Population Projections Branch
Population Division
Bureau of the Census
U.S. Department of Commerce
Washington, DC 20233
(301) 457-2428
January 2000
Population Division Working Paper No. 38
ABSTRACT
This working paper discusses the methodology and assumptions used to develop the recently released projections of the population of the United States from 1999 to 2100. The new series includes projections of the population by single year of age, sex, race, Hispanic origin, and nativity. While the basic methodology used to produce these projections is the same as in earlier Census Bureau national population projections, there have been changes, in both the time horizon and reference dates of the projections, as well as in the specific methods used to estimate population change. The extension of the series to 2100 carries the projections 20 years further into the future than any series previously issued by the Census Bureau. For the first time, projection results include a break on nativity, defined dichotomously by the presence or absence of U.S. citizenship at birth, as well as its cross-classification with other variables. Also new with this series is the projection to quarterly reference dates, allowing users to view the national population seasonally, or simply to select annual reference dates other than July 1. In addition, international migration in the new series is allowed to vary over time, remaining somewhat lower than the constant value in the previous series for the first two decades of the century, but reaching considerably higher levels than in the previous one after 2020. Fertility rates in both models are allowed to change very little over time. However, fertility rates by race and Hispanic origin are allowed to converge in the new middle series, whereas in the previous middle series they remained constant within race and origin category. Finally, the new mortality assumptions show more improvement in life expectancy for all racial and Hispanic origin groups, except the non-Hispanic White population, than did the assumptions of the previous projection series.
* This paper reports the results of research and analysis undertaken by Census Bureau staff. It has undergone a more limited review than official Census Bureau publications. This report is released to inform interested parties of research and to encourage discussion.
| Table A. | Comparisons of Total Population, Present Series with 1994-Based Projections |
| Table B. | Projected Total Fertility Rates by Race and Hispanic Origin, 1999 to 2100 |
| Table C. | Projected Life Expectancy at Birth by Race and Hispanic Origin, 1999 to 2100 |
| Table D. | Projected Migration by Race and Hispanic Origin, 1999 to 2100 |
| Table E. | Major Components of Net International Migration to the United States, 1991 to 2100 |
| Table F. | Population and Dependency Ratios per 100 Persons, Four Series, 1990 to 2100 |
| Table G. | Standardized Rates of Foreign-Born Emigration, 1991 to 2100 |
This working paper discusses the methodology and assumptions used to develop the recently released projections of the population of the United States from 1999 to 2100.1 The new series includes projections of the population by single year of age, sex, race, Hispanic origin, and nativity.2 While the basic methodology used to produce these projections is the same as in earlier Census Bureau national population projections, there have been changes, in both the time horizon and reference dates of the projections, as well as in the specific methods used to estimate population change. The extension of the series to 2100 carries the projections 20 years further into the future than any series previously issued by the Census Bureau. For the first time, projection results include a break on nativity, defined dichotomously by the presence or absence of U.S. citizenship at birth, as well as its cross- classification with other variables. Also new with this series is the projection to quarterly reference dates, allowing users to view the national population seasonally, or simply to select annual reference dates other than July 1. In addition, international migration in the new series is allowed to vary over time, remaining somewhat lower than the constant value in the previous series for the first two decades of the century, but reaching considerably higher levels than in the previous one after 2020. Fertility rates in both models are allowed to change very little over time. However, fertility rates by race and Hispanic origin are allowed to converge in the new middle series, whereas in the previous middle series they remained constant within race and origin category.3 Finally, the new mortality assumptions show more improvement in life expectancy for all racial and Hispanic origin groups, except the non-Hispanic White population, than did the assumptions of the previous projection series.
Aside from these changes, the basic structure of the product closely resembles previous Census Bureau projections. Race consists of four categories; 1) White, 2) Black, 3) American Indian, Eskimo, and Aleut, 4) Asian and Pacific Islander (API). Hispanic origin is dichotomous: the two categories are Hispanic and non-Hispanic. All race and Hispanic origin detail incorporates the full distribution of eight cross-categories. As in previous projections, we have provided alternate series, defined by alternative assumptions on the three major determinants of population change, fertility, mortality, and migration. However, the interpretation of "low" and "high" assumptions has changed somewhat with respect to previous projections. In the present series, the extreme assumptions are presented primarily with the purpose of illustrating a degree of uncertainty around the central series. They should not be interpreted as alternative scenarios to be adopted on their face value, as they are not intended to be probable developments.
The results of the new projections are not substantially different from those of the last series issued by the Census Bureau, when the comparison is made across matching dates.4 Both middle series show the national population growing at a large fraction of one percent per year until 2050. Both series show the rate of growth declining over time, from approximately 0.9 percent per year in 1999 to about 0.7 percent per year around 2050. These results are shown in Table A. The lack of major difference in the population results for the middle series between the new and old projections can be explained in large part by the deterministic nature of the age distribution of the base population, and the predictability of its aging over time. This initial age distribution represents essential information that is conveyed to the projected series. The means of its conveyance is the cohort component method, discussed in the section that follows.
THE METHOD OF PROJECTING THE POPULATION
The method used to produce projections of the United States population for future reference dates from a current base population reflects three fundamental principles.
1) The projections are demographic. Future populations are derived from a base population through the projection of population change by its major demographic components, births, deaths, and migration.
2) The projection of the demographic components of change is driven by the composition of the population by age, sex, race, Hispanic origin, and nativity, and the way these variables determine the propensity to bear children, die, and migrate to or from the United States.
3) The definition of the population with respect to who is included and the characteristics of included people remains the same throughout the projection period. We refer to these definitions collectively throughout the work as the "population universe." This concept embraces such issues as the inclusion or exclusion of people uncounted by a census, the rule defining residency in the United States, and the way we classify people by age, race, and Hispanic origin. The population universe for these projections is defined primarily by the 1990 census, albeit with some modifications.
The first two principles mandate the use of "cohort component" methodology in projecting the population. Under this methodology, knowledge of the age and sex composition of the population at any point in time is fundamental to the projection of the population. Knowing the age-sex distribution at one date allows us to impute the age-sex distribution of those still alive at later dates, since sex does not change while age advances with the passage of time. This knowledge also allows the projection of demographic behaviors such as fertility, mortality, and the propensity to migrate, differentiated by age. Thus, current age-sex distribution influences future age-sex distribution through the components of change, as well as the aging of people over time.
To comply with the second principle described above, standard cohort component methodology is applied to each racial and Hispanic origin category as if they were separate populations. Race and Hispanic origin are chosen because they are reflected in a wide range of administrative data in the United States, and because their categories are distinct with respect to rates of fertility and mortality. Nativity, defined by citizenship at birth, is used to distinguish rates of emigration from the United States. The foreign-born population is also projected separately, but without births, since children born within the United States are U.S. citizens at birth (native) by United States law.
The third principle, preservation of the population universe, imposes the need for a special adaptation of cohort component methodology. The population universe for these projections is defined by the decennial census of April 1, 1990, with some adaptations. In certain critical regards, the distribution of this population by age, sex, race, and Hispanic origin does not submit well to projection by the cohort component method. It is characterized by a pattern of underenumeration highly differentiated by age, as well as some misreporting of age, and a distribution by race and Hispanic origin substantially different from what appears in other administrative data sources. In order to preserve these irregularities of the age detail in the projected population while maintaining the applicability of the cohort component method, we apply the standard method to a synthetic base population with characteristics "friendly" to the method. We then adapt the resulting projections back to the actual base population universe. This process is known as "inflation-deflation." The following sections discuss this modified cohort component methodology.
The current series of population projections are
"launched" from an estimated resident
population by age, sex, race, Hispanic origin,
and nativity, as of January 1, 1999.5 While we
refer to this population as the base population
for the series, the population universe for the
series is defined by the estimates base
population of April 1, 1990. The estimates base
population is the population that forms the base
for national-level estimates produced for the
Census Bureau's population estimates program.
This program yields the projections base
population of January 1, 1999. We refer to the
population series from April 1, 1990, to January
1, 1999, as the base series for the projections.
This series, and its associated estimates of the
demographic components of change, form the
data base from which most of the assumptions
regarding fertility, mortality, and migration in
the projections are formulated.
The base population universe is derived
primarily from the 1990 census and consists of
residents of the 50 states and the District of
Columbia. The universe excludes the U.S.
