DESTINY 2005
Demographic Estimation, Forecasting and Analysis System
USER’S
MANUAL
INTERNATIONAL
VERSION 3.0.01
Joseph George Caldwell, PhD
Tel. (001)(864)439-2772, e-mail jcaldwell9@yahoo.com
Internet website http://www.foundationwebsite.org
Copyright © 2005 Joseph George
Caldwell. All rights reserved.
Table
of Contents
III.
How to Use the DESTINY System
The DESTINY
computer program package enables the user to make projections of phenomena that
are related to population demographic characteristics. It does this using the procedure of synthetic
estimation. Synthetic estimation is a
procedure by which the future value of a quantity related to population
demographic characteristics is estimated by estimating the relationship of the
quantity to population demographic characteristics from historical data and
evaluating that relationship (or a suitable modification of it) using projected
(future) values of the population demographic characteristics.
Synthetic
estimation is one of many tools used to assist planning for the future. Other techniques include time series
analysis, econometric models, anticipation surveys, technological forecasting,
“Delphi” techniques, and microsimulation. The method of synthetic estimation works well
for forecasting quantities that are closely related to demographic
characteristics, such as demand for teachers, hospital beds, and social
services. For such applications,
synthetic estimates work well. They are
easy to understand, and, using appropriate computer software, easy to
produce. The DESTINY system performs the
data processing necessary to produce synthetic estimates. While the demographic theory underlying
cohort-component population projection models is complicated, the synthetic
estimates alone, as ratio estimates, are very easy to
understand, even by nontechnical personnel. From this perspective, synthetic estimation
has a significant advantage over alternative procedures, such as microsimulation, econometric, and time-series methods,
which require advanced technical training to implement, whose estimation
procedures are difficult to explain to lay persons, and whose functional form
is usually not at all “transparent” (e.g., involving the inverse of a matrix,
or its eigenvalues).
A word is in
order concerning some of the terminology used in the realm of synthetic
estimation. An “estimate” of an unknown
numerical quantity is simply a statement or opinion about its value. There are lots of kinds of estimates in the
field of statistics, of which synthetic estimates are just one example. A “projection” is an extrapolation of a
quantity into future time, based on the values specified in a projection
formula, or model. A “forecast” is an
estimate of a value of some quantity at a future time, for which there is some
confidence expressed about its likelihood of being close to the actual value,
when that future time arrives. An
analyst may make several projections, by specifying alternative values for
various model parameters (fertility, mortality, migration, service-system
parameters). None of these projections
are forecasts until the analyst represents them as such. The United Nations regularly publishes three
different projections of world and country populations – the “low variant,”
“medium variant,” and “high variant” projections. None of these are represented as
“forecasts.” They are simply projections
of what the population will be under the specified assumptions about fertility,
mortality and migration. If someone
agrees with one set of assumptions, such as those for the “medium variant”
projection, then that projection becomes his forecast. The analyst does not have to specify a single
projection as the forecast. He may
produce a variety of projections, all under reasonable but different
assumptions, and state that any of them are reasonable future outcomes. In this case, the forecast at a future point
in time is not a single value, but a range of values. The responsibility of planners and managers
is to recognize the range of likely variation in the future, and to exercise
prudent management procedures to cope with the future, whichever of these
likely alternative futures is realized.
The original
version of DESTINY was developed in 1981.
It was programmed in the FORTRAN programming language and designed for
use on microcomputers. That version
included not only routines for calculating synthetic estimates, but also
routines for making population projections based on the “cohort component”
method. The cohort-component method of
population projection projects a future value of population age-by-sex cohorts
based on assumptions about the fertility, mortality, and migration
characteristics of a population. This version
of DESTINY is a much-simplified version of the original. It has been developed using the Microsoft
Access database development system. This
version is an “international” one, in which much of the complexity of the
original version has been eliminated.
The major simplification is elimination of the capability to construct
cohort-component population projections.
The reason for this simplification is that the World Bank releases, each
year, a set of cohort-component projections for most countries of the
world. The international version of the
DESTINY system uses these projections as the basis for synthetic
estimation. (The World Bank projections
are contained in the World Development
Indicators CD, which is issued each year.)
The advantage of using World Bank population projections is not just to
avoid the work involved in making the projection – which is considerable. The use of World Bank population projections
as the basis for making synthetic estimates lends credibility to those
estimates. From a political perspective,
many users of synthetic estimates are more likely to accept synthetic estimates
that are based on World Bank (or United Nations) population projections, than
those based on the opinions of a local analyst, no matter how well-founded the
latter may be (the “no one ever got fired for buying IBM” syndrome).
