Current Year Estimates and Projections - AGS (Applied Geographic Solutions) Variable Groups

The Estimates and Projections (E&P) database is the most extensive update available, covering a broad range of demographic characteristics for the current year, and 5- year projections. Variables include:

·                  Population

·                  Population by household type (family, non-family, group quarters)

·                  Households

·                  Households by type (family, non-family)

·                  Households by size of household

·                  Households by age of head of household

·                  Household type (e.g. lone parent male family with children)

·                  Average Household Size

·                  Population by age (19 age breaks)

·                  Population by age and sex (38 breaks)

·                  Population by sex

·                  Population by race

·                  Population by Hispanic origin

·                  Population by race and Hispanic origin (e.g. white Hispanic, white non-Hispanic)

·                  Population by Marital Status

·                  Population by Educational Achievement

·                  Labor Force Employment Status

·                  Labor Force Employment Status by Sex

·                  Aggregate Income (family, non-family households, group quarters)

·                  Household income distribution (15 breaks)

·                  Family income distribution (15 breaks)

·                  Extended Upper-Income distributions

·                  Median and average income (family, household)

·                  Households by Disposable Income

·                  Age of head of household by income

·                  Median income by age of head of household

·                  Vacant Dwellings

·                  Tenure

·                  Length of Residence

·                  Total Vehicles Available

·                  Households by number of vehicles available

·                  Households by number of vehicles available and tenure

Methodologies and Data Sources

AGS uses a wide range of data sources in constructing its estimates and projections, including:

·                  Census Bureau tabulations from 1970, 1980, 1990 and most recently, the release of the 2000 Census

·                  USPS and commercial source ZIP+4 level delivery statistics

·                  Census Bureau estimates and projections of population characteristics at various levels of geographic detail, including the latest estimates of population at the city level

·                  The Census Bureau's American Community Survey results, which cover over 60% of the national population and serve as an increasingly important attribute base at the county, metro, and state levels.

·                  Bureau of Labor Statistics estimates and projections of employment by industry and occupation at the county level

·                  Medicare eligible population counts at the ZIP code level, including population by sex and 5-year age cohorts, provided by the Health Care Financing Administration of Social Security. These counts provide a very accurate local count of the population aged 65 and higher.

·                  Internal Revenue Service statistics on tax filers and year-to-year migration

·                  Census Bureau's Current Populations Survey (CPS), which provides detailed demographic breakdowns and enables a thorough longitudinal analysis of demographic trends

·                  Experian's INSOURCE, a household level credit and demographic database which covers the vast majority of households

INSOURCE is a vast database at the household and individual level that Experian provides to AGS for use in its demographic estimates. The INSOURCE database was 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 INSOURCE were utilized in building the current year estimates, including:

·                  Population

·                  Population by Age

·                  Households

·                  Household Size

·                  Household Type (presence of children)

·                  Marital Status

·                  Income

·                  Hispanic origin

·                  Population of Asian origin

·                  Dwelling Tenure (own/rent)

·                  Length of Residence

In turn, the AGS demographic estimates are used as the foundation of Experian's U.S. MOSAIC segmentation system.

Now in its seventh year of use within the AGS estimates methodology, INSOURCE provides an excellent source of small area year-to-year change which greatly improves the quality of local estimates, especially in areas of growth.

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.

Summary of Methodology for each Major Variable Group

Population

The current population of the United States is obtained from the monthly Census Bureau 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 year projections have been derived from the middle-series projections of the Census Bureau.

The current year estimates rely heavily on the 2000 Census block level population counts, as these provide the most accurate recent data available. These 2000 Census counts replace the 1990 Census counts as the basis for undertaking estimates. In effect, the latest Census tabulation provides a baseline for the estimates and projections.

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, the American Community Survey, 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, INSOURCE 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, INSOURCE population by age summaries 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 preliminary estimates 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 projects 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.

Households and Household Type

Total households were modeled by:

·                  projecting trends in the population per household over time at the national level to provide a control total;

·                  reviewing currently available household size statistics at the State level; and utilizing the current estimates of population by age and sex to determine household formation rates for small areas

The ACS data has been extensively used in order to bridge the gap between population estimates and dwelling/postal delivery counts.

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 have 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 that 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

Income estimates include aggregate income by household type and income distributions as well as derived measures include per capita income, and various median income measures.

All income estimates produced by AGS (Applied Geographic Solutions) are in current, rather than constant, dollars. In other words, a projection of income for the year 2010 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 international competitiveness of the economy.

Aggregate income estimates for the current year are based on an analysis of income information from the SF3 database of Census 2000, supplemented heavily by the 2003 ACS estimates. 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. Total household income distributions are simply the aggregate of the two detailed distributions.

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.

As of the 2003 release, for the current year estimates, a new set of income breaks are provided for the $150,000+ category, namely $150000-$199999, $200000-$249999, $250000-$499999, and $500000+. Created by using logistic regression techniques that account for the local income distribution, these should be considered as maximum likelihood estimates. Although little data exists to substantiate incomes in these ranges, comparisons have been made to IRS taxation statistics to ensure that the results are consistent. Users are cautioned that these estimates are statistical in nature only.

Employment Characteristics

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, 2000 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.

