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IV. POPULATION ESTIMATES AND PROJECTIONS

Standards of service provide important assessments of existing public facilities and programs in light of desired objectives and the population/client groups to be served.

Estimates of future population, including demographic and geographic distribution, are required to translate these standards into future capital improvement needs.

Demographic Techniques

Until very recently demographic projections (frequently known as "conditional forecasts") have had no predictive pretensions.

Demographers often apply a range of projections in lieu of more definitive estimates of future population characteristics. Such parameters usually are extrapolated from current data with insufficient detail to be of much utility to the capital facilities planner.

The basic demographic equation is P2 = P1 + B - D + I - O, which indicates that the population at any given point in time (P2) is a function of the population at a previous point in time (P1) plus the amount of natural increase (births minus deaths) and the net migration (in-migration minus out-migration) during the interim.

Population estimates are used to update population data gathered from the last census to approximate the current situation.

Population projections refer to future population levels and indicate what changes might occur, given assumptions inherent in the projection method and data. Analysts typically develop more than one set of projections, each set embodying different assumptions.

A population forecast is the set of projections deemed most likely to occur. Projections do not necessarily lead to forecasts.

o Sets of projections often are prepared, ranging from slow growth to rapid growth, so that users may select the forecast that most closely approximate their needs.

o Alternative projections may be based on the same method, differing only in their designated growth rates, birth rates, population densities, and so forth.

Population change involves three separate components: births, deaths, and migration.

o Component models consider the separate effects of each of these factors.

o Noncomponent models use the net effects of the three components.

Noncomponent models may be based on past patterns of net population growth or may relate net growth to some indicator, such as changes in housing or the economic base of the community.

Symptomatic data are used to determine a correlation between population size and various other events, such as tax returns, voter registration, school enrollments, utility connections, telephone installations, occupancy permits issued, and motor vehicle licenses.

Noncomponent models lack detailed age-sex breakdowns which are useful in planning for schools, community services, and different housing types.

Most models that project population below the state scale are usually of the noncomponent variety because of data limitations (and demographic skills).

Births and deaths are referred to as vital statistics, usually available on an annual basis.

o Natural increase (or decrease) is numerical difference between births and deaths.

o A crude death rate is a gross statistic which indicates the number of deaths per 1,000 of population; it provides no age-sex detail.

o A crude birth rate indicates births per 1,000 population, but provides no age-sex information.

o General fertility rate is the ratio of births to women of child-bearing age (15 to 44 years of age).

o Age specific fertility rate provides a greater level of specification by calculating fertility rates for each 5-year age cohort of women.

o Birth rates and fertility rates change fairly slowly, and are subject to regional, racial, and ethnic differences.

o Birth rates used in population projections often are determined empirically for the area under analysis.

Migration is subject to relatively rapid fluctuations and is influenced by the location, size, shape, and economic base of the locality. A large county or city will have a lower proportion of migrants than will a small one, since many moves cover a relatively short distance.

The intercensal component method of estimating migration makes use of the population balancing equation which rewrites the basic population equation as follows: I - O = P2 - P1 - B + D

The reverse survival rate method may be used to produce net migration estimates by age, race, and sex groups.

o Estimates of net migration are produced by applying 10-year survival rates to the number of individuals recorded in a particular cohort in the earlier census in order to predict members in that cohort who should have survived to the current census.

o The difference between the actual number of individuals in the cohort that has been "aged" by 10 years and the estimated number based on the survival rate is assumed to be the estimated migration.

Types of Population Models

In choosing a population model, it is important to consider its relative accuracy, the type of data available, the quality of available data, the scale of the analysis, the length of the projection period, the purpose of the projections, and the budget and time frame implications of the study.

Trend extrapolation is involved, to some extent, in nearly all projection methods.

o This model uses historical growth patterns to project the future pattern, dealing with the net effects of births, deaths, and migration rather than with individual components.

o The primary disadvantage is the lack of detail regarding the components of population.