Armed Forces overseas and citizens ordinarily
residing outside the United States. It is subject
to net underenumeration in the 1990 census,
with the exceptions of adjustments for net
underenumeration in certain localities resulting
from the Census Test of 1995. The race
distribution is modified to comply with the
Office of Management and Budget Directive 15,
which places all individuals within one of four
major racial groups, 1) White, 2) Black, 3)
American Indian, Eskimo, and Aleut, and 4)
Asian and Pacific Islander.6 The age
distribution is modified to eliminate the effect of
inconsistencies between age and year of birth in
the census, arising primarily from delayed
reporting of an age inconsistent with the
decennial enumeration date (April 1, 1990).7
The cohort-component method for estimating
and projecting a population, as previously
indicated, is distinguished by its ability to
preserve knowledge of an age distribution of a
population (which may be of a single sex, race,
and Hispanic origin) over time. It is a special
case of a component method, which is defined
simply by the use of estimates or projections of
births, deaths, and net migration to update a
population.8 In its simplest statement, the
component method is expressed by the
following equation:
where
Pt = population at time t;
Components of population change are estimated
or projected separately, and applied to equation
(1) recursively to produce a series of
populations. We have not specified the
measurement unit of time, so the interval from t-1 to t
may be of any duration.
The cohort-component method is based on
similar logic for individual age groups,
recognizing that the source population for a
given age group is the population at time t-1 in
the adjacent younger age group. For the initial
age group, it is births during the interval from t-1 to
t. For the moment, let us assume that the
time unit is one year. The equation is replaced
by two equations, depending on whether the age
group is zero (meaning under 1) or any other age
as of the last birthday, denoted by a.
Pt(a) = Pt-1(a-1) - Dt-1,t(a) +
Mt-1,t(a) (3)
In the case of deaths (D) and net migration (M),
the interval a denotes age of decedents or
migrants at time t--not necessarily equal to age
at time of death or migration. Each of the terms
in equations (2) or (3), whether defined as a
population or a number of events, relates to
people born in a particular year (from t-a-1 to t-a).
Such a group is known as a birth cohort,
hence the term "cohort component method."
While it is essential that age and time in
equations (2) and (3) be measured in the same
unit, there is no requirement that the interval be
one year. For most applications, the time unit
employed is either a single year or a five-year
interval.
The current projections are somewhat unusual in
this regard, in that the time interval used is a
calendar quarter. There are various reasons for
the choice of quarter-year intervals. The base
date for the series is April 1, 1990, while the
reference date most frequently cited tends to be
mid-year, or July 1. Data sources used to
estimate the components of population change
for the base series are produced for varying time
intervals. Births and deaths are produced by
calendar year; immigration data by federal fiscal
year (ending September 30). Although these
event data are based on administrative records
coded by month, there would be no cost
advantage in standardizing them to any
particular year on the calendar. We therefore
use the calendar quarter because it is the largest
common subinterval of the various reporting
intervals in the data. Extending the series to
future dates by quarter facilitates the integration
of future assumptions with base series data, and
yields an added bonus of flexibility, in allowing
users to either utilize the quarterly series or
select any quarterly date for an annual series.
The cohort-component method described above
requires that the base population age
distribution observe the fundamental attribute
that birth cohorts are affected only by mortality
and migration as they age. The population
universe specified by the estimates base
population does not observe this simple
requirement for two salient reasons. First, the
universe reflects underenumeration of the
population at certain ages. Second, the
misstatement of year of birth in the census
causes spurious irregularities in the age
distribution, especially "heaping" on certain
terminal digits. If we did not employ the
inflation-deflation method, the application of the
cohort-component method would have the effect
of advancing the age pattern of these
irregularities over time, rendering age groups
uncomparable from one year to the next.
The inflation-deflation method is a procedure
designed to overcome this problem. It can be
summarized in six steps, each of which is
carried out for each sex, race, Hispanic origin,
and nativity category.
1) An alternative base population universe, that
is deemed to eliminate, or at least minimize the
described irregularities in the age distribution, is
utilized as a base population for cohort
component projections. The population used
here, known as a Demographic Analysis
Population (DA population), is developed from
an amalgam of historical data on births, deaths,
and migration for ages under 65, and a
population of Medicare enrollees for ages 65
and over. The reference date for this population
is April 1, 1990.9
2) An "inflation-deflation factor" is computed
for each single-year age group, as the ratio of
the estimates base population to the DA
population in that group, both as of April 1,
1990. The resulting factors may be less than or
greater than one, although they are more likely
to be less than one, because the net effect of
census underenumeration, census duplication,
age heaping, and discrepancies in racial
classification are more likely to be negative than
positive.
3) The DA population by age is updated from
April 1, 1990 to January 1, 1999, then projected
to future dates, by the cohort-component
method, per equations (2) and (3), as described
earlier. Births, deaths, and foreign-born
emigrants by age are derived by application of
rates, to be discussed in the next section.
4) The population in each age group is
multiplied by the inflation-deflation factor for
the group, for each quarterly reference date.
While the factors are defined for full-year age
groups, they are assumed to be constant across
quarter-year ages within the full-year groups.
5) The actual base population for the
projections, the estimates base universe, is
projected using the simple component method
without distribution by age, per equation (1)
described earlier. The total number of births,
deaths, and foreign-born emigrants from January
1, 1999, forward are those derived in step 3),
with results summed across age groups.
Because the number of births is considered to be
adjusted for underregistration, births are
reduced by a factor to reflect what would
actually be registered. The balance of the
migration components are derived numerically
via the projection assumptions, to be discussed
later in this report.
6) A pro-rata adjustment is used to force the age
distributions from step 4) to match the
population totals from step 5).
The application of the cohort-component
method, as stated in equations (2) and (3)
requires numerical projections of births, deaths,
and net migration. The formulation of
assumptions (see below) yields numerical
projections of the net migration component
(without the effect of foreign-born emigration)
for the full matrix of characteristics for each
quarter. These numerical projections are
exogenous, in the sense that they are unaffected
by population. However, the assumptions yield
population-based rates of fertility, mortality and
foreign-born emigration. Therefore, the
resulting numerical projections of these
components are endogenous, meaning they are
themselves partly a consequence of the
projected population. The derivation of
numerical projections of endogenous
components is part of step 3) in the procedure
described in the previous section. Because the
projection procedure produces the population at
quarterly intervals, the application of rates
occurs for each quarterly interval and by quarter
year of age. Mortality and emigration rates are
applied to the mid-quarter population of each
age group as the population is generated, taking
account of the fact that mortality and migration,
along with the exogenous components, affect
the mid-quarter population in its generation.
Equation (3) is applied to produce all quarter-year
age groups for the beginning of the
succeeding quarterly time interval. Fertility
rates are then applied to mid-quarter populations
of female age groups to generate births, and
mortality and emigration rates for first-quarter
infants are applied to complete the youngest age
group, per equation (2).
An exception to this procedure occurs in the
case of the foreign-born population. Foreign-
born and native women of the same age, race,
and Hispanic origin are assumed to have the
same fertility and mortality rates, since the base
data to differentiate fertility and mortality by
nativity were unavailable. It was therefore
convenient to project the population of both
nativity categories together, then project the
foreign-born population by assuming zero
fertility, since all newly born are native by
definition. The native population could then be
determined by subtracting foreign-born from
total population.
The projection assumptions produce rates for
full years of age, and full-year rates are assumed
constant across quarter-year subdivisions of age.
However, empirical observation of the
seasonality of death and childbearing is
considered in the derivation of deaths and births
by quarter. Data from the National Center for
Health Statistics for calendar year 1996 provide
the basis for the seasonal distribution of annual
births and deaths.10 Foreign-born emigration
rates are projected from information for an
entire decade, so no information on seasonality
was available, and none was assumed. For
foreign-born emigration the quarterly series was
determined by the quarterly application of
emigration rates to the foreign-born population.
The new projections do not include a systematic
measurement of uncertainty. However, in the
development of each of the component
assumptions, we established high and low
variants based on a reasoned assessment of what
represented "extreme" values. Applying variant
assumptions for each component individually
resulted in the range of population series that
would be identified with the maximum likely
variance of that component. To produce our
lowest and highest series, we combined the
extreme values of all three major components
that favored, respectively, the lowest and
highest population growth. Therefore, the
extreme projections do not represent likely
scenarios in themselves, but purport to represent
the extremes between which most likely
outcomes should fall. Fertility and international
migration imposed a greater uncertainty on the
projections than did mortality, because
childbearing and mobility, to a greater extent
than death, are functions of individual and
collective decision-making that are difficult to
forecast accurately.
