Below‐Replacement Fertility
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Below-Replacement Fertility
S. PHILIP MORGAN
Abstract
When a human population has underlying birth rates too low to sustain its current
population size, it has below-replacement fertility. If mortality rates are low, then
replacement-level fertility is slightly above two births per woman. Currently,
over 50% of the global population lives in a country with below-replacement
fertility; below-replacement fertility is especially widespread in developed countries
and is emerging in many developing ones. But there is substantial variation in
degree—some countries having very low fertility (below 1.5 births) and other
countries (such as the United States) have levels at or near the replacement level.
Because the level of fertility intended (or desired) approximates two births per
woman in most countries, explanations for fertility levels below replacement levels
focus on why people fail to have the number of children they intend. An important
factor is fertility timing. Postponement of fertility to older ages reduces birth rates
in current periods (lowering period fertility rates), but it also exposes persons to
events and experiences that may lead them to forego childbearing or additional
births. Below-replacement fertility produces important macro-level effects (e.g., a
population with older persons and a declining population size). Average fertility
below two births also impacts families and individuals’ life courses and activities.
INTRODUCTION
Below-replacement fertility exists when the average woman does not replace
herself with a female child before her death. The net reproduction rate (NRR)
precisely measures this concept of “replacement,” and it is a widely used
measure of species/population reproductive fitness. Using this measure,
below-replacement fertility exists when the NRR < 1.0; if such a rate were
maintained at the global level, it would lead to species extinction (because
NRR < 1.0 means that each generation will be smaller than the preceding
one). The disappearance of many evolutionary strands of humans as well
as many other species is the result of this imbalance of vital rates favoring
mortality. In contrast, dramatic human population growth over the past few
centuries is the result of fertility levels well above mortality levels (and thus
NRR well above 1.0).
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.
1
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
While less precise, other measures of replacement-level fertility are commonly used for human populations. Specifically, when mortality is low and
sex ratios modest (as in most contemporary developed countries), an average
of 2.1 children will approximate replacement-level fertility—two children
to “replace” each parent and the 0.1 as an adjustment for the few women
who do not survive through the childbearing years. Thus, birth cohorts of
women that average 2.1 children, or a sustained period in which the sum of
age-specific fertility rates (the total fertility rate, TFR) equals 2.1, will result
in replacement-level fertility. Approximately half of the world’s population
now lives in a country with a TFR < 2.1, many countries have TFRs below 1.5,
and “lowest-low fertility” (i.e., TFRs < 1.3, see Kohler, Billari, & Ortega, 2002)
is not uncommon.
To illustrate contemporary variation in below-replacement fertility, Table 1
lists selected countries with their estimated NRRs (column 1) and TFRs
(column 2) for the period 2005–2010. If these rates were maintained over a
long period, they imply, taking Germany as an example, that each succeeding
generation would be 65% as large as the former (the NRR) and that women
would average 1.36 births (the TFR). These rates imply a negative growth
rate of 1.42% per year (column 3) and 49 years for the population to reach
half its size (the halving time, column 4). Column 5 shows that most of these
countries have had low fertility for several decades, for instance Germany’s
TFR fell below 2.1 in the 1970–1975 period.
For two reasons, below-replacement fertility does not imply immediate
population decline, and replacement-level fertility does not imply zero
population growth. First, immigration adds to the population, just as births
do, and thus can offset the effects of low birth rates on population size.
Secondly, positive population momentum can also offset low birth rates; this
refers to a young age structure that will produce increasing proportions
(and numbers) of reproductive age women in subsequent years. Becuase
the number of births is the product of birth rates and the number of women
of childbearing age, an increasing number of reproductive age women can
offset low or declining birth rates, at least in the near term. To illustrate,
Table 1 column 6, shows the actual population change experienced by these
low-fertility countries in the 2005–2010 period. In most cases, population
declines are not observed despite subreplacement-level fertility due to the
effects of population momentum and/or immigration.
The difference in recent experience (rough stability or population growth
in column 6) and the long-term projections (some countries experiencing
dramatic population decline, columns 3 and 4) are striking. The long-term
projections are not inevitable. Immigration can continue indefinitely if source
populations remain and receiving countries are willing to accept migrants.
However, sustained low fertility will slowly transform a population’s age
Below-Replacement Fertility
3
Table 1
Variation in Low Fertility Rates
Country
NRR
2005–
2010a
TFR
2005–
2010a
(1)
(2)
Europe
France
0.95
Germany
0.65
Russian Federation
0.68
Italy
0.66
Spain
0.68
Sweden
0.91
Asia
China
0.71
Japan
0.64
S. Korea
0.61
Australia/New Zealand
Australia
0.93
North America
Unites States
1.00
a Source:
NRR
implied
% growth
rateb
(3)
Implied
years to
halvec
Period
when TFR
first fell
below 2.1a
(5)
Obs. rate of
pop. change
2005–2010a
1.97
1.36
1.44
1.38
1.41
1.64
−0.17
−1.42
−1.29
−1.37
−1.30
−0.30
414
49
54
50
53
231
1975–1980
1970–1975
1965–1970
1975–1980
1980–1985
1970–1975
0.6
−0.1
−0.1
0.6
1.2
0.8
1.64
1.32
1.29
−1.12
−1.50
−1.67
62
46
42
1990–1995
1955–1960
1985–1990
0.5
0
0.5
1.75
−0.25
274
1975–1980
1.7
2.07
−0.01
6921
1970–1975
0.9
(4)
(6)
United Nations (2011).
b Long-term growth rate assuming mean age of childbearing equals 30 and no migration. R = (ln(NRR))/30.
See Preston et al. (2001), p. 152.
to halve equals the absolute value of (100 × ln(2))/(% growth rate). See Preston et al. (2001), p. 12.
c Time
structure as low fertility replaces larger birth cohorts (produced by higher
fertility in the earlier period) with smaller ones. This “top-heavy” age structure generates negative population momentum (a reversal of the earlier pattern)
that can sustain population decline even if fertility rates begin to recover.
Again, column (5) shows that below-replacement fertility has been in place
for several decades and thus the force of positive population momentum is
waning. If we assume that immigration will eventually cease and acknowledge that the effect of positive population momentum is time limited, then
the import of fertility well below replacement cannot be ignored—halving
times of 50 years portend serious societal challenges.
Very low fertility has many consequences. At the macro level, fertility is
the primary determinant of a population’s age structure and low fertility
reduces population size. The lower the fertility rate, the more rapid and dramatic are these changes (see Table 1). Specifically, below-replacement fertility shifts the age distribution of the population upward. Aging populations
impact many societal institutions that are age graded—schools for children,
labor force opportunities for adults, social security for the elderly, and so
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Table 2
Variation in Low Fertility Ratesa
Grandparents
Aunts/uncles
Parents
Siblings
Cousins
Total
One child
(1)
Two children
(2)
Three children
(3)
4
0
2
0
0
6
4
2
2
1
4
13
4
4
2
2
8
20
a Ego’s parents and grandparents have the number of children indicated. This calculation assumes no
mortality.
on. These age distribution shifts (e.g., more elderly persons) require institutional adjustment (e.g., additional resources for elderly care and support).
Declining population size can also be a concern. Initially, low fertility impacts
demand/consumption of goods for children, but eventually it reduces the
number of consumers at all ages. A smaller population can also reduce the
tax base and effect economies of scale; thus, the ability to support infrastructure may decline. Further, a reduced population size may be a major threat if
key societal positions cannot be filled. Population size can also affect a country’s military strength by constraining the size of its armed forces. This in
turn might influence a country’s ability to negotiate or demand favorable
interactions with other countries (Teitelbaum & Winter, 1985).
At the household level, low fertility has a dramatic effect on family composition by shifting the number and character of available kin. For instance,
the first column of Table 2 shows that a singleton born to singleton parents
has no siblings, no aunts/uncles, and no cousins. Assuming no mortality, the
singleton does have two parents and four grandparents. Thus, low fertility
produces small kin networks dominated by the older generations. These relatives may provide considerable support when ego is young; but the burden
of old age care on ego could be significant as the senior generation ages.
If we assume constant fertility across generations of two or three births, in
columns 2 and 3 respectively, we see much larger and more diverse kinship
networks. Finally, at the individual level, fertility may be lower than intended
or desired by women and men. Most persons in most developed countries
state preferences for at least two children. Thus, given the desires of potential
parents, childlessness and one-child families may not be optimal for individual well-being or happiness.
