DESTINY

 

     PLANNING AND FORECASTING SYSTEM

 

          Module 1: Single-Country Programs

 

                User's Manual

 

             FORTRAN Version 1.0

 

 

 

 

 

                               May 1, 1995

 

                       Reformatted December 9, 2005

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

                       Joseph George Caldwell, PhD

                            503 Chastine Drive

                        Spartanburg, SC 29301 USA

           Tel. (001)864)439-2772, e-mail jcaldwell9@yahoo.com

            Internet website http://www.foundationwebsite.org

 

 

 

Copyright © 1982, 1995, 2005 Joseph George Caldwell.  All rights reserved.


Table of Contents

 

 

I.  Overview 1

II.  How to Use the PARAM Program to Create Parameter Files 5

A.  Overview 5

B.  File Names; File Structure (Input Option) Parameters; 6

Names of Races and Regions 6

C.  Demographic Parameters and Data 13

D.  Service-System (Program-Related) Parameters and Data 25

III.  How to Use the CHECK Program to Print a Parameter File 36

IV.  How to Use the PROJ Program to Make Projections 38

V.  How to Use the CHECK Program to Adjust Service-System Parameters 41

VI.  Example 1: National Population Projection, Single-Race Model 44

A.  Projection Objectives; Data Sources 44

B. PARAM Run Parameters 47

C.  Results of CHECK Run 53

D.  Results of PROJ Run 54

VII.  Example 2: National Population Projection, Two-Race Model 56

A.  Projection Objectives; Data Sources 56

B. PARAM Run Parameters 56

C.  Results of CHECK Run 62

D.  Results of PROJ Run 63

VIII.  Example 3: State Population Projection, Single-Race Model 64

A.  Projection Objectives; Data Sources 64

B.  PARAM Run Parameters 65

C.  Results of CHECK Run 69

D.  Results of PROJ Run 69

IX.  Example 4: State Population Projection, Three-Race, 14-Region Model 70

A.  Projection Objectives; Data Sources 70

B.  PARAM Run Parameters 70

C.  Results of CHECK Run 81

D.  Results of PROJ Run 81

X.  Example 5: Projection of the Hispanic Population 85

A.  Projection Objectives; Data Sources 85

B.  PARAM Run Parameters 86

C.  Results of CHECK Run 92

D.  Results of PROJ Run 92

XI.  Example 6: Rehabilitation Services, Projection of the Work-Disabled 96

A.  Projection Objectives; Model Structural Parameters 96

B.  Data 98

C.  Projection Results 101

XII. Example 7: Education, Projection of School Enrollment 102

A.  Projection Objectives; Model Structural Parameters 102

B.  Data 103

C. Projection Results 105

XIII.  Example 8: Criminal Justice, Projection of Prison Admissions and Operating Cost 106

A.  Projection Objectives; Model Structural Parameters 106

B.  Data 107

C.  Projection Results 108

XIV.  Example 9: Health Care, Projection of the Need for Short-term and Long-term Beds 110

A.  Projection Objectives; Model Structural Parameters 110

B.  Data 110

C.  Projection Results 113

XV.  Example 10: Social Services, Projection of Counselors and Budget Needed to Provide Social Services to the Elderly Population 114

A.  Projection Objectives; Model Structural Parameters 114

B.  Data 115

C. Projection Results 118

References 120

Appendix A.  Data Sources, Model Parameterization and Model Calibration 121

Appendix B.  Data Entry Forms 124

Appendix C.  Technical Notes 144

Appendix D.  Computer Program Output Listings 148

 


I.  Overview

 

The DESTINY computer program package is designed to project populations and estimate quantities related to population.  The estimated quantities may be occurrences of events, such as school enrollments or prison admissions or occurrences of diseases or accidents; or they may be special populations of interest, such as the population of students, of nursing home beds, or persons having certain disabling conditions.

 

An overall description of the DESTINY system and its uses is presented in a separate manual, DESTINY Planning and Forecasting System: Description of Capabilities (Reference 1).  This User's Manual provides a detailed description of procedures for using the system.

 

A primary objective of the DESTINY system is to enable the user to make population projections and population-related estimates using readily available demographic data about the general population and target or service populations of interest.  In addition to describing how to use the DESTINY computer programs, much of the information presented in this manual is intended to identify sources for the needed program input data, or show how to obtain the needed data from related data, in cases where the exact data desired are not available.

 

The DESTINY computer program package consists of three computer programs, called PARAM, CHECK, and PROJ.  Three separate programs are used instead of one in order to minimize the internal memory, direct-access (core) storage requirements of the package.  The PARAM program sets up a parameter file, which contains demographic information about the population of interest, and programmatic information about the target populations and service system under study.  The CHECK program is used to print out the contents of the parameter file, so that a "hard copy" printout of all parameters can be retained as documentation for the projection runs.  This program is also used to make minor adjustments to some of the service-system parameters.  The PROJ program operates on the data files created by PARAM and CHECK, and generates the desired population projections and forecasts of program-related quantities of interest, such as service requirements, resource utilization, and cost.

 

Figure 1, Major Components of the DESTINY System, illustrates the relationship of the three programs, PARAM, CHECK, and PROJ.  In Figure 1, the data files created by PARAM, CHECK and PROJ are called AZ803.DAT and AZ803CS.DAT.  (A recommended procedure for naming files is discussed later.  With this procedure, each letter of the file name indicates something about the nature of the file.  In the name AZ803CS.DAT, for example, AZ stands for Arizona, 80 for 1980, 3 for 3 races, C for geographic disaggregation by county, and S for social services.)  In running the program, the user has the option of giving whatever names he desires to these files.  The two data files AZ803C.DAT and AZ803CS.DAT are "parameter" files created by PARAM.


Figure 1.  Major Components and Functions of the DESTINY System

 

 

1.  Program PARAM: Creation of Parameter File

 

   ┌────────────────┐ ┌──────────┐ ┌────────────────────┐

   "Old" Parameter   Program   "New" Parameter  

   File AZ803C.DAT├─┤   PARAM  ├─┤   File AZ803CS.DAT

        (if any)   └──────────┘ └────────────────────┘

   └────────────────┘                        

                                               

2.  Program CHECK: Printout of Parameter File  

                                                          

   ┌───────────────┐ ┌─────────┐ ┌──────────────────────┐  

   Parameter File Program Printout of all     

       AZ803CS.DAT├─┤  CHECK  ├─┤ parameters in       

   └───────────────┘ └─────────┘ AZ803CS.DAT; Total  

                                 Fertility Rate check

                                 └──────────────────────┘

                                               

3.  Program PROJ: Computation of Projections   

                                               

   ┌────────────────┐                          

   Parameter File                           

      AZ803CS.DAT  ├───┐  ┌─────────┐ ┌────────────────────┐

   └────────────────┘   └──┤ Program    Printed Output  

   ┌───────────────────┐┌──┤  PROJ   ├─┤  (Projections,    

   Run-Time Commands ├┘  └─────────┘   crosstabulations)

   (No. of years to                 └────────────────────┘

   project, cross-             

   tabulations to   

   print)                          

   └───────────────────┘              

                                               

4.  Program CHECK: Adjustment of Service-System Parameters (Optional)                                    

 

  ┌─────────────────┐ ┌─────────┐ ┌────────────────────────┐

  "Old" Parameter Program "New" Parameter File  

  File AZ803CS.DAT├─┤  CHECK  ├─┤ AZ803CS2.DAT (has same

  └─────────────────┘ └─────────┘ structure as          

                                  AZ803CS.DAT, but      

                                  adjusted service-system

                                   data)                 

                                  └────────────────────────┘

 


The PARAM program is used to set up a parameter file, or to update a parameter file.  The first time that PARAM is used, there is no "old" parameter file -- the program is used the first time to set up only a "new" parameter file, AZ803C.DAT, which is stored on the computer's disk.  After this first parameter data file is created, it is then referred to as an "old" parameter file, and it may be modified (for example, by changing an infant mortality rate or a migration rate, or by adding service-system data.)  These changes are incorporated into a "new" parameter file, AZ803CS.DAT, which is also stored on disk.  The "old" parameter file, AZ803C.DAT, is unchanged -- it remains on the disk exactly the same as before.

 

After the parameter file (AZ803C.DAT the first time, AZ803CS.DAT in later runs) has been created, the program CHECK should be run.  This program prints out all of the parameter values that are contained in AZ803CS.DAT.  This printout is useful in two ways -- first, it facilitates a detailed review of all of the parameter values, which review should be conducted to be sure that all of the parameter values have been entered correctly; and second, it represents a permanent record of the parameter values stored in AZ803CS.DAT, which record would be retained as documentation for the projection runs produced by the PROJ program, using the parameter file AZ803CS.DAT.

 

In addition to producing a hard copy printout of the contents of the parameter file, CHECK also prints out information concerning the Total Fertility Rate specified in the parameter file.  It estimates the Total Fertility Rate from the base-year crude birth rate and age/sex population distribution, so that the user may compare it to the value specified for the first five-year projection period.  It also estimates the annual net migration for the past ten years.

 

If the user wishes to modify any of the data values in the data file, he may rerun the PARAM program to change them.  If the user wishes only to make scaling adjustments to the values of service-system parameters (without changing the numbers of parameters in the file), this may be done more easily by rerunning the CHECK program (than by rerunning PARAM).  This option is used after the user has made his first run of the projection program, PROJ, and may wish to modify some of the service-system parameters in order to "calibrate" the model to match certain known base-year quantities (such as total budgets.)

 

The PARAM program asks the user to enter the name of the old and new parameter files, and the values of the various parameters required to make projections.  The CHECK program asks for the name of the parameter file, and, if it is being used to modify service-system parameters, for the values of the adjustment factors.

 

After the programs PARAM and CHECK have been run, the program PROJ is executed to construct the desired projections.  The PROJ program asks the user for very little data -- the number of five-year periods to project, the kinds of crosstabulations that are desired, and whether single-year projections (between successive five-year intervals) are desired (and if so, for which years).  The PROJ program reads the data file created by PARAM (and perhaps modified by CHECK).

 

The preceding paragraphs have described the overall way in which the DESTINY package works.  The following chapters describe in detail how to use each of the three component programs, PARAM, CHECK, and PROJ.

 


II.  How to Use the PARAM Program to Create Parameter Files

 

A.  Overview

 

The PARAM program sets up a parameter data file containing the following categories of information:

 

o File Names; File Structure (Input Option) Parameters

 

o Demographic Parameters (one complete set of data is

         required for each race)

o Total fertility Rate

o Fertility Age Distribution

o Infant Mortality Rates or Expectation of Life at Birth

o Base-Year Population, Other Base-Year Data, and Data for the Ten-Year Period Prior to the Base Year

o Regional Populations (if the model includes more than one region; for base year and ten years previous)

o External Migration Parameters

o Internal Migration Parameters (if the model includes more than one region)

 

     o     Service-System (Program-Related) Parameters (Optional)

o  Program Data Parameters

o  Target Population Incidences or Prevalences

o  Service Population Service Ratios

o  Service Unit Data

o  Resource Unit Data

o  Cost Data

 

o    Names (Required)

o  Race/Ethnic Group Names

o  Region Names

o  Target Population Names

o  Service Population Names

o  Service Names

o  Resource Names

o  Cost Category Names

 

The sections that follow define each of the variables which characterize the above information categories, and describe in detail how to input them to the computer terminal.  Appendix A indicates likely sources for the data required by PARAM.  Appendix B contains data entry forms that can be used to record the data in an organized format, prior to entry into the computer.  Appendix D includes some technical information concerning the analytical methodology used by the DESTINY package.

 

 

B.  File Names; File Structure (Input Option) Parameters;

    Names of Races and Regions

 

The PARAM program is executed by typing PARAM at the MS-DOS prompt.  The first information required by the program is an Authorization Code -- an eight-digit code which must be input by the user before the program will work.  The Authorization Code is recorded on the DESTINY Lease Agreement Form.  The PARAM program prints the following line on the video monitor:

 

     ENTER AUTHORIZATION CODE: .

 

If the Authorization Code were ABC123, for example, the user would type ABC123 on the keyboard (using capital letters), and then depress the ENTER key:

 

     ABC123 (ENTER) .

 

(Note: the symbol (ENTER) indicates that the "ENTER" key on the keyboard is to be depressed.)  No spaces should be typed before the code, or between any of its characters.

 

Next, the PARAM program states:

 

     ENTER 0 TO MODIFY EXISTING FILE, 1 TO CREATE FILE FROM           SCRATCH:

 

The first time the program is used, there is no existing file which can be modified, and the user must enter all of the data from scratch, i.e., a "1" should be entered:

 

     1 (ENTER) .

 

For subsequent uses, the user will generally update an existing parameter file, and enter a "0".  For example, the user will probably create a base-year population file containing only demographic information, and update this file on numerous occasions to create files that contain data on certain target populations.  In such a case, all of the demographic data in the "demographic" file are simply copied into the new file without change, and the new target-population or service-system data are added to the file.

 

If the user inputs a "0" (to update an existing parameter file), the program reads through the file section by section, and shows the user what parameter values are stored in the existing file.  The program then asks for each section whether to use the existing values, or whether different values are desired.  If the user chooses to accept the existing values in a section, he types a "0" (or nothing), and depresses the ENTER key.  If the user wishes to input different values in a section, he enters a "1" (i.e., types a "1" and depresses the ENTER key).  Since the manner in which updated data are entered in each section is exactly the same as the manner in which new data are entered the first time PARAM is run, we shall discuss in this section only the latter case, in which a new parameter file is being constructed from scratch.  We assume that the user enters a "1" in response to the question:

 

     ENTER 0 TO MODIFY EXISTING PARAMETER FILE, 1 TO CREATE           FILE FROM SCRATCH: .

 

The next request printed by the program is:

 

     ENTER NAME OF NEW PARAMETER FILE (12X): .

 

The notation (12X) in parentheses is a format descriptor.  It indicates that up to 12 characters may be used in the file name.  The user may input any valid MS-DOS file name (eight-digit alphanumeric name beginning with a letter, followed by a period, followed by three additional characters), such as US801.DAT or AZ803C.DAT.  The use of easily-remembered mnemonics which suggest the contents of the file is recommended.  It is suggested that the first two characters be used to denote the geographic region (e.g., US or AZ); the next two characters the last two digits of the base year (typically a census year, such as 80 or 90); the next character the number of races (or a letter denoting one of two races); and the next the type of region.  The seventh character may describe the nature of a target population to be described by the file, e.g., S for social services.  The eighth character may be used for any purpose, such as a file version number (e.g., 1, 2, a, b).  The final three characters (the "file extension," following the period), may be any characters, such as DAT (for "data"), or DBF (for "data base file").  (It is best to use the same three-character extension for all data files, to facilitate copying of those files to a floppy disk by means of a command such as  COPY *.DAT A:/V .)

 

For example, the mnemonic AZ803CS.DAT refers to a parameter file containing data for the state of Arizona (AZ); base year 1980, 3 races; countries; and social services to the elderly.

 

To input the file name, simply type it on the keyboard, using capital letters, and depress the ENTER key.  For example,

 

AZ803C.DAT (ENTER) .

 

On later runs, the user will usually be updating an existing file, and will enter a "0" in response to the request concerning whether an existing parameter file is to be modified, or a new file created from scratch.  The user would be instructed:

 

ENTER NAME OF OLD PARAMETER FILE: ,

 

to which request he might enter:

 

AZ803C.DAT (ENTER) .

 

The next command would then be:

 

ENTER NAME OF NEW PARAMETER FILE:  ,

 

to which request he might respond with the entry:

 

AZ803CS.DAT (ENTER) .

 

The next information requested by the program is a "header" for the parameter file -- a descriptive title for the parameter file, consisting of up to 80 characters.  The program prints out:

 

     ENTER FILE HEADER.  INCLUDE NAME OF GENERAL POPULATION;          NATURE OF RACIAL/ETHNIC AND REGIONAL DISAGGREGATION:           NATURE OF TARGET POPULATIONS AND SERVICE SYSTEM.  FORMAT        80X.: .

 

The header would include the following information:

 

o  Name of the general population being projected

o  Nature of the racial/ethnic and regional disaggregation

o  Nature of the target populations and service system.

 

For example, if the parameter file will refer to the resident population of the state of Arizona, will be disaggregated by three races (white, Indian, and other), will include 14 countries, and will include data concerning social services to the elderly population, then the user might enter the following header:

 

     ARIZ RESIDENT POP, BY RACE (W/I/O) AND COUNTY: SOCIAL           SERVICES TO THE ELDERLY .

 

After the header, the program prompts the user to enter the base year to which the population applies.  This number is typically a decennial census year (for which much demographic data are available), such as 1980 or 1990.  This number should be four digits long, e.g., 1980.  The program requests:

 

     INPUT BASE YEAR: ,

 

to which the user might respond, for example,

 

     1980 (ENTER) .

 

After the file name(s), header, and base year have been entered, the next input parameters required by the PARAM program allow the user to specify which of a number of options he wishes to use, in constructing the parameter data file.  These options indicate both the types of data to be specified by the user, and the level of detail of the data.  The seven parameters (denoted by P1, P2,..., P7 in this document) are as follows:

 

     P1:  Number of Races (1-3)

     P2:  Number of Regions (1-14)

     P3:  Vital Statistics Parameter Option (1 or 2)

     P4:  Life Table Option (1 or 2)

     P5:  External Migration Parameter Option (0, 1, or 2)

     P6:  Internal Migration Parameter Option (0 or 1)

     P7:  Service System Option (0 or 1)

 

The significance of each parameter option is as follows.

 

P1: Number of Races (1-3)

 

The program requests:

 

ENTER NO OF RACIAL/ETHNIC GROUPS (1-3): .

 

The user specifies the number of races (from 1 to 3) for which he plans to enter a complete set of demographic data (fertility rates, migration rates, base year populations, and so forth).  The user should enter the number of racial/ethnic groups for which he wants breakdowns of the data in the projections, or for which he wishes to specify different demographic or programmatic parameters.  If projections are to be made for a state in which there are three major racial/ethnic groups, and projections are desired by race, then a "3" should be entered (by striking a "3" on the keyboard, followed by "ENTER").  Alternatively, if the user is not interested in projections broken down by race, he could specify a "1" for the number of races, in which case all subsequent demographic parameters entered to the program would refer to the entire state (i.e., the total population of all races combined).

 

It is emphasized that all of the demographic data items (described later) must be entered for each race specified.

 

P2: Number of Regions (1-14)

 

The program requests:

 

INPUT NO OF REGIONS (1-14): .

 

The user may specify up to fourteen geographic regions.  If no regions are specified, the user enters a "1" (or a "0" or nothing).  By specifying more than one region, the user may later request in a PROJ run that the projections be broken down by region.  If two or more regions are specified, then the user must (at a later step) specify the population of each region, for each racial/ethnic group.

 

P3: Vital Statistics Parameter Option (1 or 2)

 

The program requests:

 

     ENTER VITAL STATISTICS PARAMETER OPTION (1 OR 2): .

 

The Vital Statistics Parameter Option allows the user to specify that the following parameters:

 

o  Total Fertility Rate

o  Fertility Age Distribution

o  Infant Mortality Rate

o  Expectation of Life at Birth

 

are either the same for all future time (i.e., for all ten five-year projection periods), or are different for each of the ten five-year projection periods.  The user enters a "1" for the former option (parameter values the same for all the future)  and a "2" for the latter option (different parameter values for each five-year period).

 

P4: Life Table Option (1 or 2)

 

The program requests:

 

     ENTER LIFE TABLE OPTION (1 OR 2): .

 

The DESTINY package uses the Coale-Demeny "West" model life tables to determine the probability that an individual survives each five-year period of his life.  These tables specify the survival probabilities either as a function of the infant mortality rate or as a function of the expectation of life at birth.  The user indicates which table to use by specifying a value for either one of these two parameters.  The Life Table Option parameter is set equal to "1" in order to use infant mortalities to determine the appropriate life table, and "2" to use expectations of life as the determining parameter.  It is recommended that Option 1 be used for countries having high mortality rates (e.g., most developing countries) and Option 2 for countries having relatively low mortality rates (e.g., the US).

 

P5: External Migration Parameter Option (0, 1, or 2)

 

"External" migration refers to migration between the area under study and outside areas, e.g., migration into and out of a state or into and out of a country.  "Internal" migration (the subject of Input Parameter P6) refers to population movements among the various subregions of the area under study, such as population movements among states, provinces, or regions in the case of a country, or movements among countries or other substate regions or districts in the case of a state.

 

The program requests:

 

     ENTER EXTERNAL MIGRATION OPTION (0-2): .

 

The five options that are available for specifying external migration are as follows:

 

o    Option 0.  No net external migration, either into or out of the geographic area under study, is allowed, i.e., there is no net immigration ("in-migration") or emigration ("out-migration").

 

o    Option 1.  The same migration rate is used for all  ten five-year projection periods (of the next fifty years), or the same migration amount, or number, is used for all ten five-year projection periods.  (Note: Since all demographic parameters are specified separately for each race, a different rate or number may be specified for each race.)

 

o    Option 2.  A separate migration rate or migration number is specified for each of the ten five-year projection periods.  (Note: These parameters may vary by race.)

 

A migration rate is the average proportion of the population moving out of the area each year; the rate is expressed in the net number of persons entering or leaving an area per 1,000 persons per year.  A migration number is the average number of persons moving into or out of an area each year.  The migration rate or the migration number are used to specify net immigration (in-migration).  The user may specify either a migration rate or number, but a (negative) migration rate should be specified in cases of net population loss and a (positive) migration number should be used in cases of net population gain (although there is no requirement for this convention).  Additional discussion of migration rates and numbers will be presented later.

 

Option 0 would be used in a run to determine the "rate of natural increase" -- i.e., the growth rate of a population due to births and deaths, ignoring changes due to migration.

 

P6: Internal Migration Parameter Option (0 or 1)

 

"Internal migration" refers to the redistribution of the population among the region to area under study, due to movements of the residents of one region to another region, to settlement of the external migrants (from outside the area), and to emigration of the residents of regions to places outside the area under study.

 

The program requests:

 

     ENTER INTERNAL MIGRATION OPTION (1 or 2): .

 

Two options are available for specifying internal migration:

 

o    Option 0.  No internal migration.

 

o    Option 1.  For each region, the user must specify an annual growth rate or amount, net of births, deaths, and a proportional allocation of external migration to the regions.  (Note: Different parameter values may be specified for each race.)

 

Since internal migration is an inter-regional phenomenon, the Internal Migration Option operates only if there is more than one region.  If there are no regions specified, Option 0 is used.

 

The growth rate is the average rate of population change in a region per 1,000 population per year.

 

P7: Service System Option (0 or 1)

 

The program requests:

 

     ENTER SERVICE SYSTEM OPTION (0 0R 1): .

 

The DESTINY package may be used solely to make projections of the general population, or to make projections of target populations (subpopulations of interest), program services, resources, and costs.  To make only general population projections, enter a "0"; to use the full capability of the program to forecast the program-related items as well, enter a "1".

 

After the demographic parameter options have been specified, the program asks for the names of the races (or ethnic groups) and regions (if any).  The request is:

 

     ENTER NAME FOR RACE NO i (8X): .

 

where i ranges from 1 to the number of races specified (i.e., 2 or 3).  The user may specify any eight-character name for the race, such as WHITE, BLACK, OTHER, HISPANIC, or AMERIND.

The program next requests the user to input the names of the regions, if two or more regions are included in the model:

 

     ENTER NAME FOR REGION NO i (8X): .

 

For a country, the regions might be states, provinces or major geographic regions.  For a state or province, the regions might be districts or counties.  For a local area such as a city, the regions might be the metropolitan and nonmetropolitan areas.  If names such as "REGION 1" are used, a space may separate the word and the number, as long as the total number of characters, including blanks, is less than or equal to eight.  Hence, "REGION 10" is not allowed -- if it were entered, the eleventh character (the "0") would be dropped.

 

If PARAM is being used to update an existing parameter file, the user will be asked whether he wishes to keep all of the Demographic Option Parameters the same as in the old file, or whether he wishes to change (all of) them.  If he keeps them the same, PARAM simply reads them from the old file and writes them into the new file.  If he wishes to change them, he must input the new values through the keyboard.  This process (i.e., accept the old file values or enter new values) is used for all of the remaining parameter categories that follow.

 

 

C.  Demographic Parameters and Data

 

A complete set of demographic parameters must be specified for each race represented in the parameter data set.  When PARAM is used to construct a "new" parameter file from scratch (such as is the case the first time the DESTINY package is used), the program input section makes one complete input "cycle" for each race, and requests the user to enter values for all of the required demographic parameters.  If program is used in the update mode (i.e., a new parameter file is being constructed by modifying an existing file), then the program input section cycles through each of the races in the old parameter file, each time asking whether the user wishes to save (i.e., write to the new file) or update the data for that race.  Then, after all of the races of the old parameter file have been reviewed (and either saved or updated), the program recycles to permit entry of additional races.  This process stops when demographic data have been modified or input anew for as many races as were specified in the Input Option Parameter section.  For each cycle, the following information is requested:

 

o    Total Fertility Rate(s)

o    Fertility Age Distribution(s)

o    Infant Mortality Rate(s) or Expectation(s) of Life at  Birth

o    Base-Year Population

o    External Migration Parameter(s)

o    Regional Populations (if regions are included in the model; for the base year and ten years previous)

o    Internal Migration Parameter(s) (entered if the model contains more than one region)

 

The paragraphs that follow describe the data entry procedure for each of the preceding information categories.  The data entry is illustrated with sample values, without describing the source of those sample values.  Later chapters will describe in detail the procedures for obtaining proper values for the model parameters.

 

 

 

 

Total Fertility Rate(s)

 

The total fertility rate is the average total number of live births per female in her lifetime.  For the US population in 1975, this number was 1.799 (1.708 for white, 2.322 for black and other).

 

If Input Option Parameter P3 is a "1", then only one rate is required (per race), and this rate applies to all future time periods.  In this case, the program requests:

 

ENTER 1 TOTAL FERTILITY RATE(S) (10X.XXX): ,

 

and the user must enter one decimal number.  If Option P3 is specified as a "2", then the program requests:

 

     ENTER 10 TOTAL FERTILITY RATE(S) (10X.XXX): ,

 

and the user must input ten decimal numbers.  The rules for entry of these numbers will now be described.

 

The format X.XXX in the data entry request indicates that the Total Fertility Rate must be entered to the computer as a decimal number (e.g., 1.799), with no more than one digit before the decimal and no more than three digits after the decimal.  If a rate of 2.0 were to be specified, it must be entered as "2.", or "2.0", or "2.00", or "2.000", with the decimal point, not as "2" with no decimal point.  Each time PARAM requests one or more numerical values to be entered, it indicates the format of the number by means of an expression such as "X", "7X", "16XX.XX", or "8XXXXXXXXX.", where a digit is to be substituted for each "X" (or, in the case of names, any alphanumeric character is to be substituted for each "X".) The prefix number (7, 16, and 8 in the preceding examples) indicate how many values are to be specified (if available) before depressing the "ENTER" key.  The position of the decimal point does not matter, as long as it is present somewhere in the number.  For example, if the user wanted to enter the following ten Total Fertility Rates (one for each of the ten five-year projection periods) according to the format 10X.XXX, then the following entry would be acceptable:

 

     1.875,1.85,1.8,1.75,1.75,1.75,1.75,1.75,1.75,1.75 (ENTER).

 

Note that it is not necessary to have three digits following each decimal point, as suggested by the format.  The numbers may not, however, have more than one digit before the decimal, nor more than three digits after the decimal.  If the user violates these rules, the extra digits will be lost, and the wrong values entered into the parameter file.

 

The user has a choice of either following the specified format exactly, or separating each number by commas.  For example, if the format were 3X.XXX, and the user wished to enter the numbers .75, 1.2, and .9, then either of the following entries would be acceptable:

     0.75±1.2±±.9 (ENTER) ,

 

where ± represents a blank (obtained by depressing the space bar), or

 

     .75,1.2,.9 (ENTER) .

 

If commas are not used, each number must utilize exactly the same number of positions (including digits, decimal point, minus sign, or blanks) as specified in the format descriptor.  In the preceding example, each number of the entry must take up exactly five positions if no commas are used.  In general, it is simpler to use commas to separate all decimal numbers, but to use no commas when entering small integer numbers.  For example, if the user wished to enter the numbers 1,0,1,1,0,1,0,0,1 according to the format 9X, it is simpler to enter

 

     101101001 (ENTER) ,

 

rather than

 

     1,0,1,1,0,1,0,0,1 (ENTER) .

 

Fertility Age Distribution(s)

 

The Fertility Age Distribution indicates what proportion of a woman's children are born in each five-year period of life.  For example, in the US in 1978, these proportions are as follows:

 

                                Birth Rate

                            (per 1000 women in

       Age of Mother  specified age group)  Proportion

 

          Under 20          53.6               .15

           20-24           112.3               .31

           25-29           112.0               .31

           30-34            59.1               .17

           35-39            18.9               .05

           40+               4.1               .01

                           360.0              1.00

 

Note that the Total Fertility Rate (1.799) is equal to the sum of the birth rates (360.0) divided by 1000 (the number of women) and multiplied by 5 (the number of years), i.e., 1.799 = 360.0 x 5.0 / 1000.  (The arithmetic would actually produce 1.800, not 1.799; the value 1.799 published in vital statistics documents for 1978 is the result of more precise computations, which carried more decimal places in the birth rates.)  Possible sources of demographic data such as the fertility age distribution are identified in Appendix A.

 

If Input Option Parameter P3 is a "1," the user need input but a single Fertility Age Distribution, consisting of six decimal numbers that total to 1.0.  The program requests:

 

     ENTER FERTILITY AGE DISTRIBUTION (6 ENTRIES, FORMAT              6X.XXX) FOR PERIOD NO 1: .

 

To enter the Fertility Age Distribution illustrated in the preceding example, the user would enter:

 

     .15,.31,.31,.17,.05,.01 (ENTER) .

 

If Input Option Parameter P3 is a "2,, the user must enter ten such six-number distributions, one for each of the ten five-year projection periods.

 

Infant Mortality Rate(s)

 

The Infant Mortality Rate is the number of infant deaths per 1000 live births (where an "infant death" is the death of an infant under one year of age, excluding fetal deaths.)  For the US in 1975, the infant mortality rate was 16.1.  Note that the Infant Mortality Rate is specified to the PARAM program for both sexes combined, not separately for each sex.

 

The PARAM program will accept Infant Mortality Rates whose values lie between 11.25 and 530.76.

 

If Input Option Parameter P3 is a "1," the program requests:

 

     ENTER 1 INFANT MORTALITY RATE(S) (10XX.XX): ,

 

to which the user might respond, for example,

 

     13.8 (ENTER) .

 

If Input Option Parameter P3 is a "2," ten such numbers must be entered, one for each five-year period into the future.

 

Expectation of Life at Birth

 

The Expectation of Life at Birth is the average number of years to be lived by a newborn, assuming that the mortality rates for each age group remain constant in the future.  For persons born in the US in 1975, this number was 72.5.  Note that the expectation of life at birth is specified to PARAM for both sexes combined, not separately for each sex.

 

PARAM will accept values of the expectation of life at birth between 19.02 and 75.70.

 

If Input Option Parameter P3 is a "1," the program requests:

 

     ENTER 1 EXPECTATION(S) OF LIFE AT BIRTH (10XX.XX): ,

 

to which the user might respond

 

     70.00 (ENTER) .

 

If Input Option Parameter P3 is a "2," then ten such numbers must be entered.

 

Note that, depending on the value of the Life Table Option Parameter P4, the user specifies either Infant Mortality Rates or Expectations of Life at Birth, but not both.

 

Base-Year Population, Other Base-Year Data, and Data for the Ten-Year Period Prior to the Base Year

 

Base-Year Population  The program requests entry of the base-year population by thirty-two age x sex categories -- sixteen five-year intervals by two sexes.  To illustrate, the following table presents the US resident population for 1980, categorized by these two variables:

 

                  Age        Male          Female

 

                  0-4     8,360,135   7,984,272

                  5-9     8,537,903   8,159,231

                 10-14    9,315,055   8,925,864

                 15-19  10,751,544 10,410,123

                 20-24  10,660,063 10,652,494

                 25-29    9,703,259   9,814,413

                 30-34    8,675,505   8,882,452

                 35-39    6,860,236   7,102,772

                 40-44    5,707,550   5,960,689

                 45-49    5,387,511   5,700,872

                 50-54    5,620,474   6,088,510

                 55-59    5,481,152   6,132,902

                 60-64    4,669,307   5,416,404

                 65-69    3,902,083   4,878,761

                 70-74    2,853,116   3,943,626

                 75+      3,547,402   6,419,145

                 Total  110,032,295 116,472,530

                 Grand Total   226,504,825

 

Source: 1980 Census of Population, Supplementary Reports, PC80-S1-1, Age, Sex, Race, and Spanish Origin of the Population by Regions, Divisions, and States: 1980, Table 1. "Population of the United States by Age, Sex, Race, and Spanish Origin, 1980, US Department of Commerce, Bureau of the Census (for sale by the Superintendent of Documents, Washington, DC 20402), issued May, 1991.  This report presents resident population, i.e., excluding Armed Forces overseas.

 

The program requests:

 

     ENTER BASE-YEAR POPULATION, BY AGE (16 ENTRIES, FORMAT           8XXXXXXXXX.) FOR SEX = i: ,

 

where i = MALE or FEMALE.  The format 8XXXXXXXXX. indicates that these data are to be entered as decimal number of up to nine digits each (plus a decimal), eight at a time.  In the preceding example, the data would be entered in four steps, as follows:

 

8360135.,8537903.,9315055.,10751044.,10660063.,9703259.,8675505.,6860236. (ENTER)

5707550.,5387511.,5620474.,5481152.,4669307.,3902083.,2853116.,3547402. (ENTER)

7984272.,8159231.,8925864.,10410123.,10652494.,9814413.,8882452.,7102772. (ENTER)

5960689.,5700872.,6088510.,6132902.,5416404.,4878761.,3943626.,6419145. (ENTER)

 

Each of the four sets of entered data should be typed on a single line, not on two lines as shown here.  Note that commas may be used as delimiters between the data values, but they must not be used within each number.

 

Exactly eight population entries must be typed prior to each depression of the ENTER key.  If fewer than eight entries are typed, the remaining entries (up to eight) will be recorded as zeros.  If more than eight entries are typed, they will be lost.

 

Note that, just as is the case for all other demographic parameters, a separate set of base-year population figures is required for each race being considered.  In the preceding example, no racial structure would have been specified for the model, and the population value for each age x sex category includes persons of all races.

 

Other Base-Year Data  The following additional base-year data:

 

o crude birth rate

 

o crude death rate

 

o infant mortality rate

 

are entered.  The first two of these data elements are used, along with the base-year population, to determine an estimate of the Total Fertility Rate for the base year.  This estimate may be used if reliable data on the Total Fertility Rate are not available from published sources.  The last data item (infant mortality rate for the base-year period is not presently used in the model computations; it is entered for display purposes along with other demographic data.

 

The program makes the following three requests:

 

ENTER CRUDE BIRTH RATE (PER 1000) FOR BASE YEAR (FORMAT

          XXX.XX):

 

ENTER CRUDE DEATH RATE (PER 1000) FOR BASE YEAR (FORMAT

          XXX.XX):

 

ENTER INFANT MORTALITY RATE (PER 1000) FOR BASE YEAR

         (FORMAT XXX.XX):

 

to which the user might provide, for example, the values 15.90, 8.70, and 13.80.

 

Data for the Ten-Year Period Prior to the Base Year  In order to estimate migration, the program uses the following data for the ten-year period preceding the base year:

 

o Population ten years prior to the base year

 

o Average crude birth rate for the ten-year period prior to the base year

 

o Average crude death rate for the ten-year period prior to the base year.

 

In addition, for display/comparison purposes, the following data element is requested:

 

o Average infant mortality rate for the ten-year period prior to the base year.

 

The program makes the following requests:

 

ENTER POPULATION TEN YEARS PRIOR TO BASE YEAR (FORMAT

       XXXXXXXXX.):

 

ENTER AVERAGE CRUDE BIRTH RATE (PER 1000) FOR PREVIOUS

       TEN YEARS (FORMAT XXX.XX):

 

ENTER AVERAGE CRUDE DEATH RATE (PER 1000) FOR PREVIOUS

       TEN YEARS (FORMAT XXX.XX):

 

ENTER AVERAGE INFANT MORTALITY RATE (PER 1000) FOR

       PREVIOUS TEN YEARS (FORMAT XXX.XX):

 

to which the user might provide, for example, the values 203302301., 15.90, 8.70, and 13.80.

 

External Migration (Total Net Migration for All Regions)

 

As mentioned earlier, the PARAM program allows five options for entry of migration information.  The migration data describe the total migration for all regions.  The manner in which the migration is associated with the various regions of the model (if the model contains more than one region) is described in the following section (on internal migration).

 

The data entry for the five external migration options (0-2) are described below.

 

o Option 0. No net external migration; no data entered.

 

o Option 1. The user specifies (for each race) a single annual migration rate or a single annual migration number (amount), which apply to all future five-year projection periods.  (In the model, the total number of net migrants (immigrants and emigrants) is allocated to each age x sex cohort (category) in proportion to the size (population) of each cohort.)

 

o Option 2. The user specifies a separate migration rate or migration number for each of the ten five-year projection periods.  (As with Option 1, the model allocates the total number of net migrants (immigrants or emigrants) to each age x sex cohort in proportion to its size.)

 

The migration rates and migration numbers are annual values, and the rates are per 1,000 persons.  The migration rate is the average net number of immigrants (persons moving into the area) per 1,000 persons per year.  The migration number is the average net number of immigrants per year.  The term "net" refers to the difference between immigrants and emigrants.  Net migration may be positive or negative.

 

Net migration rates and numbers may be either positive (net gain in population from immigration and emigration) or negative (net loss in population from immigration and emigration).  For example, a migration rate of -1.0 represents a net emigration of one person per 1,000 population per year from an area.  Similarly, a migration number of -7,000 represents a net emigration of 7,000 persons from an area.

 

Migration rates and numbers are intended to represent total net migration for the race under consideration, and typically only one of these two parameters is used.  In (very) rare instances, however, the user might specify nonzero values for both parameters.  One such instance is the testing of alternative models.  In another instance, nonzero values might be used for both parameters in the situation in which accurate data were available separately for emigration and immigration.  In this case, the emigration would be represented by a negative migration rate and the immigration would be represented by a positive migration number.  In most situations, accurate data will not be available for emigration and immigration separately.  Instead, estimates will be available for total net migration (immigrants less emigrants), and the total net migration may be expressed either as a net migration rate (if negative) or a net migration number (if positive).

 

Although migration rates and numbers may be positive or negative, it is highly recommended that positive net migrations be represented by (positive) values of the net migration number and that negative net migrations by represented by (negative) values of the net migration rate.  Because migration rates are typically used in cases in which an area is losing population, we shall sometimes refer to a migration rate as an emigration rate; similarly, because migration numbers are typically used in cases in which an area is gaining population, a migration number shall sometimes be referred to as an immigration number.  This terminology may be confusing, however, since strictly speaking both the migration rate and the migration number measure immigration (migration into an area.

 

The rationale for the convention of using migration rates for negative migrations (net population losses) and numbers for positive migrations (net population gains) is both logical and practical.  In the first instance, a country that is gaining population through immigration (such as the US) may enforce numerical limits on immigration, whereas population shrinkage due to emigration is less subject to control and more logically represented as a percentage of the country's remaining population.  From a practical viewpoint, large net positive immigration levels should definitely not be used, since they quickly lead to absurdly high population projections.  As a general rule, migration numbers should always be positive (representing net positive immigration) and migration rates should always be negative (representing net positive emigration).

 

Under External Migration Option 1, the program first requests:

 

ENTER 1 NET MIGRATION RATE(S) (ANNUAL, PER 1000,            8XXXX.XXX): ,

 

(to which the user might respond, for example,

 

     -8.3 (ENTER)  ),

 

and

 

     ENTER 1 NET MIGRATION NUMBER(S) (ANNUAL, 8XXXXXXXXX.): ,

 

(to which the user might respond, for example,

 

     500000. (ENTER)   ).