The total fertility rate (TFR) for the United
States has remained fairly constant since 1989.11
As of 1997, the total fertility rate was 2,032.5
births per 1,000 women.12 Evaluating the
fertility trends of the recent past is useful in
establishing the immediate direction of fertility.
However, such evaluation provides little
information regarding the trend for the next 100
years. To formulate our fertility assumptions,
we relied on demographic theory, analyzed past
and current national and international fertility
trends, and made use of data on birth
expectations from a national survey.
Assumptions and Methodology
Short-term Fertility Assumptions
Long-term Fertility Assumptions
Long-term Assumptions for Fertility by Race and Hispanic
Origin
Fertility trends for particular Hispanic and
Asian and Pacific Islander groups also diverge
from national trends. These groups, however,
are comprised predominately of foreign-born
populations which generally maintain higher
fertility rates than native women of the same
race and origin group.19 According to
assimilation theory, the longer an immigrant
female remains in the U.S., the more likely she
will be to adopt fertility behaviors of native
women of the same racial or Hispanic origin
group. Researchers have found evidence to
support the assimilation theory in regard to
foreign-born and native fertility trends within
the United States.20 Therefore, fertility rates
among Hispanic and Asian and Pacific Islander
women are assumed to converge with national
levels. In addition, exogamy and interracial
childbearing are projected to increase in the
future, further diminishing fertility differentials
among racial and Hispanic origin groups.
Methodology
The 1995 National Survey of Family Growth
Cycle V (NSFG Cycle V) data set were obtained
and birth expectation data were calculated for
women 15 to 44 years of age.22 Total fertility
rates were adjusted by reducing birth
expectations for non-Hispanic Whites and non-Hispanic
Blacks as proposed by the van Hoorn
and Keilman method and supported by findings
from the National Center for Health Statistics.23
The model developed by van Hoorn and
Keilman adjusts birth expectations to account
for issues of uncertainty, period fertility, and
"limiting factors." Because the NSFG Cycle V
adjusts for item non-response and total non-
response, and the period adjustment is
unnecessary as specified by the proposed
method, the birth expectations were only
reduced by 10 percent to account for the
"limiting factors," which generally result in
overestimation.
Once births by single year of age of the mother
were calculated, a single set of age-specific
fertility rates were calculated and imputed to
1998 for purposes of the projections. Because
separate short- and long-term assumptions were
made, rates for each of the five race and
Hispanic origin groups were interpolated
separately from 1998 to 2025 and 2025 to 2100
to reach target total fertility rates. Age-specific
fertility rates for Whites, Blacks, American
Indians, and Asian and Pacific Islanders, with
the Hispanic and non-Hispanic component of
each group combined, were calculated after
completing the projections.
Low and High Fertility Assumptions
At the present time, significant mortality
differentials exist between males and females
and between race and ethnic groups in the U.S.
Life expectancy at birth (hereafter abbreviated as
"life expectancy") has generally increased
throughout the century for both sexes and for
Whites and Blacks. For other race and ethnic
groups, however, data are too scarce to identify
trends over time. Throughout the 20th century,
differentials in life expectancy between males
and females, and between Blacks and Whites,
have been quite irregular, increasing in some
periods, and decreasing in others. During the
1990's, the differentials between males and
females, and between Blacks and Whites, have
tended to narrow. By 1997, life expectancies
for males and females had reached 73.6 and 79.4
respectively.24
In order to project age-specific death rates
(ASDRs) and life expectancies, we construct
current ASDRs by sex, race, and Hispanic origin
groups for use as a projection base, using deaths
provided by the National Center for Health
Statistics (NCHS) and our own population
denominators. Readers with an interest in the
full details of these procedures are referred to
the latter part of this section. As discussed later,
data are not available to allow accurate
measurement of ASDRs and life expectancies
for all race and Hispanic origin groups.
Table C shows fairly large differences in life
expectancy between males and females, and
across race and Hispanic origin groups for the
first projected year (which is very similar to the
1998 base period).25 Our projections assume a
narrowing of the observed mortality gaps among
race and Hispanic origin groups over time, such
that by year 2100 the ASDRs of the race and
Hispanic origin groups are much closer together
than what is observed today. We also assume a
slight narrowing of the sex gap in mortality over
the next 100 years. As discussed in detail in the
next section on assumptions and methodology,
our projection models are based on a mixture of
projected data by other researchers, with our
own research incorporated into the models. For
example, we use the research of Lee and
Tuljapurkar as a source of overall life
expectancy levels for males and females
separately (without regard to race and Hispanic
origin) for year 2065, but we use our own
extrapolations for dates beyond that.26 Thus,
Lee and Tuljapurkar's research influences our
assumption about the future sex differential, but
our assumptions about future race and Hispanic
origin differentials are generated internally. A
few methodological considerations led to our
assumption of declining race and Hispanic
origin mortality differentials. First, such
differentials, even for the current period, are
difficult to estimate accurately. The definitions
of race and origin are themselves mutable and
ever-changing. Second, and related to the
above, increasing rates of intermarriage may
serve to reduce differentials in the future.
Assumptions and Methodology
A few different sources of information entered
into the construction of the year 2150 target life
tables for males and females. First, we used
projected life expectancies for total males and
females (all race and Hispanic origin groups
combined) for the year 2065 produced by Lee
and Tuljapurkar,29 which updates the original
Lee-Carter stochastic time-series model.30 For
our middle series, these year 2065 life
expectancies are 83 for males and 88 for
females.31 Second, we used expert opinion
regarding how much faster the mortality rates of
some age groups will decline in the future
relative to the others. These were obtained by
utilizing the results of a survey conducted at the
1997 mortality projection conference sponsored
by the Society of Actuaries.32 We use the term
"decline" to mean annual average rate of
mortality decline in the rest of this section.
Survey results are shown below.
Base Population and Base Series
Pt-1 = population at time t-1;
Bt-1,t = births, in the interval from time t-1
to time t;
Dt-1,t = deaths, in the interval from time t-1
to time t; and
Mt-1,t = net migration, in the interval from time
t-1 to time t.
The Inflation-Deflation Method
Derivation of Births, Deaths, and Foreign-Born
Emigration from Rates
Reflecting Uncertainty of Assumptions Through High and
Low Variants
ASSUMPTIONS FOR THE COMPONENTS OF CHANGE
The following sections describe the assumptions
that determined future levels of fertility,
mortality, and international migration, for
application of the methodology described above.
The previous projections assumed constant
fertility throughout the projection period by race
and Hispanic origin for the middle series. The
fertility assumptions for the current set of
projections allow fertility to vary for the short-
and long-term by race and Hispanic origin.
Fertility trends are projected separately for non-
Hispanic Whites, non-Hispanic Blacks, non-
Hispanic American Indians, non-Hispanic Asian
and Pacific Islanders, and Hispanics.
To project the short-term fertility trends, the
period from 1999 to 2025, we assumed fertility
levels will reach target total fertility rates
determined by birth expectations data and
demographic theory. Once collected and
analyzed, birth expectations are used to
represent the total number of children ever born
for three of the five race and Hispanic origin
groups in 2025. The birth expectations are
further adjusted according to the method
developed by van Hoorn and Keilman.15
Because birth expectations data for non-Hispanic
American Indians and non-Hispanic
Asian and Pacific Islanders are deficient, total
fertility rates are derived for these groups by
assuming they converge halfway to
"replacement level," a total fertility rate of
2,100 per 1,000 women, by the year 2025. The
total fertility rate for non-Hispanic American
Indians and non-Hispanic Asian and Pacific
Islanders is assumed to decline by .006 and .002
births per woman per year respectively between
1998 and 2025.
Beyond the year 2025, we relied upon an
analysis of past and current national and
international fertility trends and demographic
theory to formulate our assumptions. However,
a review of fertility trends and existing research
by Westoff16 and Day17, among others, provide
no definitive long-term direction for the fertility
of the United States. Therefore, following 2025,
long-term total fertility rates for each race and
Hispanic origin category are assumed to move
regularly toward replacement level, reaching 2.1
in 2150. The rate of increase or decrease to the
total fertility rates differ among the five race and
Hispanic origin groups. Table B displays the
total fertility rates by race and Hispanic origin
for the projections period of 1999 to 2100.
Because the long-term assumptions project a
slow stabilization of the total fertility rate, in
about 150 years, the fertility rates of racial and
Hispanic origin groups are posited to slowly
converge. Historically, such convergence was
not exhibited by non-Hispanic Blacks,
particularly in reference to non-Hispanic
Whites. While non-Hispanic Whites maintained
total fertility rates near 2.0 and 2.1 between
1989 and 1993, non-Hispanic Blacks
experienced rates between 2.4 and 2.6.18
However, since 1993 non-Hispanic Black
fertility has declined and converged toward non-Hispanic
White fertility rates.