But there are also advantages of low fertility, and some concerns attributed
to subreplacement fertility may be exaggerated. First, when fertility first
falls to low levels, there is a “demographic dividend” because the first age
Below-Replacement Fertility
5
groups to grow larger in an aging society are working age persons (Mason &
Lee, 2006). Thus, for a few decades the dependency ratio (number of persons
too young or old to work divided by number of working age persons)
remains small, and the resources needed for the education and/or care of
dependents is reduced. This allows for lower taxes and/or greater investments in infrastructure in the short term. In the longer term, low fertility
(and a smaller population) places less pressure on natural resources and on
the environment. In addition, concerns about an aging population may be
exaggerated. Older persons, especially if in good health and with support
for life-long learning, can be a valuable resource. Pay-as-you go support
systems for retirees can be adjusted (e.g., by increasing the eligibility age) so
that expenses equal revenues. Finally, the reduced numbers of siblings and
cousins resulting from low fertility may increase intergenerational transfers
advantaging the fewer children that are born. Nonfamilial transfers (e.g.,
by the government), if maintained at a given level, imply higher per-capita
investments in children (because of their smaller number). And finally, for
adults, having fewer children may allow greater time and resources for
activities that are equally or more rewarding than parenthood.
FOUNDATIONAL RESEARCH
DEMOGRAPHIC INTERRELATIONS
The mathematical interrelations of birth, death, and migration rates and
their impacts on the population’s age structure are well understood (Preston, Heuveline, & Guillot, 2001). Several aspects are especially important
for low-fertility populations and were noted in the earlier section. First,
replacement (NRR = 1) can hold under conditions of high and low fertility,
as not all children will survive to adulthood. Espenshade, Guzman, and
Westoff (2003) show that in the period 1995–2000, replacement-level fertility
(measured as the TFR) ranged from 2.1 (e.g., in Europe and the North
America) to 2.7 (in Africa), with the variation produced by higher mortality
in developing countries.
Second, we alluded earlier to positive population momentum—young
age structures (produced by several decades of above-replacement fertility)
guarantee larger proportions/number of women in the childbearing years
over the next generation (approximately 30 years). This momentum can
keep populations growing even as fertility falls to the replacement level or
below. But several decades of below-replacement fertility will result in the
opposite effect—an older age structure with negative momentum (shrinking
population) for approximately a generation, even if replacement-level
fertility returns. Lutz, O’Neill, and Scherbov (2003) show that Europe’s age
structure had modest negative momentum by the year 2000. Continued low
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
fertility will increase the duration and magnitude of this negative population
momentum.
COHORT AND PERIOD FERTILITY
Cohort fertility refers to the sum of births that women have over their life,
usually represented by an average (e.g., cohort replacement level equals 2.1
for women surviving to the age 45). Notably, these figures can only be
obtained after each member of the actual cohort has aged through the
reproductive lifespan and completed childbearing. Period fertility, by
contrast, measures births in a given year and is often characterized by the
sum of current age-specific rates, such as the TFR. The TFR thus describes
the number of births a hypothetical cohort would have if they experienced
the current age-specific fertility rates for the rest of their lives (again
replacement-level fertility = TFR = 2.1). This distinction is critical, as an
upward shift in the ages of childbearing would reduce the period TFR even
if (completed) cohort fertility does not change, a phenomenon known as
a tempo effect (Bongaarts & Feeney, 1998). Declining ages at childbearing
increase the TFR relative to cohort rates; postponement of childbearing
has the opposite effect. While this fact is well known, the magnitude and
duration of these timing changes on the TFR are less well known and have
been the focus of much research over the past two decades. This dynamic
is very important for understanding below-replacement fertility because
timing changes, specifically fertility postponement, has contributed greatly
to the very low fertility rates as measured by the TFR. The problem is that
the TFR, as with all period rates, contains information on both the number
(quantum) and timing (tempo) of births. Shifts in the latter (e.g., younger
cohorts having children later in life) can therefore deflate the TFR even if
the quantum remains fixed. Bongaarts and Feeney (1998) provide a simple
measure of this tempo effect and Bongaarts (2002) shows that it frequently
reduces the TFR by 0.15 to 0.35 for several decades. The magnitude of
the effect is directly related to mean shifts in ages at childbearing and the
effect lasts as long as these shifts are taking place. Importantly, these tempo
effects are time-limited—they cannot go on forever—they stop when ages
at childbearing stop increasing. Recent increases in lowest-low fertility in
some European countries are primarily the result of a cessation of fertility
postponement (Goldstein, Sobotka, & Jasilioniene, 2009).
PROXIMATE DETERMINANTS OF LOW FERTILITY
In most countries with below-replacement fertility, women report fertility
intentions that average two births (i.e., at or near the replacement level).
Below-Replacement Fertility
7
Thus the question, why do women frequently have fewer children than they
intend? Bongaarts (2001) proposed a useful macro-level conceptual model for
understanding this discrepancy between intentions and behavior. He decomposes the TFR into a set of scaling factors that represents a current (period)
fertility regime. Specifically,
TFR = Ft × (IP) × (Fu × Fg) × (Fi × Fc).
The level of current fertility (i.e., the TFR) is first adjusted by the factor Ft
for the tempo effects of shifting births toward younger or older ages at childbearing, as suggested by Bongaarts and Feeney (1998) and discussed earlier.
In recent decades, pervasive postponement implies Ft values well below 1.0
(i.e., Ft < 1.0). Thus, TFR/Ft equals the quantum of period fertility (i.e., period
fertility corrected for the effects of shifts in fertility timing).
Key to explaining TFR/Ft (quantum) is the intended parity (IP, the number
of births intended) of young women (e.g., those aged 21–25). In turn, IP is
increased or decreased by a set of model parameters that reflects forces not
incorporated into women’s reports of childbearing intentions. These factors
are not incorporated into stated intentions because they cannot be well anticipated. Factors that increase fertility relative to earlier stated intentions are
as follows:
Fu: unwanted fertility. Unwanted births measured through women’s
retrospective reports, that is, women are asked “at the time you
became pregnant did you intend to have any more children?” Thus,
these pregnancies (and births) would not have occurred in a “perfect
contraceptive” society. Unwanted fertility increases TFR relative to IP
(and Fu > 1.0, estimates for the United States in recent decades would
be 1.1 to 1.15).
Fg: gender preferences. Some couples who intend to have two children will
have strong preferences for at least one son and one daughter (see
Pollard & Morgan, 2002). But given that sex of children is not easily
controlled or anticipated, roughly half of such couples will reach the
two-child goal but not have their preferred gender composition. These
couples may revise their IP upward. Such preferences and behavior
would increase TFR relative to IP (and Fg > 1.0).
Factors that reduce fertility relative to intended parity are as follows:
Fi: impaired fecundity. In general, women (and their partners) will not know
if they are, or when they will become, sub- or infecund. Thus, women
cannot factor impaired fecundity into their IP reports. A few women
are infecund at young ages (1% or 2% at ages 15–19; see Bongaarts &
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Potter, 1983), but the proportion increases with age (especially after age
35; see Bongaarts & Potter, 1983, Menken, 1985) and with the prevalence
of some diseases/infections. Male fecundity declines with age also, but
its onset is much later than for females and its pattern of decline less
certain. Clearly, impaired couple fecundity decreases TFR relative to IP
(and Fi < 1.0).
Fc: competition. Women/couples can also revise their IP upwards or downwards depending on their experiences, opportunities, and constraints
(that encourage or compete with childbearing). Following Bongaarts,
we refer to this broad class of constraints and competing opportunities
as competition. Some of this competition may be anticipated and incorporated into IP. What is not, for example, the unanticipated difficulty of
combining career and family responsibilities, of finding a suitable partner, and so on, is reflected in this parameter. In contemporary settings,
Fc is expected to be <1.0.
In this framework, observed fertility reflects the balance of these forces.
Morgan et al. (Hagewen & Morgan, 2005; Morgan, 2003; Morgan & Hagewen,
2005; Morgan & Rackin, 2010; Quesnel-Vallée & Morgan, 2003) have applied
this framework in several different contexts as a conceptual and as an analytic
model.