 

As discussed above, typically at most one of these two entries would be nonzero.

 

Under Option 2, the program requests ten migration rates and ten migration numbers.  (Note: Since the format for the migration numbers is 8XXXXXXXXX., two data entries are required, the first line consisting of eight numbers and the second line consisting of two numbers.)

 

Note on Other Factors Included in External Migration

 

Changes in the size of a population of a specific race may result from factors other than births, deaths, and net external migration.  Other factors that may contribute to changes in the size of a population of a specific race include changes in race declarations, changes in procedures, criteria, or categories used to collect race data, and crossbreeding among races.  Changes in the size of a population of a specific race beyond those associated with births, deaths, and external migration are referred to as "race transitioning."

 

In the DESTINY model, race transitioning is included in external migration.  For example, if the net external migration of a population of a specific race over a particular time interval is 1,000, this could refer to 1,000 immigrants and no emigrants; or 4,000 immigrants and 3,000 emigrants; or no immigrants, no emigrants, and 1,000 births that are not classified as the race of the mother; or 1,000 individuals who declare their race differently at the end of the time interval from what it was at the beginning of the time interval.

 

Under the convention that external migration includes race transitioning, external migration may be defined simply as the total amount of population change (for a particular race) net of births and deaths.  This convention not only simplifies the model specification, but more importantly it simplifies the problem of estimating values for the model input parameters.  From available data, it is a simple matter to estimate the population change net of births and deaths -- the problem of attempting to decompose this quantity into a portion due to migration and a portion due to race transitioning is formidable.

 

It is noted that the population change that occurs over a time interval beyond that associated with specified birth and death rates (or, more properly, with specified fertility and mortality rates) is not limited to external migration and race transitioning.  If the fertility or mortality rates change from the specified values, the size of the population will differ from the projected size associated with the specified values.  While external migration may be a major factor explaining why a future population differs from that projected for a specified fertility and mortality rate, it is not the only factor.

 

Regional Populations

 

If the user entered "1" (or "0" or blank) for the number of regions, the program will not ask for regional populations.  If any number greater than one were entered, then the user must enter the total population of each region.  A separate set of regional populations is required for each race being entered into the parameter file.

 

If regional structure is being incorporated into the model, the program requests:

 

     ENTER BASE-YEAR POP'N BY REGION (8XXXXXXXXX.): .

 

The regional populations are entered with the same format as the base-year populations by age and sex -- eight values per entry.  Of course, if there are fewer than eight regions, then fewer than eight values will be typed.  As an example, suppose that there are twelve regions.  In this case, two entries will be required -- eight values for the first entry, and four entries for the second.

 

The sum of the regional populations must equal the sum of the base-year populations by age and sex.  If they do not, the program rejects the entered regional populations, and requests the user to enter correct values.

 

The program then requests the regional populations for the year ten years previous to the base year (same format as above).  The sum of these regional populations must equal the total population ten years prior to the base year.  If they do not, they are rejected and correct values requested.

 

Internal Migration (Including Allocation of External Migration to Regions)

 

As remarked earlier, internal migration refers to the redistribution of the population among the regions of the area, due to movement of the residents from one region to another, to settlement of immigrants, and to emigration.  Under Option 0, or if there are no regions in the model, there is no data entry.

 

If Internal Migration Option 0 is specified, the population change of each region from one projection period to the next (due to births, deaths, and external migration) is proportional to the current regional population (of a particular race), for every race.  In this case, any differences in growth rates among the regions are solely due to differences in birth and death rates resulting from different racial compositions of the regions.  Whatever external migration was specified in the preceding section is allocated to the regions of the model in proportion to their populations (of the race under consideration).  (Under Option 0, if there were but a single race represented in the model, all regions would grow at the same rate.)

 

Under Option 1, the program represents internal migration as the population change (number or rate per 1,000) net of births, deaths, and external migration allocated proportional to the regional population (of the race under consideration).  In other words, the internal migration parameters specify the average annual amount of change or rate of change (per 1,000 population) in the regional population beyond that attributable to births, deaths, and a proportional allocation of external migration to the regions.  As used in the DESTINY system, the term "internal migration" hence includes not just interregional population movements but also nonproportional allocations of external migration to the regions.

 

If external migration is estimated as the population change net of births and deaths, the regional internal migration amounts will sum to zero over all regions (the regional internal migration rates do not necessarily sum to zero, except by coincidence).  The sum of the regional population changes computed from the rates (by multiplying each regional rate by the regional population) is not necessarily zero, although it should be close to zero.  The program resolves this inconsistency through the use of an adjustment procedure analogous to that discussed previously in the section on external migration (under the option that permits the entry of age/sex-specific external migration rates).  With this procedure, changes in regional populations due to internal migration are proportional to the user-specified regional growth parameters.  If the sum of the regional population changes resulting from this procedure is not zero (so that the population total is changed), all populations are proportionally adjusted (scaled) to bring the total population back to the value prior to application of the internal migration process.

 

The user may specify an internal migration rate and/or an internal migration amount for each region.  As usual, it is recommended that a rate be used if the parameter value is negative, and an amount be used if the parameter value is positive.

 

Unless accurate data on external migration are available and race transitioning is negligible, it is recommended that external migration be estimated as population change net of births and deaths, so that the sum of the internal migration amounts is zero.

 

Under Option 1, the program requests:

 

ENTER n REGIONAL INTERNAL MIGRATION RATES (ANNUAL, PER

 1000, 8XXXX.XXX): ,

 

where n denotes the number of regions.  The user must specify one internal migration rate for each region.  The rate for a region is the annual rate of population growth per 1,000 net of births, deaths, and proportional allocation of external migration to the regions.  The format is 8XXXX.XXX, and at most fourteen regions are allowed, so that all numbers are to be entered as a single data entry.

 

The program then requests:

 

ENTER n REGIONAL INTERNAL MIGRATION AMOUNTS (ANNUAL,

 8XXXXXXXXX.): .

 

If more than eight entries are needed, more than one line will be required for data entry.  The internal migration amount for a region is the average annual population change net of births, deaths, and proportional allocation of external migration to the regions.

 

If the convention of using rates for negative numbers and amounts for positive numbers is followed, the user will be required to enter rates for some regions and amounts for other regions, but only one of these parameters will be nonzero for each region.

 

With the completion of the internal migration input, the demographic data entry cycle is completed for one race, and the program recycles to request the demographic data entry for the next race (if any.)

 

 

D.  Service-System (Program-Related) Parameters and Data

 

If the user indicated that no program-related data were to be entered (by entering a "0" for the service system option P7 in the Input Option Parameter section, then this input section is skipped by the program.  Otherwise, the data entry is as follows.

 

Service-System Parameters

 

There are five service-system parameters, corresponding to five subsections of the service-system data section of the PARAM program:

 

     S1: Number of Target Populations (1-4)

     S2: Service Population Option (0,1, or 2)

     S3: Number of Services (0-10)

     S4: Number of Resources (0-7)

     S5: Number of Cost Categories (0-4).

 

The program requests entry of each of these service-system parameters by means of five separate requests, as follows:

 

     ENTER NO OF TARGET POPULATIONS (1-4):

 

     ENTER SERVICE POPULATION OPTION (0,1, OR 2):

 

     ENTER NUMBER OF SERVICES (0-10):

 

     ENTER NUMBER OF RESOURCES (0-7):

 

     ENTER NUMBER OF COST CATEGORIES (0-4):   .

 

After each of the preceding requests, the user types the appropriate number, and depresses the ENTER key.  For all but the second parameter, the nature of the parameters is self-evident.  For the second parameter, the options are as follows:

 

o Option 0. There is no service population.

 

o Option 1. The service population is identical to the target population.

 

o Option 2. The service population is proportional to the target population.  The factor of proportionality may be less than or greater than unity.  That is, the size of the service population may be less than or greater than the target population.

 

The five parameters S1-S5 determine how much data entry follows.  If any parameter is zero, the corresponding data entry section and all succeeding data entry sections of the service-system data section are skipped.  For example, if the five entries were 1, 0, 1, 1, and 1, then only target population data would be accepted.

 

After the user enters the five service-system parameters, the program requests the user to enter names corresponding to all of the target populations, service populations, services, resources, and cost categories that have been specified.  These requests are as follows:

 

     ENTER NAME FOR TARGET POPULATION NO i (8X):

 

     ENTER NAME FOR SERVICE POPULATION NO j (8X):

 

     ENTER NAME FOR SERVICE NO k (8X):

 

     ENTER NAME FOR RESOURCE NO m (8X):

 

     ENTER NAME FOR COST CATEGORY NO n (8X):   ,

 

where i varies from 1 to the number of target populations, j varies from 1 to the number of service populations, k varies from 1 to the number of services, m varies from 1 to the number of resources, and n varies from 1 to the number of cost categories.

 

Note that in ordinary speech the service population and the target population will often have the same name, e.g., the term "elderly" could refer either to "all elderly persons," or to "elderly persons served."  In giving names to these two populations (the target population and the served population), however, it will avoid substantial confusion in the PROJ printout if different names are used.  For example, the acronym ELDERLY could be used for the target population, and the acronym ELD(SV) could be used to denote the served elderly.  Then, in the PROJ output, no confusion will arise --for example, it will be clear that a crosstabulation labeled "DISTRIBUTION OF ELDERLY BY AGE AND SEX" refers to the total elderly population, not just the served elderly population.

 

Similarly, in naming services, resources, and costs, use different labels, e.g., COUNSLNG for counseling services, COUNSELR for a counselor (a resource), and COUNCOST or COUNSLR$ for the cost of counseling, so that the PROJ printouts are unambiguously labeled.  If the single word COUNSELR were used for all three entities, the labels which PROJ prints out on the various tables would be confusing.

 

The name may consist of any eight characters, including blanks.  For example, suppose that there are two cost categories -- direct costs and administrative costs.  Names for these two cost categories could be as follows:

 

     DIR COST and ADM COST ,

 

where the blank is typed using the space bar on the console keyboard.

 

Each of the five data subsections of the Service System Data section will now be described.  The five subsections are discussed in the following order:

 

     o  Service Parameters

     o  Resource Parameters

     o  Cost Parameters

     o  Target Population Parameters

     o  Service Population Parameters.

 

Although specification of the target population and service population parameters would logically precede the specification of the other service-system parameters, they are entered last, in order to permit certain efficiencies in the program computer code.

 

Service Parameters

 

For each service population, the user must enter the average number of service units of each type expended per case served per year.  By means of example, suppose that there are two target populations, two service populations, three services, and that the average numbers of service units are as follows.

 

                                               Service Units

     Service Population      Service Type        /Case/Year

 

     1. Child Abuse    1. Counseling (COUNSLNG)       24.0 hrs.

        (CH ABUSE)     2. Physical Therapy (PHYSTHRP)  0.0 hrs.

                       3. Day Care (DAY CARE)        200.0 hrs.

     2. Disabled       1. Counseling                  12.0 hrs.

        (DISABLED)     2. Physical Therapy            80.0 hrs.

                                                       0.0 hrs.

 

In this case, the program would request:

 

     SERVICE POPULATION = CH ABUSE

     ENTER AVERAGE NO OF SERVICE UNITS (XXXXX.XXXX) PER CASE          SERVED, FOR SERVICE TYPE = COUNSELNG: .

 

The data entry in this case would be:

 

     24.  (ENTER) .

 

The program would then request:

 

     SERVICE POPULATION = CH ABUSE

     ENTER AVERAGE NO OF SERVICE UNITS (XXXXX.XXXXX) PER CASE         SERVED, FOR SERVICE TYPE = PHYSTHRP: ,

 

to which the user would respond:

 

     0.  (ENTER) .

 

The program would repeat a similar request for service type Day Care, and then make three similar requests for the service population Disabled.

 

Note that the average number of service units requested by the program is the average over all served clients in the service population, over an entire year.  It is not the conditional average, given that the client receives at least some of the service (this latter quantity would be much larger).

 

Resource Parameters

 

For each service, the user must enter the average number of resource units of each type required per service unit.  It is emphasized that this parameter is the average per service unit, not per case.  For example, suppose that there are two resource types (counselors and contract services), and that the average number of resource units per service unit are as follows.

 

                                                 Resource Unit

     Service Type   Resource Type           /Service Unit

 

     1. Counseling  1. Counselor (COUNSELR)    .0005 cnslrs/hrs

        (COUNSLING) 2. Contract Service       0.0

                        (CONT SVC)

     2. Physical    1. Counselor              0.0

         Therapy    2. Contract Service      25.0 cntrct svc

                                                  units / hour

     3. Day Care    1. Counselor              0.0

        (DAY Care)  2. Contract Service      30.0 cntrct svc

                                                  units / hour

 

In this example, it is assumed that the state does not employ physical therapists or provide day care services.  Instead, both physical therapy and day care services are provided by outside contractors (service providers).  In this case, the resource units are in fact dollars.  It is assumed that each counselor works 2000 hours per year, so that the average number of counselors (the resource) per counselor hour (the service) is (1 counselor)/(2000 hours of service) = .0005 counselors per hour of counselor service.

 

The program first requests:

 

     SERVICE TYPE = COUNSLNG

     ENTER AVERAGE NO OF RESOURCE UNITS (XXXXX.XXXX) PER              SERVICE UNIT, FOR RESOURCE TYPE = COUNSELR: ,

 

to which the user responds:

 

     .0005 (ENTER) .

 

The program next requests:

 

     SERVICE TYPE = COUNSLNG

     ENTER AVERAGE NO OF RESOURCE UNITS (XXXXX.XXXX) PER              SERVICE UNIT, FOR RESOURCE TYPE = CONT SVC: ,

 

to which the user responds:

 

     0.0 (ENTER) .

 

The program then goes on to the next service type (Physical Therapy), and asks for the average number of units of each resource type.  The same is then done for the third service type (Day Care), and the Resource Parameter section is finished.

 

Cost Parameters

 

For each resource, the user must specify the average cost (for up to four cost categories) per resource unit.  It is emphasized that this is the average cost per resource unit, not per client or per service unit.  For example, suppose that two cost categories are of interest -- state personnel costs and contract services costs -- and that the average cost per resource unit are as follows:

 

                                               Cost

     Resource Type      Cost Category       /Resource Unit

 

     1. Counselor     1. State Personnel  $20,000.00/counselor

        (COUNSELR)       (DIR SV $)

                      2. Contract Service       0.00/counselor

                         (PUR SV $)

 

2. Contract Svc  1. State Personnel        0.00/contract

        (CONTR SV)                              service unit

                      2. Contract Service      $1.00/contract

                                                service unit

 

Since the contact service units are actually dollars, the number of dollars per contract service unit is 1.00.

 

The program requests:

 

     RESOURCE TYPE = COUNSELR

     ENTER AVERAGE COST (XXXXX.XXXX) PER RESOURCE UNIT, FOR           COST CATEGORY = DIR SV $: ,

 

to which the user responds:

 

     25000. (ENTER) .

 

This question is repeated for the second cost category (Contract Services), to which the user responds with the entry 0.00.  The question is then repeated two more times for the second resource type (Contract Services), completing the data entry for the cost parameters.

 

Note that in the preceding example, the resource associated with counseling services was defined to be a counselor, and the cost was $20,000.00 per counselor (one year's salary plus overhead).  We might just as easily have defined the resource in this case to be a counselor-hour, in which case the cost would have been $20,000.00/2000 = $10/counselor-hour.

 

Target Population Parameters

 

The program requires a set of incidences (or prevalences, as the case may be) for each target population.  Incidences (used in the case of the occurrence of acute medical conditions or events such as prison admissions) indicate the rate of occurrence of each type of condition in a single year (not in a five-year period).  Prevalences (used in the case of chronic conditions) indicate the proportion of the population that has each condition at a point in time.  Both rates (incidences or prevalences) refer to the population, e.g., an incidence of .01 signifies that 1% of the total population acquires the condition defining the target population at some time during the year, each year.  Similarly, a prevalence of .01 signifies that 1% of the total population has the condition defining the target population at any given point of time in the year.  In the discussion that follows, we shall use the term "incidence" or "rate," rather than the more correct but cumbersome "incidence or prevalence."  Note that incidences may exceed one in value (since the average number of occurrences of a condition might exceed one per person), but that prevalences (which refer to a subset of a population) are less than or equal to one.

 

There are ten different ways in which the user may enter incidences, depending on the level of detail desired.  These ten ways are called "stratifications."  They are defined as follows.

 

o    ST1: A single rate is specified for the entire popu- lation.  (Strictly speaking, this case corresponds to "no stratification.")

o    ST2: A separate rate is specified for each age category.

o    ST3: A separate rate is specified for each sex category.

o    ST4: A separate rate is specified for each race.

o    ST5: A separate rate is specified for each age x sex category.

o    ST6: A separate rate is specified for each age x race category.

o    ST7: A separate rate is specified for each sex x race category.

o    ST8: A separate rate is specified for each age x sex x race category.

o    ST9: A separate rate is specified for each region.

o    ST10: A separate rate is specified for each race x region category.

 

Which level of detail, or stratification, is selected depends on two factors: what level of detail is present in available data, and what level of detail is desired in the cross- tabulations of the PROJ projections.  For example, if the user wants breakdowns of the population by race, and there are differences in the incidence by race, then stratification option ST4 should be used.

 

Note that the level of detail of the crosstabulation projections should ordinarily not exceed the level of detail of the input data.  For example, if a single incidence is specified for the entire population, then projection cross- tabulations should not be specified by age x sex x race, unless it is known that the incidence is in fact the same for all age x sex x race categories.

 

The user will usually be able to find reasonably good national-level data which indicates incidences for the general population, so that option ST1 may be used.  Furthermore, for many target populations, incidences by age, by sex, by race, or by combinations (e.g., sex x race) are available.  Incidences are generally not available by age x sex x race, except for conditions that have been studied rather extensively.  If several low-dimensional crosstabulations are available (e.g., by age, by sex, and by race), procedures are available for statistically estimating a higher-dimensional crosstabulation (e.g., age x sex x race) from these lower-dimensional crosstabulations.

 

There are two different ways in which incidences are entered to the program.  For options ST1, ST3, ST4, and ST7, the program instructs the user to enter incidences for each and every stratum "cell" (combination of levels of the variables of stratification), in a particular order specified by the program, and also specified on the data entry forms of Appendix B.

 

For example, suppose that the following incidence matrix applies:

 

                                   Race

                          W      O

                     M   .02    .04

                Sex

                     F   .03    .05

 

That is, the user wishes to specify incidences by sex and race (option ST7).  In this case, the data entry is as follows.

 

First, the program prints out the following on the video screen:

 

     THE FOLLOWING TYPES OF STRATIFICATION ARE AVAILABLE:

     1: NONE

     2: AGE

     3: SEX

     4: RACE

     5: AGE X SEX

     6: AGE X RACE

     7: SEX X RACE

     8: AGE X SEX X RACE

     9: REGION

    10: REGION X RACE

    ENTER TYPE OF STRATIFICATION (1-10): .

 

Since stratification type 7 is desired, the user enters

 

     7 (ENTER) .

 

The program then requests:

 

     ENTER 4 INCIDENCE PREVALENCE RATES (8X.XXXXXXXX): .

 

In accordance with the sequence specified by the data entry form of Appendix B, the user must enter the four rates as follows:

 

     .02,.03,.04,.05 (ENTER) .

 

The order in which the entries are made in the data entry forms is as follows:

 

     Increment age, followed by sex, followed by race.

 

Hence, in the preceding example, two age values were input for the first race, followed by two values for the second race.  Increment age in increasing order of age, sex by male followed by female, and races in the order in which they were entered in the PARAM data entry program (and are displayed by the CHECK program).

 

The preceding example illustrates the data entry procedure for options ST1, ST3, ST4, and ST7.  For the other options, ST2, ST5, ST6, ST8, ST9, and ST10, the user must specify up to nine different rates, and then specify, for each stratum cell, which rate applies.  (This approach is used for all stratification options in which the total number of stratum cells exceeds nine.)  For example, suppose that the option ST2 is used, i.e., stratification is desired by age.  Suppose that the incidences are as follows:

 

         Age Category       Incidence

 

                  0-4             0.0

                  5-9             0.0

                 10-14             .01

                 15-19             .05

                 20-24             .02

                 25-29            0.0

                 30-34            0.0

                 35-39            0.0

                 40-44            0.0

                 45-49            0.0

                 50-54            0.0

                 55-59            0.0

                 60-64            0.0

                 65-69            0.0

                 70-74            0.0

                 75+                0.0

 

In this example, the program will request:

 

     ENTER TYPE OF STRATIFICATION (1-10): ,

 

to which the user will respond:

     2 (ENTER) .

 

The program will then request:

 

     ENTER 9 INCIDENCE/PREVALENCE RATES (8X.XXXXXXXX):

 

to which the user will respond:

 

     0.0,.01,.05,.02 (ENTER) .

 

The user enters four different rates, since there are only four different rates specified in the table shown above.  There is no need to explicitly enter five additional zeros; by depressing the ENTER key after only four values, the next four values will automatically be taken as zeros.  Since the program requires that nine values be entered, but the format only allows for the entry of eight values at a time, the ENTER key must be depressed a second time, to allow for the entry of the ninth value (a blank, in this example).  In an example in which nine different values were entered, eight would be entered on the first line (followed by ENTER), and one would be entered on the second line (followed by ENTER.)

 

The program next requests:

 

     ENTER 16 INDICES (ONE FOR EACH AGE COHORT), EACH OF VALUE         1-9 (16X): ,

 

to which the user may respond either with:

 

     1,1,2,3,4,1,1,1,1,1,1,1,1,1,1,1 (ENTER) ,

 

or

 

     1123411111111111 (ENTER) .

 

The i-th index number in this list indicates which of the four entered rates applies to the i-th age category.  For example, the index "2" in the third position of the index list signifies that the second rate (.01) applies to the third age category (ages 10-14).

 

There are limits on the number of stratifications of each type (in addition to the overall limit of four target populations in all.  The following table specifies the maximum number of stratifications of each type:

 

                    ST1  4

                    ST2  4

                    ST3  4

                    ST4  4

                    ST5  4

                    ST6  4

                    ST7  4

                    ST8  4

                    ST9  4

                    ST10 4

 

From this table, we see that the incidence rates for up to four target populations can be specified using stratification type ST2 (stratification by age), but only one target population can be specified using stratification type ST8 (stratification by age, sex, and race).

 

The user is requested by the program to enter incidences for each of the target populations specified.

 

Service Population Parameters

 

With regard to service populations, there are three different cases (corresponding to the three options of the Service-System Parameter S2).  If a "0" is specified for the value of Service-System Parameter S2, then no service population data are requested, and the Service System Parameter section is skipped.  If S2 = 1, then the total target population is taken as the service population, i.e., the service population is all of the persons in the target population.  If S2 = 2, then the service population is a proportion of the target population.  The factor of proportionality may be less than or greater than one.  These factors, called service ratios, may vary by the same variables of stratification (age, sex, race, or region) as were described for the incidences/prevalences of the Target Population Parameter section, and the procedure and formats for the data entry of the service ratios are exactly the same as for the Target Population Parameters.

 

For example, suppose that there is only one target population under study, and that a flat 10% of the target population is served, regardless of age, sex, or race, then the user would specify option ST1 (no stratification), and enter a "1" when requested to enter the type of stratification.  The program would then prompt for the rate, which would be entered as ".1" (format X.XXXXXXXX).

 

Note that the services, resources, and costs do not vary by demographic characteristics of the served population.  Any dependencies of service on age, sex, race, or region must be reflected in the definition of the target population or the service (served) population.  Because of this restriction, it may be desirable (if services, resources, or costs vary by demographic characteristics of the person served) to define a service population as a number of person-years or a number of occurrences of a condition, rather than a number of individuals (subset of the target population).

This completes the data entry for the PARAM program.

 

A Note on Updating a Parameter File

 

When creating a new parameter file from an existing parameter file, it is often the case that the user retains much of the old data in the new file, without change.  For example, the user may wish simply to append some target population data to an existing demographic-data parameter file.  In this case, the program will prompt the user many times with a request such as:

 

     ENTER 1 TO CHANGE DATA, 0 OTHERWISE: .

 

The response in most cases will be:

 

     0 (ENTER) .

 

To save time, there is no need to actually enter the "0" -- the user may simply depress the ENTER key, and the program will automatically interpret that a "0" was entered.  In this way, the user may very quickly run through those portions of the file which are not to be changed (such as the demographic parameters, in the example specified.)


III.  How to Use the CHECK Program to Print a Parameter File

 

The CHECK program has two uses.  Its main use, described in this chapter, is to print out the contents of a parameter file.  A second use, to adjust the service parameters of a parameter file, is described in Chapter V.

 

After using the PARAM program to enter the parameters, it is important to review them with a CHECK run.  It is easy to enter a wrong digit, or to invert two digits, in entering the data to PARAM.  Also, if a string of data were entered using the wrong format, the data values will be recorded wrong in the parameter file.  For example, suppose that a series of fourteen numbers were required for entry by PARAM, using format 8F10.0, but the user entered ten entries on the first line and four on the second line (instead of eight entries on the first line and six on the second line).  In this case, the last two entries on the first line would be ignored by the program, resulting in an incorrect data entry.  The user would not be aware of such an error until running the CHECK program, when it would be seen that two of the entries had been lost.

 

In addition to using CHECK to review new data input, it can be used to obtain a permanent hard-copy record of the contents of the parameter file.  The reason for doing this is that the PROJ program does not print out any parameters -- it prints only projections (or summaries of the base-year data).  A CHECK printout of the parameter file should be attached to the DEST printout, so that the analyst can be certain of the parameter values to which the PROJ run corresponds.  The parameter file name is printed at the beginning of both the CHECK and PROJ printouts, for ready comparison.

 

The CHECK program is executed by typing CHECK at the MS-DOS prompt.  The first request the CHECK program makes is:

 

     ENTER 0 TO PRINT EXISTING PARAMETER FILE, 1 TO INPUT NEW         SERVICE-SYSTEM PARAMETERS FROM SERVICE-SYSTEM ADJUSTMENT        FACTORS: ,

 

to which the user responds:

 

     0 (ENTER) ,

 

in order to obtain the desired printout.

 

The program's next request is:

 

     ENTER NAME OF PARAMETER FILE (12X): .

 

The user should enter the name (a valid MS-DOS file name) exactly as he defined it in the PARAM run.  For example, if the file name is AZ03CS.DAT, the user responds with:

 

     AZ03CS.DAT (ENTER) .

 

The program then prints the parameter file.  The user may direct the output to the video monitor, the printer, or to a file named CHECKOUT.FIL .

 


IV.  How to Use the PROJ Program to Make Projections

 

The PROJ program computes projections based on the parameter values in the parameter file.  The PROJ program is executed by typing PROJ at the MS-DOS prompt.  After the program begins execution, the user specifies the names of the parameter files, the number of five-year periods to project, and the amount of printed output desired.

 

After printing out a copyright notice on the video screen and on the line printer, the PROJ program's first request is:

 

     ENTER NAME OF PARAMETER FILE (12X): ,

 

to which the user responds with entry of the name that was specified in the PARAM program run which created the parameter file, e.g., AZ803CS.DAT .  The PROJ program prints out (on the line printer) the name of this file, the file header, and the base year.

 

The program then asks the number of five-year periods to project.  This number must be between 0 and 10.  If a zero is entered, the program will analyze the base-year data, but not construct any projections.  The number of years to be projected is five times the entry, e.g., if a "3" is entered, then the program will project up to fifteen years into the future.  The number specified by the user is printed by the line printer.  The video request is:

 

     ENTER NO OF FIVE-YEAR PERIODS TO PROJECT (0-10): .

 

(Note: If the user enters "1," after the number of periods to project, the program will print out all of the cohort-specific survival probabilities.  Since these quantities are of limited interest in many applications, the program does not prompt the user concerning their printout.  If three five-year periods are to be projected, and the survival probabilities are desired, the data entry is:

 

     3,1 (ENTER) .)

 

Next, the program prints the following message:

 

     THE FOLLOWING TABLES OR CROSSTABULATIONS ARE AVAILABLE:

     1: TOTAL

     2: AGE

     3: SEX

     4: RACE

     5: AGE X SEX

     6: AGE X RACE

     7: SEX X RACE

     8: AGE X SEX X RACE

     9: REGION

     10: REGION X RACE

     SPECIFY CROSSTABS DESIRED (10 NOS, 0 OR 1, FORMAT 10X): .

 

This prompt allows the user to specify which crosstabulations he wants for the base year.  The program will repeat this request for each five-year period, so that different crosstabulations may be specified for each five-year projection period.

 

The user answers this request by typing ten numbers, each 0 or 1.  If the i-th number of this ten-tuple is a 1, then the i-th type of table or crosstab will be printed out.  For example, if only a crosstab of sex x race is desired for the base year, the user would type:

 

     0000001000 (ENTER) .

 

If a table by age is also desired, the user would type:

 

     0100001000 (ENTER) .

 

If the user does not select any tables or crossbulations, then the analysis proceeds to the next projection period.  Otherwise, the program next requests:

 

     ENTER 1 TO SKIP SERVICE-SYSTEM ANALYSIS, 0 OTHERWISE: .

 

If the user enters a 1 in response, the program will print out only demographic information, and not any service-system-related information (on the target populations, service populations, services, resources, or costs).  If a 0 is entered, a full printout (with both demographic and service-system data) will be done.  After responding to this request, the line printer then prints out the crosstabulations that were requested by the user.

 

The program then prints the following information and request on the video screen:

 

     PROJECTION PERIOD NO 1

     YEARS: 19XX TO 19XX ,

 

and repeats the request for the user to specify which crosstabs are desired, for the first five-year projection period.

 

After the user specifies the desired crosstabs, the program then requests:

 

     ENTER 1 TO SKIP SERVICE-SYSTEM ANALYSIS, 0 OTHERWISE,

 

to which the user responds 0 or 1, as desired.  Next, the program requests:

 

     ENTER 0 TO PRINT 5-YEAR PROJECTIONS, 1 TO PRINT 1-YEAR           PROJECTIONS: .

 

If the user specifies a 0, the program will print out the projection for the fifth year out.  If the user specifies a 1, the program will print intermediate years, and prompt the user to specify the intermediate years for which printouts are desired with the following request:

 

     ENTER WHICH YEARS TO PROJECT (5 INTEGERS, 0 = NO, 1 = YES,         FORMAT 5X): .

 

The user enters five numbers, each 0 or 1.  If the i-th number is a 1, then a projection will be printed out for the i-th year.  For example, if the user enters 11111, then the program will print out projections for all five years.  These intermediate-year projections are computed by linear interpolation between the results for two adjacent five-year projection periods.

 

The program then proceeds to print out all the requested crosstabulations for the specified years.  After completion of this printout, the program goes on to the next five-year period (if any), repeating the requests for the user input described above for each five-year period.

 

The user may direct the output to the video terminal, a printer, or a file named PROJOUT.FIL .

 


V.  How to Use the CHECK Program to Adjust Service-System Parameters

 

The service, resource, and cost models which are incorporated into the PROJ program are very simple in concept -- they are linear models involving small numbers of parameters.  Although these models are particularly well-suited to investigation of the impact of making marginal changes in a service system, it is unlikely that they will produce exactly the same estimates of service levels, resource levels, and cost levels, that are observed in real life -- the actual system will be far more complicated.

 

After the user has specified the target population, service population, service, resource, and cost models in terms of the parameters available in the PARAM program, the PROJ program should be run for the base year to see how closely the target population levels, service population levels, service levels, resource levels, and cost levels are to known, observable, base-year amounts.  They will likely differ somewhat.  If the differences are small, the user may proceed to make projections with PROJ.  If some of the difference are substantial, however, the user should reexamine the parameter values to make certain that they are correct.  Once any major discrepancies are resolved, and the user is satisfied that the parameter values are correct, there will still probably remain some minor discrepancies between the actual base-year amounts and the PROJ base-year amounts.

 

At this point, the user has a choice to make.  If the differences are not significant from a substantive point of view, he may proceed directly to making PROJ runs.  Alternatively, he may choose to adjust the parameter values so that the PROJ base-year levels of the target populations, service populations, services, resources, and costs match the actual base-year levels exactly.  If the analyst is interested in estimating the cost or service changes that will occur if some change is made in the service system, then minor discrepancies (between PROJ base-year levels and actual base- year levels) in the absolute level are not important.  In other situations, however, the user may be interested in estimating the actual level of some quantity (rather than a relative change).  In such cases, it is best if the base-year levels computed by the PROJ program are exactly matched to the actual base-year values.  This matching procedure is called model calibration.  It is similar to the Deming-Stefan statistical adjustment procedure ("raking"), or the "ratio estimation" procedure of sample survey analysis.  The user can accomplish this match by adjusting the various system parameters (target population incidences, service population, service ratios, service parameters, resource parameters, and cost parameters), and updating the parameter file with a PARAM run.  Using PARAM solely to adjust service-system parameters is somewhat cumbersome, however, since the program first cycles through all of the demographic parameters and data, none of which changes.  The CHECK program, on the other hand, can be used to quickly incorporate adjustments into the service-system model parameters, without having to run through all of the PARAM demographic parameter and data cycles.

 

The CHECK program allows the user to specify an adjustment factor, or adjustment ratio, for each target population, service population, service, resource, and cost total that the PROJ program computes and prints out.  These adjustment factors are the ratio of the actual (observed) base-year level of each quantity to the base-year level estimated by PROJ.  The CHECK program uses these adjustment factors to create a new parameter file containing all of the same demographic information as the original file, but corrected service-system parameters in place of the old service-system parameters.

 

Suppose, for example, that there is a single target population, service population, service, resource, and cost, and that the following actual-base-year and PROJ-base-year estimates are observed.

 

                            Actual      PROJ

                          Base-Year   Base-Year       Ratio

                            Value       Value     = Actual/PROJ

 

   Target Population No. 1   5,362       4,897        1.095

   Service Population No. 1  2,148       2,099        1.023

   Service No. 1               317         246        1.289

   Resource No. 1              117         122         .959

   Cost No. 1               33,976      38,943         .872

 

The last column of the table contains the adjustment factor, which is the ratio of the actual base-year values to the values computed by PROJ for the base year.  The CHECK program requests the user to enter these adjustment factors.  These factors are used to modify the service-system parameters of the parameter file, such that when the next PROJ run is made, it will match the base-year values exactly.  This parameter adjustment procedure is much faster than the procedure of adjusting the service-system parameters through another run of the PARAM program, which allows the user to modify all parameters, both demographic and service-system-related.

 

In order to use the CHECK program to adjust the service system parameters, the user proceeds as follows.  As usual, the program is begun by typing CHECK at the MS-DOS prompt.  In response to the first request made by CHECK,

 

     ENTER 0 TO PRINT EXISTING PARAMETER FILE, 1 TO IMPUTE NEW         SERVICE-SYSTEM PARAMETERS FROM SERVICE-SYSTEM ADJUSTMENT         FACTORS: ,

 

the user responds with the entry:

 

     1 (ENTER) .

 

The program then responds with:

 

     ENTER NAME OF OLD PARAMETER FILE (12X): ,

 

to which prompt the user responds with the name of the existing parameter file, which contains the parameters to be adjusted, e.g.,

 

     AZ803CS.DAT (ENTER) .

 

The program then request:

 

     ENTER NAME OF NEW PARAMETER FILE (12X): ,

 

to which the user responds with the entry of a different (unused) file name, e.g.,

 

     AZ03CTS2.DAT (ENTER) .

 

The program then instructs the user to enter one adjustment factor for each target population, service population, service, resource, and cost total.  For example, for the target population totals, the program requests:

 

     ADJUSTMENT FACTORS FOR TARG POP...

     ENTER ADJUSTMENT FACTOR (X.XXX) FOR nnnnnnnn: ,

 

where nnnnnnnn denotes the name of the first target population (e.g., ELDERLY, or DISABLED).  The user would respond with entry of the appropriate data.  In the example presented in the above table, this would be:

 

     1.095 (ENTER) .

 

In similar fashion ratios are entered for all of the target populations, service populations, services, resources, and costs included in the model.  When used to adjust service-system parameters, the CHECK produces all of the same printout as when it is used simply to print out a parameter file.  In addition, however, it also prints out the adjustment factors, and both the old and new values of the service-system parameters.

 


VI.  Example 1: National Population Projection, Single-Race Model

 

A.  Projection Objectives; Data Sources

 

Projection Objectives  This and the next several chapters of this manual present a number of examples of applications of the DESTINY program package.  The purpose of the examples are several -- to show in detail how to obtain the data required by the model, to illustrate how to use the model, and to provide an indication of the accuracy of the model projections.  For the examples, the model will be set up with data from 1980 and before, and used to project up to 1990.

 

This chapter and the following one present examples which illustrate in detail the use of the DESTINY package to make projections of the US resident population from the base year of 1980.  The examples identify the data sources that were used to construct the parameter (using the PARAM program), and describe the contents of the parameter file by means of a CHECK printout.  The PROJ program is then run to produce a ten-year-out projection of the population.

 

This chapter addresses a "single-race" model, in which all races are combined.  The following chapter addresses a three-race model.

 

DESTINY projections may be disaggregated to the same level of disaggregation as is represented in the population input data.  In the present chapter, the population input data are disaggregated by age and sex, and the projections may be disaggregated by age and sex.  In the following chapter, the population input data are disaggregated by age, sex, and race, and the projections may be disaggregated by any combination of those three variables.  In addition to disaggregation by age, sex, and race, later chapters will illustrate disaggregation by region and by region and race.

 

In order to permit an assessment of the reliability of the DESTINY projections, the projections in this example will be based on demographic data for the base-year of 1980 that were available in 1982.  The DESTINY projections for the year 1990 will be compared to US Census data for 1990.

 

Data Sources  A primary objective of the DESTINY package is to enable projections to be made using readily accessible demographic data, available in many libraries.  Examples of such sources are US Census publications (available decennially), the Statistical Abstract of the United States (available every year), the Vital Statistics of the United States (natality and mortality volumes available each year), and the County and City Data Book (supplement to the Statistical Abstract, various years).  A major advantage of the Statistical Abstract is that it is published regularly and contains quite recent data.  Similar publications are available for each state.  All of the demographic data used in the examples presented in this document is available from such sources.

 

The demographic data required for the present example are available from the following three publications:

 

o    CP80 Census of Population, Supplementary Report PC80-S1-1, Age, Sex, Race, and Spanish Origin of the Population by Regions, Divisions, and States: 1980. Bureau of the Census, US Department of Commerce (for sale by the Superintendent of Documents, Washington, DC 20402), issued May, 1981.  (Data for other years are published in Current Population Reports, Series P-25.)  This report presents resident population, i.e., excluding Armed Forces overseas.

 

o    VS78: Vital Statistics of the United States, 1978.  Volume I -- Natality, and Volume II -- Mortality, Part A.  National Center for Health Statistics, US Department of Health and Human Services, Hyattsville, MD, 1982.

 

o    SA81: Statistical Abstract of the United States, 1981.  Bureau of the Census, for sale by the Superintendent  of Documents, Washington, DC 20402, 1981.

 

These three publications will be referred to in the remainder of this chapter as CP80, VS78, and SA81, respectively.  CP80 provides a crosstabulation of the population by age, sex, and race, where the age categories are in five-year intervals up to age 85, and 85+.  VS78 provides vital statistics data (birth rates, death rates, infant mortality rates, total fertility rates, fertility age distributions, and life expectancy at birth), also by age, sex, and race.  SA81 population data are not sufficiently detailed for use as DESTINY input, since the five-year categories go only to age 65, and 65+.  (DESTINY requires population by five-year age intervals up to age 75, and 75+.)

