POPULATION
PROJECTIONS
Ben Jarabi
Population Studies & Research Institute
University of Nairobi
1
Projections - Objectives
At the end of the session, participants
will be able to:
 Outline the relevance of pop projections
 Detect & adjust errors in age reporting
 Prepare necessary inputs for a pop projection
 Outline projection methodologies
 Generate a pop projection at national level
 Generate a pop projection at sub-national level
 Generate sectoral pop projections
2
Presentation Outline
A. Introduction
B. Evaluation and adjustment of census data
C. Preparation of inputs for pop projections
D. Projection methodologies
E. National and provincial projections
F. Sub-national population projections
G. Sectoral population projections
3
A. Introduction
4
Projections - Definition

A population projection is:
 An extrapolation of historical data into the
future
 An attempt to describe what is likely to
happen under certain explicit assumptions
about the future as related to the immediate
past
 A set of calculations, which show the future
course of fertility, mortality and migration
depending on the assumptions used
5
Projections - Rationale
Primary needs of people in Kenya
cannot be gauged rationally without
information on expected size,
composition and distribution of the
population for different geographic
units and at various points in time
6
Projections - Rationale
Specific areas in which projections are a
necessary input:
 Allocation of resources (planning)
 Advocacy
 Research
 For M&E (basis for target setting; source of
denominators esp. non-routine data)
 To determine drivers of consumption –
corporate sector
7
Projections - Inputs

Base population

Assumptions about the course of
events (fertility, mortality, migration)