DISTAL DETERMINANTS OF LOW FERTILITY
The proximate framework given earlier is of limited value because it leaves
fundamental questions unanswered: Why does a collective have a given
intended family size (e.g., two children)? Why does one population have
high levels of unwanted births compared to another? Why is postponement
of childbearing or competition between childbearing and other activities
more intense in one population compared to another? While the conceptual
distinction can be substantively problematic (as discussed later), distal
determinants are often classified as either material or ideological. Material
ones include many of the factors that increase the costs of children—the
inability of children to be economically productive in a modern economy
and the cost of their extended periods of education and job training. Also
included are the opportunity costs of a parent’s foregone labor and/or
leisure activities. Many of these changes are considered to be constituent
parts of economic development and thus take on an inevitable and secular
character. The ideological determinants include “modern” schemas (or
world views) that celebrate independence and self-actualization. Sometimes
these schemas are viewed as powerful forces sweeping the globe because of
Below-Replacement Fertility
9
their intrinsic power or usefulness to individuals (Goode, 1963; Lesthaeghe,
1995; Lesthaeghe & Neidert, 2006) or because they are conflated with the
power, wealth, and prestige of being “modern” (Thornton, 2001, 2005).
This material/ideological distinction is problematic because the structural
and ideological are not separate or additive effects. Predictable behaviors are
the product of both material clues and means and the schemas that explain
and rationalize their use (Johnson-Hanks, Bachrach, Morgan, & Kohler, 2011;
Sewell, 1992, 2005). The material and schematic are both interdependent and
interactive; each can change with repercussions for the other. For instance,
day care for children can reduce the tension between labor force participation
and parenthood and thus increase fertility (Rindfuss, Guilkey, Morgan, &
Guzzo, 2007; Rindfuss, Guilkey, Morgan, & Kravdal, 2010). But this scenario
depends upon day care facilities being available and affordable (material
aspects) and their use must be acceptable (schematic aspects).
CUTTING-EDGE RESEARCH
To avoid long-term decline, the human population will ultimately need to
approximate replacement-level fertility—thus, women, on average, will need
to have two births before the end of reproduction. Obviously, a mean of two
can be produced by very different distributions and women can have births
within a broad age range. The future mean and distribution of family size
and ages at childbearing will almost certainly vary across population groups
and understanding these patterns is a goal of future research. Cutting-edge
research focuses on the proximate determinants identified in the previous
section and an attempt to understand change/stability in them, and in turn,
the reasons for variation in period or lifetime fertility.
Fertility timing. As described, the postponement of childbearing to later
ages is a major reason for below-replacement fertility (Kohler et al.,
2002). This fact is now well known. The remaining key question here is
how much longer before ages of childbearing stabilize. Some countries
(such as Italy) would seem to be approaching a very late pattern of
childbearing with little room for further upward movement. In fact,
the rate of postponement in several European countries has slowed
since 2000 (Goldstein et al., 2009). In contrast to these late patterns, ages
at childbearing are still quite young in places as diverse as the United
States, China, and Thailand. So, monitoring future changes in ages at
childbearing remains important.
Postponement of childbearing can also affect the number of children
women eventually have—fertility postponed is fertility at least partially
foregone. To explain, postponement is associated with lower levels
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
of childbearing (Billari & Kohler, 2004; Morgan & Rindfuss, 1999),
but the extent to which this is true varies somewhat across countries
(Lesthaeghe, 2010). The mechanisms that produce this are (i) increasing
sub- or infecundity associated with older ages and (ii) the competition
(or opportunity costs) from other activities that can increase over
time, leading to downward revisions in children intended. Both these
mechanisms are discussed later.
Fertility intentions. It is now widely documented that fertility intentions
(desires or ideals) are generally near replacement levels even when
fertility is well below replacement levels. This is a favorable situation
in that returning to replacement-level fertility requires only that
women/couples have the children they intend to have (judging from
their reports). A different scenario is that future intentions will fall
well below two children, making a return to replacement-level fertility
contingent on both increasing women/couple’s intent for more children
and assisting them in realizing these increased intentions. Thus, a key
question is how persistent is the desire to have at least two children?
There is substantial stability in the time series of the preferred or ideal
family size in the United States (Hagewen & Morgan, 2005). But there is
also evidence that economic conditions can force very low fertility for
a generation so that low fertility (and low-fertility intentions) becomes
the “new normal.” With decades of experience, childlessness and
one-child families become much more acceptable. Goldstein, Lutz, and
Testa (2003) claim this is happening in German-speaking Europe. It
may also be happening in urban China, where the one-child option is
becoming individuals’ preferred family size following a generation of
low fertility encouraged by the one-child policy (Merli & Morgan, 2011;
Merli & Smith, 2002). Stability and change in family size intentions
remain an important research area.
Unwanted fertility. The concept of unwanted fertility is controversial and
its measurement difficult. Much of the controversy can be put aside by
agreeing on its meaning: An unwanted birth is one that occurred to a
woman who did not, at the time of the child’s conception, intend to have any
more children. The measurement issue is more difficult because some
women may not have had a clear intention at the time of conception,
do not remember accurately what the intention was, or are hesitant to
report that a child was unintended. It is commonly assumed that estimates of unwanted fertility are biased downward—primarily because
of a reluctance to identify a child as unintended after the fact. Regardless
of the difficulty of measurement, the concept is an important one that
Below-Replacement Fertility
11
clearly impacts fertility levels and does so differentially across populations. For the United States as a whole, 10–15% of births are estimated to
be “unwanted.” These estimates are stable across the past four decades.
While the measurement of unwanted fertility is not attempted in some
contexts, it is assumed to be much lower in many places. Greater availability and acceptability of abortion likely reduce unwanted fertility.
A large proportion of births (in the United States an additional 20–30%)
are also mistimed—the mother reports that when the child was conceived she wanted to have a child sometime in the future but did not
intend to have a child at this time. These “earlier-than-expected” births
increase period fertility rates because they lower the ages at childbearing (compared to a counterfactual of a perfect contraceptive regime) and
likely increase cohort fertility by nullifying the effect of postponement
that operates via competition (or opportunity costs) at older ages.
Gender preferences. If women/couples intend, for instance, to have two
children and simultaneously hold strong gender preferences, then
they may have an additional child to realize these gender preferences.
In many Western countries including the United States, the desire
for balance (one son and one daughter) is most common. Given that
the sex of children is generally not controlled and that the chance of
a son/daughter is roughly 0.5, 50% of those with two children do
not have their preferred gender composition (a daughter and a son).
Consistent with this argument, there is substantial evidence that having
two children of the same sex increases the intent to have another child
and the likelihood of doing so. In other populations (as with many
in Asia) there is a strong desire to have at least one son. With two
children, approximately one-quarter will not have a son. But with only
one child, the proportion without a son is close to 50%. Note that in
the absence of sex selection, gender preferences affect fertility more
at low fertility levels. At low fertility levels, there are fewer births to
realize any preferred gender composition. The persistence of gender
preferences is an active research question (see Bongaarts, 2013). Pollard
and Morgan (2002) claim that an emerging “gender indifference”
accompanies greater gender equality in the Untied States. If true, the
long-observed desire for a balanced gender composition will cease to
affect fertility intentions and behavior. Using data for the egalitarian
Nordic countries, Andersson, Hank, Ronsen, and Vikat (2006) present
some evidence for the effects of a desire for “balance” and for some
emerging new preferences. There is mixed evidence on the decline of
sex preference in China (Hesketh & Xing, 2006).
At present, the only widely available form of sex preselection is selective abortion—using a sonogram or some other technique to determine
12
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
the sex of the fetus and abort if it is not the preferred sex. Given that
the ratio of male/female births is very close to 1.04 across time, space,
and parity, one can detect the use of selective abortion if sex ratios are
significantly higher than this value.1 Recent evidence suggests that the
wide use of sex-selective abortion in South Korea was reduced by making the practice illegal (Hesketh & Xing, 2006).
Sub- or infecundity. Being unable to conceive or carry a birth to term
can obviously lead women/couples to have fewer children than they
intended. Fecundity declines with age and the decline is more rapid
after the mid-30s. Many women are sub- or infecund by age 40 and
almost all are by age 50. Men’s fecundity declines with age as well but
much more slowly than for women. Fecundity can also be affected by
disease, such as sexually transmitted diseases, so that fecundity can
vary across populations and across time with the prevalence of relevant
diseases.
Some causes of sub- and infecundity are treatable. At present, the inability to conceive via sexual intercourse can sometimes be obviated by in
vitro fertilization (a process by which an egg is fertilized by the sperm
outside the body, e.g., in a laboratory dish/tube, and then implanted
in the uterus). This process was highly controversial in the 1960s but,
while an expensive and intrusive procedure, is becoming commonplace.
Roughly 1 of every 100 US births was conceived via in vitro fertilization
in recent years (2005–2010) and proportions are higher in other countries (Billari, Kohler, Andersson, & Lundström, 2007; Sobotka, Hansen,
Jensen, Pedersen, Lutz, & Skakkebæk, 2008). The development, dissemination, and acceptability of such procedures could reduce the effect of
sub- and infecundity.