 

All three publications present data not only for the United States as a whole (for use with the national-level model in the present chapter), but for regions of the US and for individual states (for use with the state-level models in later chapters).  A problem with VS data is that, although the data are detailed, there is a four-year lag between the latest year documented and the year of publication (e.g., the data published in 1982 comprise the "1978" edition).  SA81 provides selected vital statistics data on a more timely basis (e.g., a one- or two-year lag), but the data are generally not as disaggregated.  For example, the fertility age distribution presented in SA81 is for the US as a whole; VS78 must be consulted to obtain the fertility age distribution by race.  The SA81 does provide, however, total fertility rates and infant mortality rates by race.

 

Since the DESTINY package is concerned with population projections, the user should enter parameter values corresponding to his beliefs about the demographic situation in the future.  It is not necessary that the demographic parameter values mirror the values experienced in recent history.  Unless the user is performing a "what-if" exploratory analysis or sensitivity analysis, however, the input values would normally correspond to recent history.  For this reason, much of the discussion of this chapter is concerned with the identification of estimates derived from historical data.  If the user believes that the future demographic situation will depart in some fashion from recent history, however, the input values will differ from the historical values.

 

When using historical values of parameters, the user should normally use parameter values corresponding to the base year, unless there is substantial year-to-year variability in the parameter values.  In this case, the user should use an average, such as a five-year average value, as the specified value.  If state or local-area data are suspect because of small sample sizes or rapidly changing demographic trends, it would probably be preferable to use more stable regional or national parameter values, rather than the state or local-area values.

 

The example presented here does not describe every line of input data entered into the PARAM, CHECK, and PROJ programs.  Instead, the required data are described.  The user can readily see the order of input of the parameters from the CHECK printout, which closely follows the data entry order of the PARAM program.

 

Note on Migration Data  Prior to specifying the data for the desired run, it is necessary to make a few remarks about migration data.  Published migration data refer to legal migration, and the actual migration in recent years in the US has been more than double the legal amounts.  For this reason, SA81 is of little help in providing data for the DESTINY runs.  The approach for obtaining reasonable migration data is to make a single-race projection (as in the present chapter), and use migration estimates produced by the CHECK program for input to the two-race projection (as in the following chapter).

 

It may be asked why the CHECK program cannot be used to provide migration estimates from the two-race data.  The CHECK program estimates the difference after ten years between the total population and the population level associated with natural increase (population growth due to births and deaths, excluding migration).  In a single-race model, this difference is a reasonable estimate of the amount of migration over the ten-year period.  In a multi-race model, however, this difference is a poor estimate of migration (by race).  There are two main reasons for this.  First, race data are very subjective: they are based on the respondent's declaration of race.  Ambiguous responses may be provided to race questions, or a respondent's race declaration may differ in time.  In addition, the criteria and procedures for making race classifications have changed over the years.  Second, over a period of years the racial composition of a multi-race population becomes intermixed, because of cross-breeding.  A third source of error is associated with the fact that the DESTINY program estimates net migration.  If the racial composition of emigrants and immigrants is different, the racial composition of the resident population will change over time even if there is no net migration.

 

 

B. PARAM Run Parameters

 

Input Option Parameters

 

In running the PARAM program, the name US801.DAT was given to the parameter file, and the base year was identified as 1980.  The file header, "US Resident Population," was used.  The seven Input Option Parameters were as follows:

 

P1: Number of races = 1

P2: Number of regions = 1

P3: Demographic Parameter Option = 1 (i.e., the demographic parameters are to be the same for all ten five-year projection periods)

P4: Life Table Option = 1 (i.e., the survival probabilities for the population will be determined by the Infant Mortality Rate, rather than by the Expectation of Life at Birth)

P5: External Migration Option = 1 (i.e., a single migration rate and/or migration number will be specified, to be used for all projection periods)

P6: Internal Migration Option = 0 (no regions are specified, so there is no internal migration)

P7: Service System Option = 0 (i.e., no service system parameters are included in the model).

 

The program next requests the names of the races.  The name "All" was entered.

 

Since the present model includes but a single race, just one complete set of demographic data is required.  These data are given in the paragraphs that follow.

 

An issue that arises immediately is how the values for the model parameters shall be determined.  In some instances (e.g., base-year population), a base-year value is requested by the model.  In other cases (e.g., infant mortality rate for the first projection period), it is not obvious what value should be used -- the base year value, the average value for the preceding five years, the average value for the preceding ten years, or the extrapolation of a trend of five-year averages.  In general, the values specified for the first (or later) projection periods should be the values the user considers most likely for those periods, whether these are continuations of current values or the results of extrapolations.  In general, it is better to use multi-year averages for estimates of the future values of parameters rather than the base-year value, because of the significant amount of variability in single-year values for many demographic parameters.

 

For the present example, we shall generally use the average value of a parameter for the five years preceding the base year, as the value for the first and later projection periods.

 

Total Fertility Rate

 

Total Fertility Rates for the US population are given on page 58 of SA81, in Table 84, entitled, "Total Fertility Rate and Intrinsic Rate of Natural Increase: 1940 to 1979."  The average value for the years 1975-79 is 1.81.  (Note that the table values are per 1000 women, and must be divided by 1000 to obtain the per-woman values required by PARAM.)

 

Total Fertility Rates (TFRs) are also presented on page I-9 of VS78, in Table I-6, entitled, "Total Fertility Rates and Birth Rates by Age of Mother and Race: United States, Specified Years 1940-55, and Each Year 1960-1978."  The SA81 data are more recent than the VS78 data (i.e., for year 1979 vs. 1978).

 

Fertility Age Distribution

 

The Fertility Age Distribution for the total US population is found on page 59 of SA, in Table 85, entitled, "Births and Birth Rates: 1950 to 1979."  The last part of the table provides the following data for the year 1979:

 

                                     Birth Rate

                Age of Mother      per 1000 Women

 

                 10-14 years             1.2

                 15-19                  53.4

                 20-24                 115.7

                 25-29                 115.6

                 30-34                  61.8

                 35-39                  19.4

                 40-44                   3.9

                 45-49                    .2

                 Total                 371.2

                 TFR x 1000 (Tot x 5) 1856.

 

The Fertility Age Distribution data do not vary much from year to year, and so the single-year (1979) data were used rather than multi-year averages.

 

The PARAM program accepts a Fertility Age Distribution (FAD) for only six age categories, i.e., for ages 15-44, rather than for the eight categories presented above.  Combining the two end age categories of the above table with the adjacent age group makes a very small difference in the FAD, and yields the following table:

 

                            Birth Rate

     Age of Mother        per 1000 Women     Percentage

 

         15-19                  54.6            .147

         20-24                 115.7            .312

         25-29                 115.6            .312

         30-34                  61.8            .166

         35-39                  19.4            .052

         40-44                   4.1            .011

         Total                 371.2           1.000

         TFR x 1000           1856.

           (Total x 5)

 

Note that the value 371.2 (the sum of the birth rates) is equal to the Total Fertility Rate of all US persons for 1979 (1.856) multiplied by 1000 and divided by 5.  The "percentage" is the percentage of total lifetime births occurring to females in each of the five-year age cohorts.  The set of percentages comprise what will be referred to henceforth as the Fertility Age Distribution, or FAD.

 

The VS78 source (the same table in which the TFR is presented) provides the FAD for 1978 (a year older than the SA81 source).

 

Infant Mortality Rate

 

Infant Mortality Rates are found on page 73 of SA81, in Table 111, entitled, "Infant, Maternal, and Neonatal Mortality Rates, and Fetal Mortality Ratios, by Race: 1940 to 1978."  The average of the values for years 1975-78 is 14.80.  (Mortality data are also available from VS78 (Volume II, Part A), but the SA81 data are more recent.)

(Had a "2" been specified for the Life Table Option parameter (Input Option Parameter P4), it would be necessary to enter the Expectation of Life at Birth instead of the Infant Mortality Rate to the PARAM program.  These values are found on page 69 of SA81, in Table 105, entitled, "Expectation of Life at Birth: 1920 to 1979."  The average of the values for years 1975-79 is 73.12.  Life expectancy data are also available in VS (Volume II, Part A), in Table 5-1, entitled, "Abridged Life Tables by Color and Sex: United States, 1978.")

 

Base-Year Population by Age and Sex

 

Base-year population data by age and sex are published in CP80.  SA81 also contains population data, but these data are not usable as DESTINY input since the age categories above age 65 are combined.

 

The 1980 resident population data published in CP80 are presented in the table which follows.

 

                  Age        Male          Female

 

                  0-4     8,360,135   7,984,272

                  5-9     8,537,903   8,159,231

                 10-14    9,315,055   8,925,864

                 15-19  10,751,544 10,410,123

                 20-24  10,660,063 10,652,494

                 25-29    9,703,259   9,814,413

                 30-34    8,675,505   8,882,452

                 35-39    6,860,236   7,102,772

                 40-44    5,707,550   5,960,689

                 45-49    5,387,511   5,700,872

                 50-54    5,620,474   6,088,510

                 55-59    5,481,152   6,132,902

                 60-64    4,669,307   5,416,404

                 65-69    3,902,083   4,878,761

                 70-74    2,853,116   3,943,626

                 75+      3,547,402   6,419,145

                 Total  110,032,295 116,472,530

                 Grand Total   226,504,825

 

Crude Birth Rate for Base Year

 

From SA81, Table 85, the value for 1979 is seen to be 15.9.  (Although 1979 is not the base year (1980), it is the latest year available, and is a suitable proxy for the 1980 value.)

 

Crude Death Rate for Base Year

 

From SA81, Table 108, the value for 1979 is seen to be 8.7.

 

 

Infant Mortality Rate for the Base Year

 

Table 111 of SA81 provides the value of 13.8 for 1978.

 

Population Ten Years Prior to Base Year

 

The next data element required is the population ten years prior to the base year.  This data item is available from numerous tables of SA81, such as Table No. 29, page 26: "Resident Population, by Age, Sex, and Race: 1960 to 1980."  The 1970 population is 203,302,031.  (Note: The figure 203,302,031 is a revised figure, due to corrections for errors found after the tabulations of SA81 were done.  The figure 203,235,000 appears in many of the tables of SA81.)

 

 

 

 

Average Crude Birth Rate for the Ten-Year Period Prior to Base Year

 

From SA81, Table 85, the average for years 1973-79 is seen to be 15.14.

 

Average Crude Death Rate for the Ten-Year Period Prior to Base Year

 

From SA81, Table 108, the average for years 1973-79 is seen to be 8.96.

 

Average Infant Mortality Rate for the Ten-Year Period Prior to Base Year

 

From SA81, Table 111, the average for years 1972-78 is seen to be 16.08.

 

External Migration

 

The final demographic data required by the program are migration parameters.  Migration data for the US as a whole are found in SA81 Table 628, "Immigration, 1820 - 1979."  The table shows an annual net migration of 2.0 per 1,000 for the period 1960 - 1979, and 1.7 per 1,000 for 1970 - 1979.  These data are not satisfactory for use by the DESTINY program.  The problem is that they reflect legal immigration, and illegal immigration, which is not reflected in these figures, may be substantial and even exceed legal immigration in magnitude.

 

Because of the problems inherent in published immigration figures, it is better to estimate net migration directly from available data on crude birth rates, crude death rates, and the population ten-year growth rate.  The procedure is illustrated below.

 

First, we shall derive an estimate of the annual population change net of births and deaths.  For a single-race model, the population change net of births and deaths is due to migration.  There are two ways to proceed, depending on whether it is desired to represent migration as a rate or a number.  As discussed earlier, if the net migration is positive (i.e., the number of immigrants into the country exceeds the number of emigrants out of the country), it is represented as a migration number, and if the net migration is negative, it is represented as a migration rate.  The following will show the procedures for estimating migration both ways (as a rate and as a number), but the migration number will be used in the model specification, since the net migration is positive.

 

In terms of the annual birth rate, death rate, and migration number, an approximate expression for the population in year t+1 as a function of the population in year t is:

 

pt+1 = (1+b-d)pt + M

 

where

 

pt = population in year t

 

b = crude birth rate

 

d = crude death rate

 

M = annual (net) migration number,

 

and all of the parameter values represent average values over the ten-year period prior to the base year.

 

Solving this equation for M in terms of p10 and p0 yields the following:

 

M = (p10 - p0(1+b-d)10)(b-d)/((1+b-d)10-1) .

 

Substituting b=.01514, d=.00896, p0=203,302,031, and p10=226,504,825 yields the estimate:

 

M = 1,000,075.

 

That is, the average net annual number of immigrants per year is estimated to be M = 1,000,075, which is about double the legal immigration published in SA81, Table 128.

 

This is about 5 per thousand population per year.  This level is more than double the legal migration rate of 2 per thousand population per year.  (The legal net migration rate would be even less.)  (A certain amount of the net migration amount estimated above corresponds to a decrease in the Census undercount from 1970 to 1980, and changes in racial classification procedures between 1970 and 1980.)

 

The estimated 1,000,075 is an estimate of migration (including race transition) under the assumption that the birth and death rates of the population are as specified.

 

The figure 1,000,075 may be entered to the PARAM program as the estimate of the annual migration number.  The annual migration rate is entered as zero (since migration is specified either by the migration number or the migration rate, but not both).

 

As was mentioned, migration may be represented either as a number (as above) or as a rate.  If migration is represented as a rate, the formula for the population at time t is:

 

pt+1 = (1+b-d+m)pt ,

 

where all of the symbols introduced earlier are defined exactly as before, and

 

m = annual net migration rate.

 

Solving this equation for m in terms of p10 and p0 yields:

 

m = (p10/p0).1 -1 - b + d.

 

Substituting b=.01514, d=.00896, p0=203,302,031, and p10=226,504,825 in this formula yields the estimate:

 

m = .004769,

 

or 4.686 per 1,000.  (Note that this is just slightly different from the approximate value M/(average of populations for base year and ten years previous) = 1,000,075 /(.5(203,302,031+226,504,825) = 4.654 per 1,000.)

 

As discussed, since the net migration into the country is positive, the migration number, M = 1,000,075, will be entered into the PARAM program, and the migration rate will be specified as zero (not as 4.654).

 

The CHECK program performs the computations required to determine both M and m.  As an alternative to performing the computations by hand, zeros may be specified initially as the values for the migration number and rate (in the PARAM input), and the CHECK program may be run to obtain the preceding estimates.  The PARAM program may then be rerun to change the initial value of zero to the estimated value (the migration number, M, if the net migration is positive, or the migration rate, m, if the net migration is negative).

 

Note that the net migration estimate derived for use in the single-race model of this chapter will be used to derive net migration estimates for use in the multi-race model of the next chapter.

 

This completes the data specification for the construction of the file US801.DAT.

 

 

C.  Results of CHECK Run

 

The output of a CHECK run of the file US801.DAT is shown in Listing 1 (in Appendix D).  The program first prints out all of the input data.  A review of Listing 1 reveals that all of these input data are as described above, with the exception of the population figures, which do not agree past the seventh digit.  This minor discrepancy results from the fact that the computer on which the CHECK run was made is precise only to seven digits.  After printing out the input data, the program then proceeds to print out additional information, which can help the user assess the validity of the input data.

 

The program prints out the expectation of life at birth (73.96 years) corresponding to the infant mortality rate specified for the first projection period (14.80 deaths per 1,000 live births).  (Had the user specified a life expectancy at birth as the parameter for selecting the life table used by the model, the program would have printed out the corresponding infant mortality rate.)

 

In general, if the user enters the infant mortality rate to specify the life table (i.e., Life Table Option 1), he should examine the expectation of life at birth for reasonableness.  Alternatively, if the expectation of life at birth is specified, (i.e., Life Table Option 2), he should examine the infant mortality rate for reasonableness. 

 

If requested by the user (at the beginning of the CHECK run), the CHECK program prints out a table of survival probabilities by age and sex.

 

After printing out the input data, the program provides a number of additional estimates.  The first is an estimate of the Total Fertility Rate estimated from the base-year birth rate and the base-year population distribution.  This estimate, 1.833, is seen to be quite close to the value specified for the first projection period, 1.810.

 

The program estimates the general fertility rate (birth rate per 1,000 females of ages 15-44) as 68.18.  This compares with the value of 68.5 found in Table 85 of SA81.

 

Next, the program estimates the net migration.  As discussed above, the estimated annual net migration number is 1,000,075, and the corresponding annual net migration rate is 4.686 per 1,000.

 

The approximate projected population growth rate corresponding to the model parameters specified for the first projection period is 9.62 per 1,000.  For the previous ten years, the population growth rate per 1,000 was 10.87.

 

The CHECK run reveals no unusual features in the data.  The estimated base-year and projected total fertility rates are similar, and the projected annual growth rate is close to the historical growth rate.

 

A major purpose of the CHECK run is to enable the user to carefully examine the model input data, to make sure that no input errors have occurred.

 

 

D.  Results of PROJ Run

 

Listing 2 illustrates a run of the PROJ program, which projects the population two five-year periods out, from the base year of 1980 to the year of 1990.  From the base year of 1980, this run projects a resident US 1990 population of 250,026,462.  The actual resident population in 1990 turned out to be 248,710,000 (Statistical Abstract of the United States 1992 (referred to henceforth as SA92), Table No. 16, "Resident Population, by Race and Hispanic Origin, 1980 and 1990," page 17.  The projection for the total population is hence seen to be in error by only one-half of one percent.

 

Since the population data in the present model are disaggregated by age and sex, the projections may be disaggregated by these variables.  Listing 2 includes projections for all possible disaggregations.  (To conserve space, later projections will often project just a few of the possible tables and crosstabulations.)  These projections may be compared in detail to data presented in the 1990 Census of Population, General Population Characteristics, United States (referred to henceforth as CP90), 1990 CP-1-1, US Department of Commerce, Bureau of the Census, issued November 1992 (available in most public libraries).  For example, the number of male persons aged under five years in 1990 is 9,392,409, and the number projected by DESTINY is 9,229,281 (error of less than two percent).

 

In general, the relative (percentage) magnitude of the projections increases as the level of disaggregation increases.  That is, projections for a particular category (e.g., males aged 0-5) are not as accurate in relative terms as more-highly-aggregated projections.  Also, the magnitude of the errors increases with the distance (number of years out) of the projection.

 

The principal conclusions from the present example is that the data required for the US-population combined-race model are readily available, and that the DESTINY projections are of a high level of accuracy in this application.

 

The projection shown in Listing 2 prints the projection only for the tenth year out.  The user may specify that the projection be printed in any future year, and a different selection of tables and crosstabulations may be selected for each year.  For example, the user may request that the grand total be printed for every year, and detailed crosstabulations printed in the final projection year.

 


VII.  Example 2: National Population Projection, Two-Race Model

 

A.  Projection Objectives; Data Sources

 

Projection Objectives  This chapter presents an example in which the DESTINY program package is used to make projections of the US resident population by race.  The race categories used in this example are "white" and "other than white."  As in the preceding chapter, the model will be constructed using data available prior to 1980, and used to make projections to the year 1990.  Since the model input data are disaggregated by age, sex, and race, the projections may also be disaggregated by any combinations of those variables.

 

Data Sources  The present example will use the same data sources as the preceding chapter, i.e., CP80, SA81, and VS78.  The 1990 comparison data (for the projected populations) are found in CP90 and SA92.

 

Migration Data  As discussed in the preceding chapter, one of the motivations for making the single-race projection of that chapter was to obtain an estimate of the total net migration.  From the CHECK run of the preceding chapter, the value of 5,000,376 was obtained as an estimate of the five-year net migration for the US.  This number will be used in determining the migration parameter values for the two-race model.

 

 

B. PARAM Run Parameters

 

Input Option Parameters

 

In running the PARAM program, the name US802.DAT was given to the parameter file, and the base year was identified as 1980.  The file header, "US Resident Population by Race (W/O)," was used.  The seven Input Option Parameters were as follows:

 

P1: Number of races = 2

P2: Number of regions = 1

P3: Demographic Parameter Option = 1 (i.e., the demographic parameters are to be the same for all ten five-year projection periods)

P4: Life Table Option = 1 (i.e., the survival probabilities for the population will be determined by the Infant Mortality Rate, rather than by the Expectation of Life at Birth)

P5: External Migration Option = 1 (i.e., a single emigration rate and/or migration number will be specified, to be used for all projection periods)

P6: Internal Migration Option = 0 (no regions are specified, so there is no internal migration)

P7: Service System Option = 0 (i.e., no service system parameters are included in the model).

 

The program next requests the names of the races.  The names "White" and "Other" were entered.

 

The PARAM program requests entry of the demographic data race by race.  In the present example, all of the required data are to be entered for the "white" race, followed by all of the required data for the "other" race.  To facilitate the discussion in this chapter, however, the data shall be presented by demographic category.  For example, the total fertility rate will be presented for both races, followed by the fertility age distribution for both races, and so on.

 

As in the preceding example, we shall generally use the average value of the parameter for the five years preceding the base year, as the value of parameters in the projection period.

 

Total Fertility Rates

 

The Total Fertility Rates for the two races included in this example (i.e., "white" and "other than white") are given on page 58 of SA81, in Table 84, entitled, "Total Fertility Rate and Intrinsic Rate of Natural Increase: 1940 to 1979."  For whites, the value (average of data for 1975-79) is 1.717, and for black and other races, the value is 2.334.

 

Fertility Age Distribution

 

For the preceding example, the Fertility Age Distribution for the total US population were found on page 59 of SA81, in Table 85, entitled, "Births and Birth Rates: 1950 to 1979."  While these data were appropriate for the combined-race model, they are not very suitable for a multi-race model, since fertility varies significantly from race to race.

 

Since the DESTINY package is to be used in the present example to make projections by race (white and other), it is desirable to specify FAD data for the two separate races.  Better results are obtained by specifying race-specific data for the Fertility Age Distribution.  Such a distribution is found in Table I-6 of VS78.

 

The following table is derived from Table I-6 of VS78:

 

                             White                Other

                           Birth Rate          Birth Rate

     Age of Mother       per 1000 Women      per 1000 Women

 

        10-14                    .6                 4.1

        15-19                  43.6                99.1

        20-24                 106.3               145.7

        25-29                 111.1               117.3

        30-34                  57.9                66.7

        35-39                  17.6                27.0

        40-44                   3.5                 6.5

        45-49                    .2                  .4

 

Combining the extreme age categories (to accommodate the DESTINY input categories), we obtain:

 

                       White                  Other

                    Birth Rate             Birth Rate

Age of Mother /1000 Women Proportion /1000 Women Proportion

 

    15-19        44.2       .130        103.2      .221

    20-24       106.3       .312        145.7      .312

    25-29       111.1       .326        117.3      .251

    30-34        57.9       .170         66.7      .143

    35-39        17.6       .051         27.0      .058

    40-44         3.7       .011          6.9      .015

    Total       340.8      1.000        466.8     1.000

    TFR x 1000 1704.                   2334.

 

Note that the Total Fertility Rates (1.704 and 2.334) for 1978 are the sums of the birth rates by age of mother, multiplied by 5 and divided by 1,000.

 

It is seen from the preceding display that there is somewhat of a difference in the Fertility Age Distribution between the races, and it is hence preferable to use the race-specific data.  (It is noted, however, that the value of the Total Fertility Rate has a much more pronounced effect on the birth rate than does the Fertility Age Distribution, and the difference in results introduced by using the combined Fertility Age Distribution in place of the separate ones would not have been very large.)

 

Infant Mortality Rate

 

Infant Mortality Rates for whites and black and other races are found on page 73 of SA81, in Table 111, entitled, "Infant, Material, and Neonatal Mortality Rates, and Fetal Mortality Ratios, by Race: 1940 to 1978."  The rates (averages for 1975-78) are 12.95 for whites and 22.62 for black and other races.

 

Base-Year Population by Age, Sex, and Race

 

Base-year population data by age, sex, and race are published in CP80.  The 1980 population data published in CP80 are presented in the table which follows.  The data for the white race are presented explicitly in CP80.  The data for the other race are obtained by subtracting the white amounts from the total amounts for all races.

 

                       White                    Other

  Age Category     Male       Female       Male        Female

 

    0-4         6,482,766   6,148,431    1,877,369    1,835,841

    5-9         6,684,406   6,346,611    1,853,497    1,812,620

   10-14        7,407,610   7,052,673    1,907,445    1,873,191

   15-19        8,631.389   8,326,152    2,120,155    2,083,971

   20-24        8,680,290   8,603,095    1,979,773    2,049,399

   25-29        8,004,161   7,978,484    1,699,098    1,835,929

   30-34        7,298,603   7,344,080    1,376,902    1,538,372

   35-39        5,830,238   5,928,994    1,029,998    1,173,778

   40-44        4,849,123   4,976,012      858,427      984,677

   45-49        4,638,090   4,817,869      749,421      883,003

   50-54        4,918,050   5,238,845      702,424      849,665

   55-59        4,852,081   5,384,727      629,071      748,175

   60-64        4,172,521   4,801,456      496,786      614,948

   65-69        3,841,097   4,329,974      420,986      548,787

   70-74        2,551,944   3,542,234      301,172      401,392

   75+          3,187,257   5,851,527      360,145      567,618

   Sex Totals  91,669,626  96,671,164   18,362,669   19,801,366

   Race Totals       188,340,790               38,164,035

   Grand Total                     226,504,825

 

Crude Birth Rate for Base Year

 

From SA81, Table 85, the value for 1979 is seen to be 14.8 for whites and 22.8 for others 1979.

 

Crude Death Rate for Base Year

 

From SA81, Table 108, the value for 1979 is seen to be 8.8 for whites and 7.8 for others.

 

Infant Mortality Rate for the Base Year

 

Table 111 of SA81 provides the value of 12.0 for whites and 21.1 for others for 1978.

 

Population Ten Years Prior to Base Year

 

From SA81 Table No. 29, page 26: "Resident Population, by Age, Sex, and Race: 1960 to 1980,"  the 1970 population is seen to be 178,098,000 for whites and (by subtraction from the total 203,235,000) 25,137,000 for others.

 

 

 

 

Average Crude Birth Rate for the Ten-Year Period Prior to Base Year

 

From SA81, Table 85, the average for years 1973-79 is seen to be 14.13 for whites and 21.77 for others.

 

Average Crude Death Rate for the Ten-Year Period Prior to Base Year

 

From SA81, Table 108, the average for years 1973-79 is seen to be 9.04 for whites and 8.33 for others.

 

Average Infant Mortality Rate for the Ten-Year Period Prior to Base Year

 

From SA81, Table 111, the average for years 1972-78 is seen to be 14.11 for whites and 24.19 for others.

 

External Migration

 

As discussed earlier, published data on immigration refers to legal immigration, and is not suitable for use in the DESTINY model.  From the discussion of the single-race data in the preceding chapter, an estimate of 1,000,075 was obtained for the annual total net migration number.  The problem remains as to how to apportion this total net migration number among the two races of the present model.

 

Migration numbers and rates vary considerably by race, and so it is not satisfactory simply to allocate the total in proportion to the US population race totals.  One indication of the relative racial composition of immigrants is provided in SA81 Table 131, entitled, "Immigrants, by Country of Birth: 1951 to 1979."  The data of this table may be used to determine an approximation of the number of white and other immigrants.

 

The following data are extracted from SA81 Table 131:

 

Region       Immigrants, 1975-79

 

Europe             350.4

Asia                     879.2

North America      854.7

South America      155.8

Africa             48.8

Australia                  6.9

New Zealand          2.6

Other                    10.5

Total                 2,308.8

 

This table shows that the legal immigration from Europe, America, Australia, and New Zealand for the years 1975-79 was 1,368,400.  To estimate immigration by race, the legal immigrants from these countries will be classified as white, and all other immigrants (legal or otherwise) will be classified as other.  The five-year figure of 1,368,400 corresponds to an annual number of 273,680.  Subtracting this figure from the DESTINY estimate of 1,000075 total immigrants (legal or otherwise) per five years, this yields 726,395 as the estimate of immigrants for the other race category.

 

These two immigration estimates are very approximate, since some legal immigrants from Europe, America, Australia, and New Zealand are surely nonwhite, some legal immigrants from other countries are surely white, and some illegal immigrants (from any countries) are surely white.  Also, emigration from the US has been ignored.  From readily available published sources, however, little information is available on total immigration (legal and illegal) by race.  The estimate for whites is an approximate lower limit and the estimate for others is an approximate upper limit (since all illegal immigrants are classified as other).  What this means with respect to population projections is that the projections for whites are likely to be low, and the projections for others are likely to be high.

 

Another limitation of the preceding estimates is that they do not account for population changes associated with race transitioning (which is included in the external migration parameters of the DESTINY model).

 

In summary, published data on migration are of limited value for use in the DESTINY system.  Because of the unavailability of satisfactory published data on migration by race, migration parameters will be estimated as the population change (rate per 1,000 or amount) net of births and deaths, as was done in the case of the all-races-combined model.  As has been discussed earlier, this estimate includes population changes associated with race transitioning (changes in race declarations, changes in race classification procedures, intermarriages) as well as with migration.  Since the two-race model is a different parametric specification of the population, the sum of the external migration estimates for the two races may differ a little from the external migration estimate calculated for the two races combined.

 

The formulas for estimating net external migration, either as a rate or an amount, were given earlier.  The formula for the amount is as follows:

 

M = (p10 - p0(1+b-d)10)(b-d)/((1+b-d)10-1) ,

 

where the symbols are defined as before.

 

Substituting b=.01413, d=.00904, p0=178,098,000, and p10=188,340,790 for the white race yields the estimate:

 

M = 94,517.

 

Substituting b=.02177, d=.00833, p0=25,137,000, and p10=38,164,035 for the other race yields the estimate:

 

M = 888,003.

 

The sum of these two estimates is 982,520, which differs somewhat from the estimate of 1,000,075 for both races combined.  These estimates are somewhat different from the rough migration estimates presented above of 273,680 for whites and 726,395 for others (exclusive of race transitioning).  At this point, a decision must be made concerning whether to use these estimates, derived from the data for the ten-year-period preceding the base year, as the parameter values for the projection period, or whether some other values, considered more likely to apply in the projection period, should be used.  The primary factor is whether it is expected that the migration rates during the projection period will be similar to those for the preceding ten-year period.  Another factor to consider is whether the amount of race transitioning for the projection period is expected to be similar to that in the past.  Since the figure of 273,680 was considered to be an approximate lower bound for white migration (exclusive of race transitioning), the estimate of 94,517 net external white migration may be somewhat low for the projection period.  If changes in race classification procedures caused relatively fewer people to be classified as white in 1970 than in 1980, and if this trend was not expected to continue, a higher figure should be used for the projection period.

 

The goal of the present example is to project the population from the base year of 1980, using data that were readily available in 1980.  To keep the example as simple as possible, the estimated population change net of births and deaths (94,517 and 888,083) will be used for the values of the external migration parameters, but in should be understood that other values may be used.  For example, if it is believed that illegal immigration will increase, higher values would be indicated.  Or, it may be desired to construct several alternative projections under different assumptions about external migration levels.

 

This completes the data specification for the construction of the file US802.DAT.

 

 

C.  Results of CHECK Run

 

The output of a CHECK run of the file US802.DAT is shown in Listing 3.  For each race, the program first prints out all of the input data.  No discrepancies are observed from the data presented above.

 

The estimated Total Fertility Rates for the two races are 1.748 and 2.335, which are in close agreement with the rates specified for the first projection period (1.717 and 2.334, respectively).  The race transition parameter values as calculated by the program are identical to the values calculated manually above.

 

 

D.  Results of PROJ Run

 

Listing 4 illustrates a run of the PROJ program, which projects the population two five-year periods out, from the base year of 1980 to the year of 1990.  Since the input population data are disaggregated by age, sex, and race, the projections may be also.  The total projected population for 1990 is 250,738,546, which corresponds to the actual value for 1990 of 248,710,000 (SA92, Table No. 18, "Resident Population, by Age, Race, and Hispanic Origin: 1980 and 1990").  This is an error of 1%.  The projected population for this example differs from the projected population for the previous (combined-race) model since the demographic specification is different -- more detailed (two races vs. one) -- and the projection model is nonlinear.

 

The projection yields values of 197,443,844 for white and 53,294,702 for other.  These correspond to the actual 1990 values of 199,686,000 for white and (by subtraction from the total 248,710,000) 49,024,000 for other (SA92, Table No. 18).  These race-specific projections are in error by -1.1% and 8.7%, respectively.  The white race projection is slightly low and the other race projection is somewhat too high.  Since the Total Fertility Rate for black and other races was steadily increasing over the period 1980-1990, the reason for the overshot is that the migration number specified for the black and other races for the projection period was too large.  This is a not unexpected result, in view of the fact that the value used for the external migration number (888,003) for others exceeded the approximate upper limit (726,395) for other migration.  (Based on this result, the migration numbers could be revised to obtain more accurate projections from a later base year, such as 1990.  It is noted that if the values 273,680 and 726,395 are used for the migration amounts, the 1990 projection is 199,252,780 whites and 51,620,900 others, both of which are somewhat closer to the actual 1990 values.)

 


VIII.  Example 3: State Population Projection, Single-Race Model

 

A.  Projection Objectives; Data Sources

 

This chapter presents an example illustrating the use of the DESTINY package to make a projection of the population of the state of Arizona from the base year of 1980.  The purpose of this example is primarily to obtain a migration estimate for the three-race model presented in the following chapter.

 

In addition to the national demographic data sources cited earlier, the following state data sources were used:

 

o    CPAZ80: 1980 Census of Population, Volume 1, Characteristics of the Population, Chapter B, General Population Characteristics, Part 4, Arizona, PC80-1-B4), issued April 1982, Bureau of the Census, US Department of Commerce, Washington, DC.

 

o    VSAZ80: 1980 Arizona Vital Health Statistics, Arizona Department of Health Services, Phoenix, Arizona

 

These two publications will be referred to in the remainder of this chapter as CPAZ80 and VSAZ80, respectively.  CPAZ80 includes data on the state population by age, sex, and race.  VSAZ80 includes data on birth and death rates.

 

Another source of demographic data for Arizona is the Arizona Statistical Abstract: A 1990 Data Handbook published by the College of Business and Public Administration of the University of Arizona, Tucson, Arizona.

 

For comparing DESTINY projections for 1990 to actual 1990 values, the 1990 Census of Population, General Population Characteristics, United States, 1990 CP-1-1 ("CPUS90"), contains data by age, sex, and race for each state.  Data on county by race (including white, black, Indian, and Hispanic status) are presented in the County and City Data Book 1994 ("CCDB94"), and also in 1990 Census of Population, General Population Characteristics, Arizona, 1990 ("CPAZ90").

 

The example presented in this chapter is particularly illustrative of a state-level application of the DESTINY package, since it reveals the difficulties in obtaining accurate state-level data, and shows how these difficulties are overcome.

 

As in the preceding examples, we will generally use, if available, the average for the five years preceding the base year as the value of parameters in the projection period.

 

B.  PARAM Run Parameters

 

The example presented here includes a single racial group and region, representing the total population of the state.

 

In the run of the PARAM program, the name AZ801.DAT was given to the parameter file, and the base year was stated as 1980.  (In the file name, AZ stands for Arizona, 0 stands for 1980, and 1 is the number of races.

 

P1: Number of races = 1

P2: Number of regions = 1

P3: Demographic Parameter Option = 1 (i.e., the demo- graphic parameters are to be the same for all ten five-year projection periods)

P4: Life Table Option = 1 (i.e., the survival prob- abilities will be determined by the Infant Mortality Rate, rather than by the Life Expectancy at Birth)

P5: External Migration Option = 1 (i.e., a single migration rate and/or migration number will be specified, to be used for all projection periods)

P6: Internal Migration Option = 0 (no regions are specified, so there is no internal migration)

P7: Service System Option = 0 (i.e., no service system parameters are included in the model)

 

The following paragraphs describe the demographic data input to the PARAM program.

 

Fertility Age Distribution; Total Fertility Rate

 

Total Fertility Rates are not available for Arizona from published state vital statistics sources.  VSAZ80 presents crude birth rates (CBRs), but not Total Fertility Rates (TFRs).  The TFR will be hence be estimated from the CBR and base-year population data.

 

The following formula relates TFR to CBR and the base-year population:

 

TFR = .005*CBR*POPT/BFAC

 

where

 

TFR = total fertility rate

 

CBR = crude birth rate

 

POPT = total population

 

BFAC = ' FADi*FPOPi

 

and

 

FADi = the "fertility age distribution," i.e., the

              percentage of total lifetime births occurring to

              females in the i-th five-year age cohort

 

FPOPi = female population in the i-th five-year age

               cohort.

 

All of the preceding parameters refer to the base year.

 

The crude birth rate for Arizona for 1979 is given in on page 60 of SA81, Table No. 71, "Live Births -- Number and Rate, by States, 1960 to 1979": 19.1.  Note that this differs somewhat from the 1979 rate presented in VSAZ80, which is 17.7 (the state 1980 value is 18.4).  Since the state value is more recent (i.e., for 1980 rather than 1979), we shall use it (i.e., 18.4).

 

The total population for the base year is 2,718,215 (from CPAZ80).

 

Since no state-specific data are available on the fertility age distribution, the national (all-race) data are used.  These data, from SA81 Table No. 85, were presented on the chapter dealing with the US single-race model, and are presented below, along with the female population for the relevant age cohorts (the full base-year population distribution by age and sex, from CPAZ80, is presented later):

 

                         Fertility Age           Female

     Age of Mother     Distribution, FADi   Population, FPOPi

 

         15-19                .147               123,734

         20-24                .312               130,297

         25-29                .312               116,911

         30-34                .166               102,909

         35-39                .052                82,540

         40-44                .011                68,279

         Total               1.000

 

Substituting in the formula presented above, we obtain

 

BFAC = .147(123,734) + .312(130,297) + .312(116,911)

           +.166(102,909) + .052(82,540) + .011(68,279)

 

          = 117,443.837

 

and so

 

TFR = .005(18.4)(2,718,215)/117,443.837

 

         = 2.129 .

 

Infant Mortality Rate

 

Data on infant mortality for Arizona are found in SA81, VS78, and VSAZ80.  SA81 presents IMRs for whites and blacks, but not for all races combined (later editions of the SA also report for the total).  VS78 reports IMRs for white and other races, but the data are for 1978, not for 1980.  The most recent source is VSAZ80.  VSAZ80 reports (Table 3.11) the infant mortality rate for 1980 as 12.4.  The average for years 1975-80 is 13.56; this value will be used for the first projection period.

 

Base-Year Population by Age and Sex

 

Population data by age and sex are presented for the year 1980 in CPAZ80.  These data are as follows.

 

                  Age        Male          Female

 

                  0-4      109,075    104,808

                  5-9      107,650    103,417

                 10-14     111,583    107,990

                 15-19     128,283    123,734

                 20-24     133,486    130,297

                 25-29     119,140    116,911

                 30-34     104,855    102,909

                 35-39      80,333     82,540

                 40-44      66,836     68,279

                 45-49      61,538     63,533

                 50-54      60,295     66,454

                 55-59      61,155     71,352

                 60-64      57,682     66,718

                 65-69      53,009     61,835

                 70-74      39,867     47,409

                 75+        43,155     62,087

                 Total  1,337,942  1,380,273

                 Grand Total     2,718,215

 

Crude Birth Rate for Base Year

 

In VSAZ80, Table 2.8, the crude birth rate for Arizona for 1980 is reported as 18.4.

 

Crude Death Rate for Base Year

 

In VSAZ80, Table 3.3, the crude death rate for 1980 is reported as 7.8.

 

Infant Mortality Rate for the Base Year

 

In VSAZ80, Table 3.13, the infant mortality rate for 1980 is reported as 12.4.

 

Population Ten Years Prior to Base Year

 

Numerous tables in SA81, such as Table No. 8, page 9 ("Resident Population -- States 1970 to 1980") report the 1970 resident population of Arizona as 1,775,000.

 

Note that CPAZ80 reports (Table 20) a slightly different figure -- 1,770,900.  The 1,775,000 figure is cited more frequently, and appears in later editions of SA.  For use in the multi-race model of the next chapter, however, the 1970 population is needed disaggregated by race.  Since these data are presented in CPAZ80 (Table 17) but not in SA81, the CPAZ80 data (i.e., the value 1,770,900) will be used, solely for the sake of consistency.

