries, the analysis here adds signi…cant value by considering
22 European countries - essentially all independent political entities in 19th
century Europe other than Turkey. My data comes from the International
Historical Statistics (Palgrave Macmillan Ltd. 2013), and tracks mortality,
fertility and marriage rates as far back as the year 1750 (though in most cases
since the middle decades of the 19th century). The data o¤ers a coverage
starting usually several decades before the onset of each country’s fertility
transition and is, to the best of my knowledge, the most comprehensive
source using common measures of fertility and mortality for all European
countries. The data is available annually, and I use 5-year averages in what
follows.
With the data at hand, the …rst important part of the analysis is the
determination of the onset of the fertility transition, which occurs at di¤erent times for di¤erent countries. For this dataset and the next one, which
track most countries from well before the onset of their fertility transition, I
follow the classical analysis of Coale and Treadway (1986). This approach,
standard among demographers, de…nes the onset of the fertility transition
as the …rst year in which the chosen measure of fertility falls to a level 10%
below its long-run average before that time, provided it does not rise above
15
that average again. The pre-transition long-run average of fertility is allowed
to di¤er from country to country. Coale and Treadway (1986, p.38) give the
results of this procedure when applied to 19 European countries, all of which
are on my European dataset. I take these dates as they are, and derive the
dates for the remaining three countries using the same approach.10
Table 2 below shows summary statistics for the three variables at our
disposal: the crude birth rate, the crude death rate and the marriage rate
(de…ned as the number of births, deaths and marriages per 1,000 population). The table also reports the time trends for mortality and fertility, both
before and after the onset of the fertility transition, controlling for country
…xed e¤ects. This calculation con…rms the initial impression, mentioned
in the introduction, of a disconnect between the time series of fertility and
mortality along the European demographic transition. While both series experience an increase in their average change per period as the demographic
transition advances, the change in fertility is far more radical. Notice, however, that fertility is on average declining, albeit at a very slow rate, even
before its transition.
[Table 2]
Table 3 presents the results when equation (1) is estimated separately
for pre- and post-transition observations using the crude birth rate as a
gross fertility measure, the crude death rate as a mortality measure, and
the marriage rate as an additional determinant of fertility. Crude rates have
the disadvantage of being a¤ected by the age structure of the population,
an aspect for which we cannot control in the present case but which will be
addressed with our second dataset. Marriage rates are an important determinant of fertility throughout this period as childbearing outside marriage
was highly unusual.
10
The three additional countries are Bulgaria, Romania and Serbia. It should be noted
that the transition years from Coale and Treadway (1986) are calculated using marital
fertility rates, while those I derive here use the crude birth rate. These two measures
of fertility tend to give very similar transition dates, judging by the cases in which both
series are available.
16
[Table 3]
Columns 1 and 2 report the results when no time dummies are included in
the regressions, while columns 3 and 4 report the results with time dummies.
Both sets of results lead to similar conclusions, with some minor di¤erences
that I note below. First, and most important, the e¤ect of mortality on
fertility is indeed clearly heterogeneous: coe¢ cient
experiences a large
jump in its value between the pre- and post-transition periods. The posttransition estimate of
is well above 1 without time dummies and 0:9 when
time dummies are included, while its pre-transition value is between 0:16
and 0:23. Worthy of notice, the e¤ect of mortality on gross fertility is still
positive during pre-transition times, reaching statistical signi…cance at the
1% level in column 1 and at the 10% level in column 3. Our discussion in the
previous section is thus corroborated not only by the increase in
following
the transition but also by the existence of a small positive e¤ect even before
the transition.
Marriage rates have, as expected, a positive and statistically signi…cant
e¤ect on fertility in all regressions (marginally so in column 4). Of more
interest, the size of the coe¢ cient falls by more than half between the preand post-transition periods. This arguably re‡ects a looser association between marriage life and childbearing following the fertility transition. Indeed, post-transition couples were characterized precisely by limiting their
fertility within marriage, while the occurrence of childbirth out of wedlock
progressively became more common.