The middle series age-specific fertility rates
were calculated for women 10 to 49 years old by
single year of age and five race and Hispanic
origin groups from 1999 to 2100. To begin,
single year age-specific fertility rates were
calculated using birth registration data from the
National Center for Health Statistics and
population estimates for 1996 to 1998. Age-specific
fertility rates by race and Hispanic
origin for 1996 and birth registration data by
race and Hispanic origin (adjusted for under-registration)
for 1997 and 1998 were available.
However, at the time of production, birth
registration data by age of the mother were not
available for 1997 and 1998. Therefore, total
births by mother's age and race were calculated
for 1996, 1997 and 1998 using indirect
standardization. The base population used to
create the age-specific fertility rates was the
mid-year population of the Demographic
Analysis (DA) universe, as defined for purposes
of the inflation-deflation method, described
above.21
The fertility assumptions for the highest and
lowest series are based on a proportional
increase or decrease relative to the middle
series. The range widens steadily as an
acknowledgment of increased uncertainty,
although the series do not represent statistical
confidence intervals. The assumptions required
the calculation of an increase and decrease to
the middle series age-specific fertility rates by a
series of proportions. The proportions were
interpolated linearly from zero in 1998 to reach
15 percent in 2025, and from there to 25 percent
in 2100. Inflating the middle series fertility
rates by this series of proportions yields the high
variant, while deflating it by the same
proportion yields the low variant. The total
fertility rates by race and Hispanic origin for the
middle, low, and high series for the projections
period of 1999 to 2100 are detailed in Table B.
The previous projections report projected
survival rates primarily by extrapolating past
annual rates of change, separately by age, sex,
race and Hispanic origin group.27 In the current
set of projections we create male and female
target life tables corresponding to a far-future
year (2150, which is beyond our projection
horizon), and we force the base life tables
(which are discussed later) for the separate race
and Hispanic origin groups to converge over
time to these target life tables.28 The end result
of this process is a slight narrowing of the sex
difference in mortality over time, and a more
prominent narrowing of race and Hispanic
origin differences over time, such that by year
2100 the race and origin groups are quite a bit
more similar in their life expectancy than they
are today. The year 2150 was chosen as a target
for race and ethnic convergence because it
allowed our models to yield plausible rates of
mortality decline over time for each sex, race,
and Hispanic origin group.
| Age 0-14 vs. 65+ | Age 15-64 vs. 65+ | |
| "Next 10 years" | 2.1 | 1.3 |
| "After 25 years" | 1.6 | 1.2 |
For example, most participants at the Society of Actuaries conference predict that the decline experienced by the age group under 14 years will be 2.1 times that of the age group 65 years and older over the "next ten years."
Instead of "next 10 years" and "after 25," as reported in the Society of Actuaries report, we used two time periods: 1990 to 2020 and 2021 to 2150. This was done because one of our projection base years is 1990 (as discussed later), and we wanted to adapt the Society of Actuaries report data to fit our data requirements. We also constrained the age group 65 years and older decline to be the same for the two time periods, since there is no information in the Society of Actuaries report about the 65 years and older decline for time periods before year 2020.
With the above-mentioned projected life expectancies and ratios, and with a base set of ASDRs by sex, race, and Hispanic origin, we obtain declines out to the year 2150 that satisfy the above conditions (four ratios representing age patterns of decline over time) as well as the conditions involving life expectancies for year 2065 as explained above. Given the assumed fixed relationships between the declines across the broad age groups over time, there is only one trend that needs to be derived, which is the decline for the age group 65 years and older. We then use these declines to produce ASDRs and life tables for males and females in 2150. This is done by a simple extrapolation which assumes that the declines that led to year 2065 life tables will continue thereafter. Projected ASDRs for each sex, race, and Hispanic origin group are then derived by interpolating between the 1990 base ASDRs (by each sex, race, and Hispanic origin) and the year 2150 ASDRs, a procedure which reflects our race and Hispanic origin convergence assumption. This yields life tables for the ten groups which are consistent with the year 2065 male and female life expectancies (all race and origin groups combined) projected by Lee and Tuljapurkar.
However, we do not present life expectancies and ASDRs for years beyond 2100--those data points are beyond our projection horizon, and were developed solely to achieve a narrowing of differentials over time within the projection period (to 2100). Year 2150 was chosen because it yields the most acceptable rates of mortality decline for the sex, race, and ethnic groups. For example, using year 2100 as a target life table would yield too rapid rates of mortality decline for some subgroups, in our opinion.
Table C shows projected life expectancies for each of the ten specific sex, race, and Hispanic origin groups. Life expectancies for aggregations of these groups (White, Black, American Indian, and API) are based on life tables we constructed at a later stage using weighted averages of ASDRs. To weight the averages, we used the separate sex and race populations (in the case of race aggregation) or the separate sex populations (in the case of sex aggregation) (not shown).
Low and High Mortality Assumptions
As discussed earlier, the year 2150 target life
tables for males and females are based partly on
Lee and Tuljapurkar's projected life
expectancies for year 2065 (83 for males, 88 for
females). The low and high life expectancy
series are constructed using the same
methodology and data as the middle series,
except that different values are used for year
2065 life expectancies. For the low life
expectancy series, we use 81 and 86 for males
and females respectively. For the high life
expectancy series, we use 86 and 90 for males
and females respectively. These low and high
values are the lower limit and upper limit
respectively of the 95 percent confidence
interval reported by Lee and Tuljapurkar.33
Thus, we end up with a set of male and female
target life tables (year 2150) for each of the
three series. The procedures for producing the
ASDRs for all intervening years between the
base and target (year 2150) years, and for the
sex, race, and ethnic groups, are identical across
the three series. As expected, there is an
increasing divergence of life expectancies over
the course of the projection period between the
low and high series, for any given sex, race, and
ethnic group.
Two Sets of Base Mortality Rates: General Issues
While the general procedure to obtain projected
ASDRs for all sex, race, and Hispanic groups
involves interpolation between a base set of
ASDRs (one set for each sex, race, and Hispanic
origin subgroup) and year 2150 target ASDRs
(one set for each sex, as described earlier), the
procedures are, in fact, more complicated
because we use two sets of base ASDRs at
different stages of the projection process.
We first create the long-term series of ASDRs out to year 2150 using 1990 ASDRs as a starting point. We call these 1990 ASDRs the "primary base." We construct these base ASDRs using 1990 deaths from NCHS and 1990 census population denominators, by sex, race, and Hispanic origin. We consider these to be more appropriate for projecting a long-term series, as compared with rates which use our postcensal population estimates as denominators. Yet, we prefer to have a smooth transition from our national estimates in 1998 to our national projections for subsequent years. In order to avoid sharp breaks between the ASDRs for 1998 (and earlier) assumed in our national estimates, and those assumed for the projections for 1999 and beyond, we subsequently create a new set of ASDRs for 1999 through 2020 for use in the projections. These new ASDRs are produced by interpolating from the 1996 to 1998 combined ASDRs of the national estimates series (which we refer to here as the "secondary base") to the year 2021 ASDRs of the projection series that was based on the primary base, for each sex, race, and Hispanic origin group. We call these new and more consistent ASDRs the "bridge series," and we replace the original 1999 to 2020 projected ASDRs with this bridge series, in order to smooth out the transition from national estimates to national projections.
Base Mortality Rates: Detailed Construction
Procedures for constructing the primary base
ASDRs are discussed below. Because the
procedures for constructing the secondary base
ASDRs are similar, we do not repeat those here.
Base ASDRs are constructed with 1990 deaths obtained from NCHS (by age, race, and Hispanic origin) divided by a July 1, 1990, population in the demographic analysis (DA) universe (as discussed under "inflation-deflation") for the appropriate subgroup. All ASDRs in this study are central death rates, and based on single years of age. Although we obtain NCHS deaths for Whites, Blacks, American Indian, API, and Hispanics, we do not obtain deaths for the non-Hispanic portions of the four racial groups. The latter are constructed using a series of steps described below.
Mortality Rates by Hispanic Origin
We first calculate Hispanic ASDRs using a 45-state
1990 numerator of Hispanic deaths and a
corresponding 45-state Hispanic population
denominator (1990 uncorrected, census-level).