 

Average Crude Birth Rate for the Ten-Year Period Prior to Base Year

 

From VSAZ80, Table 2.8, the average for years 1971-80 is seen to be 18.32.

 

Average Crude Death Rate for the Ten-Year Period Prior to Base Year

 

From VSAZ80, Table 3.3, the average for years 1971-80 is seen to be 7.71.

 

Average Infant Mortality Rate for the Ten-Year Period Prior to Base Year

 

From VSAZ80, Table 3.11, the average for years 1971-80 is seen to be 14.94.

 

External Migration

 

As was done before, the annual migration amount will be estimated as the average annual population change net of births and deaths, which is:

 

pt+1 = (1+b-d)pt + M

 

where

 

pt = population in year t

 

b = crude birth rate

 

d = crude death rate

 

M = annual (net) migration number,

 

and all of the parameter values represent average values over the ten-year period prior to the base year.

 

Solving this equation for M in terms of p10 and p0 yields the following:

 

M = (p10 - p0(1+b-d)10)(b-d)/((1+b-d)10-1) .

 

Substituting b=.01832, d=.00771, p0=1,770,900, and p10=2,718,215 yields the estimate:

 

M = 71,507.

 

This completes the data specification for the construction of the file AZ801.DAT.

 

 

C.  Results of CHECK Run

 

The output of a CHECK run of the file AZ801.DAT is shown in Listing 5.  The printout reveals no errors in the data entry.

 

The run shows that the manual computations of the Total Fertility Rate (2.129) and the annual net migration number (71,507) were correct.

 

 

D.  Results of PROJ Run

 

Listing 6 illustrates a run of the PROJ program, which projects the population two five-year periods out, from the base year of 1980 to the year of 1990.  Since the input population data are disaggregated by age and sex, the projections may be also.  The projected total population for 1990 is 3,694,625, which corresponds to the actual value for 1990 of 3,665,000 (SA92, Table No. 25, "Resident Population -- States: 1970 to 1991").  This is an error of less than 1%.

 


IX.  Example 4: State Population Projection, Three-Race, 14-Region Model

 

A.  Projection Objectives; Data Sources

 

This chapter presents an example illustrating the use of the DESTINY package to make a multi-race, multi-region projection of the population of the state of Arizona from the base year of 1980.  The races are white, American Indian, and other.  The regions are the 14 counties of Arizona.

 

In the following chapter, the DESTINY package will be used to project social services to the elderly.  That projection will use the population model constructed in this chapter.

 

The data sources used for this example are the same as those of the preceding chapter.  A minor problem that arose in the present example in that population data were not immediately available by county and race for 1970 (i.e., 10 years prior to the base year).  In order not to delay preparation of the projections, the 1970 county-by-race data were estimated.  Later, the actual (1970 Census) county-by-race data were obtained.  In order to illustrate the procedure for estimating ten-year-prior region-by-race data (for applications in which the ten-year-prior region-by-race data are unavailable), the estimation procedure will be illustrated, and the estimates will be compared to the actual values.  The estimates will be used in this example, rather than the actual values; in a real application, the projection would be redone using the 1970 actual race-by-county values.

 

The special features illustrated in this example are the estimation of net migration numbers by race, and the procedure for estimating regional growth rates and migration.

 

 

B.  PARAM Run Parameters

 

The example presented here includes three racial groups (white, American Indian, and other) and fourteen regions (the fourteen counties of Arizona in 1980).  (Note: In 1983, Yuma County was split to form the two counties of Yuma and La Paz.  The Yuma County of the example presented here refers to the union of the present Yuma and La Paz Counties.)  In the run of the PARAM program, the name AZ803C.DAT was given to the parameter file, and the base year was stated as 1980.  (In the file name, AZ stands for Arizona, 80 stands for 1980, 3 is the number of races, and C stands for county.)  The seven Input Option Parameters were as follows:

 

P1: Number of races = 3

P2: Number of regions = 14

P3: Demographic Parameter Option = 1 (i.e., the demo- graphic parameters are to be the same for all ten five-year projection periods)

P4: Life Table Option = 1 (i.e., the survival prob- abilities will be determined by the Infant Mortality Rate, rather than by the Life Expectancy at Birth)

P5: External Migration Option = 1 (i.e., a single migration rate and/or migration number will be specified, to be used for all projection periods)

P6: Internal Migration Option = 1 (i.e., internal migra- tion among the counties will be specified)

P7: Service System Option = 0 (i.e., no service system parameters are included in the model)

 

The following paragraphs describe the demographic data input to the PARAM program.  As in the previous chapter, the data are presented demographic-category-by-demographic-category, rather than race-by-race (the order requested by the PARAM program.)

 

Total Fertility Rates; Fertility Age Distributions

 

Total Fertility Rates are not available by race for Arizona from published state vital statistics sources, and they are not available by state in VS78.  Hence, the TFRs will be estimated, using the formula

 

TFR = .005*CBR*POPT/BFAC

 

given earlier.  In order to use this formula, data are required, by race, for crude birth rates for the base year, for the total population in the base year, for the fertility age distribution, and for the female populations in the child-bearing age categories.

 

The required population data are available from CPAZ80 (Table 17, "Race by Sex: 1900 to 1980").  The total populations for 1980 for the three races of the model are 2,240,761 for whites, 152,498 for American Indians, and 324,956 for others.

 

Obtaining data on crude birth rates for 1980 is problematic.  VS78 presents crude birth rates by state or by race, but not by race for each state.  Although data on births are available by race from VSAZ80, the racial classification used for these data do not correspond to the racial classifications used for the population figures available from the Census.  For this reason, it is not possible to construct rates directly from the birth-by-race data presented in the Arizona vital statistics report (VSAZ80).

 

The following table presents the 1980 US Census data on the Arizona population by race (CPAZ80, Table 17. "Race by Sex: 1900 to 1980"), and the 1980 Arizona vital statistics data on Arizona births by race (VSAZ80, Table 2.12).

 

          Arizona                      Arizona

           1980                         1980            Crude

        Population            Race     Births           Birth

  Race   (CPAZ80)  Percent  of Child  (VSAZ80)  Percent  Rate

 

  White  2,240,761   82.4     White    42,308     84.6   18.9

  Indian   152,498    5.6     Indian    5,061     10.1   33.2

  Black     74,977    2.8     Black     2,062      4.1   27.5

  Other    249,979    9.2     Asian       618      1.2

  Total  2,718,215  100.0     Total    50,049    100.0

 

The problem is apparent: the Asian birth category of VSAZ80 does not correspond to the Other population category of CP80.  Evidently, many births that would be classified as "other" using US Census race classification criteria are included in other categories in the state birth counts.  Birth rates estimated from the preceding data would be seriously biased (low) for the "other" race category (nonwhite, nonIndian) of the model.

 

Note that since the model will be projecting the populations obtained from the CP80 source, it is the birth rates that must correspond to those population categories, and not vice versa.

 

To overcome the comparability problem, crude birth rates will be estimated for the white and Indian categories from the VSAZ80 data, but the US crude birth rate will be used for the other category.  This approach produces 18.9 for the white crude birth rate (VSAZ80, Table 2.12), 33.2 for the Indian crude birth rate (also Table 2.12), and 22.8 for the other crude birth rate (SA81, Table 85).

 

The remaining data required by the TFR estimation formula are the fertility age distributions and the populations of females in the fertile age categories.

 

For the fertility age distributions, the national-level data presented in VS78 will be used (no state-level FAD data are available from VSAZ80).  These data are available for total, white, all other, and black races.  The data for the "all other" race category will be used for the Indians and other race category of the model.  These data were presented earlier in the chapter dealing with the US two-race model, and are presented in the following table.

 

                Fertility Age Distribution

        Age      White    Indian    Other

 

       15-19     .130      .221      .221

       20-24     .312      .312      .312

       25-29     .326      .251      .251

       30-34     .170      .143      .143

       35-39     .051      .058      .058

       40-44     .011      .015      .015

       Total    1.000     1.000     1.000

 

The final data required are the numbers of females in the fertile age cohorts.  These counts are available from Table 20 of CPAZ80, and are presented in the following table (the complete population distributions are presented later).

 

                    Female Population

        Age      White    Indian    Other

 

       15-19     95,899    9,973    17,862

       20-24    104,137    7,979    18,181

       25-29     95,364    6,237    15,310

       30-34     85,981    4,988    11,940

       35-39     69,718    4,054     8,768

       40-44     57,394    3,522     7,363

 

With the preceding data, the TFR estimates may now be calculated for the three race categories.

 

For whites, we have:

 

BFAC = .130(95,899) + .312(104,137) + .326(95,364)

            +.170(85,981) + .051(69,718) + .011(57,394)

 

          = 94,850.00

 

and

 

     TFR = .005*18.9*2,240,761/94,850.00 = 2.232.

 

For Indians, we have:

 

BFAC = .221(9,973) + .312(7,979) + .251(6,237)

            + .143(4,988) + .058(4,054) + .015(3,522)

 

          = 7,260.214

 

and

 

TFR = .005*33.2*152,498/7,260.214 = 3.487.

 

For others, we have:

 

BFAC = .221(17,862) + .312(18,181) + .251(15,310)

            + .143(11,940) + .058(8,768) + .015(7,363)

 

          = 15,789.193

 

and

 

TFR = .005*22.8*324,956/15,789.193 = 2.346.

 

Infant Mortality Rates

 

Infant Mortality Rates are available from VS78 by state, for the race categories total, white and all other (Table 2-6, "Infant Mortality Rates by Color: United States, Each Division and State, 1974-78").  (Later editions of VS also present data for the black race category.)  SA81 presents IMR data by state for white and black races.  VSAZ80 presents birth and infant death data for white, Indian, black, and Asian races.

 

Estimation of the Infant Mortality Rate (IMR) for Arizona faces similar problems to those encountered in estimation of the Total Fertility Rates, namely the incomparability of the Arizona vital statistics race categories with the Census population race categories (which are used for the model population categories).  The data presented in VSAZ80 for births (Table 2.12) and infant deaths (Table 3.12) are as follows:

 

                                    Arizona

           Arizona                   1980

   Race     1980             Race   Infant           Infant

    of     Births             of    Deaths          Mortality

   Child  (VSAZ80)  Percent  Child (VSAZ80)  Percent  Rate  

 

  White    42,308    84.6   White    497      80.3    11.7

  Indian    5,061    10.1   Indian    82      13.2    16.2

  Black     2,062     4.1   Black     40       6.5    19.4

  Asian       618     1.2   Asian      0       0.0     0.0

  Total    50,049   100.0   Total    619     100.0    12.4

 

We shall use the IMRs calculated from the VSAZ80 state data for whites (11.7) and Indians (16.2), but use the SA81 national data for black and other races (21.1 for 1978, from Table No. 111) for the other race category.

 

Base-Year Population by Age, Sex, and Race

 

Base-year population data by age, sex, and race are presented in CPAZ80 (Table 20, "Age by Race and Sex: 1910 to 1980").  Unfortunately, these data are presented for white and black (and, by subtraction, for other than white or black), but not for white, Indian, and other than white or Indian.  The Indian population is presented by age and sex for all counties except Greenlee and Santa Cruz.  For these two counties, the population is presented by age and sex, but only the total Indian population is specified.  The Indian population by age and sex for these counties was estimated by multiplying the age-sex distribution of the county by the proportion Indian in each county (.0200772 for Greenlee and .0027861 for Santa Cruz.)  The age x sex Indian population distribution was added for all counties to obtain the age x sex Indian population distribution for the entire state.

 

The age by sex population distribution for Arizona for 1980 for the three racial groups of interest is as follows:

 

                   White          Indian          Other

    Category    Male   Female   Male  Female   Male   Female

 

      0-4     79,351    76,208  9,853  9,732  19,871  18,868

      5-9     80,415    76,578  9,288  9,237  17,947  17,602

     10-14    85,306    82,032  9,575  9,465  16,702  16,493

     15-19    99,026    95,899  9,931  9,973  19,326  17,862

     20-24   106,315   104,137  7,250  7,979  19,921  18,181

     25-29    96,311    95,364  5,681  6,237  17,148  15,310

     30-34    87,382    85,981  4,817  4,988  12,656  11,940

     35-39    68,203    69,718  3,524  4,054   8,606   8,768

     40-44    56,493    57,374  3,120  3,522   7,223   7,363

     45-49    52,916    54,059  2,532  3,103   6,090   6,371

     50-54    53,052    58,170  2,123  2,579   5,120   5,705

     55-59    55,155    64,721  1,758  2,122   4,242   4,509

     60-64    53,162    61,749  1,362  1,555   3,158   3,414

     65-69    49,283    57,527  1,154  1,382   2,572   2,926

     70-74    37,022    44,379    928    916   1,917   2,114

     75+      39,590    57,863  1,349  1,409   2,216   2,815

   Sex Tot.1,098,982 1,141,779 74,245 78,253 164,715 160,241

   Race Totals  2,240,761         152,498        324,956

   Grand Total                  2,718,215

 

Crude Birth Rate for Base Year

 

As discussed earlier, we shall use the birth rates derived from VSAZ80 (births) and CPAZ80 (population) for the white and Indian races, and the SA81 data for the other race category.  These values are 18.9 for whites, 33.2 for Indians, and 22.8 for others.

 

Crude Death Rate for Base Year

 

Crude death rates are available by race or by state from SA81 and VS78, but not by state and race.  Data on deaths by race are available from VSAZ80.  As was the case with the VSAZ80 data on births, these data are not comparable with the CPAZ80 population data.  The following table presents the death data from VSAZ80 (Table 3.5).

 

          Arizona                  Arizona

           1980             Race     1980             Crude

        Population           of     Deaths            Death  

  Race   (CPAZ80)  Percent  Child  (VSAZ80)  Percent  Rate

 

  White  2,240,761   82.4   White   19,631     92.4    8.8

  Indian   152,498    5.6   Indian     988      4.7    6.5

  Black     74,977    2.8   Black      552      2.6    7.4

  Other    249,979    9.2   Asian       55      0.3

  Total  2,718,215   100.0  Total   21,226    100.0

 

We shall use the crude death rate from the VSAZ80 data for whites and Indians (8.8 and 6.5 respectively), but the national-level data from SA81 for the other race category (7.8 for 1979, Table 108).

 

Infant Mortality Rate for the Base Year

 

As discussed earlier, we shall use IMR data derived from VSAZ80 for the white and Indian races, but national-level data presented in SA81 for the other race category.  These rates are 11.7 for whites, 16.2 for Indians, and 21.1 for other.

 

In VSAZ80, Table 3.13, the infant mortality rate for 1980 is reported as 12.4.

 

Population Ten Years Prior to Base Year

 

Data for the 1970 population by race are available from CPAZ80 (Table 17, "Race by Sex: 1900 to 1980").  These data are as follows: 1,604,948 for whites, 95,812 for Indians, and (by subtraction from the total of 1,770,900) 70,140 for others.

 

Average Crude Birth Rate for the Ten-Year Period Prior to Base Year

 

Data on birth rates by race for the entire ten-year period prior to the base year are available from past editions of the Arizona Vital Health Statistics, but these data are not readily available.  For this reason, the base-year data presented above shall be used (18.9 for whites, 33.2 for Indians, and 22.8 for others).

 

Average Crude Death Rate for the Ten-Year Period Prior to Base Year

 

For the same reason given in the preceding paragraph on crude birth rates, the base-year data presented above will be used (8.8 for whites, 6.5 for Indians, and 7.8 for others).

 

Average Infant Mortality Rate for the Ten-Year Period Prior to Base Year

 

For the same reason given above, the base-year data presented above will be used (11.7 for whites, 16.2 for Indians, and 21.1 for others).

 

Base-Year Population by Region (County)

 

CPAZ80 presents the population of each county, by race.  The data are presented in the table which follows:

 

                       Population by Race (Base Year, 1980)

     County          White      Indian     Other      Total

 

     Apache           11,902    39,024     1,182      52,108

     Cochise          73,261       489    11,936      85,686

     Coconino         49,235    20,904     4,869      75,008

     Gila             30,147     5,083     1,850      37,080

     Graham           17,085     2,740     3,037      22,862

     Greenlee          9,357       229     1,820      11,406

     Maricopa      1,307,455    22,788   178,809   1,509,052

     Mohave           53,477     1,462       926      55,865

     Navajo           32,543    32,122     2,964      67,629

     Pima            442,888    14,880    73,675     531,443

     Pinal            61,849     8,487    20,582      90,918

     Santa Cruz       16,515        57     3,887      20,459

     Yavapai          65,322       997     1,826      68,145

     Yuma             69,725     3,236    17,593      90,554

     Total         2,240,761   152,498   324,956   2,718,215

 

External Migration

 

External migration will be estimated, as before, as the change in population net of births and deaths.  Using the same formula (M = (p10 - p0(1+b-d)10)(b-d)/((1+b-d)10-1)) as before, the estimates 44,535 for whites, 2,462 for Indians, and 22,756 for others are obtained.  These estimates are considered "rough," since the data on fertility rates by race were approximate, especially for the other race category.  Errors in the fertility rate will affect the migration estimate (since this estimate is the population net of estimated births and deaths, and the estimated births is uncertain), but these errors tend to compensate (i.e., if the TFR for others is too low, the external migration estimate will be too high, and vice versa).

 

Regional Populations Ten Years Prior to Base Year

 

As mentioned earlier, county-by-race data were not immediately available (from the US Bureau of the Census) for the year 1970, and so these data were estimated.  Later, the actual 1970 data were received.  The following paragraphs illustrate a procedure for estimating region-by-race data for a ten-year-earlier year, using base-year region-by-race data.

 

The data that were initially available for 1970 were the population totals for the three races and the population totals for the 14 counties (i.e., the "marginal" totals are available for race and county).  For 1980, the data were available for county-by-race.  These data may be used to compute estimates of the proportion of population in each race-by-county category.  What is desired is to determine an allocation of the 1970 population over the various race-by-county categories that matches the marginal race and county totals, for which the race-by-county proportions are "close" to the 1980 values.

 

The problem of determining a set of race-by-county category counts that matches the specified marginal totals and is close to the specified cell proportions is called "statistical adjustment of data."   The recommended procedure for solving this problem is to determine the adjustments by the method of least-squares, using a procedure known as "Deming-Stefan raking."  To avoid the complexity of this (iterative) method, we shall use a simpler procedure.

 

The procedure we shall use involves two steps.  First, we shall apportion the total 1970 population for each race to the counties in proportion to the 1980 county populations for the race.  The problem that arises is that the county populations (summed over all races) obtained in this way may not match the known 1970 totals.  To address this problem, the population values for the white race (usually the largest in every county) will be adjusted (in each county) to force the county total to match the known 1970 county total.

 

The result of applying the first step produces the following table:

 

           Population by Race (Estimated, 1970, Unadjusted)

                                             Unadjusted   1970

  County           White   Indian    Other     Total      Total

 

  Apache           8,525   24,518      255     33,298    32,298

  Cochise         52,473      307    2,576     55,356    61,910

  Coconino        35,265   13,134    1,051     49,450    48,326

  Gila            21,593    3,194      399     25,186    29,255

  Graham          12,237    1,721      656     14,614    16,578

  Greenlee         6,702      144      393      7,239    10,330

  Maricopa       936,466   14,317   38,595    989,378   967,522

  Mohave          38,303      919      200     39,422    25,857

  Navajo          23,309   20,182      640     44,131    47,715

  Pima           317,219    9,349   15,902    342,470   351,667

  Pinal           44,299    5,332    4,443     54,074    67,916

  Santa Cruz      11,829       36      839     12,704    13,966

  Yavapai         46,787      626      394     47,807    36,733

  Yuma            49,941    2,033    3,797     55,771    60,827

  Total        1,604,948   95,812   70,140  1,770,900 1,770,900

The result of adjusting the white county amounts so that the three races sum to the correct county totals (by adding the 1970 total less the unadjusted total to each white amount) is as follows:

 

                 Population by Race (Estimated, 1970)

                                                 1970

  County           White   Indian    Other      Total

 

  Apache           7,525   24,518      255     32,298

  Cochise         59,027      307    2,576     61,910

  Coconino        34,141   13,134    1,051     48,326

  Gila            25,662    3,194      399     29,255

  Graham          14,201    1,721      656     16,578

  Greenlee         9,793      144      393     10,330

  Maricopa       914,610   14,317   38,595    967,522

  Mohave          24,738      919      200     25,857

  Navajo          26,893   20,182      640     47,715

  Pima           326,416    9,349   15,902    351,667

  Pinal           58,141    5,332    4,443     67,916

  Santa Cruz      13,091       36      839     13,966

  Yavapai         35,713      626      394     36,733

  Yuma            54,997    2,033    3,797     60,827

  Total        1,604,948   95,812   70,140  1,770,900

 

The entries of this table are entered into to program as the regional populations ten years prior to the base year.

 

The following table shows the actual 1970 region-by-race values, for comparison to the estimated values.  (The source of the data is 1970 Census of Population, Volume 1, Characteristics of the Population, Part 4: Arizona, US Department of Commerce, Bureau of the Census, Washington, DC 1972.  The other values are obtained by subtraction of the white and Indian values from the total.)

 

                 Population by Race (Actual 1970)

                                                 1970

  County           White   Indian    Other      Total

 

  Apache           7,734   23,994      570     32,298

  Cochise         59,250      152    2,508     61,910

  Coconino        34,512   11,996    1,818     48,326

  Gila            24,409    4,591      255     29,255

  Graham          14,124    1,682      772     16,578

  Greenlee        10,099      124      107     10,330

  Maricopa       914,464   11,159   41,899    967,522

  Mohave          24,850      869      138     25,857

  Navajo          23,425   23,023    1,267     47,715

  Pima           329,278    8,837   13,552    351,667

  Pinal           57,516    6,405    3,995     67,916

  Santa Cruz      13,740       22      204     13,966

  Yavapai         35,754      686      293     36,733

  Yuma            55,793    2,033    3,001     60,827

  Total        1,604,948   95,812   70,140  1,770,900

 

In general, the estimated values are close to the actual values.  Large relative errors occur for some of the counties having very small numbers of Indian and other races.  Except for these instances, using the estimated values instead of the actual values will have a negligible impact on the projection results.

 

Internal Migration

 

As discussed earlier, the parameters used to determine internal migration are the amount (or rate) of population change net of births, deaths, and net external migration allocated proportional to region (county) population size.

 

The formulas for estimating the internal migration parameter values are similar to those used for estimating external migration parameters.

 

The formulas for the internal migration amount (N) and the internal migration rate (n) are:

 

N = (p10 - p0(1+b-d+m)10)(b-d+m)/((1+b-d+m)10-1) - M

 

and

 

n = ((p10-MC)/p0).1 -1 - b + d - m,

 

where

 

C = ' (1+b-d+m+r)i ,

 

the sum is from 1 to 9, and the other symbols are as previously defined.  In this case, however, p10 refers to a county population of a particular race in the base year, and p0 refers to the county population of a particular race ten years previous.  Also, the value of M for each county is the total external migration for the race times the proportion of the race in that county, where the external migration is estimated (as above) as the population change net of births and deaths.

 

The formula for the amount is a closed-form expression, whereas the formula for the rate is not (i.e., n occurs on both sides of the equation and it is not possible to obtain a closed-form expression for n).  The CHECK program evaluates both of these expressions (using an iterative method for the rate), and so it is not necessary to perform the computations by hand.

 

As an approximation for the rate, the amount divided by the population, times 1,000, may be used.

 

The following table presents the values of the internal migration amounts and rates (per 1,000) for the three races, as determined by the preceding formula for N and n.  As discussed earlier, the amount will be used (entered to the PARAM program) if the estimate is positive (or zero), and the rate will be used otherwise.

 

                 Internal Migration Amounts and Rates

                      White        Indian         Other

     County       Amount  Rate  Amount  Rate  Amount  Rate

 

     Apache        106   11.257    0    .001     0    .021

     Cochise      -692  -10.599    0    .070     0    .005

     Coconino      119    2.290    0   -.003     0   -.002

     Gila         -430  -15.539    0   -.013     0    .033

     Graham       -207  -13.399    0    .027     0   -.031

     Greenlee     -327  -34.043    0   -.079     0   -.018

     Maricopa    2,309    2.130    0    .002     0    .000

     Mohave      1,433   39.480    0   -.045     0   -.027

     Navajo       -379  -12.877    0   -.001     0   -.016

     Pima         -972   -2.576    0   -.001     0    .001

     Pinal      -1,462  -24.442    0    .004     0   -.005

     Santa Cruz   -133   -9.132    0   -.486     0   -.001

     Yavapai     1,170   24.387    0    .059     0    .014

     Yuma         -534   -8.687    0    .006     0    .004

     Total           0             0             0

 

The internal migration amounts for Indians and others are zeros for all counties because the populations for 1970 for those races were estimated for each county as proportional to the 1980 populations.

 

Some of the internal migration rates are so large that it is difficult to imagine that they would continue for very long.  The value 39.480 for the white race in Mohave County, for example, corresponds to a migration of about 4% per year, net of births, deaths, and proportional allocation of external migration.  Although the estimated values will be used for this example, in a real application consideration would be given to reducing the magnitudes of migration parameters that are very large (since continuation of high rates for many years is unlikely).

 

This completes the data specification for the construction of the file AZ803.DAT.

 

 

C.  Results of CHECK Run

 

The output of a CHECK run of the file AZ803C.DAT is shown in Listing 7.  The printout reveals no errors in the data entry.

 

The run shows that the manual computations of the Total Fertility Rates (2.232, 3.487, and 2.346) were correct.

 

 

D.  Results of PROJ Run

 

Listing 8 illustrates a run of the PROJ program, which projects the population two five-year periods out, from the base year of 1980 to the year of 1990.  Since the input population data are disaggregated by age, sex, race, and region, the projections may be also.  The total projected population for 1990 is 3,735,219, which corresponds to the actual value for 1990 of 3,665,000 (SA92, Table No. 25, "Resident Population -- States: 1970 to 1991").  This is an error of 1.9%.

 

Note that the 1990 total-population projection of this model differs slightly from the 1990 total-population projection of the single-race model of the preceding chapter (3,694,625).  It is not quite as accurate, probably a result of the difficulty of estimating net migration by race.

 

The projections for 1990 by race are 2,886,323 for whites, 228,240 for Indians, and 620,656 for others.  These may be compared to the actual 1990 figures available from the 1990 Census (1990 Census of Population, General Population Characteristics, United States, 1990 CP-1-1, issued November, 1992, US Department of Commerce, Bureau of the Census, Washington, DC (henceforth referred to as CP90), Table 262, "Age and Sex by Race and Hispanic Origin: 1990"): 3,665,228 total, 2,963,186 for whites, 203,527 for Indians, and (by subtraction) 498,515 for others.  The errors in these race-by-race projections are -2.6% for whites, 12.1% for Indians, and 24.5% for others.  These results are displayed in the following table.

 

                    1990 Projected   1990 Actual  Percentage

       Race           Population     Population     Error

 

       White            2,886,323    2,963,186       -2.6

       Indian             228,240      203,527       12.1

       Other              620,656      498,515       24.5

       Total            3,735,219    3,665,228        1.9

 

The projection for the other race is poor.  The reason for this is that the explosive growth in this racial group from 1970 to 1980 (70,140 to 324,956, or an average annual rate of 16.6% dropped dramatically for the 1980-1990 decade (from 324,956 to 498,515, or an average annual rate of only 4.4%).  It is not known whether this dramatic drop in the growth rate of the other race category is the result of substantial changes in race classification procedures, racial mixing, or a real drop in the number of other-race persons migrating to Arizona.

 

The projections for 1990 by county may be compared to the 1990 actual values, available from the County and City Data Book, 1994, US Department of Commerce, Bureau of the Census, Washington, DC.  The following table compares the 1990 county projections and the 1990 actual values.

 

                    1990 Projected   1990 Actual  Percentage

       County         Population     Population     Error

 

       Apache            72,497        61,591       17.7

       Cochise           97,683        97,624         .1

       Coconino          97,171        96,591         .6

       Gila              40,759        40,216        1.4

       Graham            26,383        26,554        -.6

       Greenlee          11,039         8,008       37.8

       La Paz                 *        13,884          *

       Maricopa       1,893,992     2,122,101      -10.7

       Mohave            83,827        93,497      -10.3

       Navajo            84,127        77,658        8.3

       Pima             649,633       666,880       -2.6

       Pinal            101,590       116,379      -12.7

       Santa Cruz        24,075        29,676      -18.9

       Yavapai           95,609       107,714      -11.2

       Yuma             108,068       106,895      -10.5*

       Total          3,735,219     3,665,228        1.9

 

No projection is available for La Paz County, since that county was created in 1983, and was not included in the model.  Since that county was created from Yuma County, the sum of the 1990 actual populations for La Paz and Yuma Counties (120,779) should be compared to the projection for Yuma County (108,068).  The error in this projection is -10.5%.  The largest projection error is for Greenlee County, for which the population decreased from 11,406 to 8,008 between 1980 and 1990.

 

The average absolute projection error for the county projections is 10.4%.  For 10-year-out projections for highly disaggregated local areas in a state in which the population is growing rapidly because of migration, errors of this magnitude are considered very reasonable.  The magnitude of the errors for nearer-term projections would be less.

 

The following table shows the 1990 projections by race and county and compares them to the 1990 actual values.  The actual values are from CCDB94, with the "other" race obtained by subtracting the white and Indian amounts from the county totals.

 

                     1990 Population by Race and County

                   White            Indian           Other

  County     Projected Actual Projected Actual Projected Actual

 

  Apache      15,397    12,456  55,256  47,803   1,844   1,332

  Cochise     78,373    79,724     692     790  18,618  17,110

  Coconino    59,977    61,836  29,599  28,233   7,595   6,522

  Gila        30,676    30,776   7,197   5,238   2,886   4,202

  Graham      17,766    20,603   3,880   3,951   4,737   2,000

  Greenlee     7,876     6,835     324     183   2,839     990

  La Paz           *    10,335       *   2,402       *   1,107

  Maricopa 1,582,814 1,799,420  32,267  38,017 278,911 284,664

  Mohave      80,313    88,834   2,070   2,145   1,444   2,518

  Navajo      34,020    34,205  45,483  40,417   4,623   3,036

  Pima       513,643   524,976  21,069  20,330 114,920 121,574

  Pinal       57,469    87,219  12,017  10,785  32,104  18,375

  Sta Cruz    17,931    22,159      81      64   6,063   7,453

  Yavapai     91,349   103,106   1,412   1,740   2,848   2,868

  Yuma        76,044*   80,702*  4,582*  1,429* 27,442* 24,764*

  Total    2,886,323 2,963,186 228,240 203,527 620,656 498,515

 

Even though the level of disaggregation is quite high and the number of years out is far (10 years), the projections are reasonably close to the actual values in magnitude in most cases.  Substantial relative errors may occur for counties having small populations of the other race category.  The relative projection error may be reduced by combining (adding together) counties having small populations of the other races.

 

Recall that the actual totals for La Paz and Yuma Counties is to be compared to the projected for Yuma County.

 


X.  Example 5: Projection of the Hispanic Population

 

A.  Projection Objectives; Data Sources

 

This chapter presents an example illustrating the use of the DESTINY package to project the Hispanic population of the state of Arizona.  The model is a "two-race" one, in which the two "race" categories are Hispanic and other (non-Hispanic).  The model includes representation of the 14 Arizona counties of 1980.

 

Any racial, ethnic, or other classification of a population may be represented as a "race" in the DESTINY model.  The classification Hispanic/other is not a racial one, the model treats this classification in the same fashion as it does actual races.  To maintain parallelism of the presentation of this chapter with that of previous chapters, the discussion of this chapter will refer to the two categories of the Hispanic/other classification as "races" of the model, even though they are not races in the ethnic sense.

 

There is the likelihood of some confusion in the descriptors used for the racial categories of this model, when references are being made to some of the other multi-race models.  The problem is that the term "other" becomes ambiguous when several different multi-race models are under discussion.  It may refer to "other than white," or "other than white and Indian," or "other than Hispanic."  To avoid confusion, and yet avoid using such awkward descriptors (particularly in table titles), we shall make occasional use of terms such as "nonwhite" and "nonHispanic," despite the current "political incorrectness" of ethnic category descriptors having the prefix "non."

 

One needed data element needed for the present example that is not available from the referenced sources is the 1970 Arizona population by Hispanic status (for the whole state and by county).  The 1970 county-by-Hispanic-status data will hence be estimated.  Hispanic-status data are available for 1980 and later years, so this is no longer a problem in using the program to make forecasts from a base year of 1990 or later.

 

The approach used earlier to estimate 1970 populations for whites, Indians, and others does not work here, since the 1970 population totals are not available for Hispanics and nonHispanics.  Hence, it is not possible to apportion a known 1970 race population total over the counties in the same proportions as observed for 1980.  Instead, it will be assumed that the relative proportion of the races (Hispanic and nonHispanic) in each county was the same in 1970 as in 1980, and apportion the 1970 total county population (which is known) between the two races accordingly.  This procedure provides estimates of the population of each county by race and, by summing, estimates of the total population of each of the two races.

 

 

B.  PARAM Run Parameters

 

The example presented here includes two ethnic groups (Hispanic and other) and fourteen regions (the fourteen counties of Arizona in 1980).  (As noted earlier, in 1983, Yuma County was split to form the two counties of Yuma and La Paz.  The Yuma County of the example presented here refers to the union of the present Yuma and La Paz Counties.)  In the run of the PARAM program, the name AZ80HC.DAT was given to the parameter file, and the base year was stated as 1980.  (In the file name, AZ stands for Arizona, 80 stands for 1980, H stands for Hispanic, and C stands for county.)  The seven Input Option Parameters were as follows:

 

P1: Number of races = 2

P2: Number of regions = 14

P3: Demographic Parameter Option = 1 (i.e., the demo- graphic parameters are to be the same for all ten five-year projection periods)

P4: Life Table Option = 1 (i.e., the survival prob- abilities will be determined by the Infant Mortality Rate, rather than by the Life Expectancy at Birth)

P5: External Migration Option = 1 (i.e., a single migration rate and/or migration number will be specified, to be used for all projection periods

P6: Internal Migration Option = 1 (i.e., internal migra- tion among the counties will be specified)

P7: Service System Option = 0 (i.e., no service system parameters are included in the model)

 

The following paragraphs describe the demographic data input to the PARAM program.  As in the previous chapter, the data are presented demographic-category-by-demographic-category, rather than race-by-race (the order requested by the PARAM program.)

 

Total Fertility Rates; Fertility Age Distributions

 

Total Fertility Rates are not available by Hispanic status for Arizona from published state vital statistics sources, and they are not available by state in VS78.  Hence, the TFRs will be estimated, using the formula

 

TFR = .005*CBR*POPT/BFAC

 

given earlier.  In order to use this formula, data are required, by Hispanic status, for crude birth rates for the base year, for the total population in the base year, for the fertility age distribution, and for the female populations in the child-bearing age categories.

 

The required population data are available from CPAZ80 (Table 16, "Total Persons and Spanish Origin Persons by Type of Spanish Origin and Race: 1980").  The total populations for 1980 for the two races of the model are 440,701 for Hispanics and 2,277,514 for others.

 

The crude birth rates for 1980 are estimated from data on births presented in VSAZ80.  For 1980, Table 2.12 reports 13,082 Hispanic births out of a total of 50,049 births, implying (by subtraction) that there are 36,967 in the other (nonHispanic) category.  Dividing these figures by the respective populations produces the crude birth rate of 29.7 for Hispanics and 16.2 for others (nonHispanics).

 

The remaining data required by the TFR estimation formula are the fertility age distributions and the populations of females in the fertile age categories.

 

For the fertility age distributions, the national-level data presented in VS78 will be used (no state-level FAD data are available from VSAZ80).  These data are available for total, white, all other, and black races.  The total fertility rates for these four categories are 1.799, 1.708, 2.312, and 2.284, respectively.  Data are not available by Hispanic status.  Hispanic persons may be of any race.  Since the Hispanic group has a very high birth rate, its fertility rate is high.  Groups having high fertility rates typically have a FAD that has larger probabilities in the lower-age categories, such as the "all other" and "black" FADs.  This suggests using either the "all other" or "black" FADs for the Hispanic category.

 

With respect to the "other" (nonHispanic) category of the model, it is observed that it is heavily white, since the combined size of the other racial groups (Indians, blacks, etc.) is small.  This suggests using the "white" FAD for the nonHispanic category.

 

In view of the preceding considerations, we shall use the "all other" FAD for the Hispanic category and the "white" FAD for the nonHispanic category of the model.

 

The FAD data for these categories were presented earlier, in the chapter on the US two-race model, and are repeated here.

 

                           Fertility Age Distribution

     Age of Mother       Hispanic    Other(NonHispanic)

 

         15-19             .221           .147

         20-24             .312           .312

         25-29             .251           .312

         30-34             .143           .166

         35-39             .058           .052

         40-44             .015           .011

         Total            1.000          1.000

 

The final data required are the numbers of females in the fertile age cohorts.  These counts are available from Table 45 of CPAZ80 ("Age by Race, Spanish Origin, and Sex for Counties: 1980").  The data in this table are presented county by county, and must be totalled to obtain the total populations for all counties.  The complete population distributions are presented later.

 

                       Female Population

        Age      Hispanic    Other (NonHispanic)

 

       15-19      24,824          98,910

       20-24      22,734         107,563

       25-29      19,195          97,716

       30-34      15,780          87,129

       35-39      12,241          70,299

       40-44      10,217          58,062

 

With the preceding data, the TFR estimates may now be calculated for the two race categories.

 

For Hispanics, we have:

 

BFAC = .221(24,824) + .312(22,734) + .251(19,195)

            + .143(15,780) + .058(12,241) + .015(10,217)

 

          = 20,516.83

 

and

 

     TFR = .005*29.7*440,701/20,516.83 = 3.190.

 

For others (nonHispanics), we have:

 

BFAC = .147(98,910) + .312(107,563) + .312(97,716)

            + .166(87,129) + .052(70,299) + .011(58,062)

 

          = 97,344.462

 

and

 

TFR = .005*16.2*2,277,514/97,344.462 = 1.895.

 

 

Infant Mortality Rates

 

Infant Mortality Rates are available from VS78 by state, but not by Hispanic status.  VSAZ80 presents data on births by Hispanic status, but not infant deaths by Hispanic status.  Infant deaths are reported for the categories all races, white, and nonwhite.  Rather than make somewhat tenuous assumptions about which of these categories might approximate the IMR experience of Hispanics, we shall simply use the overall IMR for both Hispanics and nonHispanics.  For 1980 the birth data are 50,049 total births, and the infant death data are 619.  Dividing these numbers yields the rate 12.4.

 

Base-Year Population by Age, Sex, and Hispanic Status

 

Base-year population data by age, sex, and Hispanic status are presented in CPAZ80 (Table 45, "Age by Race, Spanish Origin, and Sex for Counties: 1980").  Summing over the counties produces the following population distribution by age, sex, and Hispanic status for the state.

 

                   Hispanic        Other(NonHispanic)

    Category    Male     Female      Male      Female

 

      0-4      27,940    26,823     81,135     77,985

      5-9      25,652    25,079     81,998     78,338

     10-14     24,234    23,538     87,349     84,452

     15-19     26,081    24,824    102,202     98,910

     20-24     23,080    22,734    110,406    107,563

     25-29     20,171    19,195     98,969     97,716

     30-34     15,889    15,780     88,966     87,129

     35-39     11,668    12,241     68,665     70,299

     40-44      9,644    10,217     57,192     58,062

     45-49      8,380     9,015     53,158     54,518

     50-54      7,608     8,290     52,687     58,164

     55-59      6,317     6,759     54,838     64,593

     60-64      4,672     5,073     53,010     61,645

     65-69      3,525     3,986     49,484     57,849

     70-74      2,545     2,938     37,322     44,471

     75+        2,840     3,963     40,315     58,124

   Sex Tot.   220,246   220,445  1,117,696  1,159,818

   Race Totals     440,701            2,277,514

   Grand Total              2,718,215

 

Crude Birth Rate for Base Year

 

As discussed earlier, we shall use the birth data available in VSAZ80 to calculate the crude birth rate of 29.7 for Hispanics and 16.2 for others (nonHispanics).