A third and …nal observation concerns net fertility. The di¤erence between crude birth rates and crude death rates, the rate of population growth,
is the best approximation we have here to net fertility rates. The e¤ect of
mortality on this measure can therefore be easily gauged by subtracting one
from the coe¢ cients on mortality reported in table 3. It follows that a
coe¢ cient above 1 would denote a positive e¤ect of mortality on net fertility, while a coe¢ cient below 1 would denote a negative e¤ect. From this
we deduce that the e¤ect of mortality on net fertility is de…nitively nega17
tive in the pre-transition period, as was indeed expected from the previous
section. For the post-transition period, on the other hand, the outcome is
less clear. The results in column 2 suggest a positive e¤ect on net fertility,
but the inclusion of time dummies in column 4 render this uncertain. While
the con…dence interval for
in column 4 does include values higher than 1,
the point estimate of 0.9 suggest that the e¤ect is more likely to be slightly
negative.
In de…nitive, all of the above results are in accordance with our discussion from the previous section. The usual assumption of a constant-size
e¤ect of mortality on fertility all along the demographic transition is soundly
rejected, as the existence of an heterogeneous e¤ect in European countries
is given solid support.
4.2
Developed and developing countries, 1870-2010
Our second dataset was put together by Murtin (2013) from a variety of
sources, and o¤ers observations of crude birth rates, crude death rates, and
additional determinants of fertility every 10 years from 1870 until the year
2000. This dataset includes 72 countries, 49 of which are from outside
Europe and its o¤shoots. I extend the time coverage of the original dataset
by one period by incorporating crude birth rates for 2010 from the World
Bank (other variables are not required for 2010 as they enter the equation
with a lag)11 .
I determine the onset of fertility transitions using the procedure of Coale
and Treadway (1986) as described above, unless the country in question is
one of the 19 European countries for which these authors originally calculated the transition date - in which case I use their date. Two special cases
11
In addition to this, I extend the time coverage for the United States. Murtin’s dataset
only covers this country over the period 1950-2000 for the crude death rate and 1960-2000
for the crude birth rate. Instead, I use data from the International Historical Statistics to
cover the period 1900-2000 for crude death rates and 1910-2000 for crude birth rates, plus
data from the World Bank for the year 2010. The data for 1900-1990 refers to the white
population, while the observations for the years 2000 and 2010 are for the whole American
population. The data for the white population reported in the IHS is practically identical
to the one used by Murtin over the years 1950-2000.
18
are France and the United States, as the onset of their fertility transitions
is placed by the literature well before the year 187012 . I place all available
observations from these two countries in the post-transition group. Furthermore, because some developing countries are characterized by very high
values of the crude birth rate which may su¤er changes of 10% or more following events such as wars or famines, I have also added the condition that
the onset of the fertility transition should be characterized by a crude birth
rate below the level of 36 per 1,000 inhabitants. To put this in perspective,
the average crude birth rate at the onset of the fertility transition for the 21
OECD countries for which we can provide this data is 29.69, and the highest
value among them is 35.7.
Table 4 shows summary statistics of the variables at our disposal in this
second dataset. As in the …rst one, the available measures of fertility and
mortality are the crude birth and death rates, with rather similar average
values as previously but somewhat larger variability around the mean - a
normal occurrence given the more heterogeneous set of countries we now
consider. As additional determinants of fertility we have the level of GDP
per capita and female education, measured as the average number of years
of schooling among the female population aged 15 and over. In addition to
them, we can also include two controls for the age structure of the population: the share of the population aged 20-29 and that of the population aged
30-39. As these two age intervals cover most child-bearing years, these controls largely correct for the e¤ect of the population age structure on crude
birth rates.
[Table 4]
As in the previous section, the last two rows of table 3 report the time
trends of fertility and mortality before and after the fertility transition, controlling for country …xed e¤ects. While the pattern of fertility is as expected,
with a large acceleration following the transition, we now see that mortality
12
In 1827 for France according to Coale and Treadway (1986), in 1848 for the United
States according to Bailey (2009).
19
reductions are far slower following the fertility transition among this group
of countries. The explanation is that fertility transitions in most developing
countries took place much later than in Europe - with few exceptions during
the second half of the 20th century and quite often during the last two or
three decades. By this time the important reductions in mortality due to
the adoption of vaccines and antibiotics had been largely achieved, leaving
less scope for further reductions in the post-transition period. As it turns
out, methods for reducing mortality travelled from Europe to developing
countries much faster than the practice of limiting fertility.
