Demographic Estimates & Projections

Demographic Estimates and Projections from both AGS and ESRI-BIS are now available from RPM.

Applied Geographic Solutions

Applied Geographic Solutions was incorporated early in 1997 in response to the rapidly decreasing number of reliable demographic data providers in the United States. The primary mission of AGS is to provide a reliable and cost-effective alternative source of demographics to the market analysis community.

AGS demographics are produced by Gary Menger, a fifteen-year veteran in both the domestic and international geodemographics industry with a wealth of experience in the development and dissemination of small-area demographic data. He has produced consistent and well-respected small area demographic estimates and projections in both Canada and the United States for the past twelve years, producing the most extensive set of updates currently available for the United States.

About AGS Demographic Estimates & Projections

A very select group of AGS Estimates & Projections (E&P) variables that RPM has shown are particularly important in financial services has been selected for use in dataBank.

The Estimates and Projections database consists of a wide range of demographic attributes that together cover the key demographic characteristics of an area. A wide range of data sources are utilized in constructing the estimates and projections, including:

• Census Bureau estimates and projections of population characteristics
• Bureau of Labor Statistics estimates employment by industry and occupation
• Medicare eligible population by 5 year age cohort counts at the ZIP code level
• Internal Revenue Service statistics on tax filers and year-to-year migration
• The Census Bureau’s Current Population Survey
• Experian’s Performance Data System (PDS)

PDS is a vast database at the household and individual level that Experian provides to AGS for use in its demographic estimates. The PDS files were aggregated to the ZIP+4 and Block Group levels of geography for analysis and standardized to Census Bureau county level current estimates. A large number of demographic attributes from PDS were utilized in building the 1998 estimates, including population by age, household size and type, marital status, income, and dwelling tenure.

The estimates and projections methodology combines the best current and projected information from the data sources noted above. It is supplemented by the extensive experience of Applied Geographic Solutions in creating accurate and reliable estimates and projections. A summary of the methodology for each of the major variable groups is included in the sections that follow.

The current population of the United States is obtained from the monthly Census population estimate. This is a very accurate and current estimate of the population and serves as the basis for projection and estimation at lower levels of geographic detail. The five and ten year projections have been derived from the middle-series projections of the Census Bureau.

State and county level estimates are based on the compilation of data from a range of Federal and State authorities, including the latest county population estimates from the Census Bureau, reviews of building permit statistics, the current population survey (CPS), and additional local sources. Where required, the resulting estimates are then ratio-adjusted so that the sum of the county estimates is equal to the state total, and the state estimates equal to the national total. For the five- and ten-year projections, a similar method is employed. However, rather than using simple straight-line techniques, AGS uses straight-line methods only for growing areas. For declining areas, a log-normal extrapolation is used. This has the effect of slowing decline over time, which is characteristic of long term population decline at the state level.

At the block group level, the population model consists of the application of a non-linear trend model which estimates population given historical patterns, PDS population counts, and the latest Census age distributions (using cohort-survival techniques). Special consideration is given to the population age 65+ by applying ZIP code level counts by age and sex of all Medicare eligible persons. This provides considerable improvement in the estimates of this important segment of the population. The final results are then carefully balanced to the county and city level population estimates to ensure consistency with current Census Bureau estimates.

The result is a comprehensive set of population estimates and projections which includes the knowledge of State, County, and private agencies about their detailed areas but also ensures that the total population is consistent with the Census Bureau estimates, which have proved extremely reliable over time.

Population By Age, Sex, and Race

National and State level Census bureau projections of age by sex and race/Hispanic origin were used as overall controls to ensure consistency with the Census projections. Detailed forecasts by age, sex, and race, as well as Hispanic origin, were obtained from the Census Bureau ‘middle series’ projections.

At the state level, the projections of individual state agencies were combined with the results of a cohort survival approach to obtain reliable state estimates by age and sex. The block group estimates were compiled using cohort survival methods, then balanced to both the estimated block group population totals and to the state level control totals. Consistency checks with the annual CPS (Current Population Survey) are used to ensure the validity of the resulting age/sex distributions. Further, PDS population by age statistics were used to adjust local estimates for the adult population, with further adjustments applied using the ZIP code level Medicare eligibility statistics.

Trends in the racial distribution and Hispanic populations were used to derive a preliminary estimate at the block group level, which were then adjusted to balance with appropriate control totals. This method allows the utilization of the historical changes in race and Hispanic origin distributions and project those changes into the future while maintaining consistency with national level projections. Again, the CPS is used extensively to assist in the verification of the models.

Total households were modeled by projecting trends in the population per household over time at the national level to provide a control total and reviewing currently available household size statistics at the State level.

All household based numbers are initially estimated / projected separately for family and non-family households. Non-family households have been growing in number at a higher rate than family households over the past several decades. Average household sizes for family households have been decreasing for several decades. However, during the 1990’s, the decline has stopped in most areas and has actually reversed in several states.

The group quarters population, that is population which is not in households (such as persons in institutions, military barracks, nursing homes, college dormitories, and homeless persons), is expected to increase slightly during the decade, but remain relatively constant as a percentage of the total population. This is a reflection of two trends: the decreasing armed forces employment since the 1980’s and the longer term increasing elderly population which results in high populations in nursing homes and other institutions which cater to the elderly population. As a result, the total group quarters population has been relatively constant.

Income

All income estimates produced by Applied Geographic Solutions are in current, rather than constant, dollars. In other words, a projection of income for the year 2008 includes both an inflationary component and a ‘real’ component, the latter being the difference between the change in income and the change in inflation during the period. The ‘real’ component is normally attributed to productivity gains in the economy and to differences in the competitiveness of the economy relative to other nations.

Aggregate income estimates for the current year are based on an analysis of changes in per capita income between the 1990 Census and the most recently available income statistics (Census Bureau and IRS) at the national, state, and county levels. The projections of aggregate income are based on a review of Bureau of Economic Analysis (BEA) projections, which assume an effective increase of 3.5% per annum in per capita incomes during the next ten years at the national level.

Income distributions are estimated and projected for both family households and non-family households separately. Income distributions were derived by using a complex distribution shifting technique which utilizes the changes in per family household and non-family household incomes as a means of adjusting the income distributions over time. The relative ratio between changes in per household average incomes and median incomes were used to adjust for above-average growth in high-income households within some geographic areas. The resulting distributions were then normalized to higher order totals and adjusted to national level expectations and were verified for internal consistency with respect to the mean and median measures.

Current employment characteristics are available from a range of sources covering unemployment rates, labor force participation rates, and occupations. The primary information sources are the Bureau of Labor statistics and the Census Bureau. Projections are based on a set of county level projections compiled by the Bureau of Labor Statistics, using the "moderate growth" series. It should be noted that there are substantial differences in the population estimates and projections between the BLS and Census estimates. The BLS numbers were therefore used as an allocation guide rather than in absolute form, as the Census estimates are generally considered more reliable. Below the county level, 1990 Census breakdowns were used as a base for simultaneously adjusting to the new labor force totals at the block level and the updated industry/occupation breakdowns at the county level. The method used is a maximum entropy matrix balance, which ensures that the new totals will be met with minimal change to the overall structure of the original detailed matrix. In simple terms, it adjusts the values as little as possible to ensure that the new totals are reflected.

About ESRI-BIS