A method by which the assumptions
are applied
8
B. Evaluation & Adjustment
9
Types of Errors
 Content
 Age mis-reporting
 Digit preference
 Coverage
 Omitting a unit that should have been
included
 Including a unit more than once
 Including a unit that should not have been
included
10
Evaluation - Rationale
 Age structure is very important with
respect to social and economic
characteristics - hence the need for
accuracy in age and sex structure
 Knowledge of age structure is essential to
the analysis of fertility, mortality, and
migration
 Errors by age & sex are replicated and
repeated in population projections
11
Detecting errors – age reporting
 Age misreporting may be suggested by
irregularities evident in indices or
graphs
 Population pyramid
 Age and sex ratios
 Cohort comparison
 Summary indices of “irregularities” in
age structure or in age-sex structure
12
Evaluation - Digit Preference
 Frequently used indices for detecting digit
preference:
 Myers
 Whipple’s
 Bachi
 Ramachandran
 They provide not only an overall idea of the
extent of age misreporting but also indicate
the preference for certain ending age digits
13
Evaluation - Age Ratios
 Age ratios for 5-year age groups are
used as indices for detecting possible
age misreporting
 Normally age ratios are expected to
be similar throughout the age
distribution, and all of them should be
close to a value of 100
14
Evaluation - Age Ratios
 An age ratio is defined as:
5Px
5ARx
= 100
1/2 (5Px-5 + 5Px+5)
Where: 5ARx = age ratio for ages x to x+4
5Px
= population at ages x to x+4
 The larger the departure of this ratio from
100, the larger the error
15
Evaluation - Sex Ratios
 The level of the sex ratios depends on the
number of male and female births and on
the mortality of the population
 All populations have more male than female
births, and so the sex ratio at the early
ages is expected to be slightly over 100
 Since mortality is usually higher for males
than females, the sex ratio is reduced
continuously up to the oldest ages
16
Evaluation - Sex Ratios
 A sex ratio is defined as:
5MPx
5SRx
= 100
5FPx
Where: 5SRx = sex ratio for ages x to x+4
5MPx
& 5FPx = male & female populations,
respectively, at ages x to x+4
 The larger the departure of this ratio from 100, the
larger the error
17
The Age-Sex Accuracy Index
 The UN suggested a joint accuracy index to
summarize the age & sex ratios
 The index of sex-ratio score (SRS) is
defined as: The mean difference between sex
ratios for the successive age groups, averaged
irrespective of sign
 The index of age-ratio score (ARS) is
defined as: The mean deviation of the age
ratios from 100 percent, also irrespective of
sign
18
The Age-Sex Accuracy Index
 Based on empirical relationships between
the sex-ratio scores and the age-ratio
scores, the following index is defined as the
joint score (JS) or age-sex accuracy index
 JS = 3xSRS + ARSM + ARSF
19
The Age-Sex Accuracy Index
 The age and sex structure of a
population will be:
 accurate if the joint score index is under 20
 inaccurate if the joint score index is
between 20 and 40
 highly inaccurate if the index value is over
40
20
Correcting for Age Misreporting
 Smoothing techniques have
frequently been used for correcting
data for age misreporting
 These techniques involve the
application of a formula to the
original data
21
Correcting for Age Misreporting
 Smoothing techniques may be classified
into 2 categories:
 Those which accept the population in
each 10-year age group & separate it into
two 5-year age groups without modifying
the total population size
 Those which smooth the 5-year age
groups and modify slightly (either up or
down) the population being smoothed
22
Smoothing Methods
 Methods that preserve the original total:
 The Carrier-Farrag and Karup-King-Newton
 The Arriaga formula
 Arriaga’s “strong smoothing”
 Methods that alter the total slightly:
 The United Nations method
23
Smoothing Methods
 There is no generalized solution for all
populations
 The technique to be used will depend on the
errors in the age and sex distributions
 While, as Arriaga and Associates (1994) note,
differences in results across procedures are
small, a decision to use strong smoothing
should not be taken lightly
 The whole age distribution need not be
smoothed if only part is considered problematic
24
Exercise 1
Evaluation and adjustment
25
C. Preparation of inputs for
population projections
26
Smoothing Methods
 There is no generalized solution for all
populations
 The technique to be used will depend on the
errors in the age and sex distributions
 While, as Arriaga and Associates (1994) note,
differences in results across procedures are
small, a decision to use strong smoothing
should not be taken lightly
 The whole age distribution need not be
smoothed if only part is considered problematic
27
Projections - Inputs
 Accurate baseline data are critical to
producing accurate population
projections
 Population size and age structure
 Fertility
 Mortality
 Net migration
28
Projections - Inputs
Base
population
Population adjusted
for coverage,
consistency with
fertility & mortality,
smoothed
Fertility
Fertility and
projected
fertility
Mortality
Mortality &
projected
mortality
Migration
Migration &
projected
migration
Projection
29
Inputs - Base Population
 A population by sex & age is required to serve
as the base population for the starting date of
the projection
 Usually, the base population is taken from the
latest available census
 Census enumerations are not always perfect the reported data on age and sex may be
affected by errors – hence the need for
adjustment
 Where necessary, move the adjusted
population from a given date (e.g. a census
date) to another date (e.g. midyear)
30
Projections - Inputs

Current levels of the demographic
processes (fertility, mortality, and
migration) are determined for the base
year and then projected to future
years
31
Projecting future fertility
 Level of fertility has the greatest effect on
population growth due to its multiplier effect:
additional children born today will have additional
children in the future
 Fertility projections are made by projecting the
course of TFR over time, and translating this
into ASFRs
 Normally, long-term projections assume that
fertility will eventually stabilize at replacement
level, leading to a stationary population
32
Projecting future mortality
 Mortality projections are based on
projecting future life expectancy at birth for
males and females
 Life expectancy (like TFR), is a period
measure, and does not reflect the actual
experience of a particular individual
 Mortality projections must also specify how
mortality is distributed over different age
groups for both sexes
33
Projecting future mortality
 Future migration levels are more difficult to
project than fertility or mortality
 Although fertility generally has a larger
impact on long-term population growth,
volatile migrations can exert a strong
influence as well
 In addition, since no single, compelling
theory of migration exists, projections are
generally based on past trends and current
policies; however, data on historical
migration are sparse
34
Exercise 2
Preparation of inputs
35
D. Projection methodologies
36
Projections - Methodology