 

Crude Death Rate for Base Year

 

Data on deaths by Hispanic status are not available from any of the referenced sources.  VSAZ80 reports the death rate for all persons in Arizona (based on a total of 21,226 deaths) as 7.8.  This number will be used for both Hispanics and nonHispanics.

 

Infant Mortality Rate for the Base Year

 

As discussed earlier, we shall use the single IMR, 12.4, for both Hispanics and nonHispanics.

 

Population Ten Years Prior to Base Year

 

As discussed in the introduction to this chapter, data are not available on Hispanic status of the Arizona population for the year 1970, and the hypothetical numbers 282,293 and 1,488,607 will be used in place of the actual number of Hispanics and nonHispanics.  This number does not affect the projections, but it does affect the population growth estimates produced by the CHECK program.

 

Average Crude Birth Rate for the Ten-Year Period Prior to Base Year

 

In lieu of better estimates, the base-year crude birth rate estimates of 29.7 and 16.2 will be used.

 

Average Crude Death Rate for the Ten-Year Period Prior to Base Year

 

The base-year crude death rate of 7.8 will be used for both Hispanic and nonHispanic statuses, in lieu of better estimates.

 

Average Infant Mortality Rate for the Ten-Year Period Prior to Base Year

 

For the same reason given above, the base-year data presented above will be used (12.4 for both Hispanics and nonHispanics).

 

External Migration

 

As before, external migration will be estimated as the population change net of births and deaths.  Using this procedure, the estimates of net external migration are 8,159 per year for Hispanics and 63,450 for nonHispanics.  (Note that the total of these estimates, 71,609, is close to the net external migration estimate of 71,507 obtained for the combined-race model.

 

 

Base-Year Population by Region (County)

 

CPAZ80 presents the Hispanic population of each county, by Hispanic status (Table 16, "Total Persons and Spanish Origin Persons by Type of Spanish Origin and Race: 1980").  The data are presented in the table which follows:

 

                       Population by Hispanic Status (1980)

     County          Hispanic   Other (NonHispanic)   Total

 

     Apache           1,983          50,125          52,108

     Cochise         22,846          62,840          85,686

     Coconino         7,315          67,693          75,008

     Gila             7,723          29,357          37,080

     Graham           5,457          17,405          22,862

     Greenlee         5,446           5,960          11,406

     Maricopa       199,003       1,310,049       1,509,052

     Mohave           2,148          53,717          55,865

     Navajo           4,538          63,091          67,629

     Pima           111,418         420,025         531,443

     Pinal           26,752          64,166          90,918

     Santa Cruz      15,229           5,230          20,459

     Yavapai          4,205          63,940          68,145

     Yuma            26,638          63,916          90,554

     Total          440,701       2,277,514       2,718,215

 

Regional Populations Ten Years Prior to Base Year

 

As mentioned earlier, county-by-race data were not collected until the 1980 Census, and so such data are not available for the year (1970) ten years prior to the base year of this example.  We shall estimate the 1970 county populations by race by apportioning the 1970 population of each county between the races in the same proportion as existed in 1980.  The result of this procedure is shown in the following table.  The populations under the column labeled "Total" are known (not estimated).  The other two populations in each row are estimated.  This is a rough estimate, since the fertility rates for Hispanics and nonHispanics are believed to be substantially different.  A more elaborate procedure could be used to obtain better estimates, but these estimates are quite adequate for illustration purposes.

 

          Population by Hispanic Status (Estimated, 1970)

     County          Hispanic   Other (NonHispanic)   Total

 

     Apache           1,229           31,069          32,298

     Cochise         16,507           45,403          61,910

     Coconino         4,713           43,613          48,326

     Gila             6,093           23,162          29,255

     Graham           3,957           12,621          16,578

     Greenlee         4,932            5,398          10,330

     Maricopa       127,590          839,932         967,522

     Mohave             994           24,863          25,857

     Navajo           3,202           44,513          47,715

     Pima            73,728          277,939         351,667

     Pinal           19,984           47,932          67,916

     Santa Cruz      10,396            3,570          13,966

     Yavapai          2,267           34,466          36,733

     Yuma            17,893           42,934          60,827

     Total          293,485        1,477,415       1,770,900

 

Internal Migration

 

As before, internal migration is estimated as the population change net of births and deaths and proportional allocation of external migration to the regions.  The following table presents the results of this estimation (using the formulas for the rate, n, and the amount, N).  The rate is per 1,000 people.  As noted before, there is no need to compute any of the internal migration parameter estimates (table entries) by hand, since the CHECK program computes them and displays them.

 

                 Internal Migration Amounts and Rates

                     Hispanic     NonHispanic

     County       Amount   Rate  Amount    Rate

 

     Apache         10.    6.697   151.    3.852

     Cochise      -145.   -7.581  -486.   -9.138

     Coconino       18.    3.079    31.     .579

     Gila         -107.  -15.731  -431.  -16.613

     Graham        -36.   -7.913  -139.   -9.445

     Greenlee     -147.  -28.458  -160.  -28.348

     Maricopa      555.    3.535  1035.     .991

     Mohave         49.   34.036  1045.   28.402

     Navajo        -20.   -5.378  -375.   -7.120

     Pima           53.     .593  -573.   -1.684

     Pinal        -244.  -10.672  -660.  -11.968

     Santa Cruz    -29.   -2.304   -19.   -4.317

     Yavapai        60.   19.723   734.   15.632

     Yuma          -17.    -.801  -154.   -2.955

     Total           0               0

 

As usual, the rate is used if it is negative and the amount is used if it is positive.

 

This completes the data specification for the construction of the file AZ80HC.DAT.

 

 

C.  Results of CHECK Run

 

The output of a CHECK run of the file AZ80HC.DAT is shown in Listing 9.  The printout reveals no errors in the data entry.

The run shows that the manual computations of the Total Fertility Rates (3.190 and 1.895) were correct.

 

 

D.  Results of PROJ Run

 

Listing 10 illustrates a run of the PROJ program, which projects the population two five-year periods out, from the base year of 1980 to the year of 1990.  Since the input population data are disaggregated by age, sex, race, and region, the projections may be also.  The total projected population for 1990 is 3,702,132, which corresponds to the actual value for 1990 of 3,665,000 (SA92, Table No. 25, "Resident Population -- States: 1970 to 1991").  This is an error of approximately 1%.

 

Note that the 1990 total-population projection of this model differs slightly from the 1990 total-population projection of the single-race model for Arizona presented earlier (3,694,625).  It is not quite as accurate, probably a result of the difficulty in estimating net migration by race.

 

The projections for 1990 by race are 647,662 for Hispanics and 3,054,470 for nonHispanics.  These may be compared to the actual 1990 figures available from the 1990 Census (1990 Census of Population, General Population Characteristics, United States, 1990 CP-1-1, issued November, 1992, US Department of Commerce, Bureau of the Census, Washington, DC (henceforth referred to as CP90), Table 262, "Age and Sex by Race and Hispanic Origin: 1990"): 3,665,228 total, 688,388 for Hispanics, and (by subtraction) 2,976,840 for nonHispanics.  The errors in these race-by-race projections are -5.9% for Hispanics and 2.6% for others.  These results are displayed in the following table.

 

                        1990 Projected  1990 Actual  Percentage

       Ethnic Group       Population    Population     Error

 

       Hispanic              647,662       688,388     -5.9

       Other (nonHisp.)    3,054,470     2,976,840      2.6

       Total               3,702,132     3,665,228      1.0

 

The projections for 1990 by county and Hispanic status may be compared to the 1990 actual values, available from the County and City Data Book, 1994, US Department of Commerce, Bureau of the Census, Washington, DC.  The following table compares the 1990 county projections and the 1990 actual values.

 

 

 

 

 

                            Hispanic Population

 

                    1990 Projected   1990 Actual  Percentage

       County         Population     Population     Error

 

       Apache             2,867         2,599       10.3

       Cochise           29,228        28,379        3.0

       Coconino          10,332         9,696        6.6

       Gila               9,098         7,486       21.5

       Graham             6,958         6,682        4.1

       Greenlee           5,633         3,456       63.0

       La Paz                 *         3,139          *

       Maricopa         281,931       345,498      -18.4

       Mohave             3,602         4,919      -26.8

       Navajo             5,936         5,652        5.0

       Pima             153,500       163,262       -6.0

       Pinal             33,174        34,062       -2.6

       Santa Cruz        20,544        23,221      -11.5

       Yavapai            6,584         6,899       -4.6

       Yuma              36,480        43,388      -21.6*

       Total            647,662       668,338       -5.9

 

No projection is available for La Paz County, since that county was created in 1983, and was not included in the model.  Since that county was created from Yuma County, the sum of the 1990 actual populations for La Paz and Yuma Counties (46,527) should be compared to the projection for Yuma County (36,480).  The error in this projection is -21.6%.

 

The mean absolute deviation of the relative projection errors for the race-by-county Hispanic population projections is 14.6%.  As might be expected, the relative (percentage) error is largest for counties having small Hispanic populations.  For ten-year-out regional projections of a small minority in a state whose population is changing very rapidly, the accuracy of the projections is considered, overall, quite good.

 

                            NonHispanic Population

 

                    1990 Projected   1990 Actual  Percentage

       County         Population     Population     Error

 

       Apache            62,147        58,992        5.3

       Cochise           69,032        69,245        -.3

       Coconino          81,880        86,895       -5.8

       Gila              29,898        32,730       -8.7

       Graham            19,061        19,872       -4.1

       Greenlee           5,383         4,552       18.3

       La Paz                 *        10,705          *

       Maricopa       1,589,762     1,776,603      -10.5

       Mohave            77,062        88,578      -13.0

       Navajo            70,732        72,006       -1.8

       Pima             497,322       503,618       -1.3

       Pinal             68,501        82,317      -16.8

       Santa Cruz         6,031         6,455       -6.6

       Yavapai           85,688       100,815      -15.0

       Yuma              74,720        63,507         .7*

       Total          3,054,470     2,976,890        2.6

 

No projection is available for La Paz County, since that county was created in 1983, and was not included in the model.  Since that county was created from Yuma County, the sum of the 1990 actual populations for La Paz and Yuma Counties (74,212) should be compared to the projection for Yuma County (74,720).  The error in this projection is 2.6%.

 

The mean absolute deviation of the projection errors for the ten-year-out race-by-county projections for the nonHispanic population is 7.3%.  This level of accuracy for regional projections of a particular ethnic group is quite good.

 

Both the Hispanic and nonHispanic results show that the relative error of a ten-year-out projection can be substantial for counties having small respective populations.  As mentioned earlier, the relative projection error may be reduced by combining counties having very small populations (of a particular race).

 


XI.  Example 6: Rehabilitation Services, Projection of the Work-Disabled

 

A.  Projection Objectives; Model Structural Parameters

 

This chapter illustrates a typical use of the DESTINY program -- the estimation of a target population, based on available incidence or prevalence data.  This example illustrates the application of the technique of "synthetic estimation," by which national incidence/prevalence rates by demographic category are used to construct state estimates.  This procedure assumes, of course, that the national rates do in fact apply to the state.

 

In order to use the DESTINY system, it is necessary to enter data on the incidences or prevalences of conditions of interest.  In some cases, such data are available directly from published sources, but in many cases the available data are not in the exact form required for input to the program, and some additional processing or assumptions are required to obtain data in the exact form needed.  The examples presented in this and the following chapters will illustrate in detail the way in which the required data may be obtained from available data.

 

Service-system data may be specified to the program in varying levels of detail, ranging from values (means or proportions) for the entire population to rates by age, sex, race, and region.  The level of detail used for the data entry should match, whenever possible, the level of detail desired for the output.  For example, if it is desired to make projections of the number of persons with a work disability by age, then the prevalence of persons with a work disability should, if possible, be specified by age.  If it is desired to make projections by race, then the prevalences should be specified by race (unless it can be shown or safely assumed that the prevalences do not vary much by race).

 

The example of this and the next several chapters will illustrate the use of the DESTINY system to project the number of persons with having various conditions for the state of Arizona, and the services, resources, and costs associated with these "target" populations.  These examples will use the three-race, 14-region population data base (parameter file) that was presented earlier.  The PARAM program is used to derive the data base for these examples from the AZ803C.DAT data base presented earlier.  When the program requests

 

ENTER NAME OF OLD PARAMETER FILE (12X):

 

the user enters AZ803C.DAT, and when the program requests

 

ENTER NAME OF NEW PARAMETER FILE (12X):

the user enters, for example, AZ803CD.DAT ("D" for "work disabled").

 

From this point on, the program prints out sections of the AZ803C.DAT parameter file, requesting the user to accept the original values or to modify them.

 

The first change to the data base is to change the value of the Input Option parameter P7 to reflect the fact that a "service system" will be included in the model:

 

P7: Service System Option = 1 (i.e., service system parameters are included in the model)

 

The program prints out all of the input option parameters, and requests:

 

ENTER 1 TO CHANGE PRECEDING PARAMETERS, 0 TO LEAVE AS IS:

 

The user enters a 1 and reenters the values as before, except for the Service System Option parameter, for which the value is changed from a 0 to a 1.  From this point on, the user accepts all of the original file parameters, since the demographic specification is exactly as before.  When the demographic-parameter section of the program is finished, the program requests entry of the target-population and/or service-system parameters.

 

As discussed earlier, service system data include data on target populations, service populations, services, resources, and costs.  The example of the present chapter will include just target population data, but the examples of later chapters will include more elaborate service-system specifications.

 

In some cases, service-system data may be available for the same political unit of the population data base (in these examples, Arizona).  In many cases, however, it will be necessary to use national-level data as a proxy for the state data.

 

The present example will estimate the numbers of persons with work disabilities.  There are two target populations: persons with severe work disabilities and persons with partial work disabilities.  The target population and service-system parameter values to be specified to the PARAM program are as follows:

 

No. of target populations = 2 (i.e, severely work-disabled and partially work-disabled)

Service Population Option = 0 (i.e., no service-system data will be included in the model)

Names of target populations: WRKDISSV, WRKDISPT .

 

 

B.  Data

 

Information about work disabilities is presented in SA81, Table 555, "Persons with Work Disability, by Selected Characteristics: 1978."  A portion of this table is presented below.  In this example, it is assumed that the national data on the prevalence of work disabilities may be used as a proxy for the state prevalences.

 

                       Persons with Work Disability (percent)

      Characteristic            Severely    Partially

 

     18-24 years old              2.2          4.0

     25-34 years old              3.0          7.2

     35-44 years old              6.5          8.5

     45-54 years old             11.3         12.8

     55-64 years old             24.9         12.1

 

There are two problems with the available data, from the point of view of data entry to the DESTINY system.  First, the data are relative to the civilian noninstitutionalized population and members of Armed Forces living off post or with their families on post.  The population included in the three-race, 14-region AZ803C.DAT data base are resident population.  The total resident population of the US in 1980 was 226,505,000, and the total civilian noninstitutionalized population was 220,208,000 (227,020,000 total population (Table 30 SA81) less 2,051,000 military population (Table 602 SA81) less 5,786,000 population in institutions and other group quarters (1970 est., Table 77 SA81) + 1,025,000 in military barracks already subtracted (Table 77 SA81) = = .  Since the population data in the data base are resident population, all incidences and prevalences must be expressed relative to that population.  The percentages presented in the above table will be converted to percentages of the resident population by multiplying by the factor 220,208,000/226,505,000 = .972199.  Multiplying by this factor produces the following table.  (Had data on the civilian noninsitutionalized population of Arizona in 1980 been available, this adjustment factor would have been obtained from the state, rather than the national, populations.)

 

                       Persons with Work Disability (percent)

      Characteristic            Severely    Partially

 

     18-24 years old              2.1          3.9

     25-34 years old              2.9          7.0

     35-44 years old              6.3          8.3

     45-54 years old             11.0         12.4

     55-64 years old             24.2         11.8

 

The second problem with the available data is that they do not match the five-year age categories of the DESTINY program (0-4, 5-9, 10-14, 15-19, 20-24, etc.).  The rates for the desired age categories are obtained by assuming the rate specified in the preceding table for each individual age category, and averaging.  For example, the severely-disabled rate for the age category 15-19 is estimated as:

 

(0 (for age 15) + 0 (for age 16) + 0 (for age 17)

          + 2.1 (for age 18) + 2.1 (for age 19))/5

 

    = .84 .

 

Applying this process produces the following table, which includes prevalences for all of the age categories used by the DESTINY program.  Values of zero are used for ages below 14 and above 65.  In this table, the percentages have been converted to fractions, since it is fractional rates, not percentage rates, that are entered into the PARAM program.

 

                       Persons with Work Disability (percent)

      Age                     Severely    Partially

 

      0-4                       0            0

      5-9                       0            0

     10-14                      0            0

     15-19                     .0084        .0156

     20-24                     .021         .039

     25-29                     .029         .070

     30-34                     .029         .070

     35-39                     .063         .083

     40-44                     .063         .083

     45-49                     .110         .124

     50-54                     .110         .124

     55-59                     .242         .118

     60-64                     .242         .118

     65-69                      0            0

     70-74                      0            0

     75+                        0            0

 

Although the prevalence data are now available by the age categories used by the DESTINY system, they cannot be entered in the same format as above.  As discussed, the PARAM program accepts at most nine different incidence or prevalence values (per condition).  Up to nine values are specified, and the index of one of these values is specified for each cell of a stratification table.

 

In the present case, the data are available by age category, so the age stratification table is used.  The program presents the following prompt:

 

THE FOLLOWING TYPES OF STRATIFICATION ARE AVAILABLE:

1: NONE

2: AGE

3: SEX

4: RACE

5: AGE X SEX

6: AGE X RACE

7: SEX X RACE

8: AGE X SEX X RACE

9: REGION

10: REGION X RACE

ENTER TYPE OF STRATIFICATION (1-10): ,

 

to which the user enters a 2 (for stratification by age).  The program then requests:

 

ENTER 9 INCIDENCE/PREVALENCE RATE(S) (8X.XXXXXXXX): .

 

For the partial disability condition, there are seven different values entered in the preceding table -- 0, .0084, .021, .029, .063, .110, and .242.  A total of nine different values must be entered, so the user responds:

 

0., .0084, .021, .029, .063, .110, .242, 0., 0. .

 

Next, it is necessary to specify which of these seven stratum values is used by each of the 17 age categories.  This is done by specifying the stratum index for each of the 17 age categories.  These are as follows:

 

          Age         Stratum Index

 

          0-4             1 (corresponding to the value 0)

          5-9             1

         10-14            1

         15-19            2 (corresponding to the value .0084)

         20-24            3 (i.e., the value .021)

         25-29            4 (i.e., the value .029)

         30-34            4 (i.e., the value .029)

         35-39            5 (i.e., the value .063)

         40-44            5 (i.e., the value .063)

         45-49            6 (i.e., the value .110)

         50-54            6

         55-59            7

         60-64            7

         65-70            1

         70-74            1

         75+              1

 

The program requests:

 

ENTER 16 INDICES (1 FOR EACH AGE COHORT) EACH OF VALUE 1-9

 (16X): .

 

to which the user responds:

 

1112344556677111 .

 

Similarly, for the partial work disability, the user specifies the stratification type as 2, the nine incidence/prevalence rates as 0, .0156, .039, .070, .083, .124, .118, 0., 0., and the nine stratification indices as 1112344556677111.

 

The forms of Appendix B may be used to record the stratification values and indices, prior to data entry.

 

The CHECK program may be run to display or print the entered service-system data, so that it may be reviewed for correctness.  Listing 11 presents the CHECK run for this example.

 

 

C.  Projection Results

 

Listing 12 presents a projection of the work-disabled population to the year 1990.  The projection is disaggregated by age.  The base-year work-disabled population is also printed out.

 

In the printout, the acronym WRKDISSV stands for "Severely Work-Disabled," and the acronym WRKDISPT stands for "Partially Work-Disabled."

 


XII. Example 7: Education, Projection of School Enrollment

 

A.  Projection Objectives; Model Structural Parameters

 

This example is similar to the previous one, since it deals with the estimation of a specific target population -- in this case, those enrolled in schools.  This example carries the estimation process a little further, in also estimating the number of elementary and secondary school teachers.  The number of teachers is estimated for 0-18 year olds, assuming a student/teacher ratio of 20.  The total salary cost of the teachers is also estimated, assuming an average salary of $17,200 per year.

 

As in the previous example, the PARAM program is executed to develop a new parameter file from the AZ803C.DAT population data file.  The new file is called AZ803CE.DAT ("E" for education).  The Input Option parameter values are the same as in the previous example, i.e., Service-System Option = 1.

 

The target population in this example is all students, and the served population is all students in elementary and secondary schools.  The service is teaching, the resource is teachers, and the cost is the dollar cost of the teachers' salaries.

 

The target population and service-system parameter values to be specified to the PARAM program are as follows:

 

No. of target populations = 1 (i.e, school students)

Service Population Option = 2 (i.e., service-system data will be included in the model, and the service population is taken to be some subset of the target population)

No. of services = 1 (teaching)

No. of resources = 1 (teachers)

No. of cost categories = 1 (salaries)

 

The names entered for the various model variables are as follows:

 

Name of target population: STUDENTS

 

Name of service population: ELEM/SEC

 

Name of service: TEACHING

 

Name of resource: TEACHERS

 

Name of cost category: SALARIES .

 

The amount service provided to each served person is one "unit" of teaching.  As mentioned, the projection will be done assuming a student/teacher ratio of 20, so that the amount of resources (teachers) expended per student served is .05.  For the projection, an average teacher salary of $17,200 will be assumed.

 

The preceding data are entered in response to the various program requests.  At this point, the structure of the target population and service system has been specified.  What remains is to specify the incidence/prevalence data for the target population and the service ratios that specify what proportion of the target population is served.

 

 

B.  Data

 

Table No. 225 of SA81, "School Enrollment and Rate, by Age, Sex, and Race: 1960 to 1980," provides data on the proportions of the noninstitutional civilian population that are enrolled in school.  It is assumed that the state enrollment rates are similar to the national rates.  The enrollment rates do not vary much by sex or race, so the prevalence of students will be specified only by age.  The following table, which is extracted from the previous table, presents enrollment rates by age for 1980.  As was done in the preceding example, the rates are adjusted by the factor .972199 to convert to the rates to proportions of the resident population.

 

                               Enrollment Rate

               Age     Noninst Civ Pop Base   Res Pop Base

 

3-4               .367              .357

5-6               .957              .930

7-13              .993              .965

14-15       .982              .955

16-17       .890              .865

18-19       .464              .451

20-21       .310              .301

22-24       .163              .158

25-29       .093              .090

30-34       .064              .062

 

The age categories used in this table do not correspond to the age categories used in the DESTINY model.  The estimates for the DESTINY age categories will be estimated by the same procedure used in the preceding example, viz., by assuming the rates specified in the preceding table for individual years and averaging over five-year intervals.  For example, the rate for the 0-4 age category is:

 

( 0 (for age 0) + 0 (for age 1) + 0 (for age 2)

 + .357 (for age 3) + .357 (for age 4) )/5 = .143 .

 

Application of this procedure results in the following table:

           Age    Enrollment Rate

 

           0-4         .143

           5-9         .952

          10-14        .963

          15-19        .717

          20-24        .215

          25-29        .090

          30-34        .062

          35-39        0

          40-44        0

          45-49        0

          50-54        0

          55-59        0

          60-64        0

          65-69        0

          70-75        0

          75+          0

 

These prevalences are stratified by age, and so, as in the preceding example, they will be specified to the model using stratification by age.  The nine stratum values are .143, .953, .965, .717, .216, .090, .060, 0.0, and 0.0, and the 16 stratum indices are 1234567888888888.

 

The next items to be specified are the service ratios -- the proportion of the target population that is served, by age category.  In this example we are interested in the students in elementary and secondary schools.  It will be assumed that these are all of the students aged 0-18.  Under this assumption the service ratios are 1.0 for the first three age categories, .874 for the fourth age category, and zero for all later age categories.  The number .874 (for ages 15-19) is obtained as:

 

(.955+.865+.865+.451+0 )/(.955+.865+.865+.451+.451)

 

= .874 .

 

This computation is based on the assumption that the numbers of students in each age category (of the cohort 15-19) are identical, all students through age 18 are served, and no students aged 19 are served.

 

           Age    Service Ratio

 

           0-4         1.0 (i.e., all are served)

           5-9         1.0

          10-14        1.0

          15-19        .874

          20-24        0

          25-29        0

          30-34        0

          35-39        0

          40-44        0

          45-49        0

          50-54        0

          55-59        0

          60-64        0

          65-69        0

          70-75        0

          75+          0

 

These prevalences are stratified by age.  The nine age-stratum values are 1.0, .874, and seven zeros.  The 16 age-stratum indices are 1112333333333333.

 

Listing 13 presents the CHECK run for this example.

 

 

C. Projection Results

 

Listing 14 presents a projection of the elementary and secondary school student population by age and region.  The projection also shows the projected number of teachers and salaries by region.

 

In the printout, the acronym ELEM/SEC stands for "Elementary and Secondary School Students."  Also, in the distribution of teachers and teachers' salaries by age, "age" refers to age of students.

 


XIII.  Example 8: Criminal Justice, Projection of Prison Admissions and Operating Cost

 

A.  Projection Objectives; Model Structural Parameters

 

This example illustrates the use of DESTINY to project prison admissions and operating cost.

 

As in the previous examples, the PARAM program is executed to develop a new parameter file from the AZ803C.DAT population data file.  The new file is named AZ803CP.DAT ("P" for prison population).  The Input Option parameter values are the same as in the previous example, i.e., Service-System Option = 1.

 

The approach taken in this example will be somewhat unusual, in that the target population will be taken to be prison admissions, rather than prison inmates.  The size of the target population will hence be specified in terms of incidences (admissions per capita per year), instead of prevalences (inmate population as a proportion of the resident population).  Furthermore, the system will be used to estimate the expected cost of care until the earliest possible release date associated with the admissions of each year, rather than the annual cost of care.  The reason for this approach is that the average time served to parole eligibility is increasing, and it is desired to project the contingent liability associated with incarceration.

 

In this example, the service population will be the sentence-years associated with the admissions.  The service will be incarceration, the resource will be cells, and the cost will be operating cost per cell.  The reason for defining the service population as sentence-years rather than admissions (i.e., identical to the target population) is that sentences vary substantially by sex, but the service, resource, and cost parameters do not vary (in the DESTINY model) by the demographic features of the person served.  It is necessary to reflect dependencies on demographic characteristics either in the target population incidences/prevalences or the service population service ratios.

 

The target population and service-system parameter values to be specified to the PARAM program are as follows:

 

No. of target populations = 1 (i.e, prison admissions)

Service Population Option = 2 (i.e., service-system data will be included in the model, and the service population will be proportional to the target population)

No. of services = 1 (incarceration)

No. of resources = 1 (cell)

No. of cost categories = 1 (operating cost per cell)

 

The names entered for the various model variables are as follows:

 

Name of target population: ADMIS'NS

 

Name of service population: SENTYR

 

Name of service: INCARC'N

 

Name of resource: CELL

 

Name of cost category: OP COST .

 

The service provided to each service population unit (a sentence-year) is a one-year incarceration.  For each one-year incarceration, the resource expended is a prison cell (for one year).  For each cell, the cost will be taken as $16,000 (for one year).

 

The preceding data are entered in response to the various program requests.  At this point, the structure of the target population and service system has been specified.  What remains is to specify the incidence/prevalence data for the target population and the service ratios that specify the served population as a proportion of the target population.

 

 

B.  Data

 

The data for this example were obtained from the Arizona Department of Corrections.  The $16,000 figure cited earlier was the approximate per-inmate operating cost in 1980 (source: Arizona Department of Corrections Information Office).

 

The following data are available from Arizona Correctional Statistics, 1980.  The average time to serve to parole eligibility in 1979 was 35.8 months for men (sample size 1,338) and 27.7 months for women (sample size 741).  In 1979, the number of admissions, by age and sex, was as follows:

 

   Adult Admissions

 Age          Male    Female

 

15-19      254       25

20-24       560       25

25-29       345       28

30-34       224       17

35-39       104        8

40-44       55        4

45-49       43        4

50-54       36        2

55-59       16        1

60+               13        0

                    Total        1,652      114

 

Dividing these numbers by the Arizona resident population in each age category produces the following table of admissions rates.  (For example, 254/128,283 = .00198, and 25/123,734 = .00020.)

 

 Admission Rate

Age               Male        Female

 

15-19       .0020 .00020

20-24       .0042 .00019

25-29       .0029 .00024

30-34       .0021 .00016

35-39       .0013 .00010

40-44       .00082      .00006

45-49       .00070      .00006

50-54       .00060      .00003

55-59       .00026      .00001

60+               .00007      0

 

These data are stratified by age and sex, and so the age-by-sex stratification option will be used to enter them into the PARAM program.  At most nine stratification values are allowed. These values will be taken as 0., .002, .004, .003, .001, .0003, .00007, .0002, and .00002.  The index values are 1112342555567777 for males and 1118888777991111 for females.  Note that there are more than nine different values in the incidence table, but that a maximum of nine different stratum values is allowed.  In this case, an approximation is made, and the actual incidences are represented by nearby values.  This approximation will have little effect on the overall estimate of admissions, but projections should not be made by age and sex jointly (since individual cell incidences are not correct for some of the smaller cells).

 

Service ratios (the number of sentence-years per admission) will be computed from the average number of months to parole eligibility.  For men, this average is 35.8, corresponding to 3.0 years.  For females, the average is 27.7, corresponding to 2.3 years.  These service ratios are stratified by sex, and so the stratification-by-sex data entry option will be used.  The stratum values are 3.0 (male) and 2.3 (female).

 

Listing 15 presents the CHECK run for this example.

 

 

C.  Projection Results

 

Listing 16 presents a projection of admissions and obligated cost associated with the admissions.  Recall that the term "cost" in this example is the total sentence-long operating cost associated with (obligated by) the admissions of a particular year, not just the expense during that year.  (To estimate the expense for particular years, the model should be respecified with inmates as the target population and service population, instead of admissions as the target population and sentence-years as the service population.)

 

In the printout, the acronym ADMIS'NS denotes "admissions," SENTYR denotes "sentence-years," CELL denotes "prison cell," and OP COST denotes the cost of care for inmates (exclusive of capital costs).

 

In an actual policy analysis, a number of runs similar to the example would be required.  For example, to determine the effect of sentencing only violent criminals to prison, and at different sentence lengths from current practice, a run would be required which included not just one but several inmate ("target") populations, each representing a different level of violence and past behavior.

 


XIV.  Example 9: Health Care, Projection of the Need for Short-term and Long-term Beds

 

A.  Projection Objectives; Model Structural Parameters

 

This example illustrates the projection (by year) of bed needs for short-term care (less than 30 days) and for long-term care (30 days or more).  This example illustrates the application of DESTINY to estimate four different target populations simultaneously.

 

The PARAM program is run to construct a new parameter file from the AZ803C.DAT file.  The new file is called AZ803CH.DAT ("H" for health). In this example, there will be four target populations but no service population.  The four target populations are short-term-stay hospital beds, nursing-home beds, psychiatric-hospital beds, and mental-hospital beds.

 

The target population and service-system parameter values to be specified to the PARAM program are as follows:

 

No. of target populations = 4 (i.e, four bed types)

Service Population Option = 0 (i.e., no service-system data will be included in the model)

 

The names entered for the various model variables are as follows:

 

Names of target population: ST BEDS, NH BEDS, PSY BEDS, and MH BEDS

 

The preceding data are entered in response to the various program requests.  The incidence/prevalence data for the target populations will now be specified.

 

 

B.  Data

 

The need for beds will be measured by applying the national number of short-term-stay beds per 100,000 population to the Arizona population, and applying the national proportions of the population in long-term-care institutions to the Arizona population.

 

Data on short-term-stay beds are found in Table 179 of SA81, "Hospital Utilization Rates, by Sex and Age of Patient: 1965 to 1979."  The rates are relative to the total civilian noninstitutional population; as before, they are converted to the resident population base by multiplying by .972199

 

                           Beds/100,000

             Age   Civ noninst pop    Res pop

          Under 1       360             350.0

            1-4          93              90.4

            5-14         58              56.4

           15-24        180             175.0

           25-34        249             242.1

           35-44        262             254.7

           45-64        440             427.8

           65+        1,146           1,114.1

 

The rate for the 0-4 age category is estimated as .2(350) + .8(90.4) = 142.3.  Using the stratification-by-age option for data entry, the nine age stratum values are (dividing by 100,000) .00142, .00056, .00175, .00242, .00255, .00428, .01114, 0. and 0., and the 16 stratification indices are 1223344556666777.

 

Data for long-term-stay beds are found in Table 182 SA81, "Long-Term Care Institutions -- Summary: 1976," a portion of which is shown below:

 

                       Number of Residents (US, 1976)

        Age    Nursing Home  Psychiatric  Mentally Handicapped

 

        0-17       9,000        28,000           56,000

       18-64     154,000        32,000          125,000

       65+       989,000         5,000            6,000

 

Additional data for nursing homes are found in Table 184 SA81, "Nursing and Personal Care Homes -- Selected Characteristics of Homes and Residents, and Primary Sources of Payment: 1964-1977," a portion of which is shown below (excluding personal care homes without nursing):

 

                   Number of Residents (US, 1973-74)

           Age         Male       Female

 

         Under 65     52,000      62,000

          65-74       65,000      98,000

          75-84      102,000     283,000

          85+         98,000     315,000

 

From Table 30 SA81, the total population in the various age categories of the preceding tables may be determined.  The proportion male is taken from the Coale-Demeny model life table for the US for life expectancy 74 years.  The 1974 and 1976 populations are obtained by multiplying the 1980 populations by the ratios of the 1974 and 1976 populations (213,342,000 and 217,563,000, from Table 8 SA81) to the 1980 population (226,505,000).  The populations of the table are in millions.  The vertical bars above and below the entry 24.49 indicates that that value includes the populations for the preceding and following age categories.

                Total                     Est 1974

                 1980  Prop               Res Pop      Est 1976

          Age     Pop  Male  Male Female  Male Female   Res Pop

 

         0-17    63.7  .508   32.4  31.3  30.52 29.48   61.18

        18-64   137.7  .49    67.5  70.2  63.58 66.12  132.26

        65-69     8.8  .43     3.78  5.02  3.56  4.73    |

        70-74     6.8  .41     2.79  4.01  2.63  3.78   24.49

        75+       9.9  .34     3.37  6.53  3.17  6.15    |

                226.9             226.9      213.72    217.94

 

 

Dividing the populations into the numbers of residents produces the following results.

 

          Proportion of Population in Indicated Facility, 1976

               Nursing                 Mentally

     Age        Home    Psychiatric   Handicapped

 

     0-17      .00015      .00046      .00092

     18-64     .00117      .00024      .00095

     65+       .0404       .00020      .00024

 

         Proportion of Population in Nursing Homes, 1974

        Age        Male      Female

 

       0-64       .00055     .00065

      65-74       .0105      .0115

      75+         .063       .097

 

Combining the preceding results for nursing homes produces the following table:

 

      Proportion of Population in Nursing Homes, 1974 and 1976

        Age        Male      Female

 

       0-17      .00015     .00015

      18-64      .0012      .0012

      65-74      .011       .012

      75+        .063       .097

 

Residents of nursing homes, psychiatric, and mentally handicapped facilities will be used as a proxy for beds.

 

The prevalence data for nursing home beds are stratified by age and sex, and so they will be entered using the corresponding option.  The nine stratum values are .00015, .0012, .011, .063, .00015, .0012, .012, .097, and 0.  The 16 stratification indices for males are 1111222222222334, and the indices for females are 1111222222222556.

 

The prevalence data for psychiatric facility beds are stratified by age.  The nine stratification values are .00046, .00024, .00020, and six zeros.  The stratification indices are 1111222222222333.

 

The prevalence data for mentally handicapped facilities are also stratified by age.  The stratification values are .00092, .00095, .00024, and six zeros.  The stratification indices are 1111222222222333.

 

Listing 17 presents the CHECK run for this example.

 

 

C.  Projection Results

 

Listing 18 presents a projection of the need for the four types of beds by year to 1990.

 

In the printout, ST BEDS refers to beds in short-stay hospitals, and the acronyms NH BEDS, PSY BEDS, and NH BEDS refer to beds in long-term care facilities (nursing homes, psychiatric facilities, and facilities for the mentally handicapped, respectively).

 


XV.  Example 10: Social Services, Projection of Counselors and Budget Needed to Provide Social Services to the Elderly Population

 

A.  Projection Objectives; Model Structural Parameters

 

This example illustrates the use of the DESTINY program to project service levels, personnel, and budget levels required to provide social services to the elderly.  The data used in this example are hypothetical.  In a real application, the service ratios would be estimated from client caseload data, and the unit of service, unit of resource, and unit cost data would be estimated from program administrative records.

 

This example will build on the three-race, 14-region population data file for Arizona, AZ803C.DAT.  The PARAM program is run to construct a new parameter file from the AZ803C.DAT file.  The new file is called AZ803CS.DAT ("S" for social services).  In this example, there will a single target population (the elderly) and a single service population (a subset of the target population), seven services, three resources, and three cost categories.  The seven services are counseling, chore services, homemaker services, substitute care, day care, transportation, and other.  The three resources are counselors, purchased services, and payments.  The three cost categories are direct services, purchased services, and payments.

 

The target population and service-system parameter values to be specified to the PARAM program are as follows:

 

No. of target populations = 1 (i.e, the elderly)

Service Population Option = 2 (i.e., service-system data will be included in the model, and the service population will be proportional to the target population)

No. of services = 7

No. of resources = 3

No. of cost categories = 3

 

The names entered for the various model variables are as follows:

 

Names of target population: ELDERLY

 

Name of service population: ELDR(SV)

 

Names of services: COUNSLNG, CHORE SV, HOMEMAKR, SUBSCARE, DAY CARE, TRANSPRT, OTHER

 

Names of resources: COUNSELR, PURCHSVC, PAYMENTS

 

Names of cost categories: DIRCTSV$, PURCHSV$, PAYMENT$ .

 

 

B.  Data

 

The preceding data are entered in response to the various program requests.  The incidence/prevalence data for the target population will now be specified.  As mentioned, hypothetical data will be used for this example.  This example assumes that approximately five percent of the elderly population requires social services (specifically, 3% of those aged 65-69, 5% of those aged 70-74,and 7% of those aged 75+).

 

Target Population Parameters

 

In the present example, the target population is all persons aged 65 or older.  The prevalence of the target population in the general population is hence to be specified in terms of age categories.  The data are hence entered into the program by selecting stratification option number 2 (ST2), in which a separate rate is specified for each five-year age category.  Under this option, the user may enter up to nine different prevalences.  In the present example, however, only two are needed:  the prevalence is 0.00 (0%) for all persons whose age is less than 65, and 1.00 (100%) of those whose age is 65 or over.

 

The following table indicates the nine prevalences entered to the PARAM program (only the first two are of concern in this example:

 

                   Index          Rate

 

                     1            0.00

                     2            1.00

                     3            0.00

                     4            0.00

                     5            0.00

                     6            0.00

                     7            0.00

                     8            0.00

                     9            0.00

 

Next needs to be specified which of the preceding rates applies to each of the sixteen age categories.  The first rate (0.00, Index = 1) applies to the first 13 age categories (ages 0 - 64), and the second rate (1.00, Index - 2) applies to the last three age categories (ages 65+.)  The list of indexes to be entered is hence as follows:

 

               Stratum (Age Category)   Index

 

                        0-4               1

                        5-9               1

                       10-14              1

                       15-19              1

                       20-24              1

                       25-29              1

                       30-34              1

                       35-39              1

                       40-44              1

                       45-49              1

                       50-54              1

                       55-59              1

                       60-64              1

                       65-69              2

                       70-74              2

                       75+                2

 

Service Population Parameters

 

The service population is assumed to be 3% of the target population aged 65-69, 5% of the target population aged 70-74, and 7% of the target population aged 75+.  Once again, since these prevalences depend only on age, stratification option ST2 is used.  There are four rates of interest: 0.00 (0%), .03 (3%), .05 (5%), and .07 (7%).