Table 5 presents the results of our empirical analysis when applied to
this second dataset. Equation (1) is run controlling only for the age structure of the population in columns 1 and 2, while subsequent columns show
regressions where GDP per capita, female education and a full set of time
dummies are added progressively. In all cases the di¤erence between the preand post-transition estimates of coe¢ cient
added
is large - when all controls are
takes a value of 0:3 in pre-transition years and 0:8 in post-transition
ones. These values are quite in line with those reported previously in table
3.13
[Table 5]
As was the case above, the estimates imply that the e¤ect of mortality
on gross fertility in pre-transition times was not zero but slightly positive
- albeit the e¤ect is statistically signi…cant only at the 10% level when all
controls are included. In the post-transition phase, on the other hand, the
positive e¤ect of mortality on gross fertility is always statistically signi…cant
at the 1% level.
Turning to the e¤ect of mortality on net fertility, this was certainly negative in the pre-transition phase as none of the relevant con…dence intervals
ever comes close to the value of 1. For the post-transition case, however,
13
I note that none of these regressions contain all 72 countries available. This is the
case because: (a) some countries are not observed over the pre-transition period, and (b)
some countries have not reached the post-transition period by the year 2010.
20
three of the four con…dence intervals we estimate include the value of 1 - at
which point the e¤ect on net fertility would be exactly zero. Thus, while
the post-transition e¤ect on net fertility was probably still negative, a nil or
even slightly positive e¤ect would be possible.
With regards to our control variables, it is interesting to note that the
e¤ect of GDP per capita on fertility looks quite unstable over our di¤erent
speci…cations. When all controls are included, in columns 7 and 8, the
coe¢ cient on GDP per capita is not statistically signi…cant in pre- or posttransition times. Female education, on the other hand, appears to have a
more consistent negative e¤ect on fertility. Its coe¢ cient is negative and
statistically signi…cant at the 1% level in columns 5 to 7, but not so in
column 8 (post-transition times controlling for time dummies).
I conclude by noting that, although the number of countries has more
than tripled with respect to the previous analysis and they now come from
every corner of the globe, the coe¢ cients on mortality do not change dramatically. As for the case of Europe, the change in the e¤ect of mortality on
fertility following the transition appears large and in accordance with our
priors.
4.3
Developed and developing countries, 1960-2010
The third and …nal dataset I consider comes from the World Bank’s World
Development Indicators (all variables except female education) and from
the Barro-Lee Educational Attainment Dataset (for female education). This
dataset brings two important bene…ts. First, it o¤ers an almost comprehensive coverage of developing countries, with a total of 187 countries for which
data is available. Second, it uses Total Fertility Rates as the measure of
gross fertility and Child Mortality Rates as the measure of mortality - both
superior choices to the crude birth and death rates considered previously.14
14
In particular, the Total Fertility Rate is not a¤ected by the age structure of the
population as it corresponds to the number of births that a woman would experience over
her lifetime if subjected to all current age-speci…c fertility rates. As a shorthand, we may
refer to it as the number of births per woman. The Child Mortality Rate is the number
21
On the other hand, the time coverage is reduced to a maximum of eleven
quinquennial observations between the years 1960 and 2010. The main disadvantage of this reduced time span is that for many countries the onset of
the fertility transition would lie before the start of the sample.
This last feature of the data implies that the Coale and Treadway (1986)
methodology cannot be used, as the pre-transition level of fertility is not
observed in several cases. Instead, I simply set a threshold level of the Total
Fertility Rate and classify all country-year observations with values below
that threshold as post-transition. I set this threshold at 5.5 births per woman
in my baseline calculations, but I consider both higher and lower values in
order to check the robustness of my results.
Table 6 presents summary statistics for the variables in this dataset.
As in the previous case, two important determinants of fertility which we
control for are the GDP per capita of the country and the average years
of schooling among the female population aged 15 and over. To this we
add the urbanization rate, a factor often emphasized in the demographic
literature as indicative of cultural norms. Indeed, migration to the city is
often accompanied by a change in modes of behavior, whereby traditional
beliefs may be abandoned in favour of more "modern" ones. Finally, the
World Bank also provides us with two alternative measures of mortality,
the infant mortality rate and life expectancy at birth. Both will be used
as extensions to our baseline results so their summary statistics are also
reported.