The World Bank
population projections project the population of each country in five-year
intervals from the present time to the year 2090. These projections specify the composition of
the population by sex and five-year age intervals (“cohorts”). The original version of DESTINY included the
ability to project populations not only by age and sex, but by race and region
as well. Since the World Bank
projections do not include race or regional breakdowns, this feature of the
original DESTINY system has been removed from the international version.
The original
version of DESTINY was written before the availability of
mouse-and-windows-based microcomputer operating systems, and before the
widespread availability of low-cost relational database development systems,
such as Microsoft Access. The
line-by-line model data entry was somewhat tedious and, because the model
required specification of the population demographic characteristics (base-year
population by age, sex, race and region; fertility data; mortality data;
migration data), it could be time-consuming.
The data entry in this new version is much reduced in quantity, since
the World Bank population projections are contained in the model and it is
therefore not necessary to specify any of the demographic data behind these
projections. Furthermore, the limited
data entry that remains (to specify the synthetic-estimation parameters) is
accomplished by means of easy-to-use data-entry screens.
This User’s Manual describes how to install
(set up) the DESTINY system on a Microsoft Windows-based microcomputer, and use
it.
The User’s Manual for the FORTRAN version of
DESTINY was 233 pages in length. Because
of the simplification of this international version, and the ease of use of the
system enabled by the Microsoft Access database system, this manual is much
shorter. After describing how to install
the system on your computer, the use of the system will be documented by
describing how to set up and examine the examples presented in the DESTINY Description of Capabilities.
The DESTINY
system is designed for use with the Microsoft Access database system, version
2002 (or later). For DESTINY to work on
your computer, MS Access, version 2002 or later, must be installed on your
computer. If the system is downloaded
from the Internet, you will also need to have WinZip (version 8.0 or later)
installed on your computer, in order to decompress (“unzip”) the file.
The DESTINY
system is included on a CD, or may be downloaded from the Foundation website,
at Internet address http://www.foundationwebsite.org
. If the system is installed from CD by
running the “setup.exe” installation program, all files are copied to the
c:\Program Files\Destiny2005\ folder or other folder specified by the
user. If the system is downloaded from
the Internet, it may be copied to this or any other folder the user specifies.
To install the
system from CD, insert the CD in the CD drive, navigate in Windows Explorer to
this drive, and double-click on the setup.exe file. (Alternatively, create a new folder of your
choice and copy all of the files from the CD to that folder.)
If the system
is downloaded from the Internet, create a new folder named “Program Files” in
the c:\ folder, and download the files to this folder. The downloaded file is a “WinZip” compressed
file. After copying the file to the desire
folder decompress (“extract”) the WinZipped files (to
that same folder).
After copying
the DESTINY files to the desired folder, create a shortcut of the DESTINY
program (called Destiny2005.mde) and paste it on your computer “desktop”
screen. (To create a shortcut, simply
right-click on the Destiny2005.mde file, click on “Create shortcut,” and
cut-and paste the created shortcut (named Shortcut to Destiny2005.mde) to the
Windows desktop.
The DESTINY
system requires about 105 megabytes of disk storage.
The DESTINY system
is started by double-clicking on the DESTINY shortcut on the Windows desktop
(or by double-clicking on the Destiny2005.mde file in the folder in which the
DESTINY system was installed. When the
introductory screen opens, click on the “Go” button.
The next
screen shows the major options of the DESTINY system:
The output
produced by each of these selections is as follows.
View
Historical Time Series Data
As mentioned,
the cohort-component population projections used in the DESTINY model are those
distributed each year by the World Bank on its World Development Indicators
CD. Those projections and other time
series related to population projections may be viewed in graphical displays. The indicators selected from World
Development Indicators 2005 CD include mainly population and vital statistics,
but a few others are included as well (land use, energy use, environment,
income, health, education). Graphs may
be produced for 43 indicators and 208 countries. In one option, each of the indicators may be
viewed for a single country; in the other option, a selected indicator may be
viewed for each country.
View
World Bank Population Projection
This button
leads to detailed graphical displays of the World Bank cohort-component
population projection. These
projections are available for 193 countries.
The projections depend on eleven different input parameters – vital
statistics such as fertility rates, mortality rates, and migration rates. Each of the parameters on which the
projection depends must be itself projected into the future. In this section, the user may display graphs
showing the values of the various input parameters over the projection period,
2000-2090.
The World Bank
cohort-component population projection is displayed in a number of graphs. These graphs show the total population of
each country for each five year point of the projection period. They also show the age distribution by year
or for all years.
View
United Nations Population Projection
The World Bank
CD contains a cohort-component population projection for a single set of
assumptions about the input parameters (fertility rates, etc.). At the United Nations website are presented
population projections for three different sets of demographic assumptions. These are referred to as the “low variant,”
“medium variant,” and “high variant” projections. These projections are not used as the basis
for the DESTINY synthetic estimation, because the UN website does not provide
the age-by-sex breakdown of the population, as the World Bank WDI CD does. The UN population projections are included
here for information only – they are not used in the DESTINY calculations.