Projection methodologies can be divided
into two main categories:

procedures for projecting the population
considering fertility, mortality, and
migration, by age and sex (component
method)

procedures for projecting the population
using mathematical functions applied to
population figures but not to each of the
components (ratio method)
37
Projections - Methodology
 Cohort component - projects separately, the
components of population change (fertility,
mortality & net migration)
 Ratio method – generates total size of the
population but not the age-sex structure
 With HIV prevalence > 1%, mortality is
projected to include HIV/AIDS impact
38
Cohort component method
 This method simulates how a population
changes according to its components of
growth: fertility, mortality, and migration
 Based on past information, assumptions are
made about future trends in these
components of change
 Then, the projected rates are applied to the
age and sex structure of the population, in
a simulation taking into account that people
die according to their sex and age, that
women have children, and that some
people change their residence
39
Cohort component method
 Base population is grouped into cohorts
defined by age and sex
 The projection proceeds by updating the
population of each age- and sex-specific
group according to assumptions about
three components of population change
40
Cohort component method
 Each cohort survives forward to the next
age group according to assumed ASMRs
 Migration is accounted for by applying ageand sex-specific net migration rates to each
cohort as well
 Projected ASFRs rates are applied to the
female population in childbearing ages to
estimate the number of births
41
Cohort component method
 A sex ratio at birth is used to divide total
births into males and females
 These births are exposed to the
appropriate mortality schedule and then
the survivors fed into the projection
model
42
Cohort component method
 Time span
 No standard time span over which a
projection should be made
 Select a span that is equal to the maximum
length of time required for completion of the
planned activities
 NB: the longer the time span, the greater the
potential deviation of the projected from the
actual population
 It is usually most convenient to project
population by time intervals equal to the
age intervals
43
Ratio method
 Ratio method is applied mainly for
projecting the population of small areas
within a country for which all inputs
required by the component method are not
always readily available
 The method is also useful in the projection
of urban and rural populations
44
Ratio method
 The method is based on the ratio of the
sub-national unit, say district, population to
that of the national population
 After the ratio of the district to national
population is obtained, assumptions are
made on the future values of ratios
 Once the future values of ratios are fixed,
the population of the district can be
obtained by applying that ratio to the
projected national population in that year
45
Ratio method
Year
2001
2006
2011
2016
640054
708185
773854
840603
population
(P1)
(P2)
(P3)
(P4)
District
population
78855
-
-
-
Ratio of
district to
ntl pop,
2001
0.1232
-
-
-
87248
95338
103562
(P2 x X1)
(P3 x X1)
(P4 x X1)
National
Projected
district
pop
(X1)
46
Ratio method
 Once the projection for each small area has
been made, ensure the sum of the
population of all small areas tallies with the
national total
 Using the national total as a control, adjust
proportionally the projections of the small
areas
47
Population projection
 There is no single method or technique that
can improve accuracy
 Accuracy depends on the quality of the input
data and the assumptions made about the
course of future change
48
Population projection
 Identifying which projection method is optimal
for a specific type of projection depends on
several factors
 Of crucial importance is whether the projections
are to be carried out for larger geographical
areas (e.g. nations and groups of countries)
where uncertainty is lower, or smaller areas
(e.g. sub-national, urban) where migration
makes future population changes more volatile
and projections more difficult
49
E. National and provincial
projections
50
Exercise 3
Generating national and
provincial projections
51
F. Sub-national population
projections
52
Sub-national projections
 Generating sub-national projections that are
both internally consistent and consistent with a
national projection is usually more challenging
than preparing a national projection
 Each region presents the same data problems
as the national projection but, in addition,
preserving consistency across regions and
dealing with data problems that are often more
severe than those at the national level adds to
the challenge
53
Exercise 4
Generating sub-national
projections
54
G. Sectoral population
projections
55
Exercise 5
Generating sectoral
projections
56