[Table 6]
The bottom of table 6 reports the time trends of mortality and fertility
before and after the onset of the fertility transition. The pattern is quite
similar to that uncovered in table 4. The decrease in fertility rates posttransition is, on average, about 0.5 births per decade, a …gure which would
of deaths between ages 0 and 5 normalized by the number of live births.
22
be much larger if we were to exclude the countries that experienced their
fertility transition long ago.
The econometric results using this dataset are reported in table 7 and
continue to be favorable to the central hypothesis of the paper. In all cases,
the post-transition e¤ect of mortality on gross fertility is positive, statistically signi…cant at the 1% level, and far larger in magnitude than in the
pre-transition period. The estimate of
appears to stabilize around a value
of 15.5 in columns 6 and 8, implying that a decrease in child mortality
of 10 percentage points would lead to 1.55 less births per woman in the
post-transition period - a large and meaningful e¤ect. The pre-transition
e¤ect, on the other hand, is much smaller and eventually disappears when
all control variables and time dummies are accounted for.
[Table 7]
Turning to the set of control variables, the e¤ect of female education
appears to be robust and negative both before and after the onset of the
fertility transition - which accords well with the results of table 5. The rate of
urbanization has also the negative coe¢ cient we would have expected, but
the e¤ect appears to characterize only post-transition periods. GDP per
capita, …nally, has once again a rather unstable relationship with fertility although the results of columns 6 and 8, when most controls are included,
do suggest a positive e¤ect post-transition.
The e¤ect on net fertility cannot be immediately deduced from these
regressions since, contrary to what was the case when crude birth and death
rates were used, net fertility is no longer the di¤erence between these two
rates. Instead, let net fertility be de…ned as n = g(1
m15 ) where g is
gross fertility (the number of births per woman), m15 is the number of
deaths between birth and age 15 per live birth (age 15 being our de…nition
of adulthood), and n is net fertility, thus de…ned as the number of adult
children each woman brings about. This de…nition of net fertility is roughly
proportional to the Net Reproduction Rate, a standard demographic mea23
sure which calculates the number of daughters reaching their reproductive
age per woman15 .
The derivative of net fertility with respect to m15 is given by
@g
@m15 (1
=
m15 ) g. Since our regressions have made use of mortality rates up
to the age of 5, this last expression may be rewritten as
m15 )
@n
@m15
@n
@m15
=
g , where m5 is nothing but the child mortality rate
responds to coe¢ cient
@g @m5
@m5 @m15 (1
@g
and @m
cor5
as estimated above. Using data from the United
Nations, I am then able to calculate the derivative
@n
@m15
for di¤erent groups
of nations over time under the assumption of a constant value for the derivative
@g
@m5 :
By using the value
@g
@m5
= 15:5 I approximate the e¤ect of mortality
on net fertility among post-transition countries.
The results are given in table 8 and suggest that, on average, the e¤ect
of mortality on net fertility has been positive throughout the world over the
last …ve decades in post-transition countries. This resonates well with the
…ndings of Angeles (2010), who provides direct statistical evidence of a positive e¤ect on net fertility using Net Reproduction Rates as the dependent
variable - albeit without distinguishing between pre- and post-transition observations. Together, these two sets of results support the idea that mechanisms other than pure replacement e¤ects are in place, leading couples to
reduced their desired target family size when mortality rates diminish.
[Table 8]
Tables 9 and 10 o¤er some robustness checks on the above results. First,
in table 9, I experiment with di¤erent values of the threshold level of gross
fertility separating pre- from post-transition periods. I set this level equal
to 4.5, 5, 5.5 (the baseline value) and 6 children per woman. All regressions
include the most comprehensive set of controls: GDP per capita, the urbanization rate, female education and time dummies, but their coe¢ cients
are not reported for conciseness. Results are very consistent: in all cases
15
Net Reproduction Rates are not reported in the World Development Indicators, which
is why a direct estimation of the e¤ect on net fertility is not possible.