We excluded five states either because they did
not collect Hispanic origin on the death
certificate (Louisiana, New Hampshire, and
Oklahoma) or because they had relatively high
proportions of unknown Hispanic origin
(Connecticut and New York). Excluding these five
states eliminates most of the approximately 106,000
unknown Hispanic origin deaths (5 percent of
all deaths) that appear in the 1990 NCHS
mortality files. Among the 45 states, only 0.67
percent of the deaths are of unknown Hispanic
origin and are excluded from the calculation of
ASDRs (probably contributing to an
underestimation of Hispanic death rates).
The following steps are used to derive ASDRs for the non-Hispanic portions of racial groups:
1) We obtain estimated numbers of deaths to Hispanic White, Hispanic Black, Hispanic American Indian, and Hispanic API by multiplying the Hispanic ASDRs by the Hispanic portion of each race population (DA-level), by age and sex.
2) We obtain estimated numbers of deaths to four race (any Hispanic) groups by multiplying race (any Hispanic) ASDRs by the respective race populations.
3) Subtracting 1) from 2) yields deaths to Non-Hispanic White, Non-Hispanic Black, Non-Hispanic American Indian, and Non-Hispanic API, by age and sex.
4) ASDRs for each sex, race, and Hispanic origin group are then obtained by dividing these deaths by their respective sex, race, and Hispanic origin population denominator.
Problems With Race and Hispanic Origin Mortality Rates
There are well-known difficulties in calculating
accurate mortality rates for some race and
Hispanic origin groups in current or past years,
including both the 1990 primary base years and
the 1996 to 1998 secondary base years. The
numerators and denominators of the ASDRs
come from different sources, and they differ in
important ways. Some of these differences
include 1) how race and ethnicity is reported
and classified (being self-reported in the census,
but not self-reported on death certificates) 2)
how missing data are handled, and 3) how
responses such as "other race" are handled.
Thus, there is inconsistent reporting of race and
ethnicity between the two data sources--death
records and census records. There is convincing
evidence that the ASDRs for some race and
ethnic groups, as currently measured, are
underestimated. One study that compared race
and ethnic identification on CPS surveys with
those of death certificates suggests that API
death rates could be underestimated by 12
percent, and by 25 percent for American
Indians.34 35 However, we do not yet know of an
adequate way to adjust our race and ethnic
mortality rates, and correction factors are not
available at this time. We currently use the
existing data until we have a stronger basis for
making adjustments.
Old-age Mortality Rates
We do not calculate ASDRs for the age group
85 years and older in the same manner as we do
for the under 85 years population (i.e, NCHS
deaths divided by population denominators),
due to the inaccuracies that can result from such
a procedure. There are problems of age mis-reporting
in both the numerators (death records)
and denominators (census-based population
data). Instead, we use a mathematical model
developed by Coale and Kisker to obtain
ASDRs for each subgroup.36 We inserted
different parameters into the original Coale and
Kisker formulas in order to force them to
produce death rates of 1.0 for both males and
females at age 115 for all race and Hispanic
origin groups.
Among the three major components of national
population change--births, deaths, and
international migration--international migration
is the component for which demographic
science offers the least to future projections.
Births and deaths can be projected as rates, with
demographic detail, so the emerging size and
structure (age, sex, race, and Hispanic origin) of
the populations at risk of death and childbearing
are a key determinant of these components of
population change. Moreover, the
epidemiological basis for the propensity to die,
as well as the social and economic basis for the
propensity to bear children are both the subjects
of substantial academic inquiry. This body of
research has yielded a basis for projecting their
future course, as reflected in previous sections
of this report. International migration to the
United States, by contrast, has public policy as a
major determinant. While it may be acceptable
in the near term to view migration as a
consequence of existing immigration law and
policy, this assumption loses merit for the
longer term. Emigration of the foreign-born
population can be projected relative to a
population at risk (e.g., the foreign-born
population) through the use of emigration rates,
but there is little or nothing in the way of theory
to indicate how these rates might change over
time.
Assumptions and Methodology
The current projection series incorporate three
major changes from past practice in the
projection of international migration. First, we
decided that the constant migration assumption
was inappropriate for a projection series (the
middle series) that would be widely interpreted
as the Census Bureau's forecast of population.
This determination was primarily on account of
an increased level of public debate regarding
immigration policy, as well as the highly
transitory nature of some recent developments
in international migration. The former
mandated a more critical view of how migration
might change in the future, while the latter
tended to discredit the interpretation of the base
series in a simplistic manner. However, we
have not been able to develop a dynamic model
for future international migration that reflects
adequately the current base series information,
yet conforms to any unifying theory of future
change. We have, therefore, projected
migration with consideration of a large amount
of underlying current detail, coupled with some
consideration of factors that could influence its
change in the future. The resulting projections
seek to reflect current trends in specific aspects
of migration, and to gauge their likely future
direction and magnitude.
The second change from past practice is that we
allow characteristics of the projected population
to influence the migration assumption. In the
past, we have expressly avoided incorporating
population "feedback" mechanisms when
formulating assumptions on any components of
population change, assuming a unidirectional
causative sequence from determinants of
components to components and from
components to the population. In the case of
fertility and mortality, we continue this practice,
simply because there is little evidence that such
feedbacks are important. In order to develop a
dynamic assumption regarding future migration,
it is necessary to consider the plausible links
that tie demographic characteristics of the future
population to immigration policy. Thus, we
consider the future direction in the age
composition of the population, as it might affect
policy regarding the immigration of working-age people.
A third major innovation in the current
projections of international migration relates to
the projection of the emigration of foreign-born
residents. Because we have projected the
foreign-born population in the current
projections, we were able to model foreign-born
emigration as a function of the population at
risk, in much the same way as we projected
mortality. Thus, foreign-born emigration is
projected, in all series, as rates by age, and sex,
rather than as number of emigrants. The
comparatively low level of native-born
emigration is projected numerically, as in the
past.
We are unable to project total in-migration and
total out-migration, as we have no such
estimates in the base series. For some of the
components of international migration,
information sources for the base series offer no
disaggregation of gross in-migration from gross
out-migration. Specifically, the net flow of
migrants from Puerto Rico (treated as
international in this context), the net flow of
undocumented migrants from foreign countries,
and the net flow of other legal non-immigrant
residents (mostly foreign students) are imputed
only as net flows--not as a balance of measured
in- and out-migration. Consequently, the
concept of "in-migration" to the U.S. in these
projections is a somewhat artificial construct
consisting of in-migration of refugees, in-migration
of newly arriving legal immigrants,
in-migration of non-immigrants who will later
become legal immigrants, net undocumented
migration, net Puerto Rican migration, and the
net movement of other legal but temporary non-immigrants
to the United States. This flow is in
large part a one-way flow to the U.S., but
embodies some reverse elements in the
components only measurable as net flows in the
base series. By the same token, the separately
projected "out-migration" component is
confined to the emigration of legal permanent
U.S. residents to permanent residence abroad,
excluding resettlement in Puerto Rico.
Table D provides a summary of "in-migration"
(as previously described) and the emigration of
legal residents for four single years in the
projection series.
Projection of the Level of In-Migration: Middle Series, 1999 to
2020
1) A rapid increase in the level of migration
during the 1990's occurred largely because
millions of people legalized in 1987 and 1988
under the Immigration Reform and Control Act
(IRCA) of 1986, were becoming U.S. citizens in
increasing numbers. As they became citizens,
they could sponsor the legal immigration of
immediate relatives without being subject to
numerical limits. We deemed this flow,
composed largely of people from Mexico and
Central America, to be somewhat transitory.
Hence, migration from this source is projected
to reach a peak early in the decade of 2000 to
2010, then gradually decline to zero as the
supply of potential reunifications is exhausted.
In particular, legal migration from Mexico is
assumed to return to the levels of the early
1990's by 2010.
2) We assume that there will be no change in
immigration policy which would result in any
change in the quantity of immigrant visas
available in numerically limited legal categories
between 1998 and 2020. Numerically limited
categories embrace all legal immigration except
for the adjustment of refugees and asylees to
immigrant status, the admission of immediate
relatives of U.S. citizens, and a few other
categories of little demographic consequence.
3) The flow of refugees to permanent residence
in the U.S. would tend to decline between 1998
and 2020, except for a near-term increase to
2000 in the number of refugees from the
republics of the former Yugoslavia. The decline
in the flow from the principal sources of the last
30 years, Southeast Asia and Cuba, is apparent
in the current refugee data series from 1995
forward. The trend from the former Yugoslavia
has been sharply upward since 1991, although
the timing and the height of the peak in this
trend will depend on the course of world events,
as well as the direction of United States refugee
resettlement policy.