Specify,
Select, and Run a Cohort-Component Synthetic-Estimation Model
The next
system option allows the user to construct and execute synthetic estimation
models. Under the first option (“Specify
a Cohort-Component Population-Projection Model (Data-Entry Screens)”) displays
various data-entry screens which the user may use to specify parameters for a
synthetic-estimation model. On the first
screen, the user specifies “model meta data” – parameters that describe the
major features of the model:
After
specifying the preceding “model metadata,” the user then proceeds to enter more
detailed model data on the following screens.
These data include the names for all model entities (target population,
served population, services, resources, cost categories), and the parameters
that define the target population, served population, service utilization,
resource utilization, and cost. The
nature of these parameters is described in the examples presented in the
DESTINY Description of Capabilities. These data are obtained either from policy
decisions or alternatives (e.g., the specification of a served population may
be prescribed by law) or from historical data (e.g., unit costs of program services).
Target
Population.
The user must specify the incidence or prevalence of the target
population, as a proportion (decimal number between zero and one) of the
various age-by-sex cohorts of the general population. This may be done in a number of different
ways, depending on the application. It
is not necessary to specify separate incidence/prevalence ratios for each of
the different age-by-sex cohorts of the population, by year. Instead, if the ratios are constant over some
variables, the user can specify these parameters efficiently in eight different
“stratification” tables: (1) one overall ratio; (2) ratio varies by age; (3)
ratio varies by sex; (4) ratio varies by age and sex; (5) ratio varies by year;
(6) ratio varies by year by age; (7) ratio varies by year by sex; and (8) ratio
varies by year by age and sex.
Served
Population.
The user specifies the served proportion as a fraction of the target
population, for each demographic category.
As in the case of specification of the target population, this may be
done using the same eight stratification tables described above.
Services. For each served population, the user
specifies the average number of service units provided per case, for each type
of service included in the model.
Resources. For each service, the user specifies the
average number of resource units utilized per service unit.
Cost. For each cost category, the user specifies
the average cost per resource unit.
The Description of Capabilities provides several
examples of DESTINY runs. The first
example is simply a projection of the general population (
The second
example presented in the Description of
Capabilities contains a full set of service-system parameters. In this example, the parameters displayed in
the Model Meta Data table are: Model ID = 2, Country Code = zmb,
Country Model Number = 2, Cohort Component Projection Model = 1, Model
Description = “Zambia HIV/AIDS: VCT and CSM Services”, NTgtPop
= 1, NSerPop = 1, NSer = 1,
NRes = 7, and NCostCats =
7. A detailed description of the target
population, served population, services, resources and cost categories is
presented in the Description of
Capabilities.
The third
example (“Zambia HIV/AIDS: ART Services”) is very similar to the second, but
with one service instead of two. The
fourth example (“Zambia Basic-Schooling: Formal Education”) contains one target
population, one served population, one service (formal schooling), four
resources (teachers, classrooms, desks, textbooks) and four cost categories
(one for each resource).
In the
examples, the cost categories corresponded to the resource types. It is not necessary to do this – it was done
to keep the examples simple. In a real
application, both the resource types and the cost categories would correspond
generally to whatever categories were actually used, and they would usually not
be matched one-to-one.
Make
analytical graphs
This option
shows graphs in which historical World Bank data have been interpolated and
extrapolated through the year 2015.
There are several purposes in making these interpolations and
extrapolations. First, they are
presented to provide suggestions for projected values of projection model input
parameters, such as fertility rates, for use in instances where the user wishes
to construct his own cohort-component population projection model, to use as an
alternative to the World Bank model (this feature is not included in the
international version of DESTINY).
Second, they are done to provide complete (uninterrupted) time series
for use in time series analysis (e.g., smoothing of a time series, or
comparison of two different time series) in which values are desired at every
point in time (smoothing and time-series-analysis functions are not included in
the international version). Finally,
data series from international organizations such as the World Bank often have
an ill-defined end point, with some series ending at one year and some at
another. In order to have a complete set
of statistics for the final year, it is useful to extrapolate available data
for a year or two for the shorter series.
Many of the vital statistics employed in making population projections
fluctuate little from year to year, except for obvious trends. In such cases, a standard method for making a
quick estimate a few years ahead is simply to linearly extrapolate the
data. By this means, reasonable
estimates are easily and readily available for all indicators for, e.g., for
2003 or 2004 or 2005, for all countries, even though data may be missing for
many countries for the last year or two.