Comparative forecasting examines the locality's past growth pattern in conjunction with growth patterns of older, larger, civil divisions, the assumption being that the locality's pattern will match that of communities more advanced in their stage of growth.

Ratio trend or step-down techniques assume that the relationship of a locality to some larger geographic entity--county or state--will prevail in the future and that population projections at the larger scale represent degrees of reliability and component detail that are not possible to achieve at the smaller scale of analysis.

Density ceiling models use capacity constraints by assuming that when a given density is reached, population will either stabilize or decline.

o The density model may utilize linear, exponential, or logistic curves to express population density growth rates.

o Maximum population levels typically determined via zoning and land use development patterns that affect population density.

The ratio correlation method is similar to the ratio trend method except that population is treated as a function of some other independent variables--employment, housing units, motor vehicles registered, or other symptomatic data. Multiple regression may be used to determine the population's historic relationship to the independent variables.

The housing unit method establishes a relationship between the number of dwelling units and population via a family-size multiplier.

o Net changes in dwelling units presumed to indicate net changes in population.

o Dwelling units can be estimated by utility or telephone connections, building permit data, land use surveys, vacancy rates, home interviews, and other local records.

Market force methods include: deterministic regression models, holding capacity, multiplier studies, and mathematical programming.

o Linear regression may be used to formulate equations that will relate population distribution to such factors as vacant land, the presence of minority group populations, accessibility to work, land values, and other important variables.

o Employment forecasts made by shift and share, economic base, and input-output techniques may be converted by the use of multipliers to population forecasts.

o The future population distributions may be modeled to represent improved conditions in which a specific objective is sought--such as minimizing travel time to work--subject to equations representing constraints on supply and demand for developable land, avail-ability of services, and other factors.

The Greenberg-Kruckeberg-Mautner (GKM) model combines historical extrapolation, ratio trend, and density ceiling alternatives at the local scale, constrained by federal-state-county projections developed by component and market force techniques, and provides the option of five separate submodels to project local population.

The residual method--through an examination of the records of births and deaths, the known population (based on the last census) is adjusted accordingly to produce an estimate of current population--the difference between this anticipated population and the actual population is assumed to be the result of net migration.

The vital rates method is a ratio technique that relates total population to births and deaths.

o Ratios between state and local births and deaths are derived from the historical records and are then used to develop estimated populations based on births and deaths.

o Estimates based on the ratio are averaged to reduce errors involved in each of the projections.

o Rapid migration, which affects the age structure, will impact the vital statistics, resulting in inaccurate estimates.

Cohort-survival models project future population based on growth due to natural increase.

o The population is disaggregated into male and female age five-year cohorts, and age-specific death rates (or survival rates) are developed and applied to each cohort.

o Age-specific fertility rates are applied to female cohorts between the ages of 15 and 44.

o Each cohort group is then "aged forward" towards the final projection year, with mortality and fertility rates applied to the survivors at five year intervals.

o Births are added to the bottom of the pyramid and aged forward accordingly.

Various cohort-component methods have been developed by the Bureau of the Census.

o Method I uses school enrollment data to estimate the migration component--net migration is assumed to be the difference between the growth rate of school-age cohorts at the national level and the growth rate of school-age population at the scale of analysis.

o Method II assumes that the migration component is the difference between the anticipated school-age population, based on natural increase, and the actual population of school age. A variation of Method II is the grade progression method that breaks down school enrollment by grades.

The composite model applies various techniques to different segments of the total population.

o Instead of analyzing the components of change, the population is projected for different age groups using different methods and then summed for a total population figure.

o It takes advantage of the fact that different methods are better focused for estimating population of different groups.

The choice of the methods employed to develop population estimates or projections usually involves a trade-off of some sort with the level of accuracy required, the availability of data, and the composition of the final product as the chief determining factors.

Exhibit 1. Comparison of Population Estimation & Projection Methods