24
the coe¢ cient on mortality is close to zero and not statistically signi…cant
for pre-transition times, becoming large, positive and statistically signi…cant
for the post-transition period. The size of the post-transition coe¢ cient is
very stable, around 15.5 for threshold values between 4.5 and 5.5, and only
somewhat smaller when the threshold value is raised to 6. This last result
is unsurprising as such a high number of children per woman is probably
allowing some pre-transition observations into our post-transition group.
Table 10 experiments with the other two mortality measures at our disposal, the infant mortality rate and life expectancy at birth. The threshold
value of gross fertility is set again at 5.5, and all available controls are used
but not reported. The results for the infant mortality rate mirror those obtained for child mortality rates, which is unsurprising as the two variables
are highly correlated. For life expectancy we obtain the same qualitative
result, with the pre-transition coe¢ cient being not statistically signi…cant
while the post-transition one is statistically signi…cant at the 1% level (the
sign of the coe¢ cients is negative, as life expectancy is an inverse function
of mortality rates). There are, however, some quantitative di¤erences. The
pre-transition coe¢ cient of life expectancy, while not signi…cant, is fully one
third the size of the post-transition coe¢ cient. Furthermore, for other values of the threshold level of fertility a statistically signi…cant coe¢ cient may
be obtained for the pre-transition case (not reported in the table). The result makes sense as life expectancy incorporates adult mortality rates, and
lower adult mortality may well have a separate impact on fertility decisions
- for instance by shifting female preferences away from early marriage and
child rearing and towards longer education and participation in the labour
market.
5
Concluding remarks
The evidence presented in this paper should leave no doubts as to the importance of mortality decline as a major driving force behind demographic
transitions. As a rule, changes in mortality are only weakly associated with
25
gross fertility in the early phase of the process, but this should not surprise
us given that families are most likely unable to reach their desired number of
surviving children. Once they do so, thanks in large part to lower mortality
rates, further decreases in mortality tend to be matched by lower fertility
rates; and the e¤ect is both statistically signi…cant and large in magnitude.
What is more, lowering mortality rates is quite possibly the single largest
cause of declining gross fertility rates.
To substantiate this last point, I use the third dataset considered above
and perform the following calculation. First, for all countries with the required data, I compute the change in the Total Fertility Rate and the change
in the Child Mortality Rate between each country’s …rst post-transition period and 2010 (for countries with a fertility transition before 1960 I compute
the di¤erence between the 1960 and 2010 values). I obtain results for 122
countries. For each of these, I compute the percentage of the change in gross
fertility that would be accounted by the change in child mortality using a
coe¢ cient of 15:5, following the last column of table 7. I discard 9 countries
for which the predicted change in fertility is larger than the actual change,
and then take the average of all remaining countries. I …nd that, as an average, 40.5% of the change in the total fertility rate experienced since the
onset of the transition (or since 1960) can be explained by changes in child
mortality rates. Given that no more than 79% of the within-country variation in total fertility rates among all post-transition observations is ever
explained in the regressions of table 7, no single factor is likely to be of more
consequence than mortality change as a driver of gross fertility.
26
References
Acemoglu, D. and Johnson, S. (2007), Disease and Development: The
E¤ect of Life Expectancy on Economic Growth, Journal of Political Economy 115, 925-985.
Angeles, L. (2010), Demographic transitions: analyzing the e¤ects of
mortality on fertility, Journal of Population Economics 23, 99-120.
Bailey, A. K. (2009), How personal is the political? Democratic revolution and fertility decline, Journal of Family History 34, 407-425.
Becker, G. S., Murphy, K. M. and Tamura, R. (1990), Human capital,
fertility, and economic growth, Journal of Political Economy 98, S12-S37.
Cervellati, M. and Sunde, U. (2015), The e¤ect of life expectancy on
education and population dynamics, Empirical Economics 48, 1445-1478.
Clark, G. and Hamilton, G. (2006), Survival of the richest: The Malthusian method in England, 1585-1638, Journal of Economic History 66, 707736.
Coale, A. J. (1986), The decline of fertility in Europe since the eighteenth
century as a chapter in demographic history, in: Coale, A. J. and Watkins, S.
C. (eds.), The decline of fertility in Europe. Princeton: Princeton University
Press, 1-30.