Competition. In the proximate determinants framework mentioned earlier,
competition refers to the alternatives to childbearing (or the opportunity
costs) that become apparent at older ages (i.e., were not factored into
fertility intentions at younger ages). For simplicity, let us divide all decisions into one of three domains: family, work, and leisure. At young
ages, the trade-offs between choices in one of these domains and others
may not be obvious. But as the life-course unfolds, decisions to marry
or to have children may impact other domains. To the extent that family
(i.e., fertility-related) events are postponed or foregone because of the
emerging opportunity costs (to career or leisure), we can say that competition is lowering fertility. An extreme case would be where mothers
1. Other possible reasons for high sex ratios would be infanticide or neglect of girl babies or a failure
to register them. These alternatives may be relevant in some contexts but not in the recent case of very high
sex ratios for third and fourth births in South Korea, for instance. Sex-selective abortions are considered
the more important mechanism producing abnormally high sex ratios in India and China after 2000.
Below-Replacement Fertility
13
find it very difficult to work in full-time jobs because of the institutional
incompatibility of family and work. McDonald (2000) has conceptualized this as variable gender equity across institutions. In recent decades,
the degree of gender equity in formal education and market employment has increased dramatically. But there is, he argues, substantial variability in movement toward gender equity in the family. When gender
equity in the family domain lags behind that in other institutions, many
women may forego marriage, childrearing, or larger families. Very low
fertility may result.
KEY ISSUES FOR FUTURE RESEARCH
A key question for future research: Is below-replacement fertility inevitable?
There are three possible answers. First, the cross-country and cross-time associations suggest that with economic development and associated changes,
fertility decline from high levels is inevitable. These declines are driven by
a combination of institutional/material changes and the diffusion of “modern” schema or ideas. Some argue that these forces are far from running their
course and that as a result below-replacement fertility will be a broad-based
twenty-first century crisis (Lesthaeghe, 2010).
A second position is that below-replacement fertility is transitional.
Myrskyla, Kohler, and Billari (2009) analysis of cross-country and cross-time
data leads them to argue that advanced levels of development lead to an
upturn in very low fertility. But their analysis and discussion do not identify
the mechanisms that lead to the reversal and thus counter the arguments
given. Ongoing work by Myrskyla, Kohler, and Billari (2012) suggests that
the upturn associated with advanced economic development is concentrated
in countries that have attained greater levels of gender equity in the family
institution.
Third, Morgan (2003), consistent with the notion of differential levels and
differential response, argues that existing diversity will not disappear. Some
developed countries have never experienced fertility well below replacement
and have stable and sustainable fertility at near-replacement levels (e.g., the
United States). For other countries, a full-blown crisis exists (e.g., Japan).
Inability to even approximate replacement-level fertility on a decadal time
scale is a crisis because the implications of very low fertility are clear—either
dramatic population decline or very high levels of immigration. Given this
fact, there are powerful incentives to identify and pursue policies that facilitate replacement-level higher fertility. Identifying policies that work and
policies that work better/worse in particular contexts are very important
contemporary research questions (see McDonald, 2006).
14
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
REFERENCES
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Population Studies, 58(2), 161–176.
Billari, F. C., Kohler, H.-P., Andersson, G., & Lundström, H. (2007). Approaching the
limit: Long-term trends in late and very late fertility. Population and Development
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Bongaarts, J. (2001). Fertility and reproductive preferences in post-transitional societies. Population and Development Review, 27(Supplement: Global Fertility Transition), 260–281.
Bongaarts, J. (2002). The end of fertility transition in the developed world. Population
and Development Review, 28(3), 419–444.
Bongaarts, J. (2013). The implementation of preferences for male offspring. Population
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Bongaarts, J., & Feeney, G. (1998). On the quantum and tempo of fertility. Population
and Development Review, 24(2), 271–291.
Bongaarts, J., & Potter, R. G. (1983). Fertility, biology and behavior. New York, NY:
Academic Press.
Espenshade, T. J., Guzman, J. C., & Westoff, C. F. (2003). The surprising global Variation in replacement fertility. Population Research and Policy Review, 22(5), 575–583.
Goldstein, J. R., Lutz, W., & Testa, M. R. (2003). The emergence of sub-replacement
family size ideals in Europe. Population Research and Policy Review, 22, 479–496.
Goldstein, J. R., Sobotka, T., & Jasilioniene, A. (2009). The end of "lowest-low" fertility? Population and Development Review, 35(4), 663–699.
Goode, W. J. (1963). World revolution and family patterns. New York, NY: Free Press of
Glencoe.
Hagewen, K. J., & Morgan, S. P. (2005). Intended and ideal family size in the United
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Hesketh, T., & Xing, Z. W. (2006). Abnormal sex ratios in human populations:
Causes and consequences. Proceedings of the National Academy of Sciences, 103(36),
13271–13275.
Johnson-Hanks, J., Bachrach, C., Morgan, S. P., & Kohler, H.-P. (2011). Understanding family change and variation: Structure, conjuncture, and action. New York, NY:
Springer.
Kohler, H.-P., Billari, F. C., & Ortega, J. A. (2002). The emergence of lowest-low fertility in Europe during the 1990s. Population and Development Review, 28, 641–680.
Lesthaeghe, R. (1995). The second demographic transisiton in western countries: An
interpretation. In K. Oppenheim Mason, A.-M. Jensen & W. T. Mason (Eds.), Gender
and family change in industrialized countries (pp. 17–62). Oxford, England: Clarendon.
Lesthaeghe, R. (2010). The unfolding story of the second demographic transition.
Population and Development Review, 36(2), 211–251.
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Lesthaeghe, R., & Neidert, L. (2006). The second demographic transition in the
United States: Exception or textbook example? Population and Development Review,
32, 660–698.
Lutz, W., O’Neill, B. C., & Scherbov, S. (2003). Europe’s population at a turning point.
Science, 299(5615), 1991–1992.
Mason, A., & Lee, R. (2006). Reform and support systems for the elderly in developing countries: Capturing the second demographic dividend. Genus, 62(2), 11–35.
McDonald, P. (2000). Gender equity in theories of fertility transition. Population and
Development Review, 26(3), 427–439.
McDonald, P. (2006). Low fertility and the state: The efficacy of policy. Population and
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Menken, J. (1985). Age and fertility: How late can you wait? Demography, 22(4),
469–483.
Merli, M. G., & Morgan, S. P. (2011). Below replacement fertility preferences in Shanghai. Population (English Edition), 66(3), 519–542.
Merli, M. G., & Smith, H. L. (2002). Has the Chinese family planning policy been
successful in changing fertility preferences? Demography, 39(3), 557–572.
Morgan, S. P. (2003). Is low fertility a twenty-first-century demographic crisis?
Demography, 40(4), 589–603.
Morgan, S. P., & Hagewen, K. (2005). Is very low fertility inevitable in America?
Insights and forecasts from an integrative model of fertility. In A. Booth & A. C.
Crouter (Eds.), The new population problem: Why families in developed counties are
shrinking and what it means (pp. 3–28). Lawrence Erlbaum Associates: Mahwah,
NJ.
Morgan, S. P., & Rackin, H. (2010). The correspondence of fertility intentions and
behavior in the U.S. Population and Development Review, 36(1), 91–118.
Morgan, S. P., & Rindfuss, R. R. (1999). Re-examining the link of early childbearing
to marriage and to subsequent fertility. Demography, 36(1), 59–75.
Myrskyla, M., Kohler, H.-P., & Billari, F. C. (2009, August 6). Advances in development reverse fertility decline. Nature, 460, 741–743.
Myrskyla, M., Kohler, H.-P., & Billari, F. C. (2012). High development and fertility: fertility at older reproductive ages and gender equality explain the positive
link. Max Planck Institute for Demographic Research, Konrad-Zuse-Str. 1, 18057
Rostock, Germany. Under review at Population Studies.
Pollard, M. S., & Morgan, S. P. (2002). Emerging gender indifference: Sex composition
of children and the third birth. American Sociological Review, 67, 600–613.
Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and modeling population processes. Malden, MA: Blackwell.
Quesnel-Vallée, A., & Morgan, S. P. (2003). Missing the target? Correspondence of
fertility intentions and behavior in the U.S. Population Research and Policy Review,
22(5–6), 497–525.
Rindfuss, R. R., Guilkey, D., Morgan, S. P., & Guzzo, K. B. (2007). Child care availability and fertility in Norway: Pro-natalist effects. Demography, 44, 345–372.