 

The following table indicates the nine prevalences entered to the PARAM program (only the first four of which are of interest in this example.):

 

                 Index                Rate

 

                   1                  0.00

                   2                  0.03

                   3                  0.05

                   4                  0.07

                   5                  0.00

                   6                  0.00

                   7                  0.00

                   8                  0.00

                   9                  0.00

 

The four prevalences apply to the last four age categories, in order.  The list of indexes to be entered to the program:

 

          Stratum (Age Category)      Index

 

                  0-4                   1

                  5-9                   1

                 10-14                  1

                 15-19                  1

                 20-24                  1

                 25-29                  1

                 30-34                  1

                 35-39                  1

                 40-44                  1

                 45-49                  1

                 50-54                  1

                 55-59                  1

                 60-64                  1

                 65-69                  2

                 70-74                  3

                 75+                    4

 

Service Parameters

 

The following table indicates the average number of units of service of each type provided to each served client per year:

 

     Average Number of Service Units Per Case Per Year

 

                              No. of Service Units

       Service                 per Case per Year

 

S1.  Counseling               2 hours

S2.  Chore Services               16 dollars

S3.  Homemaker Services    750 dollars

S4.  Substitute Care        12 dollars

S5.  Day Care                       7 dollars

S6.  Transportation               10 dollars

S7.  Other                  10 dollars

 

 

In this example, counseling is the only "direct" service, i.e., service provided by the state social service staff.  All of the other services are purchased from "service providers," and the unit of service is taken to be equal to one dollar.

 

Resource Parameters

 

The average number of service units per served client is as specified in the following table:

 

 

      Average Number of Resource Units Per Service Unit

      (Service types as defined in the preceding table)

 

                              No. of Resource Units per

                            Service Unit (by Service Type)

Resource                 S1  S2  S3  S4  S5  S6  S7

 

R1.  Counselor                1    0   0   0   0   0 0

R2.  Dollar (Purchase)  0    1   1   1   1  .5  .5

R3.  Dollar (Payment)   0   0   0   0   0  .5  .5

 

 

In this example, half of the TRANSPRT service (S6) is a payment to the client, and half is a payment to the service provider.  The same is true of the OTHER service.

 

Cost Parameters

 

It is assumed that the cost of counselor service is $15 per hour.  Since the other services are in fact dollars, their cost is $1 per dollar.  The following table summarizes these costs:

 

 

               Average Cost Per Resource Unit

      (Resource types as defined in the preceding table)

 

                             Cost per Resource Unit

                               (by resource type)

Cost Category           R1     R2     R3

 

C1.  Direct Service              15      0      0

C2.  Purchased Service      0      1      0

C3.  Payment                 0      0      1

 

 

Listing 19 presents the CHECK run for this example.

 

 

C. Projection Results

 

Listing 20 presents a projection of the social services served population, services, resources, and costs.  In this example we show a three-year-ahead projection, as opposed to the ten-year-ahead projections that were illustrated in the other examples.

 

The printout shows the services, resources, and budget required to provide services to the served population.

 

The DESTINY program could be used to estimate the changes in the budget that would occur if different service levels or different service costs were adopted.  Used in this way, DESTINY is an ideal tool in the evaluation of alternative strategies for rationing social services.

 

The example illustrates several of the different types of crosstabulations that can be constructed by the DESTINY program.  The total number of possible crosstabs is very large, and typically only a few of them would be selected by the user for printout.  Up to nine demographic distributions or crosstabs may be constructed for each of the many variables forecast by the program (general population, target population (the elderly), seven social services, three resources, and three cost categories).  These include crosstabs by age, sex, race, age by sex, age by race, sex by race, age by sex by race, region, and race by region.  In addition, nine different service-system-related distributions or crosstabs may be specified:

o  distribution of services by type

o  distribution of resources by type

o  distribution of costs by type

o  distribution of services by served population

o  distribution of resources by served population

o  distribution of cost by served population

o  distribution of resources by services

o  distribution of costs by services

o  distribution of costs by resources

 

In this example, we present only a small fraction of the possible output tables.

 

Data such as these may be used to back up legislative budget requests, to prepare Comprehensive Annual Services Program plans, or to estimate staffing levels.  Additional runs could reveal the budgetary impact of changes in service levels or costs.

 


        References

 

1. DESTINY Planning and Forecasting System: Description of Capabilities, Joseph George Caldwell, 503 Chastine Drive, Spartanburg, SC 29301 USA 1995

 


Appendix A.  Data Sources, Model Parameterization and Model Calibration

 

There are two types of information required by the PARAM program, in order to construct a parameter file for use by the DESTINY package -- demographic information and service-system information.  The demographic information consists of a number of demographic parameters, such as birth and death rates, and some demographic variables, such as population totals by age, sex, race, and geographic region.  The service-system information consists of incidences or prevalences for target populations of interest, service ratios, and various service, resource, and cost parameters.

 

Demographic Specification

 

The demographic data (parameters and variables) required by the DESTINY program are very basic quantities, and most of them are available at the national and state levels.  For the United States, the publications which are of greatest value in obtaining these data are the following:

 

1.  Statistical Abstract of the United States (annual) (various years)

 

2.  Vital Statistics of the United States (annual), Volume I, Natality and Volume II, Mortality, Part A

 

3.  Census of Population (decennial)

 

At the state level, major data source is the County and City Data Book supplement to the Statistical Abstract; it is published in various years.  Each state publishes state-level versions of the statistical abstract and vital statistics reports; the 1980 Census data are available at the state level as well.

 

The Census of Population presents detailed population breakdowns by age, sex, race, and geographic region.  The Vital Statistics and Statistical Abstract present demographic parameters such as birth and death rates.

 

Most countries other than the US have publications similar to those cited above, at least for the national level.  For some developing nations, however, even basic demographic parameters such as fertility rates are not available on a reliable or timely basis, and other sources must be consulted.  Such sources include:

 

     1.  World Fertility Survey

 

     2.  United Nations Demographic Handbook

The DESTINY program population projections are based on a five-year time interval, and the required parameters refer to future five-year periods.  The program makes projections corresponding to whatever demographic assumptions the user wishes to specify about the future, and the user's specified values may differ from historical values.  If historical data are used to determine these parameters, the average values over the last five years should normally be used.  If data for a recent five-year period are not available, data for the latest available year may be used.  If historical values fluctuate substantially from year to year, a several-year average would usually be preferable to an estimate based on a single year.  If a demographic parameter appears to be changing over time (e.g., a declining trend in the birth rate), the value entered to DESTINY may be based on the five-year average of values derived from a statistical time-series forecasting model.

 

Even in the US reliable information on Total Fertility Rates (TFRs) and Fertility Age Distributions (FADs) may not be available at the state level for different races.  If reliable state data are not available, national-level data may be used.  Perhaps the most critical parameter of all is the TFR, since it has a substantial impact on even the nearer-term population projections.  If state data are used for the TFR, the user should always make a CHECK run to examine the reasonableness of the state TFR.  If the ratio of the estimated base-year TFR to the user-specified TFR is quite different from unity, the user should attempt to ascertain why the population is evidently so unstable.  If no reason is apparent, it would be prudent to revise the specified TFR.

 

The user must decide whether to characterize the population survival rates by the Infant Mortality Rate (IMR) or the Expectation of Life at Birth (ELB), corresponding to Life Table Option parameter value equal to 1 or to 2, respectively.  As a general rule, use Option 1 (i.e., specify the IMR) for countries in which the IMR is high, and the ELB for countries in which the IMR is low.  For whichever option the user specifies, the CHECK program will print out the value of the non-specified parameter, according to the Coale-Demeny "West" model life table.

 

For example, suppose that the user has specified Life Table Option 1 (specify the IMR), but he is particularly interested in projections of the elderly population.  If the CHECK printout indicates that the user-specified value of the IMR implies an ELB value that is quite different from the observed value, it would be advisable to respecify the model in terms of Life Table Option 2, and enter the desired Expectation of Life at Birth.

 

 

Service-System Parameters

 

Because of the tremendous variety of target populations and service systems to which the DESTINY program may be applied, it is not possible to identify standard sources from which information pertaining to these model aspects may be obtained.  With regard to target populations, local-level data are often not available on incidences and prevalences, and national- or regional-level data, by age, sex, or race must be used.  Such data are available in published form from nationwide surveys, such as the Disability Survey of 1972 or the National Health Interview Survey.

 

With regard to service-system data, most health or social service programs are operated at the state or local level, and data on program services, resources, and costs are often available from administrative records maintained at these levels.  A major problem that may be encountered is that the DESTINY program needs these parameters on an annual basis (e.g., average number of cases per year, average number of service units per case per year), and many organizations do not collect client caseload data this way.  This situation is changing, however, as the awareness of the need to do planning based on parametric models is increasing.

 


Appendix B.  Data Entry Forms

 

This appendix includes data entry forms for use in collecting the data required by the PARAM and CHECK programs.  The data entry forms list the data in order of entry to the PARAM program.  To assist the user in remembering where each data element was obtained, space is provided to record the "source" of each element.

 

The data entry forms do not describe the meaning of the various options that are available for each input parameter.  Those descriptions are presented in the text of this user's manual.  The forms do specify, however, the format required for each data element.

 


              PARAM Form 1: Basic File Structure Parameters

 

 

Parameter File Name (12X): ________________

 

General Population Description (8OX):_________________________

 

______________________________________________________________

 

Base Year (4X):________________

 

Basic File Structure Parameters:

 

     P1: Number of Races (1-3):_____________________

 

     P2: Number of Regions (1-14):__________________

 

     P3: Demographic Parameter Option (1 or 2):_____

 

     P4: Life Table Option (1 or 2):________________

 

     P5: External Migration Parameter Option

                                (0, 1, or 2):_______

 

     P6: Internal Migration Parameter Option

                                    (0 or 1):_______

 

     P7: Service System Option (0 or 1):____________

 

Names of Races (8X):RA1__________

 

                    RA2__________

 

                    RA3__________

 

Names of Regions (8X):RE1_______________    RE8_______________

 

                      RE2_______________    RE9_______________

 

                      RE3_______________    RE10______________

 

                      RE4_______________    RE11______________

 

                      RE5_______________    RE12______________

 

                      RE6_______________    RE13______________

 

                      RE7_______________    RE14______________

 


            PARAM Form 2: Demographic Parameters and Variables

 

      for Race = __________ (one complete set needed for each race)

 

 

Total Fertility Rate(s)

 

     Source:__________________________________________________

 

If P3 = 1, specify 1 TFR (X.XXX):__________

 

If P3 = 2, specify 10 TFRs (10X.XXX), one for each 5-year projection period:

 

     ____,____,_____,_____,_____,_____,_____,_____,_____,_____

 

Fertility Age Distribution(s)

 

     Source:__________________________________________________

 

If P3 = 1, specify 1 FAD (6X.XXX):

 

     _________,_________,_________,________,________,_________

 

If P3 = 2, specify 10 FADs (6X.XXX), one for each 5-year projection period:

 

     _________,_________,_________,________,________,_________

 

     _________,_________,_________,________,________,_________ 

     _________,_________,_________,________,________,_________ 

     _________,_________,_________,________,________,_________

 

     _________,_________,_________,________,________,_________

 

     _________,_________,_________,________,________,_________ 

     _________,_________,_________,________,________,_________ 

     _________,_________,_________,________,________,_________

 

     _________,_________,_________,________,________,_________ 

     _________,_________,_________,________,________,_________

 

Infant Mortality Rate(s) (required if P4 = 1)

 

     Source:__________________________________________________

 

If P3 = 1, specify 1 IMR (XXX.XX):__________

 

If P3 = 2, specify 10 IMRs (10XXX.XX), one for each 5-year projection period:

 

     _____,_____,_____,_____,_____,_____,_____,____,____,_____

 

Expectation(s) of Life at Birth (required if P4 = 2)

 

     Source:__________________________________________________

 

If P3 = 1, specify 1 ELB (XX.XX):__________

 

If P3 = 2, specify 10 ELBs (10XX.XX), one for each 5-year projection period:

 

     _____,_____,_____,_____,_____,_____,_____,____,____,_____

 

Base-Year Population

 

     Source:__________________________________________________

 

     For Males (8XXXXXXXXX.):

 

     _____,_____,______,______,______,______,______,______(CR)

 

     _____,_____,______,______,______,______,______,______

 

     For Females (XXXXXXXXX.):

 

     _____,_____,______,______,______,______,______,______(CR)

 

     _____,_____,______,______,______,______,______,______

 

Base-Year Infant Mortality Rate (XXX.XX):____________

 

Source:__________________________________________________

 

Base-Year Birth Rate (XXX.XX):____________

 

Source:__________________________________________________

 

Base-Year Death Rate (XXX.XX):____________

 

Source:__________________________________________________

 

Population Ten Years Prior to Base Year (XXXXXXXXX.):

 

        ___________     Source:_____________________

 

Infant Mortality Rate Ten Years Prior to Base Year (XXX.XXXX):

 

        ___________     Source:_____________________

 

Birth Rate Ten Years Prior to Base Year (XXX.XXXX):

 

        ___________     Source:_____________________

 

Death Rate Ten Years Prior to Base Year (XXX.XX):

 

        ___________     Source:_____________________

 

External Migration Parameters (data required only if P5 is

 greater than zero)

 

     Source:__________________________________________________

 

     If P5 = 1:

 

         Annual Migration Rate (XXXX.XXX)__________________

 

         Annual Migration Number (XXXXXXXXX.)_____________

 

     If P5 = 2:

 

Specify ten annual migration rates (10XXXX.XXX), one for each 5-year projection period:

 

     _____,_____,_____,_____,_____,_____,_____,____,____,_____

 

Specify ten annual migration numbers (8XXXXXXXXX.), one for each 5-year projection period:

 

     _____,_____,_____,_____,_____,_____,_____,____,____,_____

 

Regional Population (data required only if P2 is greater than 1)

 

     Source:__________________________________________________

 

     ______,______,______,______,______,_______,_______,______

 

     ______,______,______,______,______,_______,_______,______

 

 

Regional Population Ten Years Prior to Base Year (data required only if P2 is greater than 1)

 

     Source:__________________________________________________

 

     ______,______,______,______,______,_______,_______,______

 

     ______,______,______,______,______,_______,_______,______

 

 

Internal Migration Parameters (Data required only if P6 is greater than zero)

 

     Source:__________________________________________________

 

Specify one annual internal migration rate for each region (8XXXX.XXX):

 

     ______,______,______,______,______,______,______,______

 

     ______,______,______,______,______,______

 

Specify one annual internal migration amount (number) for each region (8XXXXXXXXX.):

 

     ______,______,______,______,______,______,______,______

 

     ______,______,______,______,______,______

 


                 PARAM Form 3: Service-System Parameters

 

                        (Required only if P7 = 1)

 

Service-System Structural Parameters

 

     S1: Number of Target Populations (1-4):__________

 

     S2: Service Population Option (0, 1, or 2):______

 

     S3: Number of Services (0-10):___________________

 

     S4: Number of Resources (0-7):___________________

 

     S5: Number of Cost Categories (0-4):_____________

 

Names of Target Populations (8X):

 

     TP1:_______________

 

     TP2:_______________

 

     TP3:_______________

 

     TP4:_______________

 

Names of Service Populations (8X):

 

     SP1:_______________

 

     SP2:_______________

 

     SP3:_______________

 

     SP4:_______________

 

Names of Services (8X):

 

     S1:________________

 

     S2:________________

 

     S3:________________

 

     S4:________________

 

     S5:________________

 

     S6:________________

 

     S7:________________

 

     S8:________________

 

     S9:________________

 

     S10:_______________

 

Names of Resources (8X):

 

     R1:________________

 

     R2:________________

 

     R3:________________

 

     R4:________________

 

     R5:________________

 

     R6:________________

 

     R7:________________

 

Names of Cost Categories (8X):

 

     C1:________________

 

     C2:________________

 

     C3:________________

 

     C4:________________

 

     Service Parameters

 

Service Population                  Service Type

                       S1  S2  S3  S4  S5  S6  S7  S8  S9  S10

     Name        Names:___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

SP1:__________         ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

SP2:__________         ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

SP3:__________         ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

SP4:__________         ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

Note: Each table entry (XXXXX.XXXX) is entered to the program separately, reading across the first row, then the second row, etc.

 

     Resource Parameters

 

Service Type                        Resource Type

                       R1  R2  R3  R4  R5  R6  R7  R8  R9  R10

     Name        Names:___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S1:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S2:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S3:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S4:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S5:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S6:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S7:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S8:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S9:__________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

S10:_________          ___ ___ ___ ___ ___ ___ ___ ___ ___ ___

 

Note: Each table entry (XXXXX.XXXX) is entered to the program separately, reading across the first row, then the second row, etc.

 

 

     Cost Parameters

 

Resource Type

                        

     Name        Names:_________ _________ _________ _________

 

R1:__________          _________ _________ _________ _________

 

R2:__________          _________ _________ _________ _________

 

R3:__________          _________ _________ _________ _________

 

R4:__________          _________ _________ _________ _________

 

R5:__________          _________ _________ _________ _________

 

R6:__________          _________ _________ _________ _________

 

R7:__________          _________ _________ _________ _________

 


                PARAM Form 4: Target Population Parameters

 

                  for Target Population = ______________

 

(Required only if P7 = 1, in which case one form is needed for each target population.)

 

Data Source:__________________________________________

 

Stratification Option:

 

     Specify 1 Option:

 

         ___ST1  No stratification (single rate for entire

                 population)

 

         ___ST2  Stratify by Age

 

         ___ST3  Stratify by Sex

 

         ___ST4  Stratify by Race

 

         ___ST5  Stratify by Age x Sex

 

         ___ST6  Stratify by Age x Race

 

         ___ST7  Stratify by Sex x Race

 

         ___ST8  Stratify by Age x Sex x Race

 

         ___ST9  Stratify by Region

 

         ___ST10 Stratify by Region x Race

 

Enter data in the section below corresponding to the Stratification Option selected above.

 

     Option ST1: No Stratification

 

     Specify a single rate for the entire population: _________

 

     Option ST2: Stratification by Age

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

     Option ST3: Stratification by Sex

 

               Sex           Rate

 

              Male          ______

              Female        ______

 

     Option ST4: Stratification by Race

 

               Race          Rate

 

             RA1______      ______

             RA2______      ______

             RA3______      ______

 

     Option ST5: Stratification by Age x Sex

 

         Sex = Male

 

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

     Sex = Female

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

     Option ST6: Stratification by Age x Race

 

         Race = RA1__________

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

        

         Race = RA2__________

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

   

         Race = RA3__________

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

     Option ST7: Stratification by Sex x Race

 

         Race = RA1__________

 

                   Sex       Rate

 

                  Male      ______

                  Female    ______

 

         Race = RA2__________

 

                   Sex       Rate

 

                  Male      ______

                  Female    ______

 

          Race = RA3__________

 

                   Sex       Rate

 

                  Male      ______

                  Female    ______

 

     Option ST8: Stratification by Age x Sex x Race

 

         Race = RA1__________

 

         Sex = Male

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

         Sex = Female

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

         Race = RA2__________

 

         Sex = Male

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

         Sex = Female

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

         Race = RA3__________

 

         Sex = Male

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

         Sex = Female

 

         Age Category        Rate

 

              0-4           ______

              5-9           ______

             10-14          ______

             15-19          ______

             20-24          ______

             25-29          ______

             30-34          ______

             35-39          ______

             40-44          ______

             45-49          ______

             50-54          ______

             55-59          ______

             60-64          ______

             65-69          ______

             70-74          ______

             75+            ______

 

     Option ST9: Stratification by Region

 

               Region          Rate

 

            RE1_________      ______

            RE2_________      ______

            RE3_________      ______

            RE4_________      ______

            RE5_________      ______

            RE6_________      ______

            RE7_________      ______

            RE8_________      ______

            RE9_________      ______

            RE10________      ______

            RE11________      ______

            RE12________      ______

            RE13________      ______

            RE14________      ______

 

     Option ST10: Stratification by Region x Race

 

          Race = RA1___________

 

               Region          Rate

 

            RE1_________      ______

            RE2_________      ______

            RE3_________      ______

            RE4_________      ______

            RE5_________      ______

            RE6_________      ______

            RE7_________      ______

            RE8_________      ______

            RE9_________      ______

            RE10________      ______

            RE11________      ______

            RE12________      ______

            RE13________      ______

            RE14________      ______

 

          Race = RA2___________

 

               Region          Rate

 

            RE1_________      ______

            RE2_________      ______

            RE3_________      ______

            RE4_________      ______

            RE5_________      ______

            RE6_________      ______

            RE7_________      ______

            RE8_________      ______

            RE9_________      ______

            RE10________      ______

            RE11________      ______

            RE12________      ______

            RE13________      ______

            RE14________      ______

 

          Race = RA3___________

 

               Region          Rate

 

            RE1_________      ______

            RE2_________      ______

            RE3_________      ______

            RE4_________      ______

            RE5_________      ______

            RE6_________      ______

            RE7_________      ______

            RE8_________      ______

            RE9_________      ______

            RE10________      ______

            RE11________      ______

            RE12________      ______

            RE13________      ______

            RE14________      ______


               PARAM Form 5: Service Population Parameters

 

         for Service Population = __________________

 

         (Needed only if P7 = 1 and S2 = 2, in which

         case one form is needed for each service

         population.)

 

Data Source:__________________________________________________

 

Stratification Option:

 

     Specify 1 Option:

 

         ___ST1  No stratification (single rate for entire

                 population)

 

         ___ST2  Stratify by Age

 

         ___ST3  Stratify by Sex

 

         ___ST4  Stratify by Race

 

         ___ST5  Stratify by Age x Sex

 

         ___ST6  Stratify by Age x Race

 

         ___ST7  Stratify by Sex x Race

 

         ___ST8  Stratify by Age x Sex x Race

 

         ___ST9  Stratify by Region

 

         ___ST10 Stratify by Region x Race

 

Enter data in the section below corresponding to the Stratification Option selected above.

 

     Option ST1: No Stratification

 

     Specify a single rate for the entire population:_________

 


                               CHECK Form 1

 

(This form is needed only if the CHECK program is used to adjust the service-system parameters.)

 

 

                  Actual Base-Year PROJ Base-Year        Actual

Target Population       Value           Value     Ratio = PROJ

 

TP1______________    ___________     __________     _________

TP2______________

TP3______________

TP4______________

 

Service Population

 

SP1_______________

SP2_______________

SP3_______________

SP4_______________

 

     Service

 

S1________________

S2________________

S3________________

S4________________

S5________________

S6________________

S7________________

S8________________

S9________________

S10_______________

 

     Resource

 

R1________________

R2________________

R3________________

R4________________

R5________________

R6________________

R7________________

 

     Cost

 

C1________________

C2________________

C3________________

C4________________


Appendix C.  Technical Notes

 

Demographic Projection Equations

 

This Appendix presents the basic demographic equations which define the cohort-component method for making population projections.  Only a summary description of the demographic equations is presented here.  For detailed discussion of the cohort-component method, refer to a demographic text such as:

 

     Shryock, Henry S., Jacob S. Siegel and Associates,

       The Methods and Materials of Demography, Fourth

       Printing (rev.), US Bureau of the Census, US

       Government Printing Office, Washington, DC 1980

 

The formulas presented below correspond to External Migration Option 1 and Internal Migration Option 0.  In the model, the complete set of formulas is used once for each race represented in the model, with appropriate changes in the values of the parameters.

 

The following notation is introduced.  The index t refers to time.  The index k refers to five-year age cohort.  There are sixteen age cohorts, first one being ages 0-5, and the last being ages 75+.

 

     TFRt    = total fertility rate at time t (the average

               number of children born to a woman in her

               lifetime)

 

     FADt(k) = fertility age distribution density function

               (probability that a woman giving birth belongs

               to age cohort k) at time t

 

     Stj(1)  = probability at time t that an infant of sex j

               survives to age 1 (j = 1, 2)

 

     Stj(k)  = probability that a person of sex j in cohort k-1

               alive at time t survives to time t+5 (k = 2, 3,

               ..., 17; j = 1, 2)

 

     Stj*    = (Stj(k) + Stj+5(k))/2

 

     IMt     = number  of immigrants in time t to time t+5

 

     EMt     = rate of emigration in time period t to t+5

               (number of emigrants divided by the total

               population)

 

     Pt(k)   = total population in age cohort k at time t

 

     Rt(m)   = population in region m at time t

 

     BSRt    = birth sex ratio (proportion of newborns that

               are males)

 

     BIRt    = births in time period t to t+5

 

In terms of the preceding notation, the following formulas define the population at the time t+5, given the population at time t.

 

     1.  Survivors, Age Cohorts 2-15:

 

           PSt+5j(k) = Ptj(k) Stj*(k+1)     (k=2,3,...,16)

 

     2.  Survivors, Last Age Cohort:

 

           PSt+5j(16) = PSt+5j(16) Stj*(17)

 

     3.  Births

                       9

           BIRt = TFRt Σ FAD(k) (Pt2(k) + PSt+52(k))/2

                      k=4

 

     4.  Survivors, First Age Cohort

 

           PSt+5j(1) = BIRt Stj*(1)

 

     5.  Total Survivors Plus Births

 

           TS = Σ PSt+5j(k)

               j,k

 

     6.  External Migration (Option 1)

 

           Total Net Migration = TM = IMt - EMt TS

 

           F = 1 + TM/TS

 

           Pt+5j(k) = PSt+5j(k) F

 

     7.  Total Population at Time t

 

           TP = Σ Ptj(k)

               j,k

 

     8.  Internal Migration (Option 0)

 

           Rt+5(m) = Rt(m) (TS + TM)/TP

 

External Migration Options 2-4 and Internal Migration Option 1 are similar to the above.

Service-System Parameter Adjustment Equations

 

In the CHECK program, the user has the option of entering an adjustment factor, or calibration factor, for each target population, service population, service, resource, and cost total that the PROJ program computes and prints.  Each adjustment factor is the ratio of the actual (observed) base-year level of each quantity to the base-year level estimated by PROJ.

 

After the user enters the adjustment factors, the CHECK program modifies each incidence, service ratio, service, resource, and cost parameter, and creates a new parameter file containing the modified parameters.  The parameters are modified so that the base-year estimates printed by the PROJ program will each be multiplied by the adjustment factor.  The formulas which the CHECK program uses to modify the parameters are as follows:

 

     tpR'  = fRtp tpR          (R = 1,2,...,ntp)

 

     spR'  = fRsp spR1/fRtp)   (R = 1,2,...,ntp)

 

     skR'  = fks skR1/fRsp)   (k = 1,2,...,ns; R = 1,2,...,ntp)

 

     rjk'  = fjr rjk (1/fks)  (j = 1,2,...,nr; k = 1,2,...,ns)

 

     c'ij  = fic cij (1/fjr)  (i = 1,2,...,nc; j = 1,2,...,nr)

 

where

 

     tpR   = old incidence

 

     tpR'  = new incidence

 

     spR   = old service ratio

 

     spR'  = new service ratio

 

     skR   = old number of units of service type k per served

             case of type R

 

     skR'  = new number of units of service type k per served

             case of type R

 

     rjk   = old number of units of resource type j per unit

             of service type k

 

     rjk'  = new number of units of resource type j per unit

             of service type k

 

     cij   = old number of dollars of cost type i per unit of

             resource type j

     cij'  = new number of dollars of cost type i per unit of

             resource type j

 

     fRtp  = adjustment factor for target population R

 

     fRsp  = adjustment factor for service population R

 

     fks   = adjustment factor for service type k

 

     fjr   = adjustment factor for resource type j

 

     fic   = adjustment factor for cost type i

 

     ntp   = number of target populations

 

           = number of service populations

 

     ns    = number of service types

 

     nr    = number of resource types

 

     nc    = number of cost categories.

 

 


Appendix D.  Computer Program Output Listings

 

 

 


                       Computer Program Output Listings

 

1.    CHECK Run for Example 1 (National Population

            Projection, Single-Race Model)................................ 157

 

2.    PROJ Run for Example 1 (National Population

            Projection, Single-Race Model)................................ 159

 

3.    CHECK Run for Example 2 (National Population

            Projection, Two-Race Model)................................... 161

 

4.    PROJ Run for Example 2 (National Population

            Projection, Two-Race Model)................................... 165

 

5.    CHECK Run for Example 3 (State Population

            Projection, Single-Race Model)................................ 168

 

6.    PROJ Run for Example 3 (State Population

            Projection, Single-Race Model)................................ 170

 

7.    CHECK Run for Example 4 (State Population

            Projection, Three-Race, 14-Region Model)...................... 172

 

8.    PROJ Run for Example 4 (State Population

            Projection, Three-Race, 14-Region Model)...................... 180

 

9.    CHECK Run for Example 5 (Projection of the Hispanic

            Population)................................................... 182

 

10.   PROJ Run for Example 5 (Projection of the Hispanic

            Population)................................................... 188

 

11.   CHECK Run for Example 6 (Rehabilitation Services,

            Projection of the Work-Disabled).............................. 190

 

12.   PROJ Run for Example 6 (Rehabilitation Services,

            Projection of the Work-Disabled).............................. 193

 

13.   CHECK Run for Example 7 (Projection of School

            Enrollment)................................................... 195

 

14.   PROJ Run for Example 7 (Projection of School

            Enrollment)................................................... 198

 

15.   CHECK Run for Example 8 (Criminal Justice, Projection

            of Prison Admissions and Operating Cost)...................... 203

 

16.   PROJ Run for Example 8 (Criminal Justice, Projection

            of Prison Admissions and Operating Cost)...................... 206

 

17.   CHECK Run for Example 9 (Health Care, Projection of

            the Need for Short-Term and Long-Term Beds)................... 208

 

18.   PROJ Run for Example 9 (Health Care, Projection of

            the Need for Short-Term and Long-Term Beds)................... 212

 

19.   CHECK Run for Example 10 (Social Services, Projection

            of Counselors and Budget Needed to Provide

            Social Services to the Elderly Population).................... 215

 

20.   PROJ Run for Example 10 (Social Services, Projection

            of Counselors and Budget Needed to Provide

            Social Services to the Elderly Population).................... 219


Listing 1.  CHECK Run for Example 1 (National Population Projection, Single-Race Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   10:49:59

 

 NAME OF PARAMETER FILE = US801.DAT       

 GENERAL POPULATION DESCRIPTION:

 UNITED STATES RESIDENT POPULATION                                              

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 1

 NO OF REGIONS =  0

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 0

 SERVICE SYSTEM OPTION = 0

 NAME(S) OF RACE    ...

      ALL    

 

 PARAMETERS FOR RACE = ALL    

 TOTAL FERTILITY RATE(S)...

      1.810

 FERTILITY AGE DISTRIBUTION(S)...

       .147 .312 .312 .166 .052 .011

 INFANT MORTALITY RATE(S)...

       14.80

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 73.96

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9793    .9852

        0‑4       8360135.    7984272.      .9967    .9977

        5‑9       8537903.    8159231.      .9981    .9989

       10‑14      9315055.    8925864.      .9974    .9987

       15‑19     10751544.   10410123.      .9960    .9980

       20‑24     10660063.   10652494.      .9953    .9973

       25‑29      9703259.    9814413.      .9951    .9966

       30‑34      8675505.    8882452.      .9940    .9954

       35‑39      6860236.    7102772.      .9913    .9933

       40‑44      5707550.    5960689.      .9857    .9894

       45‑49      5387511.    5700872.      .9757    .9830

       50‑54      5620474.    6088510.      .9586    .9731

       55‑59      5481152.    6132902.      .9321    .9567

       60‑64      4669307.    5416404.      .8913    .9265

       65‑69      3902083.    4878761.      .8282    .8727

       70‑74      2853116.    3943626.      .7358    .7856

       75+        3547402.    6419145.      .4891    .5275

       TOTAL    110032295.  116472530.

 TOTAL BASE‑YEAR POPULATION (POPBASE) = 226504825.

 CRUDE BIRTH RATE FOR BASE YEAR =  15.90

 CRUDE DEATH RATE FOR BASE YEAR =   8.70

 INFANT MORTALITY RATE FOR BASE YEAR =  13.80

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR = 203302031.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  15.14

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   8.96

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  16.08

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

        1000075.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 1.833

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 1.810

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR =  68.18

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =   1000075.

   ESTIMATED ANNUAL RATE PER 1000 =    4.686

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =   1000075.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =   1000075.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =    4.415

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 14.573

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  9.799

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =  10.87

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =   9.62

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =   9.19

 


Listing 2.  PROJ Run for Example 1 (National Population Projection, Single-Race Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   11:39: 2

 

 PARAMETER FILE NAME: US801.DAT      

 GENERAL POPULATION DESCRIPTION:

 UNITED STATES RESIDENT POPULATION                                              

 BASE YEAR: 1980

 

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =   250026462.

 

 DISTRIBUTION OF POPULATN

  BY AGE

   0‑4      18150140.

   5‑9      18340630.

  10‑14     16961798.

  15‑19     17341700.

  20‑24     18916165.

  25‑29     21907018.

  30‑34     22038919.

  35‑39     20150596.

  40‑44     18063934.

  45‑49     14262631.

  50‑54     11763287.

  55‑59     10935458.

  60‑64     11141584.

  65‑69     10411490.

  70‑74      8156979.

  75+       11484134.

 

 DISTRIBUTION OF POPULATN

  BY SEX

 MALE      122714472.

 FEMALE    127311990.

 

 CROSSTABULATION OF POPULATN

  BY AGE AND SEX

               MALE        FEMALE 

   0‑4       9229281.    8920859.

   5‑9       9321578.    9019052.

  10‑14      8668490.    8293308.

  15‑19      8858743.    8482957.

  20‑24      9644578.    9271587.

  25‑29     11108700.   10798317.

  30‑34     11004406.   11034512.

  35‑39     10003094.   10147502.

  40‑44      8909808.    9154126.

  45‑49      6987165.    7275467.

  50‑54      5721375.    6041912.

  55‑59      5251952.    5683506.

  60‑64      5234019.    5907564.

  65‑69      4745989.    5665501.

  70‑74      3592512.    4564467.

  75+        4432781.    7051353.

 


Listing 3.  CHECK Run for Example 2 (National Population Projection, Two-Race Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:16:20

 

 NAME OF PARAMETER FILE = US802.DAT      

 GENERAL POPULATION DESCRIPTION:

 UNITED STATES RESIDENT POPULATION BY RACE (W/O)                                

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 2

 NO OF REGIONS =  0

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 0

 SERVICE SYSTEM OPTION = 0

 NAME(S) OF RACE    ...

      WHITE  

      OTHER  

 

 PARAMETERS FOR RACE = WHITE  

 TOTAL FERTILITY RATE(S)...

      1.717

 FERTILITY AGE DISTRIBUTION(S)...

       .130 .312 .326 .170 .051 .011

 INFANT MORTALITY RATE(S)...

       12.95

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 74.67

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9820    .9874

        0‑4       6482766.    6148431.      .9974    .9982

        5‑9       6684406.    6346611.      .9984    .9991

       10‑14      7407610.    7052673.      .9977    .9989

       15‑19      8631389.    8326152.      .9965    .9983

       20‑24      8680290.    8603095.      .9959    .9978

       25‑29      8004161.    7978484.      .9957    .9972

       30‑34      7298603.    7344080.      .9948    .9961

       35‑39      5830238.    5928994.      .9923    .9942

       40‑44      4849123.    4976012.      .9871    .9904

       45‑49      4638090.    4817869.      .9774    .9843

       50‑54      4918050.    5238845.      .9609    .9749

       55‑59      4852081.    5384727.      .9350    .9592

       60‑64      4172521.    4801456.      .8951    .9298

       65‑69      3481097.    4329974.      .8327    .8771

       70‑74      2551944.    3542234.      .7411    .7910

       75+        3187257.    5851527.      .4938    .5322

       TOTAL     91669626.   96671164.

 TOTAL BASE‑YEAR POPULATION (POPBASE) = 188340790.

 CRUDE BIRTH RATE FOR BASE YEAR =  14.80

 CRUDE DEATH RATE FOR BASE YEAR =   8.80

 INFANT MORTALITY RATE FOR BASE YEAR =  12.00

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR = 178098000.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  14.13

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   9.04

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  14.11

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

          94517.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 1.748

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 1.717

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR =  64.59

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =     94517.

   ESTIMATED ANNUAL RATE PER 1000 =     .518

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =     94517.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =     94517.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =     .502

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 13.566

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD = 10.145

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =   5.61

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =   4.46

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =   3.92

 

 PARAMETERS FOR RACE = OTHER  

 TOTAL FERTILITY RATE(S)...

      2.334

 FERTILITY AGE DISTRIBUTION(S)...

       .221 .312 .251 .143 .058 .015

 INFANT MORTALITY RATE(S)...

       22.62

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 70.99

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9675    .9757

        0‑4       1877369.    1835841.      .9941    .9956

        5‑9       1853497.    1812620.      .9969    .9979

       10‑14      1907445.    1873191.      .9961    .9976

       15‑19      2120155.    2083971.      .9939    .9963

       20‑24      1979773.    2049399.      .9928    .9952

       25‑29      1699098.    1835929.      .9923    .9941

       30‑34      1376902.    1538372.      .9907    .9926

       35‑39      1029998.    1173778.      .9871    .9898

       40‑44       858427.     984677.      .9802    .9850

       45‑49       749421.     883003.      .9683    .9773

       50‑54       702424.     849665.      .9491    .9655

       55‑59       629071.     748175.      .9196    .9462

       60‑64       496786.     614948.      .8756    .9122

       65‑69       420986.     548787.      .8091    .8541

       70‑74       301172.     401392.      .7136    .7629

       75+         360145.     567618.      .4691    .5074

       TOTAL     18362669.   19801366.

 TOTAL BASE‑YEAR POPULATION (POPBASE) =  38164035.

 CRUDE BIRTH RATE FOR BASE YEAR =  22.80

 CRUDE DEATH RATE FOR BASE YEAR =   7.80

 INFANT MORTALITY RATE FOR BASE YEAR =  21.10

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR =  25137000.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  21.77

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   8.33

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  24.19

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

         888003.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 2.335

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 2.334

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR =  90.02

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =    888003.

   ESTIMATED ANNUAL RATE PER 1000 =   29.199

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =    888003.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =    888003.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =   23.268

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 20.621

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  7.636

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =  42.64

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =  34.74

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =  36.25

 

 TOTAL POPULATION (ALL RACES) = 226504825.

 

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED ON BIRTH RATE AND

    DEATH RATE FOR PREVIOUS TEN YEARS; TOTAL FOR ALL RACES IN THE MODEL)

    =    939359.

    ESTIMATED ANNUAL RATE PER 1000 =    4.402


Listing 4.  PROJ Run for Example 2 (National Population Projection, Two-Race Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:17: 5

 

 PARAMETER FILE NAME: US802.DAT      

 GENERAL POPULATION DESCRIPTION:

 UNITED STATES RESIDENT POPULATION BY RACE (W/O)                                

 BASE YEAR: 1980

 

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =   250738546.

 

 DISTRIBUTION OF POPULATN

  BY AGE

   0‑4      18669617.

   5‑9      18806048.

  10‑14     17101239.

  15‑19     17460667.

  20‑24     19000300.

  25‑29     21967328.

  30‑34     22058888.

  35‑39     20138388.

  40‑44     18001916.

  45‑49     14192279.

  50‑54     11705971.

  55‑59     10862325.

  60‑64     11041520.

  65‑69     10298760.

  70‑74      8064410.

  75+       11368890.

 

 DISTRIBUTION OF POPULATN

  BY SEX

 MALE      123028940.

 FEMALE    127709605.

 

 DISTRIBUTION OF POPULATN

  BY RACE

 WHITE     197443844.

 OTHER      53294702.