Coale, A. J. and Treadway, R. (1986), A summary of the changing distribution of overall fertility, marital fertility, and the proportion married in the
provinces of Europe, in: Coale, A. J. and Watkins, S. C. (eds.), The decline
of fertility in Europe. Princeton: Princeton University Press, 31-181.
Ehrlich, I. and Lui, F. T. (1991), Intergenerational trade, longevity, and
economic growth, Journal of Political Economy 99, 1029-1059.
Friedlander, D., Okun, B. S. and Segal, S. (1999), The demographic
transition then and now: processes, perspectives, and analyses, Journal of
Family History 24, 493-533.
Galor, O. (2005a), From stagnation to growth: uni…ed growth theory.
In: Aghion, P. And Durlauf, S. N. (eds.), Handbook of Economic Growth,
vol. 1A. Elsevier, Amsterdam.
Galor, O. (2005b), The demographic transition and the emergence of
27
sustained economic growth, Journal of the European Economic Association
3, 494-504.
Galor, O. (2012), The demographic transition: causes and consequences,
Cliometrica 6, 1-28.
Guinnane, T. W. (2011), The historical fertility transition: a guide for
economists, Journal of Economic Literature 49, 589-614.
Herzer, D., Strulik, H. and Vollmer, S. (2012), The long-run determinants of fertility: one century of demographic change 1900-1999, Journal of
Economic Growth 17, 357-385.
Kalemli-Ozcan, S. (2002), Does the mortality decline promote economic
growth?, Journal of Economic Growth 7, 411-439.
Kirk, D. (1996), Demographic transition theory, Population Studies 50,
361-387.
Livi-Bacci, M. (1991), Population and nutrition : An essay on European
demographic history, Cambridge: Cambridge University Press.
Murtin, F. (2013), Long-term determinants of the demographic transition, 1870-2000, Review of Economics and Statistics 95, 617-631.
Palgrave Macmillan Ltd. (ed.), 2013, International Historical Statistics,
Basingstoke: Palgrave Macmillan.
Sah, R. K. (1991), The e¤ects of child mortality changes on fertility
choice and parental welfare, Journal of Political Economy 99, 582-606.
Strulik, H. and Weisdorf, J. (2014), How child costs and survival shaped
the industrial revolution and the demographic transition, Macroeconomic
Dynamics 18, 114-144.
United Nations (2013), World Population Prospects: The 2012 Revision.
Available online at: http://esa.un.org/unpd/wpp/Excel-Data/mortality.htm
van de Walle, F. (1986), Infant mortaity and the European demorgaphic
transition, in: Coale, A. J. and Watkins, S. C. (eds.), The decline of fertility
in Europe. Princeton: Princeton University Press, 201-233.
Wachter, K. W. (2006), Essential Demographic Methods, mimeo, University of California, Berkeley.
28
Table 1
Parity-Specific Fertility Rates: Nigeria and the United States in 1990
Parity
0
1
2
3
4
5
6+
Nigeria
0.272
0.225
0.257
0.244
0.279
0.284
0.233
United States
0.276
0.246
0.116
0.110
0.124
0.148
Notes: each cell contains the fertility rate, defined as the total number of births divided by the number of
women, as a function of a woman’s parity. The subjects are women aged between 30 and 35 in both Nigeria
and the United States. Data for the United States refers to white women only, and the observation for parity 5
corresponds to women with parity 5 and above.
Source: Wachter (2006, p. 280).
Table 2
Summary statistics, European countries 1750-1949
Crude Birth Rate
Mean
30.17
Std. Dev.
7.79
Min
11.36
Max
50.92
Observations
479
Crude Death Rate
21.08
6.50
8.66
44.54
478
Marriage Rate
15.60
2.65
7.68
25.67
466
Time trends (change per 5-year period, controlling for country fixed effects):
Before the fertility
transition
After the fertility
transition
Crude Birth Rate
-0.177***
-1.053***
Crude Death Rate
-0.362***
-0.665***
Table 3
Empirical analysis, European countries 1750-1949
Dependent variable: Crude Birth Rate
Pre-transition
Post-transition
Pre-Transition
Post-Transition
0.235***
[0.094 – 0.376]
0.575***
[0.128]
1.448***
[1.253 – 1.641]
0.250***
[0.0871]
0.158*
[-0.020 – 0.335]
0.621***
[0.101]
0.904***
[0.521 – 1.287]
0.242*
[0.137]
no
no
yes
yes
247
22
0.315
193
20
0.768
247
22
0.600
193
20
0.867
One-period lag of:
Crude Death Rate
Marriage Rate
Time dummies
Observations
Countries
R2
Notes: Robust standard errors in square brackets, except for the Crude Death Rate where the 95% confidence
interval using robust standard errors is given. The symbols ***, ** and * denote statistical significance at the
1%, 5% and 10% levels.