Rindfuss, R. R., Guilkey, D. K., Morgan, S. P., & Kravdal, O. (2010). Child care availability and fertility in Norway. Population and Development Review, 36(4), 725–748.
16
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Sewell, W. H. (1992). A theory of structure: Duality, agency, and transformation.
American Journal of Sociology, 98(1), 1–29.
Sewell, W. H. (2005). Logics of history. Chicago, IL: University of Chicago Press.
Sobotka, T., Hansen, M. A., Jensen, T. K., Pedersen, A. T., Lutz, W., & Skakkebæk,
N. E. (2008). The contribution of assisted reproduction to completed fertility: An
analysis of Danish Data. Population and Development Review, 34(1), 79–101.
Teitelbaum, M. S., & Winter, J. M. (1985). The fear of population decline. Orlando, FL:
Academic Press.
Thornton, A. (2001). The developmental paradigm, reading history sideways, and
family change. Demography, 38(4), 449–467.
Thornton, A. (2005). Reading history sideways: The fallacy and enduring impact of the
developmental paradigm on family life. Chicago, IL: University of Chicago Press.
United Nations. (2011). Department of Economic and Social Affairs, Population Division. World Population Prospects. The 2010 Revision, CD-ROM Edition. Retrieved
from http://esa.un.org/unpd/wpp/Sorting-Tables/tab-sorting_population.htm
FURTHER READING
Bongaarts, J. (2001). Fertility and reproductive preferences in post-transitional societies. Population and Development Review, 27(Supplement: Global Fertility Transition), 260–281.
McDonald, P. (2000). Gender equity in theories of fertility transition. Population and
Development Review, 26(3), 427–439.
Morgan, S. P. (2003). Is low fertility a twenty-first-century demographic crisis?
Demography, 40(4), 589–603.
Morgan, S. P., & Taylor, M. G. (2006). Low fertility at the turn of the twenty-first
century. Annual Review of Sociology, 32, 375–400.
S. PHILIP MORGAN SHORT BIOGRAPHY
S. Philip Morgan is Director of the Carolina Population Center and Alan
Feduccia Distinguished Professor of Sociology at the University of North
Carolina at Chapel Hill. He is former president of the Population Association of America and former editor of the journal Demography. He has chaired
the sociology departments at the University of Pennsylvania (1993–1996) and
Duke University (2002–2008). Morgan was Director of Duke’s Social Science
Research Institute 2008–2012 and is emeriti Norb R. Schaeffer Professor of
International Studies at Duke University.
Morgan’s work focuses on family and fertility change (over time) and diversity (across groups). Much of his work has focused on the United States but he
has collaborated on projects focusing on other countries, both developed and
developing. Morgan’s recent NIH-funded projects have focused on developing new models of family and fertility change and diversity, late twentieth
Below-Replacement Fertility
17
century fertility trends and differences in the United States, emerging low
fertility in the Islamic Republic of Iran, and the association between fertility
intentions and behavior in the United States.
Also see http://www.cpc.unc.edu/people/fellows/bio?person=morganp
RELATED ESSAYS
Below-Replacement Fertility (Sociology), S. Philip Morgan
Limits to Human Longevity (Sociology), Samuel H. Preston and Hiram
Beltrán-Sánchez
Demography and Cultural Evolution (Anthropology), Stephen Shennan
Recent Demographic Trends and the Family (Sociology), Lawrence L. Wu
-
Below-Replacement Fertility
S. PHILIP MORGAN
Abstract
When a human population has underlying birth rates too low to sustain its current
population size, it has below-replacement fertility. If mortality rates are low, then
replacement-level fertility is slightly above two births per woman. Currently,
over 50% of the global population lives in a country with below-replacement
fertility; below-replacement fertility is especially widespread in developed countries
and is emerging in many developing ones. But there is substantial variation in
degree—some countries having very low fertility (below 1.5 births) and other
countries (such as the United States) have levels at or near the replacement level.
Because the level of fertility intended (or desired) approximates two births per
woman in most countries, explanations for fertility levels below replacement levels
focus on why people fail to have the number of children they intend. An important
factor is fertility timing. Postponement of fertility to older ages reduces birth rates
in current periods (lowering period fertility rates), but it also exposes persons to
events and experiences that may lead them to forego childbearing or additional
births. Below-replacement fertility produces important macro-level effects (e.g., a
population with older persons and a declining population size). Average fertility
below two births also impacts families and individuals’ life courses and activities.
INTRODUCTION
Below-replacement fertility exists when the average woman does not replace
herself with a female child before her death. The net reproduction rate (NRR)
precisely measures this concept of “replacement,” and it is a widely used
measure of species/population reproductive fitness. Using this measure,
below-replacement fertility exists when the NRR < 1.0; if such a rate were
maintained at the global level, it would lead to species extinction (because
NRR < 1.0 means that each generation will be smaller than the preceding
one). The disappearance of many evolutionary strands of humans as well
as many other species is the result of this imbalance of vital rates favoring
mortality. In contrast, dramatic human population growth over the past few
centuries is the result of fertility levels well above mortality levels (and thus
NRR well above 1.0).
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.
1
2
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
While less precise, other measures of replacement-level fertility are commonly used for human populations. Specifically, when mortality is low and
sex ratios modest (as in most contemporary developed countries), an average
of 2.1 children will approximate replacement-level fertility—two children
to “replace” each parent and the 0.1 as an adjustment for the few women
who do not survive through the childbearing years. Thus, birth cohorts of
women that average 2.1 children, or a sustained period in which the sum of
age-specific fertility rates (the total fertility rate, TFR) equals 2.1, will result
in replacement-level fertility. Approximately half of the world’s population
now lives in a country with a TFR < 2.1, many countries have TFRs below 1.5,
and “lowest-low fertility” (i.e., TFRs < 1.3, see Kohler, Billari, & Ortega, 2002)
is not uncommon.
To illustrate contemporary variation in below-replacement fertility, Table 1
lists selected countries with their estimated NRRs (column 1) and TFRs
(column 2) for the period 2005–2010. If these rates were maintained over a
long period, they imply, taking Germany as an example, that each succeeding
generation would be 65% as large as the former (the NRR) and that women
would average 1.36 births (the TFR). These rates imply a negative growth
rate of 1.42% per year (column 3) and 49 years for the population to reach
half its size (the halving time, column 4). Column 5 shows that most of these
countries have had low fertility for several decades, for instance Germany’s
TFR fell below 2.1 in the 1970–1975 period.
For two reasons, below-replacement fertility does not imply immediate
population decline, and replacement-level fertility does not imply zero
population growth. First, immigration adds to the population, just as births
do, and thus can offset the effects of low birth rates on population size.
Secondly, positive population momentum can also offset low birth rates; this
refers to a young age structure that will produce increasing proportions
(and numbers) of reproductive age women in subsequent years. Becuase
the number of births is the product of birth rates and the number of women
of childbearing age, an increasing number of reproductive age women can
offset low or declining birth rates, at least in the near term. To illustrate,
Table 1 column 6, shows the actual population change experienced by these
low-fertility countries in the 2005–2010 period. In most cases, population
declines are not observed despite subreplacement-level fertility due to the
effects of population momentum and/or immigration.
The difference in recent experience (rough stability or population growth
in column 6) and the long-term projections (some countries experiencing
dramatic population decline, columns 3 and 4) are striking. The long-term
projections are not inevitable. Immigration can continue indefinitely if source
populations remain and receiving countries are willing to accept migrants.
However, sustained low fertility will slowly transform a population’s age
Below-Replacement Fertility
3
Table 1
Variation in Low Fertility Rates
Country
NRR
2005–
2010a
TFR
2005–
2010a
(1)
(2)
Europe
France
0.95
Germany
0.65
Russian Federation
0.68
Italy
0.66
Spain
0.68
Sweden
0.91
Asia
China
0.71
Japan
0.64
S. Korea
0.61
Australia/New Zealand
Australia
0.93
North America
Unites States
1.00
a Source:
NRR
implied
% growth
rateb
(3)
Implied
years to
halvec
Period
when TFR
first fell
below 2.1a
(5)
Obs. rate of
pop. change
2005–2010a
1.97
1.36
1.44
1.38
1.41
1.64
−0.17
−1.42
−1.29
−1.37
−1.30
−0.30
414
49
54
50
53
231
1975–1980
1970–1975
1965–1970
1975–1980
1980–1985
1970–1975
0.6
−0.1
−0.1
0.6
1.2
0.8
1.64
1.32
1.29
−1.12
−1.50
−1.67
62
46
42
1990–1995
1955–1960
1985–1990
0.5
0
0.5
1.75
−0.25
274
1975–1980
1.7
2.07
−0.01
6921
1970–1975
0.9
(4)
(6)
United Nations (2011).
b Long-term growth rate assuming mean age of childbearing equals 30 and no migration. R = (ln(NRR))/30.