Make
long-term population projections
The
methodology of synthetic estimation based on cohort-component population
projections is appropriate only for making short-term projections, such as to
year 2015. For these short periods, it
is reasonable to examine alternative futures in which the population “ages” in
accordance with current trends in demographic phenomena (such as fertility,
mortality and migration). Most countries,
organizations and social programs have a five- or ten- year planning horizon,
to which the useful time horizon of cohort-component population projection and
synthetic estimation are appropriate, if not ideally suited.
As the
planning horizon extends farther and farther into the future, the use of the
cohort-component method becomes more and more difficult to justify. For long-term projections, e.g., several
decades, the method is not appropriate, other than to demonstrate that
extrapolation of current demographic trends eventually results in ridiculous
population sizes (extremely small or extremely large). For long-term population projections, other
methods are more appropriate.
The DESTINY
system includes a facility for making long-term population projections. These projections are “resource-constrained”
projections, in which the dependence of global population on the availability
of petroleum supplies is taken into account.
Many petrogeologists believe that global oil
production is in the process of peaking, that it will soon start to decline
noticeably, and that global oil reserves will be depleted by about 2050. Since the current large world population
(over 6 billion) owes its existence to petroleum, and no comparable substitute
has been found despite years of intensive searching, it is reasonable to
project that global population will decline roughly in proportion to the
decline in global oil production.
DESTINY
includes long-term population projections for three different scenarios. In the first scenario, it is assumed that human
population will continue in accordance with recent demographic trends. In the long run, this is not a reasonable
scenario, since large human numbers owe their existence to petroleum
availability, and this availability is about to decline with no comparable
substitute resource in sight. This
scenario is not considered realistic or likely – it is considered simply for
comparison purposes. This population
projection is similar to the World Bank projection, or to the United Nations
“medium variant” projection. The other
two scenarios considered for long-term population projections are: (1) As
global oil supplies run out, all countries share equally in the remaining
supply; and (2) As global oil supplies exhaust, the “rich” countries keep all
of the oil to themselves.
Here follows a
more detailed description of the long-term population projections, taken from
the DESTINY program on-screen documentation.
“The following
population projections take into account that global oil production is peaking
(Hubbert's Curve, Hubbert's
Peak), and that, as a result, world population will fall dramatically over the
next few years. For the three scenarios
considered, it is assumed that Hubbert's Peak occurs
around 2010, and that global commercial oil production ceases by 2050. Refer to notes below. Scenario / Projection 1 shows a hypothetical
(and unrealistic) "no-constraint" case, in which population growth
continues in accordance with current growth-rate trends (Note A). Scenario 2 assumes that all countries share the
dwindling oil supplies, that population declines to a level supportable by
low-productivity agriculture (Note B) by 2040, and to a sustainable
primitive-agriculture population level (Note C) by 2050. For Scenario 3, it is assumed that the
world's developed countries ("High Income OECD") keep all oil supply
to themselves, starting in 2010. Their
population continues at present levels (Note A) until 2030, declines slowly to
a solar-energy low-level-of-living level (Note D) by 2040, and to a
solar-energy high-level-of-living level (Note E) by 2050. The population of all other countries falls
to low-productivity-agriculture levels (Note B) by 2020, to
primitive-agriculture levels (Note C) by 2040, and to a hunter-gatherer level
(Note F) by 2050. (Population in
thousands, pop. growth rate as decimal fraction.) (These projections are based on historical
data from the UN FAO State of Food and Agriculture 2003-2004 report (i.e.,
UN/SOFA data to 2003, our projection from 2003).)
“Notes: The various population levels are associated
with the following energy-utilization cases.
A. Max.
high-agricultural-productivity population (10 persons/hectare of arable land,
corresponding to global pop. of up to 14.0 billion).
B. Max.
low-agricultural-productivity population (1 person/hectare of arable land,
corresponding to global pop. of 1.40 billion).
C. Sustainable
primitive-agricultural population (.2140 persons/hectare of arable land,
corresponding to global pop. of 300 million).
D. Max.
solar-energy population, low level of living (.3567 persons/hectare of arable
land, corresponding to global pop. of 500 million).
E. Max.
solar-energy population, high level of
living (.003567 persons/hectare of arable land, corresponding to global
pop. of 5 million).
F. Sustainable
hunter-gatherer population (.003567 persons/hectare of arable land,
corresponding to global pop. of 5 million).
G.
“Minimal-Regret” population: a “solar civilization” consisting of a
single-nation high-technology population of 5 million (Note E) and a
globally-distributed primitive (hunter-gatherer) population of 5 million (Note
F).”
View
documentation
This screen
points to documentation associated with DESTINY. It includes the Description of Capabilities, this User’s Manual, the documentation for the FORTRAN version of
DESTINY, and a case study (a population / environmental analysis of