Table 4
Summary statistics, 70 Developed and Developing countries, 1870-2010
Crude Birth Rate
Mean
29.78
Std. Dev.
12.22
Min
8.3
Max
59.20
Observations
717
Crude Death Rate
14.65
7.22
3.56
37.80
751
GDP per capita (in logs)
8.51
0.92
6.62
10.87
806
Years of schooling among
the female population
3.77
3.38
0.04
13.37
1080
Share of pop. aged 20-29
0.173
0.018
0.103
0.224
1004
Share of pop. aged 30-39
0.134
0.017
0.083
0.205
1004
Time trends (change per 10-year period, controlling for country fixed effects):
Before the fertility
transition
After the fertility
transition
Crude Birth Rate
-0.407***
-1.832***
Crude Death Rate
-2.340***
-0.752***
Table 5
Empirical analysis, 72 Developed and Developing countries, 1870-2010
Dependent variable: Crude Birth Rate
Pre-transition
Post-transition
Pre-Transition
Post-Transition
Pre-transition
Post-transition
Pre-Transition
Post-Transition
One period lag of:
Crude Death Rate
0.276**
1.262***
0.449***
0.919***
0.376**
0.798***
0.316*
0.797***
[0.03 – 0.52]
[1.10 – 1.42]
[0.16 – 0.73]
[0.75 – 1.09]
[0.07 – 0.68]
[0.62 – 0.98]
[-0.02 – 0.65]
[0.59 – 1.00]
3.338*
[1.881]
-3.895***
[0.663]
4.589**
[1.738]
-1.638***
[0.540]
-0.750
[0.979]
-1.411***
[0.338]
2.086
[1.776]
-2.394***
[0.576]
0.874
[1.328]
-0.242
[0.307]
GDP per capita
Female education
Controls for pop.
age structure
yes
yes
yes
yes
yes
yes
yes
yes
Time dummies
no
no
no
no
no
no
yes
Yes
Observations
Countries
R2
259
336
237
335
237
335
237
335
67
57
65
57
65
57
65
57
0.155
0.734
0.286
0.786
0.340
0.809
0.491
0.859
Notes: Robust standard errors in square brackets, except for the Crude Death Rate where the 95% confidence interval using robust standard errors is given. The symbols
***, ** and * denote statistical significance at the 1%, 5% and 10% levels.
Table 6
Summary statistics, 187 Developed and Developing countries, 1960-2010
Mean
4.21
Std. Dev.