4) Undocumented migration of people born in
Mexico and Central America is viewed
primarily as a function of the degree of success
in controlling the southwest border, and is not
projected to change from levels assumed for the
1990's base series.
5) Legal migration from places other than
Mexico, Central America, and refugee sources
will vary in trend, depending on recent
observations, and, to a lesser extent, the
perceived demographic capacity of the source
countries to supply migrants. The emerging
sources of migration that continue to increase in
importance under this assumption are South
Asia, Sub-Saharan Africa, and the Middle East.
We project a modest decline for the Philippines,
and little change in the influx from other areas.
A summary of the numerical assumption for
migration to the United States used for the
middle series is excerpted in Table E, together
with the current trend from 1991 to 1998. The
first block of this table, showing the middle
series assumption, indicates a modest rise in in-
migration from 1,234,000 in 1998 to 1,272,000
in 2002, a decline to 1,036,000 by 2010,
followed by a gradual rise to 1,090,000 by 2020.
The rise and decline are propelled mainly by the
previously postulated trends from Mexico
(IRCA-related family reunifications) and the
former Yugoslavia (refugee movements), while
the subsequent rise is dominated by the
relatively more gradual trends from the
emerging sources identified in point 4 above.
Projection of the Level of In-Migration: Middle Series, 2021 to
2100
1) Driven by a rapid increase in the dependency
ratio (number of people in the traditionally
dependent age groups, under 15 years and 65
years and over, relative to the balance of the
population), migration to the U.S. would
increase from 2020 to 2030, from a level of
1,090,000 in 2020 to 1,450,000 in 2030.
2) From 2030 to 2100, migration into the United
States would remain numerically constant at
1,450,000, even in the presence of an increasing
population, hence, its direct proportional impact
on the population would decline.
The phenomenon underlying the projected
increase through the 2020's is a pervasive one in
all considerations of the future demographic
characteristics of the United States. The historic
rise in births that occurred in the United States
from 1946 through the 1950's, followed by the
decline through the early 1970's, left a bulge in
the age distribution that has ensured an
unnaturally low dependency burden through the
1980's and 1990's on into the early 2010's.
Table F shows the trend in population, the
dependency ratio, and the elderly dependency
ratio (defined as the ratio of people aged 65
and over to people in ages 15 to 64), under
various migration assumptions. In the complete
absence of migration in or out of the United
States from 1999 onward ("zero migration," in
Table F), the dependency ratio rises from 53.0
percent in 2015 (close to the current level) to
69.4 percent by 2030, while the elderly
dependency ratio endures a near parallel rise
from 23.5 to 37.1. Our projections anticipate an
increase in the influx of migrants to the United
States as a response to this dramatic downward
shift in the availability of potential workers
relative to people outside the normal working
ages. The anticipated increase, from 1,090,000
to 1,450,000 annually, while large in percentage
terms (33 percent) is modest relative to shifts
that have occurred in migration in the United
States and elsewhere in the industrialized world
in response to economic and demographic shifts
of this importance. The migration response to
the economic boom of the 1920's in the United
States, and the labor migration from
southeastern to northern Europe in the period
following World War II are examples of
migratory shifts far more dramatic than the one
projected here. On the other hand, to project a
much larger shift (for example, a shift
comparable to what the U.S. experienced in the
early 20th century) would tend to overlook the
possibility of restrictive policies intended to
limit such a shift.
The impact of this projected migration trend on
the dependency ratio, while not impressive,
should be of some significance in the long-term.
In the zero migration model (first block, Table
F), the dependency ratio increases from 58.1
percentage points, to 69.4, an increase of 11.3
percentage points, from 2020 to 2030. Under
the middle-series migration assumption, it
increases from 57.2 percentage points to 65.9,
up 8.7 percentage points during the same period.
Migration to the U.S. by Race and Hispanic Origin
The strategy in these projections was to allow
the composition of international migrants by
race and Hispanic origin to reflect the probable
contribution of the various world regions to the
level of in-migration to the United States
dynamically. The resulting percentage
distribution by race and Hispanic origin for the
middle series is shown in Table D, middle
block, for selected years in the series. The
declining contribution of the Western
Hemisphere and Europe, and the industrialized
countries of East Asia are reflected in
decreasing levels of in-migration for the
Hispanic and White populations. The
increasing contribution of the Middle East,
South Asia, Southeast Asia, China, and sub-Saharan
Africa are reflected in increased
migration for the Black and API populations.
Low and High International Migration Assumptions
1) The margin of uncertainty around the middle-level
assumption is, of necessity, relatively
wider for international migration than for births
and deaths. The exogenous character of this
component, and its reliance on unpredictable
external factors such as the internal policy
environment and world events, as well as the
lack of demographic determinism in its
projection, ensure a comparatively high level of
uncertainty for this component.
2) The displacement between high, middle, and
low variants should increase over time, as it did
for both fertility and mortality. Uncertainty in
any component increases along with the elapsed
time from the relatively certain present to any
projected reference date.
3) The pace of the increase in the spread
between high and low should decrease over
time. While somewhat less obvious, this
follows from the goal to reflect uncertainty in
the population series. The population series is
most affected by cumulative, rather than current
levels of international migration. Because some
of the error in the middle series migration
assumption should be caused by fluctuations in
the level of migration, rather than long-term
trends, a portion of it can be expected to wash
out with the passage of time. Similar reasoning
was applied to the projection of the low and
high variants of fertility, where fluctuations over
time are also expected. This effect was not
considered important in the projection of
mortality.
4) We assume that the difference between high
and middle assumptions will exceed the
difference between low and middle
assumptions. Specifically, we assume that the
differences in the logarithms of the three series
(high minus middle, middle minus low) are
equal. This is equivalent to saying that the
series are equidistant in a multiplicative sense,
or that the ratios of high to medium equal the
ratios of medium to low. This follows from the
nature of the theoretical upper and lower
bounds. We can presume that the theoretical
high-end constraints on gross in-migration are
defined only by the population of the rest of the
world, and can thus be ignored (treated as
infinity), while the low-end constraint is zero.
We discount the fact that some out-migration of
illegal residents, temporary residents, and
people moving to Puerto Rico are included in
our definition of in-migration, previously
described, on the assumption that these elements
are small relative to in-migration as a whole. A
similar reasoning would not apply to fertility
and mortality, because the determinants of their
variability above and below the middle
assumption are presumed comparable.
To establish the high variant, we assumed a
deviation from the middle series of zero in 1998
(since this was the base year), 75 percent in
2010, and 150 percent in 2100. Multipliers
applied to the middle series were thus 1.00 for
1998, 1.75 for 2010, and 2.50 for 2100. A
logarithmic function was fitted to these three
multipliers to produce an annual series. We
established the low variant by computing the
reciprocal of these multipliers: 1.00 for 1998,
0.57 for 2010, and 0.40 for 2100, which
amounted to reducing the middle series by 43
percent (actually 3/7) in 2010, and 60 percent in
2100.
At its most extreme, the implied range for
international migration to the U.S. in 2100 was
from 580,000 migrants to the U.S. to 3,625,000,
with the middle-level assumption at 1,450,000.
In 2010 (the low point in the middle series), the
low, high, and middle values were, respectively,
592,000, 1,812,000, and 1,036,000. Data for
these and other selected dates in the series are
shown in Table E.
In reviewing the extreme variants for their
plausibility (albeit as extreme assumptions), we
also considered their impact on population size
and dependency ratios over the period of the
projections. We projected the population using
each of the three migration assumptions and
equal values for fertility and mortality rates.
These results are shown in Table F. The results
for dependency ratios show a spread between
the low and high migration series of 1.3
percentage points in 2020, increasing to 4.3
points by 2030, after the projected increase
(reflected in all three series) of the 2020's. The
spread increases to 6.2 percentage points by
2100. For total resident population, the three
models produce levels of 437 million, 571
million, and 854 million, respectively, in 2100.
The long-term spread in the dependency ratio
between high and low appears comparatively
modest, and changed very little over the last 70
years of the projection period. This is explained
by the fact that many of the larger numbers of
annual migrants entering under the high
assumption have dependent children and age out
of the working life span during the period of the
projections, thereby reducing the difference in
the dependency ratio. The differences in
population are indeed stark, with the high-migration
assumption yielding near double the
population produced by the low-migration
assumption in 2100. International migration may
address a high dependency ratio decisively in
the short-term, yet is highly inefficient in
reducing it over the longer term--especially if
considerations of population scale, as well as
age composition, are taken into account.