See Preston et al. (2001), p. 152.
to halve equals the absolute value of (100 × ln(2))/(% growth rate). See Preston et al. (2001), p. 12.
c Time
structure as low fertility replaces larger birth cohorts (produced by higher
fertility in the earlier period) with smaller ones. This “top-heavy” age structure generates negative population momentum (a reversal of the earlier pattern)
that can sustain population decline even if fertility rates begin to recover.
Again, column (5) shows that below-replacement fertility has been in place
for several decades and thus the force of positive population momentum is
waning. If we assume that immigration will eventually cease and acknowledge that the effect of positive population momentum is time limited, then
the import of fertility well below replacement cannot be ignored—halving
times of 50 years portend serious societal challenges.
Very low fertility has many consequences. At the macro level, fertility is
the primary determinant of a population’s age structure and low fertility
reduces population size. The lower the fertility rate, the more rapid and dramatic are these changes (see Table 1). Specifically, below-replacement fertility shifts the age distribution of the population upward. Aging populations
impact many societal institutions that are age graded—schools for children,
labor force opportunities for adults, social security for the elderly, and so
4
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Table 2
Variation in Low Fertility Ratesa
Grandparents
Aunts/uncles
Parents
Siblings
Cousins
Total
One child
(1)
Two children
(2)
Three children
(3)
4
0
2
0
0
6
4
2
2
1
4
13
4
4
2
2
8
20
a Ego’s parents and grandparents have the number of children indicated. This calculation assumes no
mortality.
on. These age distribution shifts (e.g., more elderly persons) require institutional adjustment (e.g., additional resources for elderly care and support).
Declining population size can also be a concern. Initially, low fertility impacts
demand/consumption of goods for children, but eventually it reduces the
number of consumers at all ages. A smaller population can also reduce the
tax base and effect economies of scale; thus, the ability to support infrastructure may decline. Further, a reduced population size may be a major threat if
key societal positions cannot be filled. Population size can also affect a country’s military strength by constraining the size of its armed forces. This in
turn might influence a country’s ability to negotiate or demand favorable
interactions with other countries (Teitelbaum & Winter, 1985).
At the household level, low fertility has a dramatic effect on family composition by shifting the number and character of available kin. For instance,
the first column of Table 2 shows that a singleton born to singleton parents
has no siblings, no aunts/uncles, and no cousins. Assuming no mortality, the
singleton does have two parents and four grandparents. Thus, low fertility
produces small kin networks dominated by the older generations. These relatives may provide considerable support when ego is young; but the burden
of old age care on ego could be significant as the senior generation ages.
If we assume constant fertility across generations of two or three births, in
columns 2 and 3 respectively, we see much larger and more diverse kinship
networks. Finally, at the individual level, fertility may be lower than intended
or desired by women and men. Most persons in most developed countries
state preferences for at least two children. Thus, given the desires of potential
parents, childlessness and one-child families may not be optimal for individual well-being or happiness.
But there are also advantages of low fertility, and some concerns attributed
to subreplacement fertility may be exaggerated. First, when fertility first
falls to low levels, there is a “demographic dividend” because the first age
Below-Replacement Fertility
5
groups to grow larger in an aging society are working age persons (Mason &
Lee, 2006). Thus, for a few decades the dependency ratio (number of persons
too young or old to work divided by number of working age persons)
remains small, and the resources needed for the education and/or care of
dependents is reduced. This allows for lower taxes and/or greater investments in infrastructure in the short term. In the longer term, low fertility
(and a smaller population) places less pressure on natural resources and on
the environment. In addition, concerns about an aging population may be
exaggerated. Older persons, especially if in good health and with support
for life-long learning, can be a valuable resource. Pay-as-you go support
systems for retirees can be adjusted (e.g., by increasing the eligibility age) so
that expenses equal revenues. Finally, the reduced numbers of siblings and
cousins resulting from low fertility may increase intergenerational transfers
advantaging the fewer children that are born. Nonfamilial transfers (e.g.,
by the government), if maintained at a given level, imply higher per-capita
investments in children (because of their smaller number). And finally, for
adults, having fewer children may allow greater time and resources for
activities that are equally or more rewarding than parenthood.
FOUNDATIONAL RESEARCH
DEMOGRAPHIC INTERRELATIONS
The mathematical interrelations of birth, death, and migration rates and
their impacts on the population’s age structure are well understood (Preston, Heuveline, & Guillot, 2001). Several aspects are especially important
for low-fertility populations and were noted in the earlier section. First,
replacement (NRR = 1) can hold under conditions of high and low fertility,
as not all children will survive to adulthood. Espenshade, Guzman, and
Westoff (2003) show that in the period 1995–2000, replacement-level fertility
(measured as the TFR) ranged from 2.1 (e.g., in Europe and the North
America) to 2.7 (in Africa), with the variation produced by higher mortality
in developing countries.
Second, we alluded earlier to positive population momentum—young
age structures (produced by several decades of above-replacement fertility)
guarantee larger proportions/number of women in the childbearing years
over the next generation (approximately 30 years). This momentum can
keep populations growing even as fertility falls to the replacement level or
below. But several decades of below-replacement fertility will result in the
opposite effect—an older age structure with negative momentum (shrinking
population) for approximately a generation, even if replacement-level
fertility returns. Lutz, O’Neill, and Scherbov (2003) show that Europe’s age
structure had modest negative momentum by the year 2000. Continued low
6
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
fertility will increase the duration and magnitude of this negative population
momentum.
COHORT AND PERIOD FERTILITY
Cohort fertility refers to the sum of births that women have over their life,
usually represented by an average (e.g., cohort replacement level equals 2.1
for women surviving to the age 45). Notably, these figures can only be
obtained after each member of the actual cohort has aged through the
reproductive lifespan and completed childbearing. Period fertility, by
contrast, measures births in a given year and is often characterized by the
sum of current age-specific rates, such as the TFR. The TFR thus describes
the number of births a hypothetical cohort would have if they experienced
the current age-specific fertility rates for the rest of their lives (again
replacement-level fertility = TFR = 2.1). This distinction is critical, as an
upward shift in the ages of childbearing would reduce the period TFR even
if (completed) cohort fertility does not change, a phenomenon known as
a tempo effect (Bongaarts & Feeney, 1998). Declining ages at childbearing
increase the TFR relative to cohort rates; postponement of childbearing
has the opposite effect. While this fact is well known, the magnitude and
duration of these timing changes on the TFR are less well known and have
been the focus of much research over the past two decades. This dynamic
is very important for understanding below-replacement fertility because
timing changes, specifically fertility postponement, has contributed greatly
to the very low fertility rates as measured by the TFR. The problem is that
the TFR, as with all period rates, contains information on both the number
(quantum) and timing (tempo) of births. Shifts in the latter (e.g., younger
cohorts having children later in life) can therefore deflate the TFR even if
the quantum remains fixed. Bongaarts and Feeney (1998) provide a simple
measure of this tempo effect and Bongaarts (2002) shows that it frequently
reduces the TFR by 0.15 to 0.35 for several decades. The magnitude of
the effect is directly related to mean shifts in ages at childbearing and the
effect lasts as long as these shifts are taking place. Importantly, these tempo
effects are time-limited—they cannot go on forever—they stop when ages
at childbearing stop increasing. Recent increases in lowest-low fertility in
some European countries are primarily the result of a cessation of fertility
postponement (Goldstein, Sobotka, & Jasilioniene, 2009).
PROXIMATE DETERMINANTS OF LOW FERTILITY
In most countries with below-replacement fertility, women report fertility
intentions that average two births (i.e., at or near the replacement level).
Below-Replacement Fertility
7
Thus the question, why do women frequently have fewer children than they
intend? Bongaarts (2001) proposed a useful macro-level conceptual model for
understanding this discrepancy between intentions and behavior. He decomposes the TFR into a set of scaling factors that represents a current (period)
fertility regime. Specifically,
TFR = Ft × (IP) × (Fu × Fg) × (Fi × Fc).
The level of current fertility (i.e., the TFR) is first adjusted by the factor Ft
for the tempo effects of shifting births toward younger or older ages at childbearing, as suggested by Bongaarts and Feeney (1998) and discussed earlier.