 

 CROSSTABULATION OF POPULATN

  BY AGE AND SEX

               MALE        FEMALE 

   0‑4       9492151.    9177466.

   5‑9       9556684.    9249364.

  10‑14      8735127.    8366112.

  15‑19      8915115.    8545552.

  20‑24      9682667.    9317633.

  25‑29     11135944.   10831384.

  30‑34     11007309.   11051579.

  35‑39      9985651.   10152737.

  40‑44      8867066.    9134850.

  45‑49      6942907.    7249371.

  50‑54      5685799.    6020171.

  55‑59      5209615.    5652710.

  60‑64      5180874.    5860647.

  65‑69      4692481.    5606280.

  70‑74      3550310.    4514099.

  75+        4389239.    6979651.

 

 CROSSTABULATION OF POPULATN

  BY AGE AND RACE

               WHITE       OTHER  

   0‑4      13386385.    5283232.

   5‑9      13621659.    5184390.

  10‑14     12648435.    4452804.

  15‑19     13055499.    4405168.

  20‑24     14468046.    4532254.

  25‑29     16941640.    5025688.

  30‑34     17251096.    4807792.

  35‑39     15930166.    4208222.

  40‑44     14547949.    3453967.

  45‑49     11604716.    2587563.

  50‑54      9575698.    2130273.

  55‑59      9022988.    1839336.

  60‑64      9362446.    1679074.

  65‑69      8906125.    1392635.

  70‑74      7060025.    1004385.

  75+       10060972.    1307918.

 

 CROSSTABULATION OF POPULATN

  BY SEX AND RACE

               MALE        FEMALE 

 WHITE      97116269.  100327575.

 OTHER      25912671.   27382030.

 

 CROSSTABULATION OF POPULATN

  BY AGE, SEX, AND RACE

                    WHITE  

               MALE        FEMALE 

   0‑4       6808785.    6577600.

   5‑9       6925470.    6696189.

  10‑14      6486648.    6161786.

  15‑19      6690797.    6364702.

  20‑24      7400519.    7067527.

  25‑29      8607548.    8334093.

  30‑34      8649989.    8601107.

  35‑39      7966863.    7963303.

  40‑44      7239716.    7308232.

  45‑49      5738483.    5866234.

  50‑54      4701144.    4874554.

  55‑59      4377281.    4645708.

  60‑64      4439947.    4922499.

  65‑69      4080277.    4825848.

  70‑74      3124926.    3935098.

  75+        3877875.    6183096.

                    OTHER  

               MALE        FEMALE 

   0‑4       2683366.    2599866.

   5‑9       2631214.    2553175.

  10‑14      2248479.    2204325.

  15‑19      2224318.    2180851.

  20‑24      2282148.    2250106.

  25‑29      2528396.    2497292.

  30‑34      2357320.    2450472.

  35‑39      2018788.    2189434.

  40‑44      1627350.    1826618.

  45‑49      1204425.    1383138.

  50‑54       984655.    1145617.

  55‑59       832334.    1007002.

  60‑64       740927.     938147.

  65‑69       612203.     780432.

  70‑74       425384.     579001.

  75+         511364.     796554.

 


Listing 5.  CHECK Run for Example 3 (State Population Projection, Single-Race Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:22:47

 

 NAME OF PARAMETER FILE = AZ801.DAT      

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION                                                    

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 1

 NO OF REGIONS =  0

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 0

 SERVICE SYSTEM OPTION = 0

 NAME(S) OF RACE    ...

      ALL    

 

 PARAMETERS FOR RACE = ALL    

 TOTAL FERTILITY RATE(S)...

      2.129

 FERTILITY AGE DISTRIBUTION(S)...

       .147 .312 .312 .166 .052 .011

 INFANT MORTALITY RATE(S)...

       13.56

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 74.44

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9811    .9867

        0‑4        109075.     104808.      .9972    .9981

        5‑9        107650.     103417.      .9983    .9990

       10‑14       111583.     107990.      .9976    .9988

       15‑19       128283.     123734.      .9963    .9982

       20‑24       133486.     130297.      .9957    .9976

       25‑29       119140.     116911.      .9955    .9970

       30‑34       104855.     102909.      .9945    .9959

       35‑39        80333.      82540.      .9920    .9939

       40‑44        66836.      68279.      .9866    .9901

       45‑49        61538.      63533.      .9769    .9839

       50‑54        60295.      66454.      .9601    .9743

       55‑59        61155.      71352.      .9340    .9583

       60‑64        57682.      66718.      .8938    .9287

       65‑69        53009.      61835.      .8312    .8757

       70‑74        39867.      47409.      .7393    .7893

       75+          43155.      62087.      .4922    .5307

       TOTAL      1337942.    1380273.

 TOTAL BASE‑YEAR POPULATION (POPBASE) =   2718215.

 CRUDE BIRTH RATE FOR BASE YEAR =  18.40

 CRUDE DEATH RATE FOR BASE YEAR =   7.80

 INFANT MORTALITY RATE FOR BASE YEAR =  12.40

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR =   1770900.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  18.32

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   7.71

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  14.94

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

          71507.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 2.129

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 2.129

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR =  80.07

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =     71507.

   ESTIMATED ANNUAL RATE PER 1000 =   33.170

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =     71507.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =     71507.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =   26.307

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 16.896

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  9.272

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =  43.78

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =  32.50

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =  33.93


Listing 6.  PROJ Run for Example 3 (State Population Projection, Single-Race Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:22:57

 

 PARAMETER FILE NAME: AZ801.DAT      

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION                                                    

 BASE YEAR: 1980

 

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3694625.

 

 DISTRIBUTION OF POPULATN

  BY AGE

   0‑4        308528.

   5‑9        309834.

  10‑14       265533.

  15‑19       262196.

  20‑24       272382.

  25‑29       312138.

  30‑34       326384.

  35‑39       291639.

  40‑44       255842.

  45‑49       199194.

  50‑54       163155.

  55‑59       147819.

  60‑64       144704.

  65‑69       142762.

  70‑74       121020.

  75+         171493.

 

 DISTRIBUTION OF POPULATN

  BY SEX

 MALE        1827212.

 FEMALE      1867413.

 

 CROSSTABULATION OF POPULATN

  BY AGE AND SEX

               MALE        FEMALE 

   0‑4        156914.     151614.

   5‑9        157507.     152327.

  10‑14       135307.     130226.

  15‑19       133601.     128596.

  20‑24       138207.     134175.

  25‑29       158591.     153548.

  30‑34       164894.     161490.

  35‑39       146991.     144649.

  40‑44       128908.     126934.

  45‑49        97980.     101214.

  50‑54        80273.      82882.

  55‑59        71925.      75893.

  60‑64        67382.      77322.

  65‑69        63623.      79139.

  70‑74        53404.      67616.

  75+          71705.      99788.


Listing 7.  CHECK Run for Example 4 (State Population Projection, Three-Race, 14-Region Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:52: 1

 

 NAME OF PARAMETER FILE = AZ803C.DAT     

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 3

 NO OF REGIONS = 14

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 1

 SERVICE SYSTEM OPTION = 0

 NAME(S) OF RACE    ...

      WHITE  

      AMERIND

      OTHER  

 NAME(S) OF REGION  ...

      APACHE 

      COCHISE

      COCONINO

      GILA   

      GRAHAM  

      GREENLEE

      MARICOPA

      MOHAVE 

      NAVAJO 

      PIMA   

      PINAL  

      STA.CRUZ

      YAVAPAI

      YUMA   

 

 PARAMETERS FOR RACE = WHITE  

 TOTAL FERTILITY RATE(S)...

      2.232

 FERTILITY AGE DISTRIBUTION(S)...

       .130 .312 .326 .170 .051 .011

 INFANT MORTALITY RATE(S)...

       11.70

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 75.14

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9839    .9889

        0‑4         79351.      76208.      .9978    .9986

        5‑9         80415.      76578.      .9986    .9992

       10‑14        85306.      82032.      .9979    .9991

       15‑19        99026.      95899.      .9968    .9986

       20‑24       106315.     104137.      .9963    .9981

       25‑29        96311.      95364.      .9962    .9975

       30‑34        87382.      85981.      .9953    .9966

       35‑39        68203.      69718.      .9930    .9947

       40‑44        56493.      57394.      .9880    .9911

       45‑49        52916.      54059.      .9786    .9852

       50‑54        53052.      58170.      .9624    .9761

       55‑59        55155.      64721.      .9370    .9608

       60‑64        53162.      61749.      .8976    .9321

       65‑69        49283.      57527.      .8357    .8801

       70‑74        37022.      44379.      .7446    .7947

       75+          39590.      57863.      .4970    .5354

       TOTAL      1098982.    1141779.

 TOTAL BASE‑YEAR POPULATION (POPBASE) =   2240761.

 CRUDE BIRTH RATE FOR BASE YEAR =  18.90

 CRUDE DEATH RATE FOR BASE YEAR =   8.80

 INFANT MORTALITY RATE FOR BASE YEAR =  11.70

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR =   1604948.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  18.90

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   8.80

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  11.70

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

          44535.

 POPULATION BY REGION...

                 BASE YEAR   TEN YEARS PRIOR

      APACHE        11902.       7525.

      COCHISE       73261.      59027.

      COCONINO      49235.      34141.

      GILA          30147.      25662.

      GRAHAM        17085.      14201.

      GREENLEE       9357.       9793.

      MARICOPA    1307455.     914610.

      MOHAVE        53477.      24738.

      NAVAJO        32543.      26893.

      PIMA         442888.     326416.

      PINAL         61849.      58141.

      STA.CRUZ      16515.      13091.

      YAVAPAI       65322.      35713.

      YUMA          69725.      54997.

      TOTAL       2240761.    1604948.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 2.232

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 2.232

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR =  83.29

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =     44535.

   ESTIMATED ANNUAL RATE PER 1000 =   23.836

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =     44535.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =     44535.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =   19.875

 ESTIMATES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION NUMBER AND RATE (PER

   1000) BASED ON THE EXTERNAL MIGRATION ESTIMATE:

                           RATE

              AMOUNT  APPROX   EXACT

 APACHE  :      106.   8.874  11.257

 COCHISE :     ‑692.  ‑9.450 ‑10.599

 COCONINO:      119.   2.411   2.920

 GILA    :     ‑430. ‑14.259 ‑15.539

 GRAHAM  :     ‑207. ‑12.143 ‑13.399

 GREENLEE:     ‑327. ‑34.897 ‑34.043

 MARICOPA:     2309.   1.766   2.130

 MOHAVE  :     1433.  26.796  39.480

 NAVAJO  :     ‑379. ‑11.634 ‑12.877

 PIMA    :     ‑972.  ‑2.194  ‑2.576

 PINAL   :    ‑1462. ‑23.642 ‑24.442

 STA.CRUZ:     ‑133.  ‑8.073  ‑9.132

 YAVAPAI :     1170.  17.909  24.387

 YUMA    :     ‑534.  7.661  8.687

 TOTAL   :        0.

 SPECIFIED AND IMPLIED VALUES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION

   NUMBER AND RATE (PER 1000):

                 SPECIFIED          IMPLIED

              AMOUNT    RATE    AMOUNT    RATE

 APACHE  :      106.    .000      106.   8.906

 COCHISE :        0. ‑10.599     ‑776. ‑10.599

 COCONINO:      119.    .000      119.   2.417

 GILA    :        0. ‑15.539     ‑468. ‑15.539

 GRAHAM  :        0. ‑13.399     ‑229. ‑13.399

 GREENLEE:        0. ‑34.043     ‑319. ‑34.043

 MARICOPA:     2309.    .000     2309.   1.766

 MOHAVE  :     1433.    .000     1433.  26.797

 NAVAJO  :        0. ‑12.877     ‑419. ‑12.877

 PIMA    :        0.  ‑2.576    ‑1141.  ‑2.576

 PINAL   :        0. ‑24.442    ‑1512. ‑24.442

 STA.CRUZ:        0.  ‑9.132     ‑151.  ‑9.132

 YAVAPAI :     1170.    .000     1170.  17.911

 YUMA    :        0.  8.687     ‑606.  ‑8.687

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 17.463

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  9.938

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =  33.94

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =  26.75

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =  27.40

 

 PARAMETERS FOR RACE = AMERIND

 TOTAL FERTILITY RATE(S)...

      3.487

 FERTILITY AGE DISTRIBUTION(S)...

       .221 .312 .251 .143 .058 .015

 INFANT MORTALITY RATE(S)...

       16.20

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 73.43

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9772    .9835

        0‑4          9853.       9732.      .9963    .9973

        5‑9          9288.       9237.      .9979    .9987

       10‑14         9575.       9465.      .9972    .9985

       15‑19         9931.       9973.      .9956    .9977

       20‑24         7250.       7979.      .9949    .9969

       25‑29         5681.       6237.      .9946    .9961

       30‑34         4817.       4988.      .9934    .9949

       35‑39         3524.       4054.      .9906    .9927

       40‑44         3120.       3522.      .9848    .9886

       45‑49         2532.       3103.      .9744    .9820

       50‑54         2123.       2579.      .9569    .9717

       55‑59         1758.       2122.      .9298    .9548

       60‑64         1362.       1555.      .8885    .9239

       65‑69         1154.       1382.      .8248    .8694

       70‑74          928.        916.      .7318    .7816

       75+           1349.       1409.      .4855    .5239

       TOTAL        74245.      78253.

 TOTAL BASE‑YEAR POPULATION (POPBASE) =    152498.

 CRUDE BIRTH RATE FOR BASE YEAR =  33.20

 CRUDE DEATH RATE FOR BASE YEAR =   6.50

 INFANT MORTALITY RATE FOR BASE YEAR =  16.20

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR =     95812.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  33.20

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   6.50

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  16.20

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

           2462.

 POPULATION BY REGION...

                 BASE YEAR   TEN YEARS PRIOR

      APACHE        39024.      24518.

      COCHISE         489.        307.

      COCONINO      20904.      13134.

      GILA           5083.       3194.

      GRAHAM         2740.       1721.

      GREENLEE        229.        144.

      MARICOPA      22788.      14317.

      MOHAVE         1462.        919.

      NAVAJO        32122.      20182.

      PIMA          14880.       9349.

      PINAL          8487.       5332.

      STA.CRUZ         57.         36.

      YAVAPAI         997.        626.

      YUMA           3236.       2033.

      TOTAL        152498.      95812.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 3.487

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 3.487

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR = 137.76

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =      2462.

   ESTIMATED ANNUAL RATE PER 1000 =   20.873

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =      2462.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =      2462.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =   16.144

 ESTIMATES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION NUMBER AND RATE (PER

   1000) BASED ON THE EXTERNAL MIGRATION ESTIMATE:

                           RATE

              AMOUNT  APPROX   EXACT

 APACHE  :        0.    .000    .001

 COCHISE :        0.    .054    .070

 COCONINO:        0.   ‑.002   ‑.003

 GILA    :        0.   ‑.010   ‑.013

 GRAHAM  :        0.    .021    .027

 GREENLEE:        0.   ‑.062   ‑.079

 MARICOPA:        0.    .002    .002

 MOHAVE  :        0.   ‑.035   ‑.045

 NAVAJO  :        0.   ‑.001   ‑.001

 PIMA    :        0.   ‑.001   ‑.001

 PINAL   :        0.    .003    .004

 STA.CRUZ:        0.   ‑.380   ‑.486

 YAVAPAI :        0.    .046    .059

 YUMA    :        0.    .004    .006

 TOTAL   :        0.

 SPECIFIED AND IMPLIED VALUES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION

   NUMBER AND RATE (PER 1000):

                 SPECIFIED          IMPLIED

              AMOUNT    RATE    AMOUNT    RATE

 APACHE  :        0.    .000        0.    .000

 COCHISE :        0.    .000        0.    .000

 COCONINO:        0.    .000        0.    .000

 GILA    :        0.    .000        0.    .000

 GRAHAM  :        0.    .000        0.    .000

 GREENLEE:        0.    .000        0.    .000

 MARICOPA:        0.    .000        0.    .000

 MOHAVE  :        0.    .000        0.    .000

 NAVAJO  :        0.    .000        0.    .000

 PIMA    :        0.    .000        0.    .000

 PINAL   :        0.    .000        0.    .000

 STA.CRUZ:        0.    .000        0.    .000

 YAVAPAI :        0.    .000        0.    .000

 YUMA    :        0.    .000        0.    .000

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 28.208

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  5.230

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =  47.57

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =  37.84

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =  39.12

 

 PARAMETERS FOR RACE = OTHER  

 TOTAL FERTILITY RATE(S)...

      2.346

 FERTILITY AGE DISTRIBUTION(S)...

       .221 .312 .251 .143 .058 .015

 INFANT MORTALITY RATE(S)...

       21.10

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 71.57

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9698    .9775

        0‑4         19871.      18868.      .9946    .9960

        5‑9         17947.      17602.      .9971    .9981

       10‑14        16702.      16493.      .9963    .9978

       15‑19        19326.      17862.      .9943    .9966

       20‑24        19921.      18181.      .9933    .9956

       25‑29        17148.      15310.      .9929    .9946

       30‑34        12656.      11940.      .9913    .9931

       35‑39         8606.       8768.      .9879    .9905

       40‑44         7223.       7363.      .9813    .9859

       45‑49         6090.       6371.      .9697    .9784

       50‑54         5120.       5705.      .9509    .9670

       55‑59         4242.       4509.      .9220    .9482

       60‑64         3158.       3414.      .8787    .9150

       65‑69         2572.       2926.      .8128    .8577

       70‑74         1917.       2114.      .7179    .7673

       75+           2216.       2815.      .4730    .5113

       TOTAL       164715.     160241.

 TOTAL BASE‑YEAR POPULATION (POPBASE) =    324956.

 CRUDE BIRTH RATE FOR BASE YEAR =  22.80

 CRUDE DEATH RATE FOR BASE YEAR =   7.80

 INFANT MORTALITY RATE FOR BASE YEAR =  21.10

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR =     70140.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  22.80

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   7.80

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  21.10

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

          22756.

 POPULATION BY REGION...

                 BASE YEAR   TEN YEARS PRIOR

      APACHE         1182.        255.

      COCHISE       11936.       2576.

      COCONINO       4869.       1051.

      GILA           1850.        399.

      GRAHAM         3037.        656.

      GREENLEE       1820.        393.

      MARICOPA     178809.      38595.

      MOHAVE          926.        200.

      NAVAJO         2964.        640.

      PIMA          73675.      15902.

      PINAL         20582.       4443.

      STA.CRUZ       3887.        839.

      YAVAPAI        1826.        394.

      YUMA          17593.       3797.

      TOTAL        324956.      70140.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 2.346

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 2.346

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR =  93.28

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =     22756.

   ESTIMATED ANNUAL RATE PER 1000 =  150.698

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =     22756.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =     22756.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =   70.028

 ESTIMATES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION NUMBER AND RATE (PER

   1000) BASED ON THE EXTERNAL MIGRATION ESTIMATE:

                           RATE

              AMOUNT  APPROX   EXACT

 APACHE  :        0.    .012    .021

 COCHISE :        0.    .003    .005

 COCONINO:        0.   ‑.001   ‑.002

 GILA    :        0.    .018    .033

 GRAHAM  :        0.   ‑.017   ‑.031

 GREENLEE:        0.   ‑.010   ‑.018

 MARICOPA:        0.    .000    .000

 MOHAVE  :        0.   ‑.015   ‑.027

 NAVAJO  :        0.   ‑.009   ‑.016

 PIMA    :        0.    .001    .001

 PINAL   :        0.   ‑.003   ‑.005

 STA.CRUZ:        0.    .000   ‑.001

 YAVAPAI :        0.    .008    .014

 YUMA    :        0.    .002    .004

 TOTAL   :        0.

 SPECIFIED AND IMPLIED VALUES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION

   NUMBER AND RATE (PER 1000):

                 SPECIFIED          IMPLIED

              AMOUNT    RATE    AMOUNT    RATE

 APACHE  :        0.    .000        0.    .000

 COCHISE :        0.    .000        0.    .000

 COCONINO:        0.    .000        0.    .000

 GILA    :        0.    .000        0.    .000

 GRAHAM  :        0.    .000        0.    .000

 GREENLEE:        0.    .000        0.    .000

 MARICOPA:        0.    .000        0.    .000

 MOHAVE  :        0.    .000        0.    .000

 NAVAJO  :        0.    .000        0.    .000

 PIMA    :        0.    .000        0.    .000

 PINAL   :        0.    .000        0.    .000

 STA.CRUZ:        0.    .000        0.    .000

 YAVAPAI :        0.    .000        0.    .000

 YUMA    :        0.    .000        0.    .000

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 20.349

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  5.571

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) = 165.70

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =  73.94

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =  84.81

 

 TOTAL POPULATION (ALL RACES) =   2718215.

 

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED ON BIRTH RATE AND

    DEATH RATE FOR PREVIOUS TEN YEARS; TOTAL FOR ALL RACES IN THE MODEL)

    =     69311.

    ESTIMATED ANNUAL RATE PER 1000 =   32.163


Listing 8.  PROJ Run for Example 4 (State Population Projection, Three-Race, 14-Region Model)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:53:32

 

 PARAMETER FILE NAME: AZ803C.DAT     

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR: 1980

 

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3735219.

 

 DISTRIBUTION OF POPULATN

  BY RACE

 WHITE       2886323.

 AMERIND      228240.

 OTHER        620656.

 

 DISTRIBUTION OF POPULATN

  BY REGION

 APACHE        72497.

 COCHISE       97683.

 COCONINO      97171.

 GILA          40759.

 GRAHAM        26383.

 GREENLEE      11039.

 MARICOPA    1893992.

 MOHAVE        83827.

 NAVAJO        84127.

 PIMA         649633.

 PINAL        101590.

 STA.CRUZ      24075.

 YAVAPAI       95609.

 YUMA         108068.

 

 CROSSTABULATION OF POPULATN

  BY REGION AND RACE

               WHITE       AMERIND     OTHER  

 APACHE        15397.      55256.       1844.

 COCHISE       78373.        692.      18618.

 COCONINO      59977.      29599.       7595.

 GILA          30676.       7197.       2886.

 GRAHAM        17766.       3880.       4737.

 GREENLEE       7876.        324.       2839.

 MARICOPA    1582814.      32267.     278911.

 MOHAVE        80313.       2070.       1444.

 NAVAJO        34020.      45483.       4623.

 PIMA         513643.      21069.     114920.

 PINAL         57469.      12017.      32104.

 STA.CRUZ      17931.         81.       6063.

 YAVAPAI       91349.       1412.       2848.

 YUMA          76044.       4582.      27442.


Listing 9.  CHECK Run for Example 5 (Projection of the Hispanic Population)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:59:28

 

 NAME OF PARAMETER FILE = AZ80HC.DAT     

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY HISPANIC STATUS AND REGION                      

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 2

 NO OF REGIONS = 14

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 1

 SERVICE SYSTEM OPTION = 0

 NAME(S) OF RACE    ...

      HISPANIC

      NON HISP

 NAME(S) OF REGION  ...

      APACHE 

      COCHISE

      COCONINO

      GILA   

      GRAHAM 

      GREENLEE

      MARICOPA

      MOHAVE 

      NAVAJO 

      PIMA   

      PINAL  

      STA.CRUZ

      YAVAPAI

      YUMA   

 

 PARAMETERS FOR RACE = HISPANIC

 TOTAL FERTILITY RATE(S)...

      3.190

 FERTILITY AGE DISTRIBUTION(S)...

       .221 .312 .251 .143 .058 .015

 INFANT MORTALITY RATE(S)...

       12.40

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 74.88

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9829    .9881

        0‑4         27940.      26823.      .9976    .9984

        5‑9         25652.      25079.      .9985    .9991

       10‑14        24234.      23538.      .9978    .9990

       15‑19        26081.      24824.      .9966    .9985

       20‑24        23080.      22734.      .9961    .9979

       25‑29        20171.      19195.      .9959    .9973

       30‑34        15889.      15780.      .9950    .9963

       35‑39        11668.      12241.      .9926    .9944

       40‑44         9644.      10217.      .9875    .9907

       45‑49         8380.       9015.      .9780    .9847

       50‑54         7608.       8290.      .9616    .9754

       55‑59         6317.       6759.      .9359    .9599

       60‑64         4672.       5073.      .8962    .9309

       65‑69         3525.       3986.      .8340    .8784

       70‑74         2545.       2938.      .7427    .7926

       75+           2840.       3963.      .4952    .5337

       TOTAL       220246.     220455.

 TOTAL BASE‑YEAR POPULATION (POPBASE) =    440701.

 CRUDE BIRTH RATE FOR BASE YEAR =  29.70

 CRUDE DEATH RATE FOR BASE YEAR =   7.80

 INFANT MORTALITY RATE FOR BASE YEAR =  12.40

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR =    293485.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  29.70

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   7.80

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  12.40

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

           8159.

 POPULATION BY REGION...

                 BASE YEAR   TEN YEARS PRIOR

      APACHE         1983.       1229.

      COCHISE       22846.      16507.

      COCONINO       7315.       4713.

      GILA           7723.       6093.

      GRAHAM         5457.       3957.

      GREENLEE       5446.       4932.

      MARICOPA     199003.     127590.

      MOHAVE         2148.        994.

      NAVAJO         4538.       3202.

      PIMA         111418.      73728.

      PINAL         26752.      19984.

      STA.CRUZ      15229.      10396.

      YAVAPAI        4205.       2267.

      YUMA          26638.      17893.

      TOTAL        440701.     293485.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 3.190

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 3.190

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR = 124.67

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =      6901.

   ESTIMATED ANNUAL RATE PER 1000 =   19.592

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =      8159.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =      8159.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =   18.514

 ESTIMATES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION NUMBER AND RATE (PER

   1000) BASED ON THE EXTERNAL MIGRATION ESTIMATE:

                           RATE

              AMOUNT  APPROX   EXACT

 APACHE  :       10.   5.193   6.697

 COCHISE :     ‑145.  ‑6.362  ‑7.581

 COCONINO:       18.   2.435   3.079

 GILA    :     ‑107. ‑13.829 ‑15.731

 GRAHAM  :      ‑36.  ‑6.653  ‑7.913

 GREENLEE:     ‑147. ‑26.947 ‑28.458

 MARICOPA:      555.   2.789   3.535

 MOHAVE  :       49.  22.846  34.036

 NAVAJO  :      ‑20.  ‑4.458  ‑5.378

 PIMA    :       53.    .475    .593

 PINAL   :     ‑244.  ‑9.114 ‑10.672

 STA.CRUZ:      ‑29.  ‑1.877  ‑2.304

 YAVAPAI :       60.  14.260  19.723

 YUMA    :      ‑17.   ‑.648   ‑.801

 TOTAL   :        0.

 SPECIFIED AND IMPLIED VALUES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION

   NUMBER AND RATE (PER 1000):

                 SPECIFIED          IMPLIED

              AMOUNT    RATE    AMOUNT    RATE

 APACHE  :       10.    .000       10.   5.043

 COCHISE :        0.  ‑7.581     ‑173.  ‑7.581

 COCONINO:       18.    .000       18.   2.461

 GILA    :        0. ‑15.731     ‑121. ‑15.731

 GRAHAM  :        0.  ‑7.913      ‑43.  ‑7.913

 GREENLEE:        0. ‑28.458     ‑155. ‑28.458

 MARICOPA:      555.    .000      555.   2.789

 MOHAVE  :       49.    .000       49.  22.812

 NAVAJO  :        0.  ‑5.378      ‑24.  ‑5.378

 PIMA    :       53.    .000       53.    .476

 PINAL   :        0. ‑10.672     ‑285. ‑10.672

 STA.CRUZ:        0.  ‑2.304      ‑35.  ‑2.304

 YAVAPAI :       60.    .000       60.  14.269

 YUMA    :        0.   ‑.801      ‑21.   ‑.801

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 26.087

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  4.570

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =  41.49

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =  38.40

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =  40.03

 

 PARAMETERS FOR RACE = NON HISP

 TOTAL FERTILITY RATE(S)...

      1.895

 FERTILITY AGE DISTRIBUTION(S)...

       .147 .312 .312 .166 .052 .011

 INFANT MORTALITY RATE(S)...

       12.40

 EXPECTATION OF LIFE AT BIRTH CORRESPONDING TO IMR FOR FIRST

   PROJECTION PERIOD = 74.88

 BASE‑YEAR POPULATION AND SURVIVAL PROBABILITIES FOR FIRST PROJECTION PERIOD...

                     MALE      FEMALE        MALE    FEMALE 

         0                                  .9829    .9881

        0‑4         81135.      77985.      .9976    .9984

        5‑9         81998.      78338.      .9985    .9991

       10‑14        87349.      84452.      .9978    .9990

       15‑19       102202.      98910.      .9966    .9985

       20‑24       110406.     107563.      .9961    .9979

       25‑29        98969.      97716.      .9959    .9973

       30‑34        88966.      87129.      .9950    .9963

       35‑39        68665.      70299.      .9926    .9944

       40‑44        57192.      58062.      .9875    .9907

       45‑49        53158.      54518.      .9780    .9847

       50‑54        52687.      58164.      .9616    .9754

       55‑59        54838.      64593.      .9359    .9599

       60‑64        53010.      61645.      .8962    .9309

       65‑69        49484.      57849.      .8340    .8784

       70‑74        37322.      44471.      .7427    .7926

       75+          40315.      58124.      .4952    .5337

       TOTAL      1117696.    1159818.

 TOTAL BASE‑YEAR POPULATION (POPBASE) =   2277514.

 CRUDE BIRTH RATE FOR BASE YEAR =  16.20

 CRUDE DEATH RATE FOR BASE YEAR =   7.80

 INFANT MORTALITY RATE FOR BASE YEAR =  12.40

 POPULATION (POPPREV) TEN YEARS PRIOR TO BASE YEAR =   1477415.

 AVERAGE CRUDE BIRTH RATE FOR PREVIOUS TEN YEARS =  16.20

 AVERAGE CRUDE DEATH RATE FOR PREVIOUS TEN YEARS =   7.80

 AVERAGE INFANT MORTALITY RATE FOR PREVIOUS TEN YEARS =  12.40

 ANNUAL EXTERNAL MIGRATION RATE(S) (PER 1000) (EMRATE)...

          .000

 ANNUAL EXTERNAL MIGRATION NUMBER(S) (IMMNO)...

          63450.

 POPULATION BY REGION...

                 BASE YEAR   TEN YEARS PRIOR

      APACHE        50125.      31069.

      COCHISE       62840.      45403.

      COCONINO      67693.      43613.

      GILA          29357.      23162.

      GRAHAM        17405.      12621.

      GREENLEE       5960.       5398.

      MARICOPA    1310049.     839932.

      MOHAVE        53717.      24863.

      NAVAJO        63091.      44513.

      PIMA         420025.     277939.

      PINAL         64166.      47932.

      STA.CRUZ       5230.       3570.

      YAVAPAI       63940.      34466.

      YUMA          63916.      42934.

      TOTAL       2277514.    1477415.

 TOTAL FERTILITY RATE (TFREST) ESTIMATED FROM BASE‑YEAR BIRTH RATE = 1.895

 TOTAL FERTILITY RATE (TFR) SPECIFIED FOR FIRST PROJECTION PERIOD = 1.895

   GENERAL FERTILITY RATE (BIRTH RATE (BRFF) PER 1000 FEMALES AGED 15‑44)

    FOR BASE YEAR =  71.00

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED  ON BIRTH RATE

   AND DEATH RATE FOR PREVIOUS TEN YEARS) =     64622.

   ESTIMATED ANNUAL RATE PER 1000 =   35.829

 ANNUAL NET MIGRATION NUMBER SPECIFIED FOR FIRST PROJECTION PERIOD =     63450.

   ANNUAL NET MIGRATION RATE PER 1000 SPECIFIED FOR FIRST PROJECTION

   PERIOD =     .000

 ANNUAL NET MIGRATION (MIG) IMPLIED BY MIGRATION NUMBER (IMMNO) AND/OR

   MIGRATION RATE (EMRATE) SPECIFIED FOR FIRST PROJECTION PERIOD =     63450.

   APPROX ANNUAL RATE PER 1000 POPULATION (MIGR) =   27.859

 ESTIMATES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION NUMBER AND RATE (PER

   1000) BASED ON THE EXTERNAL MIGRATION ESTIMATE:

                           RATE

              AMOUNT  APPROX   EXACT

 APACHE  :      151.   3.022   3.852

 COCHISE :     ‑486.  ‑7.727  ‑9.138

 COCONINO:       31.    .463    .579

 GILA    :     ‑431. ‑14.684 ‑16.613

 GRAHAM  :     ‑139.  ‑8.002  ‑9.445

 GREENLEE:     ‑160. ‑26.903 ‑28.348

 MARICOPA:     1035.    .790    .991

 MOHAVE  :     1045.  19.454  28.402

 NAVAJO  :     ‑375.  ‑5.950  ‑7.120

 PIMA    :     ‑573.  ‑1.363  ‑1.684

 PINAL   :     ‑660. ‑10.290 ‑11.968

 STA.CRUZ:      ‑19.  ‑3.549  ‑4.317

 YAVAPAI :      734.  11.479  15.632

 YUMA    :     ‑154.  ‑2.411  ‑2.955

 TOTAL   :        0.

 SPECIFIED AND IMPLIED VALUES (BY REGION) OF THE ANNUAL INTERNAL MIGRATION

   NUMBER AND RATE (PER 1000):

                 SPECIFIED          IMPLIED

              AMOUNT    RATE    AMOUNT    RATE

 APACHE  :      151.    .000      151.   3.012

 COCHISE :        0.  ‑9.138     ‑574.  ‑9.138

 COCONINO:       31.    .000       31.    .458

 GILA    :        0. ‑16.613     ‑488. ‑16.613

 GRAHAM  :        0.  ‑9.445     ‑164.  ‑9.445

 GREENLEE:        0. ‑28.348     ‑169. ‑28.348

 MARICOPA:     1035.    .000     1035.    .790

 MOHAVE  :     1045.    .000     1045.  19.454

 NAVAJO  :        0.  ‑7.120     ‑449.  ‑7.120

 PIMA    :        0.  ‑1.684     ‑707.  ‑1.684

 PINAL   :        0. ‑11.968     ‑768. ‑11.968

 STA.CRUZ:        0.  ‑4.317      ‑23.  ‑4.317

 YAVAPAI :      734.    .000      734.  11.480

 YUMA    :        0.  ‑2.955     ‑189.  ‑2.955

 CRUDE BIRTH RATE PER 1000 (CBR) FOR FIRST PROJECTION PERIOD = 15.027

 CRUDE DEATH RATE PER 1000 (CDR) FOR FIRST PROJECTION PERIOD =  9.939

 AVERAGE ANNUAL POPULATION GROWTH RATE PER 1000 FOR PREVIOUS TEN YEARS

   = 1000((POPBASE/POPPREV(IR))**.1‑1) =  44.23

 PROJECTED POPULATION GROWTH RATE (GIVEN SPECIFIED PARAMETERS):

   1000((POPPROJ/POPBASE)**.2‑1) =  31.55

   APPROX. ANNUAL POPULATION GROWTH RATE PER 1000, BASED ON CBR,

    CDR, AND MIGR = CBR‑CDR+MIGR =  32.95

 

 TOTAL POPULATION (ALL RACES) =   2718215.

 

 ESTIMATE OF ANNUAL NET EXTERNAL MIGRATION NUMBER (BASED ON BIRTH RATE AND

    DEATH RATE FOR PREVIOUS TEN YEARS; TOTAL FOR ALL RACES IN THE MODEL)

    =     71553.

    ESTIMATED ANNUAL RATE PER 1000 =   33.191


Listing 10.  PROJ Run for Example 5 (Projection of the Hispanic Population)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   12:59:49

 

 PARAMETER FILE NAME: AZ80HC.DAT     

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY HISPANIC STATUS AND REGION                      

 BASE YEAR: 1980

 

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3702132.

 

 DISTRIBUTION OF POPULATN

  BY RACE

 HISPANIC     647662.

 NON HISP    3054470.

 

 DISTRIBUTION OF POPULATN

  BY REGION

 APACHE        65014.

 COCHISE       98260.

 COCONINO      92212.

 GILA          38996.

 GRAHAM        26019.

 GREENLEE      11016.

 MARICOPA    1871693.

 MOHAVE        80664.

 NAVAJO        76668.

 PIMA         651822.

 PINAL        101675.

 STA.CRUZ      26575.

 YAVAPAI       92273.

 YUMA         111200.

 

 CROSSTABULATION OF POPULATN

  BY REGION AND RACE

               HISPANIC    NON HISP

 APACHE         2867.      62147.

 COCHISE       29228.      69032.

 COCONINO      10332.      81880.

 GILA           9098.      29898.

 GRAHAM         6958.      19061.

 GREENLEE       5633.       5383.

 MARICOPA     281931.    1589762.

 MOHAVE         3602.      77062.

 NAVAJO         5936.      70732.

 PIMA         154500.     497322.

 PINAL         33174.      68501.

 STA.CRUZ      20544.       6031.

 YAVAPAI        6584.      85688.

 YUMA          36480.      74720.


Listing 11.  CHECK Run for Example 6 (Rehabilitation Services, Projection of the Work-Disabled)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:17:49

 

 NAME OF PARAMETER FILE = AZ803CD.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 3

 NO OF REGIONS = 14

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 1

 SERVICE SYSTEM OPTION = 1

 NAME(S) OF RACE    ...

      WHITE  

      AMERIND

      OTHER  

 NAME(S) OF REGION  ...

      APACHE  

      COCHISE

      COCONINO

      GILA   

      GRAHAM 

      GREENLEE

      MARICOPA

      MOHAVE 

      NAVAJO 

      PIMA   

      PINAL  

      STA.CRUZ

      YAVAPAI

      YUMA   

 

 PRINTOUT OF DEMOGRAPHIC PARAMETERS SUPPRESSED.

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 WORK‑DISABLED POPULATION (SEVERELY AND PARTIALLY WORK‑DISABLED)                

 NO OF TARGET POPULATIONS =  2

 SERVICE POPULATION OPTION = 0

 NAME(S) OF TARG POP...

      WRKDISSV

      WRKDISPT

 

 TARGET   POPULATION = WRKDISSV

 TYPE OF STRATIFICATION =  2

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00000000

    2     .00840000

    3     .02100000

    4     .02900000

    5     .06300000

    6     .11000000

    7     .24200000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    2

       20‑24    3

       25‑29    4

       30‑34    4

       35‑39    5

       40‑44    5

       45‑49    6

       50‑54    6

       55‑59    7

       60‑64    7

       65‑69    1

       70‑74    1

       75+      1

 

 TARGET   POPULATION = WRKDISPT

 TYPE OF STRATIFICATION =  2

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00000000

    2     .01560000

    3     .03900000

    4     .07000000

    5     .08300000

    6     .12400000

    7     .11800000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    2

       20‑24    3

       25‑29    4

       30‑34    4

       35‑39    5

       40‑44    5

       45‑49    6

       50‑54    6

       55‑59    7

       60‑64    7

       65‑69    1

       70‑74    1

       75+      1


Listing 12.  PROJ Run for Example 6 (Rehabilitation Services, Projection of the Work-Disabled)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:18: 6

 

 PARAMETER FILE NAME: AZ803CD.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR: 1980

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 WORK‑DISABLED POPULATION (SEVERELY AND PARTIALLY WORK‑DISABLED)                

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3735219.

 

 DISTRIBUTION OF POPULATN

  BY AGE

   0‑4        338816.

   5‑9        338489.

  10‑14       268314.

  15‑19       263875.

  20‑24       272520.

  25‑29       312009.

  30‑34       326222.

  35‑39       290907.

  40‑44       253597.

  45‑49       196686.

  50‑54       161169.

  55‑59       145678.

  60‑64       142066.

  65‑69       139466.

  70‑74       117950.

  75+         167454.

 

 DISTRIBUTIONAL ANALYSIS OF WRKDISSV

 

 TOTAL WRKDISSV =      169750.