Projection of Emigration of Legal U.S. Residents
For the middle series, we assumed that foreign-born
emigration rates remained constant
throughout the duration of the projections. This
means that trends in emigration are driven
mainly by the size of the foreign-born
population, and secondarily by its composition
by age, sex, and country of birth. As shown in
Table G, the age-sex-country-standardized rate
(standardized on the 1990 base population) is
set at 12.1 per thousand population.
Native emigration was estimated as a constant
for the base series and the middle series, at
48,000 per year. This assumption is based on
research employing reports of U.S.-born
respondents in foreign censuses, as well as some
imputation for countries of destination for which
no such data were available.39
As shown in Table E, these two assumptions
yield an annual emigration trend from 252,000
in 1991, to 278,000 in 1998, the base year for
the projections. This increases steadily with the
increase in the foreign-born population, to a
level of 524,000 in the year 2100. The
juxtaposition of constant in-migration with
increasing emigration throughout the last 70
years of the next century, presumes a decline in
the numerical level of annual net migration to
the United States, and an even greater decline in
the impact of this component relative to overall
population size.
Low and High Emigration Assumptions
The fact that foreign-born emigration is driven
by projected rates, rather than projected
numbers, allows a crossover in numerical
emigration among the three series, around 2055.
In the early years of the projections, from 1999
to 2054, the numerical level of emigration is
higher for the low-migration series than for the
high-migration series. From 2055 to 2100 the
reverse is true, since the larger size of the
foreign-born population in the high-migration
series relative to the low-migration series
overcomes the effect of the lower emigration
rates for the foreign-born in the high migration
series.
The derivation of native-born emigration for the
high and low assumptions follows essentially
the same logic as that used to derive high and
low variants for gross in-migration. Multipliers
that increase (for the high assumption) or
decrease (for the low assumption)
logarithmically are applied to the middle series
assumption of 48,000 per year.
Net Migration of U.S. Citizens
Another area of innovation in these projections
is in the projection of international migration.
Once again, we recognize the uncertainty about
the future course of migration that has tended to
motivate simpler, more parsimonious
assumptions in the past. Yet, we decided that
this component of change had received enough
public attention in recent years that we could not
credibly assume it to be unaffected by
demographic changes in the population, as the
constant-level projection tacitly assumes.
Projecting the human population continues to be
an evolving science, and we fully expect that
future developments, including the upcoming
2000 census, will provide us with the basis to
revise these assumptions in future years.
2 The information on the Hispanic population shown in this report was collected in the
50 States and the District of Columbia and, therefore, does not include residents of Puerto Rico.
3 People of Hispanic origin may be of any race.
4 Jennifer Cheeseman Day, U.S. Census Bureau, Population Projections of the
United States by Age, Sex, Race, and Hispanic Origin: 1995 to 2050, Current Population Reports,
P25-1130, U.S. Government Printing Office, Washington, District of Columbia, 1996.
5 U.S. Census Bureau, “Population Growth Rate Remains Stable, Census Bureau
Reports,” National Population Estimates, Released as Press Release No. CB99-101, June 4, 1999.
At the time of release for this report, the results of the national estimates are located on the Census
Bureau site of the Worldwide Web. U.S. Census Bureau; “National Population Estimates;” published
June 1999,
6 Throughout the remainder of this report, “American Indian” is used to describe the
American Indian, Eskimo, and Aleut population.
7 U.S. Census Bureau, Age, Sex, Race, and Hispanic Origin Information
from the 1990 Census: A Comparison of Census Results with Results Where Age and Race Have
Been Modified, CPH-L-74, U.S. Government Printing Office, Washington, District of Columbia, 1991.
8 These methods are discussed in various demographic texts, e.g., Henry Shryock
and Jacob Siegel, Methods and Materials of Demography, Academic Press, Orlando, Florida, 1976.
9 For a description of the 1990 Demographic Analysis population and its derivation,
see J. G. Robinson, B. Ahmed, P. Das Gupta, and K.A. Woodrow, “Estimation of Population Coverage
in the 1990 United States Census Based on Demographic Analysis,” Journal of the American
Statistical Association, Vol. 88-423 (1993): pp. 1061-1071.
10 For seasonality of births see Stephanie J. Ventura, J. Martin, S. Curtin, T. Mathews,
National Center for Health Statistics, Report of Final Natality Statistics, 1996, Monthly
Vital Statistics Report, Vol. 46-11 Supplement, 1998.; for seasonality of deaths see unpublished tabulations
from National Center for Health Statistics, 1996 detailed mortality file.
11 The total fertility rate is a standardized measure of the average number of live births
per 1,000 women experiencing specific age-specific fertility rates throughout their childbearing years
without accounting for mortality.
12 Stephanie J. Ventura, J. Martin, S. Curtin, T. Mathews, National Center for Health
Statistics, Births: Final Data for 1997, National Vital Statistics Report, Vol. 47-18, 1999.
13 Jennifer Cheeseman Day, U.S. Census Bureau, Population Projections of the
United States by Age, Sex, Race, and Hispanic Origin: 1995 to 2050, Current Population Reports,
P25-1130, U.S. Government Printing Office, Washington, District of Columbia, 1996.
14 Each sub-group of Hispanics is assumed to maintain identical fertility trends.
15 W. van Hoorn and N. Keilman, “Birth Expectations and Their Use in Fertility
Forecasting,” Eurostat Working Papers, E4/1997-4 (1997).
16 Charles Westoff, “The Return to Replacement Level Fertility: A Magnet Force?”
Future of Demographic Trends in Europe and North America, Academic Press, London, England, 1991.
17 Lincoln H. Day, “Recent Fertility Trends in Industrialized Countries: Toward a Fluctuating
or Stable Pattern?” European Journal of Population, Vol. 11 (1995): pp. 275-288.
18 Stephanie J. Ventura, J. Martin, S. Curtin, T. Mathews, National Center for
Health Statistics, Report of Final Natality Statistics, 1996, Monthly Vital Statistics
Report, Vol. 46-11 Supplement, 1998.
19 Martin O’Connell, U.S. Census Bureau, Studies In American Fertility,
Current Population Reports, P23-176, U.S. Government Printing Office, Washington, District of Columbia, 1991.
20 Joan R. Kahn, “Immigrant and Native Fertility During the 1980s: Adaptation and
Expectations for the Future,” International Migration Review, Vol. 28-3, (1994): pp.
501-519.; and Deanna Pagnini, “Immigration and Fertility in New Jersey: A Comparison of Native
and Foreign-Born Women,” pp. 259-290 in Keys to Successful Immigration, Urban
Institute Press, Washington, District of Columbia, 1997.
21 Age-specific fertility rates calculated for the projections differ from those calculated
by the National Center for Health Statistics as a result of applying different base populations.
22 National Center for Health Statistics, National Survey of Family Growth, Cycle V, 1995.
23 According to the National Center for Health Statistics, “The expectations
of young women 25-29 years of age in 1988 exceed the estimated completed fertility of women
in their earliest 40’s at the time by about 9 percent (the difference between 2.33 and the average of
2.07, 2.12, and 2.17, above).” In Linda S. Peterson, National Center for Health Statistics, Birth
Expectations of Women in the United States, 1973-88, Vital and Health Statistics, Vol. 23-17, 1995: p. 8.
24 For detailed information on mortality trends between 1900 and 1990, see
Robert N. Anderson, National Center for Health Statistics, U.S. Decennial Life Tables for
1989-91, Vol. 1-3, Hyattsville, Maryland, 1999.
25 In this mortality section, the term "race and Hispanic origin groups" refers
specifically to five groups: Hispanic, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic
American Indian, and Non-Hispanic API. We use “race and ethnicity” in a more general sense
to include all race and ethnic groups.
26 Ron Lee and S. Tuljapurkar, Population Forecasting for Fiscal Planning:
Issues and Innovations, unpublished manuscript, September, 1998.
27 Jennifer Cheeseman Day, U.S. Census Bureau, Population Projections of the
United States by Age, Sex, Race, and Hispanic Origin: 1995 to 2050, Current Population
Reports, P25-1130, U.S. Government Printing Office, Washington, District of Columbia, 1996.
28 We use the term “life table” throughout this text for convenience. Most of our
work is actually based on schedules of age-specific central death rates, which can be converted to life
tables and used to calculate life expectancies at birth and at age 65.
29 Ron Lee and S. Tuljapurkar, Population Forecasting for Fiscal Planning:
Issues and Innovations, unpublished manuscript, September, 1998.