In recent decades, pervasive postponement implies Ft values well below 1.0
(i.e., Ft < 1.0). Thus, TFR/Ft equals the quantum of period fertility (i.e., period
fertility corrected for the effects of shifts in fertility timing).
Key to explaining TFR/Ft (quantum) is the intended parity (IP, the number
of births intended) of young women (e.g., those aged 21–25). In turn, IP is
increased or decreased by a set of model parameters that reflects forces not
incorporated into women’s reports of childbearing intentions. These factors
are not incorporated into stated intentions because they cannot be well anticipated. Factors that increase fertility relative to earlier stated intentions are
as follows:
Fu: unwanted fertility. Unwanted births measured through women’s
retrospective reports, that is, women are asked “at the time you
became pregnant did you intend to have any more children?” Thus,
these pregnancies (and births) would not have occurred in a “perfect
contraceptive” society. Unwanted fertility increases TFR relative to IP
(and Fu > 1.0, estimates for the United States in recent decades would
be 1.1 to 1.15).
Fg: gender preferences. Some couples who intend to have two children will
have strong preferences for at least one son and one daughter (see
Pollard & Morgan, 2002). But given that sex of children is not easily
controlled or anticipated, roughly half of such couples will reach the
two-child goal but not have their preferred gender composition. These
couples may revise their IP upward. Such preferences and behavior
would increase TFR relative to IP (and Fg > 1.0).
Factors that reduce fertility relative to intended parity are as follows:
Fi: impaired fecundity. In general, women (and their partners) will not know
if they are, or when they will become, sub- or infecund. Thus, women
cannot factor impaired fecundity into their IP reports. A few women
are infecund at young ages (1% or 2% at ages 15–19; see Bongaarts &
8
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Potter, 1983), but the proportion increases with age (especially after age
35; see Bongaarts & Potter, 1983, Menken, 1985) and with the prevalence
of some diseases/infections. Male fecundity declines with age also, but
its onset is much later than for females and its pattern of decline less
certain. Clearly, impaired couple fecundity decreases TFR relative to IP
(and Fi < 1.0).
Fc: competition. Women/couples can also revise their IP upwards or downwards depending on their experiences, opportunities, and constraints
(that encourage or compete with childbearing). Following Bongaarts,
we refer to this broad class of constraints and competing opportunities
as competition. Some of this competition may be anticipated and incorporated into IP. What is not, for example, the unanticipated difficulty of
combining career and family responsibilities, of finding a suitable partner, and so on, is reflected in this parameter. In contemporary settings,
Fc is expected to be <1.0.
In this framework, observed fertility reflects the balance of these forces.
Morgan et al. (Hagewen & Morgan, 2005; Morgan, 2003; Morgan & Hagewen,
2005; Morgan & Rackin, 2010; Quesnel-Vallée & Morgan, 2003) have applied
this framework in several different contexts as a conceptual and as an analytic
model.
DISTAL DETERMINANTS OF LOW FERTILITY
The proximate framework given earlier is of limited value because it leaves
fundamental questions unanswered: Why does a collective have a given
intended family size (e.g., two children)? Why does one population have
high levels of unwanted births compared to another? Why is postponement
of childbearing or competition between childbearing and other activities
more intense in one population compared to another? While the conceptual
distinction can be substantively problematic (as discussed later), distal
determinants are often classified as either material or ideological. Material
ones include many of the factors that increase the costs of children—the
inability of children to be economically productive in a modern economy
and the cost of their extended periods of education and job training. Also
included are the opportunity costs of a parent’s foregone labor and/or
leisure activities. Many of these changes are considered to be constituent
parts of economic development and thus take on an inevitable and secular
character. The ideological determinants include “modern” schemas (or
world views) that celebrate independence and self-actualization. Sometimes
these schemas are viewed as powerful forces sweeping the globe because of
Below-Replacement Fertility
9
their intrinsic power or usefulness to individuals (Goode, 1963; Lesthaeghe,
1995; Lesthaeghe & Neidert, 2006) or because they are conflated with the
power, wealth, and prestige of being “modern” (Thornton, 2001, 2005).
This material/ideological distinction is problematic because the structural
and ideological are not separate or additive effects. Predictable behaviors are
the product of both material clues and means and the schemas that explain
and rationalize their use (Johnson-Hanks, Bachrach, Morgan, & Kohler, 2011;
Sewell, 1992, 2005). The material and schematic are both interdependent and
interactive; each can change with repercussions for the other. For instance,
day care for children can reduce the tension between labor force participation
and parenthood and thus increase fertility (Rindfuss, Guilkey, Morgan, &
Guzzo, 2007; Rindfuss, Guilkey, Morgan, & Kravdal, 2010). But this scenario
depends upon day care facilities being available and affordable (material
aspects) and their use must be acceptable (schematic aspects).
CUTTING-EDGE RESEARCH
To avoid long-term decline, the human population will ultimately need to
approximate replacement-level fertility—thus, women, on average, will need
to have two births before the end of reproduction. Obviously, a mean of two
can be produced by very different distributions and women can have births
within a broad age range. The future mean and distribution of family size
and ages at childbearing will almost certainly vary across population groups
and understanding these patterns is a goal of future research. Cutting-edge
research focuses on the proximate determinants identified in the previous
section and an attempt to understand change/stability in them, and in turn,
the reasons for variation in period or lifetime fertility.
Fertility timing. As described, the postponement of childbearing to later
ages is a major reason for below-replacement fertility (Kohler et al.,
2002). This fact is now well known. The remaining key question here is
how much longer before ages of childbearing stabilize. Some countries
(such as Italy) would seem to be approaching a very late pattern of
childbearing with little room for further upward movement. In fact,
the rate of postponement in several European countries has slowed
since 2000 (Goldstein et al., 2009). In contrast to these late patterns, ages
at childbearing are still quite young in places as diverse as the United
States, China, and Thailand. So, monitoring future changes in ages at
childbearing remains important.
Postponement of childbearing can also affect the number of children
women eventually have—fertility postponed is fertility at least partially
foregone. To explain, postponement is associated with lower levels
10
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
of childbearing (Billari & Kohler, 2004; Morgan & Rindfuss, 1999),
but the extent to which this is true varies somewhat across countries
(Lesthaeghe, 2010). The mechanisms that produce this are (i) increasing
sub- or infecundity associated with older ages and (ii) the competition
(or opportunity costs) from other activities that can increase over
time, leading to downward revisions in children intended. Both these
mechanisms are discussed later.
Fertility intentions. It is now widely documented that fertility intentions
(desires or ideals) are generally near replacement levels even when
fertility is well below replacement levels. This is a favorable situation
in that returning to replacement-level fertility requires only that
women/couples have the children they intend to have (judging from
their reports). A different scenario is that future intentions will fall
well below two children, making a return to replacement-level fertility
contingent on both increasing women/couple’s intent for more children
and assisting them in realizing these increased intentions. Thus, a key
question is how persistent is the desire to have at least two children?
There is substantial stability in the time series of the preferred or ideal
family size in the United States (Hagewen & Morgan, 2005). But there is
also evidence that economic conditions can force very low fertility for
a generation so that low fertility (and low-fertility intentions) becomes
the “new normal.” With decades of experience, childlessness and
one-child families become much more acceptable. Goldstein, Lutz, and
Testa (2003) claim this is happening in German-speaking Europe. It
may also be happening in urban China, where the one-child option is
becoming individuals’ preferred family size following a generation of
low fertility encouraged by the one-child policy (Merli & Morgan, 2011;
Merli & Smith, 2002). Stability and change in family size intentions
remain an important research area.
Unwanted fertility. The concept of unwanted fertility is controversial and
its measurement difficult. Much of the controversy can be put aside by
agreeing on its meaning: An unwanted birth is one that occurred to a
woman who did not, at the time of the child’s conception, intend to have any
more children. The measurement issue is more difficult because some
women may not have had a clear intention at the time of conception,
do not remember accurately what the intention was, or are hesitant to
report that a child was unintended. It is commonly assumed that estimates of unwanted fertility are biased downward—primarily because
of a reluctance to identify a child as unintended after the fact. Regardless
of the difficulty of measurement, the concept is an important one that
Below-Replacement Fertility
11
clearly impacts fertility levels and does so differentially across populations. For the United States as a whole, 10–15% of births are estimated to
be “unwanted.” These estimates are stable across the past four decades.
While the measurement of unwanted fertility is not attempted in some
contexts, it is assumed to be much lower in many places. Greater availability and acceptability of abortion likely reduce unwanted fertility.