 

 DISTRIBUTION OF WRKDISSV

  BY AGE

   0‑4             0.

   5‑9             0.

  10‑14            0.

  15‑19         2217.

  20‑24         5723.

  25‑29         9048.

  30‑34         9460.

  35‑39        18327.

  40‑44        15977.

  45‑49        21635.

  50‑54        17729.

  55‑59        35254.

  60‑64        34380.

  65‑69            0.

  70‑74            0.

  75+              0.

 

 DISTRIBUTIONAL ANALYSIS OF WRKDISPT

 

 TOTAL WRKDISPT =      182943.

 

 DISTRIBUTION OF WRKDISPT

  BY AGE

   0‑4             0.

   5‑9             0.

  10‑14            0.

  15‑19         4116.

  20‑24        10628.

  25‑29        21841.

  30‑34        22836.

  35‑39        24145.

  40‑44        21049.

  45‑49        24389.

  50‑54        19985.

  55‑59        17190.

  60‑64        16764.

  65‑69            0.

  70‑74            0.

  75+              0.

 

 TOTALS OF TARGET POPULATION(S)   

 WRKDISSV     169750.

 WRKDISPT     182943.


Listing 13.  CHECK Run for Example 7 (Projection of School Enrollment)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:25:32

 

 NAME OF PARAMETER FILE = AZ803CE.DAT     

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 3

 NO OF REGIONS = 14

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 1

 SERVICE SYSTEM OPTION = 1

 NAME(S) OF RACE    ...

      WHITE  

      AMERIND

      OTHER  

 NAME(S) OF REGION  ...

      APACHE 

      COCHISE

      COCONINO

      GILA   

      GRAHAM 

      GREENLEE

      MARICOPA

      MOHAVE 

      NAVAJO 

      PIMA   

      PINAL  

      STA.CRUZ

      YAVAPAI

      YUMA   

 

 PRINTOUT OF DEMOGRAPHIC PARAMETERS SUPPRESSED.

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 ELEMENTARY & SECONDARY SCHOOL ENROLLMENT; TEACHERS; SALARIES                   

 NO OF TARGET POPULATIONS =  1

 SERVICE POPULATION OPTION = 2

 NO OF SERVICES =  1

 NO OF RESOURCES =  1

 NO OF COST CATEGORIES =  1

 NAME(S) OF TARG POP...

      STUDENTS

 NAME(S) OF SERV POP...

      ELEM/SEC

 NAME(S) OF SERVICE ...

      TEACHING

 NAME(S) OF RESOURCE...

      TEACHERS

 NAME(S) OF COST    ...

      SALARIES

 SERVICE PARAMETERS FOR SERVICE POPULATION = ELEM/SEC

      TEACHING      1.0000

 RESOURCE PARAMETERS FOR SERVICE = TEACHING

      TEACHERS       .0500

 COST PARAMETERS FOR RESOURCE = TEACHERS

      SALARIES  17200.0000

 

 TARGET   POPULATION = STUDENTS

 TYPE OF STRATIFICATION =  2

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .14300000

    2     .95200000

    3     .96300000

    4     .71700000

    5     .21500000

    6     .09000000

    7     .06200000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     2

       10‑14    3

       15‑19    4

       20‑24    5

       25‑29    6

       30‑34    7

       35‑39    8

       40‑44    8

       45‑49    8

       50‑54    8

       55‑59    8

       60‑64    8

       65‑69    8

       70‑74    8

       75+      8

 

 SERVICE  POPULATION = ELEM/SEC

 TYPE OF STRATIFICATION =  2

 SERVICE RATIO(S)...                            

  INDEX    RATE

    1    1.00000000

    2     .87400000

    3     .00000000

    4     .00000000

    5     .00000000

    6     .00000000

    7     .00000000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    2

       20‑24    3

       25‑29    3

       30‑34    3

       35‑39    3

       40‑44    3

       45‑49    3

       50‑54    3

       55‑59    3

       60‑64    3

       65‑69    3

       70‑74    3

       75+      3


Listing 14.  PROJ Run for Example 7 (Projection of School Enrollment)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:25:44

 

 PARAMETER FILE NAME: AZ803CE.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR: 1980

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 ELEMENTARY & SECONDARY SCHOOL ENROLLMENT; TEACHERS; SALARIES                   

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3735219.

 

 DISTRIBUTION OF POPULATN

  BY AGE

   0‑4        338816.

   5‑9        338489.

  10‑14       268314.

  15‑19       263875.

  20‑24       272520.

  25‑29       312009.

  30‑34       326222.

  35‑39       290907.

  40‑44       253597.

  45‑49       196686.

  50‑54       161169.

  55‑59       145678.

  60‑64       142066.

  65‑69       139466.

  70‑74       117950.

  75+         167454.

 

 DISTRIBUTION OF POPULATN

  BY REGION

 APACHE        72497.

 COCHISE       97683.

 COCONINO      97171.

 GILA          40759.

 GRAHAM        26383.

 GREENLEE      11039.

 MARICOPA    1893992.

 MOHAVE        83827.

 NAVAJO        84127.

 PIMA         649633.

 PINAL        101590.

 STA.CRUZ      24075.

 YAVAPAI       95609.

 YUMA         108068.

 

 DISTRIBUTIONAL ANALYSIS OF STUDENTS

 

 TOTAL STUDENTS =      925175.

 

 DISTRIBUTION OF STUDENTS

  BY AGE

   0‑4         48451.

   5‑9        322241.

  10‑14       258386.

  15‑19       189199.

  20‑24        58592.

  25‑29        28081.

  30‑34        20226.

  35‑39            0.

  40‑44            0.

  45‑49            0.

  50‑54            0.

  55‑59            0.

  60‑64            0.

  65‑69            0.

  70‑74            0.

  75+              0.

 

 DISTRIBUTION OF STUDENTS

  BY REGION

 APACHE        22833.

 COCHISE       23786.

 COCONINO      26060.

 GILA          10332.

 GRAHAM         6812.

 GREENLEE       2769.

 MARICOPA     457268.

 MOHAVE        19512.

 NAVAJO        24616.

 PIMA         159357.

 PINAL         26920.

 STA.CRUZ       5960.

 YAVAPAI       22237.

 YUMA          27238.

 

 DISTRIBUTIONAL ANALYSIS OF ELEM/SEC

 

 TOTAL ELEM/SEC =      794438.

 

 DISTRIBUTION OF ELEM/SEC

  BY AGE

   0‑4         48451.

   5‑9        322241.

  10‑14       258386.

  15‑19       165360.

  20‑24            0.

  25‑29            0.

  30‑34            0.

  35‑39            0.

  40‑44            0.

  45‑49            0.

  50‑54            0.

  55‑59            0.

  60‑64            0.

  65‑69            0.

  70‑74            0.

  75+              0.

 

 DISTRIBUTION OF ELEM/SEC

  BY REGION

 APACHE        19933.

 COCHISE       20393.

 COCONINO      22522.

 GILA           8897.

 GRAHAM         5865.

 GREENLEE       2377.

 MARICOPA     392016.

 MOHAVE        16710.

 NAVAJO        21394.

 PIMA         136725.

 PINAL         23184.

 STA.CRUZ       5112.

 YAVAPAI       19040.

 YUMA          23393.

 

 DISTRIBUTIONAL ANALYSIS OF TEACHING

 

 TOTAL TEACHING =      794438.

 

 DISTRIBUTION OF TEACHING

  BY AGE

   0‑4         48451.

   5‑9        322241.

  10‑14       258386.

  15‑19       165360.

  20‑24            0.

  25‑29            0.

  30‑34            0.

  35‑39            0.

  40‑44            0.

  45‑49            0.

  50‑54            0.

  55‑59            0.

  60‑64            0.

  65‑69            0.

  70‑74            0.

  75+              0.

 

 DISTRIBUTION OF TEACHING

  BY REGION

 APACHE        19933.

 COCHISE       20393.

 COCONINO      22522.

 GILA           8897.

 GRAHAM         5865.

 GREENLEE       2377.

 MARICOPA     392016.

 MOHAVE        16710.

 NAVAJO        21394.

 PIMA         136725.

 PINAL         23184.

 STA.CRUZ       5112.

 YAVAPAI       19040.

 YUMA          23393.

 

 DISTRIBUTIONAL ANALYSIS OF TEACHERS

 

 TOTAL TEACHERS =       39722.

 

 DISTRIBUTION OF TEACHERS

  BY AGE

   0‑4          2423.

   5‑9         16112.

  10‑14        12919.

  15‑19         8268.

  20‑24            0.

  25‑29            0.

  30‑34            0.

  35‑39            0.

  40‑44            0.

  45‑49            0.

  50‑54            0.

  55‑59            0.

  60‑64            0.

  65‑69            0.

  70‑74            0.

  75+              0.

 

 DISTRIBUTION OF TEACHERS

  BY REGION

 APACHE          997.

 COCHISE        1020.

 COCONINO       1126.

 GILA            445.

 GRAHAM          293.

 GREENLEE        119.

 MARICOPA      19601.

 MOHAVE          836.

 NAVAJO         1070.

 PIMA           6836.

 PINAL          1159.

 STA.CRUZ        256.

 YAVAPAI         952.

 YUMA           1170.

 

 DISTRIBUTIONAL ANALYSIS OF SALARIES

 

 TOTAL SALARIES =   683216526.

 

 DISTRIBUTION OF SALARIES

  BY AGE

   0‑4      41667598.

   5‑9     277127660.

  10‑14    222212066.

  15‑19    142209203.

  20‑24            0.

  25‑29            0.

  30‑34            0.

  35‑39            0.

  40‑44            0.

  45‑49            0.

  50‑54            0.

  55‑59            0.

  60‑64            0.

  65‑69            0.

  70‑74            0.

  75+              0.

 

 DISTRIBUTION OF SALARIES

  BY REGION

 APACHE     17142535.

 COCHISE    17538363.

 COCONINO   19369276.

 GILA        7650993.

 GRAHAM      5044023.

 GREENLEE    2044383.

 MARICOPA  337133416.

 MOHAVE     14370726.

 NAVAJO     18399076.

 PIMA      117583189.

 PINAL      19938284.

 STA.CRUZ    4396677.

 YAVAPAI    16374272.

 YUMA       20118045.


Listing 15.  CHECK Run for Example 8 (Criminal Justice, Projection of Prison Admissions and Operating Cost)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:29: 1

 

 NAME OF PARAMETER FILE = AZ803CP.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 3

 NO OF REGIONS = 14

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 1

 SERVICE SYSTEM OPTION = 1

 NAME(S) OF RACE    ...

      WHITE  

      AMERIND

      OTHER  

 NAME(S) OF REGION  ...

      APACHE 

      COCHISE

      COCONINO

      GILA   

      GRAHAM 

      GREENLEE

      MARICOPA

      MOHAVE 

      NAVAJO 

      PIMA   

      PINAL  

      STA.CRUZ

      YAVAPAI

      YUMA   

 

 PRINTOUT OF DEMOGRAPHIC PARAMETERS SUPPRESSED.

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 PRISON ADMISSIONS; PRISON CELLS; OBLIGATED OPERATING COST                      

 NO OF TARGET POPULATIONS =  1

 SERVICE POPULATION OPTION = 2

 NO OF SERVICES =  1

 NO OF RESOURCES =  1

 NO OF COST CATEGORIES =  1

 NAME(S) OF TARG POP...

      ADMIS'NS

 NAME(S) OF SERV POP...

      SENTYR 

 NAME(S) OF SERVICE ...

      INCARC'N

 NAME(S) OF RESOURCE...

      CELL   

 NAME(S) OF COST    ...

      OP COST

 SERVICE PARAMETERS FOR SERVICE POPULATION = SENTYR 

      INCARC'N      1.0000

 RESOURCE PARAMETERS FOR SERVICE = INCARC'N

      CELL          1.0000

 COST PARAMETERS FOR RESOURCE = CELL   

      OP COST   16000.0000

 

 TARGET   POPULATION = ADMIS'NS

 TYPE OF STRATIFICATION =  5

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00000000

    2     .00200000

    3     .00400000

    4     .00300000

    5     .00100000

    6     .00030000

    7     .00007000

    8     .00020000

    9     .00002000

 INDICES, BY STRATUM...

         MALE   

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    2

       20‑24    3

       25‑29    4

       30‑34    2

       35‑39    5

       40‑44    5

       45‑49    5

       50‑54    5

       55‑59    6

       60‑64    7

       65‑69    7

       70‑74    7

       75+      7

         FEMALE 

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    8

       20‑24    8

       25‑29    8

       30‑34    8

       35‑39    7

       40‑44    7

       45‑49    7

       50‑54    9

       55‑59    9

       60‑64    1

       65‑69    1

       70‑74    1

       75+      1

 

 SERVICE  POPULATION = SENTYR 

 TYPE OF STRATIFICATION =  3

 SERVICE RATIO(S)...                            

 MALE    3.00000000

 FEMALE  2.30000000


Listing 16.  PROJ Run for Example 8 (Criminal Justice, Projection of Prison Admissions and Operating Cost)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:29:55

 

 PARAMETER FILE NAME: AZ803CP.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR: 1980

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 PRISON ADMISSIONS; PRISON CELLS; OBLIGATED OPERATING COST                      

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3735219.

 

 DISTRIBUTION OF POPULATN

  BY SEX

 MALE        1849940.

 FEMALE      1885279.

 

 DISTRIBUTIONAL ANALYSIS OF ADMIS'NS

 

 TOTAL ADMIS'NS =        2262.

 

 DISTRIBUTION OF ADMIS'NS

  BY SEX

 MALE           2118.

 FEMALE          145.

 

 DISTRIBUTIONAL ANALYSIS OF SENTYR 

 

 TOTAL SENTYR   =        6686.

 

 DISTRIBUTION OF SENTYR 

  BY SEX

 MALE           6353.

 FEMALE          333.

 

 DISTRIBUTIONAL ANALYSIS OF INCARC'N

 

 TOTAL INCARC'N =        6686.

 

 DISTRIBUTION OF INCARC'N

  BY SEX

 MALE           6353.

 FEMALE          333.

 

 DISTRIBUTIONAL ANALYSIS OF CELL   

 

 TOTAL CELL     =        6686.

 

 DISTRIBUTION OF CELL   

  BY SEX

 MALE           6353.

 FEMALE          333.

 

 DISTRIBUTIONAL ANALYSIS OF OP COST

 

 TOTAL OP COST  =   106971223.

 

 DISTRIBUTION OF OP COST

  BY SEX

 MALE      101648203.

 FEMALE      5323019.


Listing 17.  CHECK Run for Example 9 (Health Care, Projection of the Need for Short-Term and Long-Term Beds)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:32:33

 

 NAME OF PARAMETER FILE = AZ803CH.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 3

 NO OF REGIONS = 14

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 1

 SERVICE SYSTEM OPTION = 1

 NAME(S) OF RACE    ...

      WHITE  

      AMERIND

      OTHER  

 NAME(S) OF REGION  ...

      APACHE 

      COCHISE

      COCONINO

      GILA   

      GRAHAM 

      GREENLEE

      MARICOPA

      MOHAVE 

      NAVAJO 

      PIMA   

      PINAL  

      STA.CRUZ

      YAVAPAI

      YUMA   

 

 PRINTOUT OF DEMOGRAPHIC PARAMETERS SUPPRESSED.

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 NEED FOR SHORT‑TERM & LONG‑TERM BEDS (LONG‑TERM: NURSING, PSYCH, MENTAL HAND.) 

 NO OF TARGET POPULATIONS =  4

 SERVICE POPULATION OPTION = 0

 NAME(S) OF TARG POP...

      ST BEDS

      NH BEDS

      PSY BEDS

      MH BEDS

 

 TARGET   POPULATION = ST BEDS

 TYPE OF STRATIFICATION =  2

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00142000

    2     .00056000

    3     .00175000

    4     .00242000

    5     .00255000

    6     .00428000

    7     .01114000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     2

       10‑14    2

       15‑19    3

       20‑24    3

       25‑29    4

       30‑34    4

       35‑39    5

       40‑44    5

       45‑49    6

       50‑54    6

       55‑59    6

       60‑64    6

       65‑69    7

       70‑74    7

       75+      7

 

 TARGET   POPULATION = NH BEDS

 TYPE OF STRATIFICATION =  5

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00015000

    2     .00120000

    3     .01100000

    4     .06300000

    5     .01200000

    6     .09700000

    7     .00000000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

         MALE   

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    1

       20‑24    2

       25‑29    2

       30‑34    2

       35‑39    2

       40‑44    2

       45‑49    2

       50‑54    2

       55‑59    2

       60‑64    2

       65‑69    3

       70‑74    3

       75+      4

         FEMALE 

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    1

       20‑24    2

       25‑29    2

       30‑34    2

       35‑39    2

       40‑44    2

       45‑49    2

       50‑54    2

       55‑59    2

       60‑64    2

       65‑69    5

       70‑74    5

       75+      6

 

 TARGET   POPULATION = PSY BEDS

 TYPE OF STRATIFICATION =  2

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00046000

    2     .00024000

    3     .00020000

    4     .00000000

    5     .00000000

    6     .00000000

    7     .00000000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    1

       20‑24    2

       25‑29    2

       30‑34    2

       35‑39    2

       40‑44    2

       45‑49    2

       50‑54    2

       55‑59    2

       60‑64    2

       65‑69    3

       70‑74    3

       75+      3

 

 TARGET   POPULATION = MH BEDS

 TYPE OF STRATIFICATION =  2

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00092000

    2     .00095000

    3     .00024000

    4     .00000000

    5     .00000000

    6     .00000000

    7     .00000000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    1

       20‑24    2

       25‑29    2

       30‑34    2

       35‑39    2

       40‑44    2

       45‑49    2

       50‑54    2

       55‑59    2

       60‑64    2

       65‑69    3

       70‑74    3

       75+      3


Listing 18.  PROJ Run for Example 9 (Health Care, Projection of the Need for Short-Term and Long-Term Beds)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:32:50

 

 PARAMETER FILE NAME: AZ803CH.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR: 1980

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 NEED FOR SHORT‑TERM & LONG‑TERM BEDS (LONG‑TERM: NURSING, PSYCH, MENTAL HAND.) 

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 2

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     2718215.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS        8883.

 NH BEDS       13025.

 PSY BEDS        837.

 MH BEDS        2337.

 

 YEAR: 1981

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     2819125.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS        9219.

 NH BEDS       13656.

 PSY BEDS        867.

 MH BEDS        2423.

 

 YEAR: 1982

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     2920035.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS        9555.

 NH BEDS       14287.

 PSY BEDS        897.

 MH BEDS        2510.

 

 YEAR: 1983

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3020944.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS        9891.

 NH BEDS       14918.

 PSY BEDS        927.

 MH BEDS        2596.

 

 YEAR: 1984

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3121854.

 

 TOTALS OF TARGET POPULATION(S)    

 ST BEDS       10227.

 NH BEDS       15549.

 PSY BEDS        957.

 MH BEDS        2682.

 

 YEAR: 1985

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3222764.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS       10563.

 NH BEDS       16180.

 PSY BEDS        986.

 MH BEDS        2768.

 

 YEAR: 1986

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3325255.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS       10889.

 NH BEDS       16852.

 PSY BEDS       1018.

 MH BEDS        2857.

 

 YEAR: 1987

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3427746.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS       11214.

 NH BEDS       17523.

 PSY BEDS       1050.

 MH BEDS        2945.

 

 YEAR: 1988

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3530237.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS       11539.

 NH BEDS       18195.

 PSY BEDS       1082.

 MH BEDS        3034.

 

 YEAR: 1989

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3632728.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS       11864.

 NH BEDS       18867.

 PSY BEDS       1114.

 MH BEDS        3122.

 

 YEAR: 1990

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3735219.

 

 TOTALS OF TARGET POPULATION(S)   

 ST BEDS       12189.

 NH BEDS       19538.

 PSY BEDS       1146.

 MH BEDS        3211.


Listing 19.  CHECK Run for Example 10 (Social Services, Projection of Counselors and Budget Needed to Provide Social Services to the Elderly Population)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: CHECK

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:36:38

 

 NAME OF PARAMETER FILE = AZ803CS.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR = 1980

 

 NO OF RACIAL/ETHNIC GROUPS = 3

 NO OF REGIONS = 14

 VITAL STATISTICS PARAMETER OPTION = 1

 LIFE TABLE OPTION = 1

 EXTERNAL MIGRATION OPTION = 1

 INTERNAL MIGRATION OPTION = 1

 SERVICE SYSTEM OPTION = 1

 NAME(S) OF RACE    ...

      WHITE  

      AMERIND

      OTHER  

 NAME(S) OF REGION  ...

      APACHE 

      COCHISE

      COCONINO

      GILA   

      GRAHAM 

      GREENLEE

      MARICOPA

      MOHAVE 

      NAVAJO 

      PIMA   

      PINAL   

      STA.CRUZ

      YAVAPAI

      YUMA   

 

 PRINTOUT OF DEMOGRAPHIC PARAMETERS SUPPRESSED.

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 SOCIAL SERVICES FOR THE ELDERLY; 8 SERVICES, 3 RESOURCES, 3 COST CATEGORIES    

 NO OF TARGET POPULATIONS =  1

 SERVICE POPULATION OPTION = 2

 NO OF SERVICES =  7

 NO OF RESOURCES =  3

 NO OF COST CATEGORIES =  3

 NAME(S) OF TARG POP...

      ELDERLY

 NAME(S) OF SERV POP...

      ELDR(SV)

 NAME(S) OF SERVICE ...

      COUNSLNG

      CHORE SV

      HOMEMAKR

      SUBSCARE

      DAY CARE

      TRANSPRT

      OTHER  

 NAME(S) OF RESOURCE...

      COUNSELR

      PURCHSVC

      PAYMENTS

 NAME(S) OF COST    ...

      DIRCTSV$

      PURCHSV$

      PAYMENT$

 SERVICE PARAMETERS FOR SERVICE POPULATION = ELDR(SV)

      COUNSLNG      2.0000

      CHORE SV     16.0000

      HOMEMAKR    750.0000

      SUBSCARE     12.0000

      DAY CARE      7.0000

      TRANSPRT     10.0000

      OTHER        10.0000

 RESOURCE PARAMETERS FOR SERVICE = COUNSLNG

      COUNSELR      1.0000

      PURCHSVC       .0000

      PAYMENTS       .0000

 RESOURCE PARAMETERS FOR SERVICE = CHORE SV

      COUNSELR       .0000

      PURCHSVC      1.0000

      PAYMENTS       .0000

 RESOURCE PARAMETERS FOR SERVICE = HOMEMAKR

      COUNSELR       .0000

      PURCHSVC      1.0000

      PAYMENTS       .0000

 RESOURCE PARAMETERS FOR SERVICE = SUBSCARE

      COUNSELR       .0000

      PURCHSVC      1.0000

      PAYMENTS       .0000

 RESOURCE PARAMETERS FOR SERVICE = DAY CARE

      COUNSELR       .0000

      PURCHSVC      1.0000

      PAYMENTS       .0000

 RESOURCE PARAMETERS FOR SERVICE = TRANSPRT

      COUNSELR       .0000

      PURCHSVC       .5000

      PAYMENTS       .5000

 RESOURCE PARAMETERS FOR SERVICE = OTHER  

      COUNSELR       .0000

      PURCHSVC       .5000

      PAYMENTS       .5000

 COST PARAMETERS FOR RESOURCE = COUNSELR

      DIRCTSV$     15.0000

      PURCHSV$       .0000

      PAYMENT$       .0000

 COST PARAMETERS FOR RESOURCE = PURCHSVC

      DIRCTSV$       .0000

      PURCHSV$      1.0000

      PAYMENT$       .0000

 COST PARAMETERS FOR RESOURCE = PAYMENTS

      DIRCTSV$       .0000

      PURCHSV$       .0000

      PAYMENT$      1.0000

 

 TARGET   POPULATION = ELDERLY

 TYPE OF STRATIFICATION =  2

 INCIDENCE/PREVALENCE RATE(S)...                

  INDEX    RATE

    1     .00000000

    2    1.00000000

    3     .00000000

    4     .00000000

    5     .00000000

    6     .00000000

    7     .00000000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    1

       20‑24    1

       25‑29    1

       30‑34    1

       35‑39    1

       40‑44    1

       45‑49    1

       50‑54    1

       55‑59    1

       60‑64    1

       65‑69    2

       70‑74    2

       75+      2

 

 SERVICE  POPULATION = ELDR(SV)

 TYPE OF STRATIFICATION =  2

 SERVICE RATIO(S)...                            

  INDEX    RATE

    1     .00000000

    2     .03000000

    3     .05000000

    4     .07000000

    5     .00000000

    6     .00000000

    7     .00000000

    8     .00000000

    9     .00000000

 INDICES, BY STRATUM...

        0‑4     1

        5‑9     1

       10‑14    1

       15‑19    1

       20‑24    1

       25‑29    1

       30‑34    1

       35‑39    1

       40‑44    1

       45‑49    1

       50‑54    1

       55‑59    1

       60‑64    1

       65‑69    2

       70‑74    3

       75+      4


Listing 20.  PROJ Run for Example 10 (Social Services, Projection of Counselors and Budget Needed to Provide Social Services to the Elderly Population)

 

 DESTINY PLANNING AND FORECASTING COMPUTER PROGRAM PACKAGE, VERSION 1.0

 

 PROGRAM NAME: PROJ

 DATE OF RUN (DD/MM/YYYY):  5/ 6/1995

 TIME OF RUN (HH:MM:SS):   13:36:48

 

 PARAMETER FILE NAME: AZ803CS.DAT    

 GENERAL POPULATION DESCRIPTION:

 ARIZONA RESIDENT POPULATION BY COUNTY AND RACE (W/I/O)                         

 BASE YEAR: 1980

 

 TARGET/SERVICE POPULATION DESCRIPTION:

 SOCIAL SERVICES FOR THE ELDERLY; 8 SERVICES, 3 RESOURCES, 3 COST CATEGORIES    

 NO OF FIVE‑YEAR PERIODS TO PROJECT = 1

 

 YEAR: 1983

 

 DISTRIBUTIONAL ANALYSIS OF POPULATN

 

 TOTAL POPULATN =     3020944.

 

 DISTRIBUTION OF POPULATN

  BY SEX

 MALE        1490114.

 FEMALE      1530830.

 

 DISTRIBUTION OF POPULATN

  BY REGION

 APACHE        56418.

 COCHISE       86046.

 COCONINO      78946.

 GILA          37068.

 GRAHAM        23057.

 GREENLEE      10853.

 MARICOPA    1564786.

 MOHAVE        62054.

 NAVAJO        70367.

 PIMA         545662.

 PINAL         90021.

 STA.CRUZ      20673.

 YAVAPAI       73847.

 YUMA          91888.

 

 DISTRIBUTIONAL ANALYSIS OF ELDERLY

 

 TOTAL ELDERLY  =      344542.

 

 DISTRIBUTION OF ELDERLY

  BY SEX

 MALE         151885.

 FEMALE       192658.

 

 DISTRIBUTION OF ELDERLY

  BY REGION

 APACHE         3592.

 COCHISE       10119.

 COCONINO       7908.

 GILA           4198.

 GRAHAM         2481.

 GREENLEE       1232.

 MARICOPA     186166.

 MOHAVE         7886.

 NAVAJO         5903.

 PIMA          63245.

 PINAL          9106.

 STA.CRUZ       2345.

 YAVAPAI        9390.

 YUMA          10114.

 

 DISTRIBUTIONAL ANALYSIS OF ELDR(SV)

 

 TOTAL ELDR(SV) =       17254.

 

 DISTRIBUTION OF ELDR(SV)

  BY SEX

 MALE           7505.

 FEMALE         9748.

 

 DISTRIBUTION OF ELDR(SV)

  BY REGION

 APACHE          181.

 COCHISE         507.

 COCONINO        396.

 GILA            210.

 GRAHAM          124.

 GREENLEE         62.

 MARICOPA       9322.

 MOHAVE          395.

 NAVAJO          296.

 PIMA           3167.

 PINAL           456.

 STA.CRUZ        117.

 YAVAPAI         470.

 YUMA            506.

 

 DISTRIBUTIONAL ANALYSIS OF COUNSLNG

 

 TOTAL COUNSLNG =       34507.

 

 DISTRIBUTION OF COUNSLNG

  BY SEX

 MALE          15010.

 FEMALE        19497.

 

 DISTRIBUTION OF COUNSLNG

  BY REGION

 APACHE          361.

 COCHISE        1013.

 COCONINO        793.

 GILA            421.

 GRAHAM          248.

 GREENLEE        123.

 MARICOPA      18645.

 MOHAVE          790.

 NAVAJO          592.

 PIMA           6334.

 PINAL           911.

 STA.CRUZ        235.

 YAVAPAI         941.

 YUMA           1012.

 

 DISTRIBUTIONAL ANALYSIS OF CHORE SV

 

 TOTAL CHORE SV =      276057.

 

 DISTRIBUTION OF CHORE SV

  BY SEX

 MALE         120083.

 FEMALE       155973.

 

 DISTRIBUTION OF CHORE SV

  BY REGION

 APACHE         2890.

 COCHISE        8106.

 COCONINO       6343.

 GILA           3366.

 GRAHAM         1988.

 GREENLEE        987.

 MARICOPA     149160.

 MOHAVE         6322.

 NAVAJO         4740.

 PIMA          50668.

 PINAL          7292.

 STA.CRUZ       1878.

 YAVAPAI        7527.

 YUMA           8100.

 

 DISTRIBUTIONAL ANALYSIS OF HOMEMAKR

 

 TOTAL HOMEMAKR =    12940160.

 

 DISTRIBUTION OF HOMEMAKR

  BY SEX

 MALE        5628914.

 FEMALE      7311246.

 

 DISTRIBUTION OF HOMEMAKR

  BY REGION

 APACHE       135452.

 COCHISE      379987.

 COCONINO     297316.

 GILA         157762.

 GRAHAM        93181.

 GREENLEE      46267.

 MARICOPA    6991865.

 MOHAVE       296350.

 NAVAJO       222174.

 PIMA        2375079.

 PINAL        341809.

 STA.CRUZ      88026.

 YAVAPAI      352815.

 YUMA         379681.

 

 DISTRIBUTIONAL ANALYSIS OF SUBSCARE

 

 TOTAL SUBSCARE =      207043.

 

 DISTRIBUTION OF SUBSCARE

  BY SEX

 MALE          90063.

 FEMALE       116980.

 

 DISTRIBUTION OF SUBSCARE

  BY REGION

 APACHE         2167.

 COCHISE        6080.

 COCONINO       4757.

 GILA           2524.

 GRAHAM         1491.

 GREENLEE        740.

 MARICOPA     111870.

 MOHAVE         4742.

 NAVAJO         3555.

 PIMA          38001.

 PINAL          5469.

 STA.CRUZ       1408.

 YAVAPAI        5645.

 YUMA           6075.

 

 DISTRIBUTIONAL ANALYSIS OF DAY CARE

 

 TOTAL DAY CARE =      120775.

 

 DISTRIBUTION OF DAY CARE

  BY SEX

 MALE          52537.

 FEMALE        68238.

 

 DISTRIBUTION OF DAY CARE

  BY REGION

 APACHE         1264.

 COCHISE        3547.

 COCONINO       2775.

 GILA           1472.

 GRAHAM          870.

 GREENLEE        432.

 MARICOPA      65257.

 MOHAVE         2766.

 NAVAJO         2074.

 PIMA          22167.

 PINAL          3190.

 STA.CRUZ        822.

 YAVAPAI        3293.

 YUMA           3544.

 

 DISTRIBUTIONAL ANALYSIS OF TRANSPRT

 

 TOTAL TRANSPRT =      172535.

 

 DISTRIBUTION OF TRANSPRT

  BY SEX

 MALE          75052.

 FEMALE        97483.

 

 DISTRIBUTION OF TRANSPRT

  BY REGION

 APACHE         1806.

 COCHISE        5066.

 COCONINO       3964.

 GILA           2103.

 GRAHAM         1242.

 GREENLEE        617.

 MARICOPA      93225.

 MOHAVE         3951.

 NAVAJO         2962.

 PIMA          31668.

 PINAL          4557.

 STA.CRUZ       1174.

 YAVAPAI        4704.

 YUMA           5062.

 

 DISTRIBUTIONAL ANALYSIS OF OTHER  

 

 TOTAL OTHER    =      172535.

 

 DISTRIBUTION OF OTHER  

  BY SEX

 MALE          75052.

 FEMALE        97483.

 

 DISTRIBUTION OF OTHER  

  BY REGION

 APACHE         1806.

 COCHISE        5066.

 COCONINO       3964.

 GILA           2103.

 GRAHAM         1242.

 GREENLEE        617.

 MARICOPA      93225.

 MOHAVE         3951.

 NAVAJO         2962.

 PIMA          31668.

 PINAL          4557.

 STA.CRUZ       1174.

 YAVAPAI        4704.

 YUMA           5062.

 

 TOTALS OF SERVICE(S)             

 COUNSLNG      34507.

 CHORE SV     276057.

 HOMEMAKR   12940160.

 SUBSCARE     207043.

 DAY CARE     120775.

 TRANSPRT     172535.

 OTHER        172535.

 

 DISTRIBUTION OF SERVICE(S)             

  BY SERVED POPULATION(S)   

            COUNSLNG    CHORE SV    HOMEMAKR    SUBSCARE    DAY CARE    TRANSPRT    OTHER  

 ELDR(SV)      34507.     276057.   12940160.     207043.     120775.     172535.     172535.

 TOTAL         34507.     276057.   12940160.     207043.     120775.     172535.     172535.

 

 DISTRIBUTIONAL ANALYSIS OF COUNSELR

 

 TOTAL COUNSELR =       34507.

 

 DISTRIBUTION OF COUNSELR

  BY SEX

 MALE          15010.

 FEMALE        19497.

 

 DISTRIBUTION OF COUNSELR

  BY REGION

 APACHE          361.

 COCHISE        1013.

 COCONINO        793.

 GILA            421.

 GRAHAM          248.

 GREENLEE        123.

 MARICOPA      18645.

 MOHAVE          790.

 NAVAJO          592.

 PIMA           6334.

 PINAL           911.

 STA.CRUZ        235.

 YAVAPAI         941.

 YUMA           1012.

 

 DISTRIBUTIONAL ANALYSIS OF PURCHSVC

 

 TOTAL PURCHSVC =    13716570.

 

 DISTRIBUTION OF PURCHSVC

  BY SEX

 MALE        5966649.

 FEMALE      7749921.

 

 DISTRIBUTION OF PURCHSVC

  BY REGION

 APACHE       143580.

 COCHISE      402786.

 COCONINO     315155.

 GILA         167228.

 GRAHAM        98772.

 GREENLEE      49043.

 MARICOPA    7411377.

 MOHAVE       314131.

 NAVAJO       235504.

 PIMA        2517584.

 PINAL        362317.

 STA.CRUZ      93307.

 YAVAPAI      373984.

 YUMA         402462.

 

 DISTRIBUTIONAL ANALYSIS OF PAYMENTS

 

 TOTAL PAYMENTS =      172535.

 

 DISTRIBUTION OF PAYMENTS

  BY SEX

 MALE          75052.

 FEMALE        97483.

 

 DISTRIBUTION OF PAYMENTS

  BY REGION

 APACHE         1806.

 COCHISE        5066.

 COCONINO       3964.

 GILA           2103.

 GRAHAM         1242.

 GREENLEE        617.

 MARICOPA      93225.

 MOHAVE         3951.

 NAVAJO         2962.

 PIMA          31668.

 PINAL          4557.

 STA.CRUZ       1174.

 YAVAPAI        4704.

 YUMA           5062.

 

 TOTALS OF RESOURCE(S)            

 COUNSELR      34507.

 PURCHSVC   13716570.

 PAYMENTS     172535.

 

 DISTRIBUTION OF RESOURCE(S)            

  BY SERVED POPULATION(S)   

            COUNSELR    PURCHSVC    PAYMENTS

 ELDR(SV)      34507.   13716570.     172535.

 TOTAL         34507.   13716570.     172535.

 

 DISTRIBUTION OF RESOURCE(S)            

  BY SERVICE(S)             

            COUNSELR    PURCHSVC    PAYMENTS

 COUNSLNG      34507.          0.          0.

 CHORE SV          0.     276057.          0.

 HOMEMAKR          0.   12940160.          0.

 SUBSCARE          0.     207043.          0.

 DAY CARE          0.     120775.          0.

 TRANSPRT          0.      86268.      86268.

 OTHER             0.      86268.      86268.

 TOTAL         34507.   13716570.     172535.

 

 DISTRIBUTIONAL ANALYSIS OF DIRCTSV$

 

 TOTAL DIRCTSV$ =      517606.

 

 DISTRIBUTION OF DIRCTSV$

  BY SEX

 MALE         225157.

 FEMALE       292450.

 

 DISTRIBUTION OF DIRCTSV$

  BY REGION

 APACHE         5418.

 COCHISE       15199.

 COCONINO      11893.

 GILA           6310.

 GRAHAM         3727.

 GREENLEE       1851.

 MARICOPA     279675.

 MOHAVE        11854.

 NAVAJO         8887.

 PIMA          95003.

 PINAL         13672.

 STA.CRUZ       3521.

 YAVAPAI       14113.

 YUMA          15187.

 

 DISTRIBUTIONAL ANALYSIS OF PURCHSV$

 

 TOTAL PURCHSV$ =    13716570.

 

 DISTRIBUTION OF PURCHSV$

  BY SEX

 MALE        5966649.

 FEMALE      7749921.

 

 DISTRIBUTION OF PURCHSV$

  BY REGION

 APACHE       143580.

 COCHISE      402786.

 COCONINO     315155.

 GILA         167228.

 GRAHAM        98772.

 GREENLEE      49043.

 MARICOPA    7411377.

 MOHAVE       314131.

 NAVAJO       235504.

 PIMA        2517584.

 PINAL        362317.

 STA.CRUZ      93307.

 YAVAPAI      373984.

 YUMA         402462.

 

 DISTRIBUTIONAL ANALYSIS OF PAYMENT$

 

 TOTAL PAYMENT$ =      172535.

 

 DISTRIBUTION OF PAYMENT$

  BY SEX

 MALE          75052.

 FEMALE        97483.

 

 DISTRIBUTION OF PAYMENT$

  BY REGION

 APACHE         1806.

 COCHISE        5066.

 COCONINO       3964.

 GILA           2103.

 GRAHAM         1242.

 GREENLEE        617.

 MARICOPA      93225.

 MOHAVE         3951.

 NAVAJO         2962.

 PIMA          31668.

 PINAL          4557.

 STA.CRUZ       1174.

 YAVAPAI        4704.

 YUMA           5062.

 

 TOTALS OF COST CATEGORY(IES)     

 DIRCTSV$     517606.

 PURCHSV$   13716570.

 PAYMENT$     172535.

 

 DISTRIBUTION OF COST CATEGORY(IES)     

  BY SERVED POPULATION(S)   

            DIRCTSV$    PURCHSV$    PAYMENT$

 ELDR(SV)     517606.   13716570.     172535.

 TOTAL        517606.   13716570.     172535.

 

 DISTRIBUTION OF COST CATEGORY(IES)     

  BY SERVICE(S)             

            DIRCTSV$    PURCHSV$    PAYMENT$

 COUNSLNG     517606.          0.          0.

 CHORE SV          0.     276057.          0.

 HOMEMAKR          0.   12940160.          0.

 SUBSCARE          0.     207043.          0.

 DAY CARE          0.     120775.          0.

 TRANSPRT          0.      86268.      86268.

 OTHER             0.      86268.      86268.

 TOTAL        517606.   13716570.     172535.

 

 DISTRIBUTION OF COST CATEGORY(IES)     

  BY RESOURCE(S)            

            DIRCTSV$    PURCHSV$    PAYMENT$

 COUNSELR     517606.          0.          0.

 PURCHSVC          0.   13716570.          0.

 PAYMENTS          0.          0.     172535.

 TOTAL        517606.   13716570.     172535.