30 Ron Lee and L. Carter, “Modeling and Forecasting US Mortality," Journal
of the American Statistical Association, Vol. 87-419 (1992): pp. 659-675.
31 Personal correspondence, Carl Boe for Lee and Tuljapurkar 10/19/98.
32 Margorie Rosenberg and Warren Luckner, “Summary of Results of Survey of
Seminar Attendees,” North American Actuarial Journal, Vol. 2-4 (1998): pp. 64-82.
33 Personal correspondence, Carl Boe for Lee and Tuljapurkar 10/19/98.
34 P. Sorlie, E. Rogot, and N. Johnson, “Validity of Demographic Characteristics
on the Death Certificate,” Epidemiology, Vol. 3-2 (1992): pp. 181-184.
35 The use of the DA universe for population denominators tends to obviate biases of
differential reporting between Blacks and all other races combined, since the DA procedure uses death
registration data to define these categories. However, the break of “other race” into American Indian,
API, and White required the use of census data, with all it’s biases relative to death registration.
36 Ansley Coale and E. Kisker, “Defects in Data on Old-Age Mortality in the U.S.:
New Procedures for Calculating Schedules and Life Tables at the Highest Ages,” Asian and
Pacific Population Forum,Vol. 4-1 (1990): p. 32.
37 U.S. Census Bureau, International Program Center; International Data Base (IDB);
38 Bashir Ahmed and J. Gregory Robinson, Population Division, U.S. Census Bureau,
“Estimates of Emigration of the Foreign-born Population: 1980-1990,” Working Paper No. 9, 1994.
39 Edward Fernandez, Population Division, U.S. Census Bureau, “Estimation of the
Annual Emigration of U.S. Born Persons by Using Foreign Censuses and Selected Administrative
Data: Circa 1980,” Working Paper No. 10, 1995.
International Migration
International migration, in previous United
States population projections produced by the
Census Bureau, has been projected as a constant
value with a constant matrix of demographic
characteristics. The constant-level assumption
has been based on the experience of the last few
years prior to the launch date of the projections,
incorporating separate assumptions for legal
immigration, refugee movements, emigration (of
natives and foreign-born combined), net
migration from Puerto Rico, and net
undocumented migration. High and low
variants have been determined by establishing
reasonable maximum and minimum values of
each of these components, and holding them
constant over time, with a linear transition over
a few years from current to ultimate values.
The determination of the trend in migration to
the United States from 1999 to 2020 in the
middle series is based on consideration of
current trends in the arrival of people born in
different areas of the world. The trend is based
on the following guiding assumptions.
For the period from 2021 to 2100, the focus of
the projection of migration into the U.S. shifts
from the individual consideration of various
sources of migration from abroad to the trend in
the aggregate level. The projection of migration
by source region follows, but only with the aim
of establishing a distribution that can be used to
impute demographic characteristics. The
principal assumptions are as follows, and are
reflected, once again, in the first block of Table E.
As previously indicated, the projection
methodology makes use of the distribution of
international migration by country of birth in the
base year, distinguishing among major regions
of the world in establishing the trend. This fact
is most reflected in the resulting distribution of
international migration by age, sex, race, and
Hispanic origin. In the projection of in-migration
from 1999 to 2020, projections are
determined primarily by current trends by
country of birth, with consideration of the legal
bases of migration. In the projections from
2021 to 2100, the international population
projections of the International Program Center
(IPC) of the Census Bureau are tapped for
information on the relative projected growth of
the working-age component of the population of
various world regions to the year 2050.37 These
projections show considerably more rapid
population growth through the early part of the
next century for countries of South Asia, sub-Saharan
Africa and the Middle East, than for
countries of the Western Hemisphere including
Mexico, which have seen considerable declines
in fertility in recent years.
The objective in projecting low and high
variants for the international migration
assumption is to establish a candid view of the
uncertainty surrounding the middle series
projection. Three qualitative considerations
governed the choice of the upper and lower
limits for in-migration.
As previously indicated, emigration of legal
foreign-born residents is projected on the basis
of age-sex-specific rates, applied to a population
at risk, rather than a postulated numerical trend.
Current values of these rates were developed on
the basis of research conducted by the Census
Bureau.38 The underlying method involves
computing a matrix of differences between the
number of foreign-born people enumerated in
the 1980 census, and the number of foreign-born
people arrived before 1980 enumerated in the
1990 census. This calculation is carried out for
large groupings of country of birth, age, and sex,
an adjustment is made for residents who died
during the decade, and the balance is assumed to
be the number of emigrants. Considerable
modification of the numbers had to be carried
out because of problems such as negative
differences for some countries of birth
(theoretically impossible, but for misreporting
on the census) and allowances for differential
reporting of undocumented residents in the two
censuses. When these distributions are divided
by an interpolated mid-decade population, they
produce a schedule of rates, which, when
applied to the foreign-born population, produce
a projection of emigration. Unlike the case of
in-migration, this projection method also
produced the results in the base series from
1990 to 1998, since no current data on foreign-born
emigration are available.
The extreme variants of foreign-born emigration
rates are based on the same logic underlying the
derivation of the extreme variants of in-migration,
except that the application was to
rates, rather than numbers. Because higher
emigration implies lower net migration, the
high-level multipliers were used to determine
the emigration rates used for the low migration
series, and the reverse was true for the high
migration series. Because emigration in a given
year in the middle series was on the order of 1.2
percent of the foreign-born population, the
upper-level constraint of 100 percent was
assumed to be infinity, while the lower-level
constraint was zero. Thus, the multiplicative
approach to producing the extreme variants was
deemed appropriate. Low-migration foreign-born
emigration rates for 2010 were obtained by
multiplying the middle-series by 1.75, while the
multiplier for 2100 was 2.50. The multipliers
for the high-migration series were the
reciprocals of the multipliers for the low-migration
series. The results are shown in Table G.
The net migration of U.S. citizens (aside from
emigrants who depart the U.S. permanently) is a
small component of population change that
tends to be driven primarily by the movement of
U.S. military personnel between the U.S. and
abroad. Because it is dominated by military
movement, this migration is highly dependent
on the future course of world events. Because of
the impossibility of projecting such
developments, we adopt a conservative strategy
in projecting this component. The overseas
population of military and dependents is held at
a constant level, with a constant distribution by
age, sex, race, and Hispanic origin. Migration is
therefore equal to the number of overseas births,
minus the number of overseas deaths, plus the
balance of net inductions and discharges to the
military from the overseas population. The age
distribution of this flow is based on the
characteristics of net migration required to
counteract the natural aging of each category of
sex, race, and Hispanic origin in the overseas
population. No high and low variants were
determined for the net migration of U.S.
citizens.
SUMMARY
In developing population projections for the
United States, we have made a number of
decisions regarding the scope of the projections
and the assumptions that were somewhat
"bolder" than those adopted in most previous
series. The boldest decision was undoubtedly
the one to extend the series to the year 2100. In
making this decision, we were fully aware of the
precarious nature of any population projection
that is three human generations past the existing
population base. While the trend over the first
20 years of a projection series is generally
dominated by the characteristics of the base
population in demographic projections,
populations for dates 50 to 100 years in the
future are highly subject to behavioral decisions
by individuals, policy decisions by governments
at home and abroad, and possible unexpected
developments in health and morbidity. In
formulating assumptions for the highest and
lowest series that are progressively extreme, we
have attempted to convey a sense of the caution
with which any such long-term projections
should be interpreted.
1 At the time of release for this report, the results of these projections are located on the
Census Bureau site of the Worldwide Web. U.S. Census Bureau; “National Population Projections;”
For mortality patterns trough 1997 and mortality rates
for the five race and Hispanic origin groups see Donna L. Hoyert, K. D. Kochanek, and S. L.
Murphy, National Center for Health Statistics, Deaths: Final data for 1997,
National Vital Statistics Reports, Vol. 47-19, Hyattsville, Maryland, 1999.
Additional discussion and evidence related to the
underestimation of American Indian mortality can be found in U.S. Department of Health and
Human Services, Indian Health Service, 1997 Trends in Indian Health,
Rockville, Maryland, 1997.; and in Support Services International, Inc., Adjusting for
Miscoding of Indian Race on State Death Certificates, Final Report Submitted to the
Division of Program Statistics, Indian Health Service, 1996.
Population Projections Branch
Authors: Frederick W. Hollmann, Tammany J. Mulder,
and Jeffrey E. Kallan (Population Division)
Questions? / 1-866-758-1060
Created: January 13, 2000
Last Revised: July 09, 2008 at 02:52:50 PM
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