A large proportion of births (in the United States an additional 20–30%)
are also mistimed—the mother reports that when the child was conceived she wanted to have a child sometime in the future but did not
intend to have a child at this time. These “earlier-than-expected” births
increase period fertility rates because they lower the ages at childbearing (compared to a counterfactual of a perfect contraceptive regime) and
likely increase cohort fertility by nullifying the effect of postponement
that operates via competition (or opportunity costs) at older ages.
Gender preferences. If women/couples intend, for instance, to have two
children and simultaneously hold strong gender preferences, then
they may have an additional child to realize these gender preferences.
In many Western countries including the United States, the desire
for balance (one son and one daughter) is most common. Given that
the sex of children is generally not controlled and that the chance of
a son/daughter is roughly 0.5, 50% of those with two children do
not have their preferred gender composition (a daughter and a son).
Consistent with this argument, there is substantial evidence that having
two children of the same sex increases the intent to have another child
and the likelihood of doing so. In other populations (as with many
in Asia) there is a strong desire to have at least one son. With two
children, approximately one-quarter will not have a son. But with only
one child, the proportion without a son is close to 50%. Note that in
the absence of sex selection, gender preferences affect fertility more
at low fertility levels. At low fertility levels, there are fewer births to
realize any preferred gender composition. The persistence of gender
preferences is an active research question (see Bongaarts, 2013). Pollard
and Morgan (2002) claim that an emerging “gender indifference”
accompanies greater gender equality in the Untied States. If true, the
long-observed desire for a balanced gender composition will cease to
affect fertility intentions and behavior. Using data for the egalitarian
Nordic countries, Andersson, Hank, Ronsen, and Vikat (2006) present
some evidence for the effects of a desire for “balance” and for some
emerging new preferences. There is mixed evidence on the decline of
sex preference in China (Hesketh & Xing, 2006).
At present, the only widely available form of sex preselection is selective abortion—using a sonogram or some other technique to determine
12
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
the sex of the fetus and abort if it is not the preferred sex. Given that
the ratio of male/female births is very close to 1.04 across time, space,
and parity, one can detect the use of selective abortion if sex ratios are
significantly higher than this value.1 Recent evidence suggests that the
wide use of sex-selective abortion in South Korea was reduced by making the practice illegal (Hesketh & Xing, 2006).
Sub- or infecundity. Being unable to conceive or carry a birth to term
can obviously lead women/couples to have fewer children than they
intended. Fecundity declines with age and the decline is more rapid
after the mid-30s. Many women are sub- or infecund by age 40 and
almost all are by age 50. Men’s fecundity declines with age as well but
much more slowly than for women. Fecundity can also be affected by
disease, such as sexually transmitted diseases, so that fecundity can
vary across populations and across time with the prevalence of relevant
diseases.
Some causes of sub- and infecundity are treatable. At present, the inability to conceive via sexual intercourse can sometimes be obviated by in
vitro fertilization (a process by which an egg is fertilized by the sperm
outside the body, e.g., in a laboratory dish/tube, and then implanted
in the uterus). This process was highly controversial in the 1960s but,
while an expensive and intrusive procedure, is becoming commonplace.
Roughly 1 of every 100 US births was conceived via in vitro fertilization
in recent years (2005–2010) and proportions are higher in other countries (Billari, Kohler, Andersson, & Lundström, 2007; Sobotka, Hansen,
Jensen, Pedersen, Lutz, & Skakkebæk, 2008). The development, dissemination, and acceptability of such procedures could reduce the effect of
sub- and infecundity.
Competition. In the proximate determinants framework mentioned earlier,
competition refers to the alternatives to childbearing (or the opportunity
costs) that become apparent at older ages (i.e., were not factored into
fertility intentions at younger ages). For simplicity, let us divide all decisions into one of three domains: family, work, and leisure. At young
ages, the trade-offs between choices in one of these domains and others
may not be obvious. But as the life-course unfolds, decisions to marry
or to have children may impact other domains. To the extent that family
(i.e., fertility-related) events are postponed or foregone because of the
emerging opportunity costs (to career or leisure), we can say that competition is lowering fertility. An extreme case would be where mothers
1. Other possible reasons for high sex ratios would be infanticide or neglect of girl babies or a failure
to register them. These alternatives may be relevant in some contexts but not in the recent case of very high
sex ratios for third and fourth births in South Korea, for instance. Sex-selective abortions are considered
the more important mechanism producing abnormally high sex ratios in India and China after 2000.
Below-Replacement Fertility
13
find it very difficult to work in full-time jobs because of the institutional
incompatibility of family and work. McDonald (2000) has conceptualized this as variable gender equity across institutions. In recent decades,
the degree of gender equity in formal education and market employment has increased dramatically. But there is, he argues, substantial variability in movement toward gender equity in the family. When gender
equity in the family domain lags behind that in other institutions, many
women may forego marriage, childrearing, or larger families. Very low
fertility may result.
KEY ISSUES FOR FUTURE RESEARCH
A key question for future research: Is below-replacement fertility inevitable?
There are three possible answers. First, the cross-country and cross-time associations suggest that with economic development and associated changes,
fertility decline from high levels is inevitable. These declines are driven by
a combination of institutional/material changes and the diffusion of “modern” schema or ideas. Some argue that these forces are far from running their
course and that as a result below-replacement fertility will be a broad-based
twenty-first century crisis (Lesthaeghe, 2010).
A second position is that below-replacement fertility is transitional.
Myrskyla, Kohler, and Billari (2009) analysis of cross-country and cross-time
data leads them to argue that advanced levels of development lead to an
upturn in very low fertility. But their analysis and discussion do not identify
the mechanisms that lead to the reversal and thus counter the arguments
given. Ongoing work by Myrskyla, Kohler, and Billari (2012) suggests that
the upturn associated with advanced economic development is concentrated
in countries that have attained greater levels of gender equity in the family
institution.
Third, Morgan (2003), consistent with the notion of differential levels and
differential response, argues that existing diversity will not disappear. Some
developed countries have never experienced fertility well below replacement
and have stable and sustainable fertility at near-replacement levels (e.g., the
United States). For other countries, a full-blown crisis exists (e.g., Japan).
Inability to even approximate replacement-level fertility on a decadal time
scale is a crisis because the implications of very low fertility are clear—either
dramatic population decline or very high levels of immigration. Given this
fact, there are powerful incentives to identify and pursue policies that facilitate replacement-level higher fertility. Identifying policies that work and
policies that work better/worse in particular contexts are very important
contemporary research questions (see McDonald, 2006).
14
EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
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FURTHER READING
Bongaarts, J. (2001). Fertility and reproductive preferences in post-transitional societies. Population and Development Review, 27(Supplement: Global Fertility Transition), 260–281.
McDonald, P. (2000). Gender equity in theories of fertility transition. Population and
Development Review, 26(3), 427–439.
Morgan, S. P. (2003). Is low fertility a twenty-first-century demographic crisis?
Demography, 40(4), 589–603.
Morgan, S. P., & Taylor, M. G. (2006). Low fertility at the turn of the twenty-first
century. Annual Review of Sociology, 32, 375–400.
S. PHILIP MORGAN SHORT BIOGRAPHY
S. Philip Morgan is Director of the Carolina Population Center and Alan
Feduccia Distinguished Professor of Sociology at the University of North
Carolina at Chapel Hill. He is former president of the Population Association of America and former editor of the journal Demography. He has chaired
the sociology departments at the University of Pennsylvania (1993–1996) and
Duke University (2002–2008). Morgan was Director of Duke’s Social Science
Research Institute 2008–2012 and is emeriti Norb R. Schaeffer Professor of
International Studies at Duke University.
Morgan’s work focuses on family and fertility change (over time) and diversity (across groups). Much of his work has focused on the United States but he
has collaborated on projects focusing on other countries, both developed and
developing. Morgan’s recent NIH-funded projects have focused on developing new models of family and fertility change and diversity, late twentieth
Below-Replacement Fertility
17
century fertility trends and differences in the United States, emerging low
fertility in the Islamic Republic of Iran, and the association between fertility
intentions and behavior in the United States.
Also see http://www.cpc.unc.edu/people/fellows/bio?person=morganp
RELATED ESSAYS
Below-Replacement Fertility (Sociology), S. Philip Morgan
Limits to Human Longevity (Sociology), Samuel H. Preston and Hiram
Beltrán-Sánchez
Demography and Cultural Evolution (Anthropology), Stephen Shennan
Recent Demographic Trends and the Family (Sociology), Lawrence L. Wu