2.04
Min
0.85
Max
9.19
Observations
2131
0.0878
0.0847
0.0024
0.4979
1848
GDP per capita (in logs)
7.93
1.62
3.91
11.75
1664
Urbanisation rate (%)
48.75
25.63
2.08
100
2320
Years of schooling among
the female population
5.45
3.31
0.01
13.23
1584
Infant Mortality Rate
(under-1 deaths per birth)
0.0577
0.0486
0.0019
0.2502
1834
Life Expectancy at Birth
62.79
11.68
23.73
83.16
2141
Total Fertility Rate
Child Mortality Rate
(under-5 deaths per birth)
Time trends (change per 5-year period, controlling for country fixed effects):
Before the
fertility transition
After the fertility
transition
Total Fertility Rate
-0.089***
-0.227***
Child Mortality Rate (%)
-1.954***
-0.576***
Table 7
Empirical analysis, 187 Developed and Developing countries, 1960-2010
Dependent variable: Total Fertility Rate
Pre-transition
Post-transition
Pre-Transition
Post-Transition
Pre-transition
Post-transition
Pre-Transition
Post-Transition
23.79***
[0.759]
3.070***
[0.960]
19.83***
[0.840]
1.787*
[0.909]
15.59***
[0.874]
-0.278
[1.251]
15.54***
[0.860]
0.236***
[0.0819]
-0.253***
[0.0485]
0.184**
[0.0815]
-0.0241***
[0.00670]
-0.0533
[0.0510]
-0.0339***
[0.00369]
0.0465
[0.0882]
-0.000472
[0.00675]
-0.420***
[0.0483]
0.259***
[0.0577]
-0.0200***
[0.00375]
-0.201***
[0.0175]
-0.141
[0.104]
0.00761
[0.00750]
-0.286***
[0.0658]
0.370***
[0.0619]
-0.0197***
[0.00363]
-0.155***
[0.0264]
no
no
no
no
no
no
yes
Yes
One period lag of:
Child Mortality Rate
GDP per capita
5.910***
[0.559]
Urban rate
Female education
Time dummies
Observations
Countries
R2
367
947
367
947
297
807
297
807
82
169
82
169
67
132
67
132
0.284
0.693
0.315
0.723
0.530
0.773
0.569
0.791
Notes: Robust standard errors in square brackets. The symbols ***, ** and * denote statistical significance at the 1%, 5% and 10% levels.
The Child Mortality Rate is expressed as number of deaths before the age of 5 per child born alive (not per 1,000 children), GDP per capita is in logs, Female education is
the average number of years of schooling among the female population aged 15 and over.
Table 8
Estimated derivate of net fertility with respect to mortality, groups of countries
Developed countries
Developing countries
Sub-Saharan Africa
Asia
Latin America
1950-55
9.87
3.09
1955-60
10.14
3.59
1960-65
10.34
3.60
1965-70
10.58
4.75
1970-75
10.66
5.57
1975-80
10.92
6.78
1980-85
10.91
7.34
1985-90
10.90
7.70
1990-95
10.60
8.51
1995-00
10.63
9.09
2000-05
10.81
9.22
2005-10
10.87
9.24
1.63
3.47
4.98
1.93
4.02
5.32
2.17
3.95
5.60
2.41
5.26
6.30
2.60
6.06
7.09
2.84
7.48
7.93
3.12
8.05
8.82
3.46
8.35
9.44
3.80
9.25
9.89
4.23
9.91
10.11
4.49
10.18
10.21
4.88
10.26
10.40
Notes: The entries give the estimate of
(2013).
as discussed in the text, using
= 15.5 and values for
is assumed to equal the ratio of under-5 to under-15 mortality rates.
, for each region and period from United Nations
Table 9
Different definitions of the onset of the fertility transition
Dependent variable: Total Fertility Rate
Threshold level of
gross fertility
TFR*=4.5
Pre-transition
TFR*=5.0
TFR*=5.5
TFR*=6.0
Post-transition
Pre-transition
Post-transition
Pre-Transition
Post-Transition
Pre-transition
Post-transition
15.75***
[1.066]
0.115
[1.183]
15.48***
[1.032]
-0.278
[1.251]
15.54***
[0.860]
-0.642
[1.500]
12.27***
[0.716]
One period lag of:
Child Mortality Rate
Observations
Countries
R2
0.744
[1.083]
422
682
368
736
297
807
217
887
78
117
73
125
67
132
52
136
0.727
0.735
0.660
0.749
0.569
0.791
0.457
0.783
Notes: All regressions control for GDP per capita, the urbanisation rate, female education, and a full set of time dummies. Robust standard errors in square brackets. The
symbols ***, ** and * denote statistical significance at the 1%, 5% and 10% levels.
Table 10
Other indicators of mortality
Dependent variable: Total Fertility Rate
Pre-transition
Post-transition
1.879
[1.941]
27.34***
[1.634]
Pre-transition
Post-transition
-0.0133
[0.00878]
-0.0387***
[0.00907]
One period lag of:
Infant Mortality Rate
Life Expectancy at Birth
Observations
Countries
R2
371
871
386
900
74
132
76
134
0.509
0.764
0.484
0.638
Notes: All regressions control for GDP per capita, the urbanisation rate, female education, and a full set of time dummies.
Robust standard errors in square brackets. The symbols ***, ** and * denote statistical significance at the 1%, 5% and 10% levels.