AGS has, for the current year, not included employment by occupation or employment by industry. They will revisit these tables on a yearly basis. At present, the Bureau of Labor Statistics does not report current year estimates nor projections using the updated definitions used by the Census 2000 tabulations. These are effectively incomparable for many categories and are unsuitable as the basis for undertaking current estimates and projections. AGS will review the availability of source data on an annual basis with the intent of reinstituting these tables when it becomes feasible.

Other Variables

A number of other variables are also projected within the series. In large part, these are derived by using available current estimates and projections at the lowest possible level of geography as the base for the estimation procedures, relying heavily upon the annual release of the ACS. The CPS is used extensively to track changes using available cross-reference information related to age, race, sex, and income. Where possible, these CPS statistics are supplemented by INSOURCE estimates.

For example, current marital status estimates are available at the state level ACS from the Census Bureau as "control targets". The ACS is used in conjunction with the annual CPS surveys (both historical and current) are used to track the changes in marital status dependent upon other symptomatic variables such as age, sex, race, and income levels. These "micro-models" are then applied to the block group level changes between the census and the current period. This results in block group level data which is consistent with higher order levels but also reflects changes in marital status owing to shifting local demography.

On the other hand, vacant housing is tracked using state and regional indicators, then adjusted for seasonally vacant dwellings which are a significant component of the marketing landscape in many areas of the country.

Consumer Expenditures - Variable Groups

The Consumer Expenditure database covers most major household expenditures in a multi-level hierarchical classification. Expenditures can be expressed either as aggregate expenditure or per household expenditure for any geographic level from the block group to national. The major categories represented are:

·                  Total Expenditure

·                  Food and Beverages

·                  Shelter

·                  Utilities

·                  Household Operations

·                  Household Furnishings/Equipment

·                  Apparel

·                  Transportation

·                  Health Care

·                  Entertainment

·                  Personal Care

·                  Reading

·                  Education

·                  Tobacco Products

·                  Miscellaneous Expenses

·                  Cash Contributions

·                  Personal Insurance

·                  Gifts

Most of these categories include two or three levels of sub-category detail. For example, a typical classification for an item in the food group is:

·                  TOTAL Total Expenditure

·                           FB Food and Beverage

·                                    FB1 Food At Home

·                                             FB102 Dairy Products

·                                                      FB10201 Cheese

This structure permits ready analysis of expenditures at any level of detail and between levels of detail. It is possible to analyze any individual category within the context of its parent category (e.g. cheese expenditures as a share of total dairy product expenditures or total food at home expenditures).

Consumer Expenditure - Data Sources and Methodology

The consumer expenditure database consists of a multi-level hierarchical classification of household expenditures, which covers the majority of annual household expenditures. It is derived from an extensive modeling effort using the 2001-2002 Consumer Expenditure Survey data from the Bureau of Labor Statistics. The BLS survey is a comprehensive survey that averages over 5,000 households four times a year using a rotating sampling frame. The use of several consecutive years of data provides a rich base of expenditure data from which to build expenditure models based on household demographics.

The database consists of a total of 493 base variables, which are aggregated in up to four levels of detail. A hierarchical structure is utilized throughout, so that it is possible to aggregate or disaggregate categories as required for analysis.

The survey includes a wide range of demographic attributes related to "consuming units" (generally households), which have been modeled separately for each discrete expenditure category. The older surveys were first inflated to the current price levels using the detailed consumer price index series. For each individual expenditure category in the survey, summary statistics were calculated for each separate element in the list below. In several cases, it was possible to utilize cross tabulation data (e.g. income by age of head of household). These variables are listed below:

·                  geographic region (Northeast, South, Midwest, West)

·                  metropolitan status (metropolitan, non-metropolitan) and size (e.g. > 4 million)

·                  housing tenure (owner or renter)

·                  age of head of household (<25 years, 25-34 years, 35-44 years, 45-54 years, 55-64 years, 65-74 years, and 75+ years)

·                  size of household (1 person, 2 persons, 3 persons, 4 persons, 5 persons, 6+ persons)

·                  household income (<5000, 5-10000, 10-15000, 15-20000, 20-30000, 30-40000, 40-50000, 50-70000, 70000+)

·                  race (White, Black, American Indian, Asian)

·                  number of vehicles (none, 1, 2+ vehicles per household)

The total sample was utilized to obtain an average expenditure for each item. For each expenditure item, a series of adjustment factors were derived for each unique demographic attribute. These adjustment factors were then applied to the block group level using the same demographic variables in order to create estimates at the local level, which are consistent with local characteristics. Consistency checks were undertaken in order to ensure that the results at the block group level were consistent in the aggregate with overall income levels and published expenditures. Finally, the 2001-2002 estimates were inflated using detailed consumer price indexes to current levels.

In total, there are 393 detail categories that can be aggregated using the field name. The field name will in all cases begin with the four-character sequence X00 in order to distinguish these variables from those of other databases and from other years. The next two characters are the major group (e.g. AP for apparel). The primary detail level is a one-digit number (e.g. AP1 is men's apparel). Two sequences of two digits then follow to indicate the remaining two levels of potential detail. The entire variable list is included in the file layout section.

In addition to providing average household expenditures, AGS also provides total market estimates for use in market share and demand analysis.

Add On Options - Methodology and Data Sources

Chain Stores

This database includes information for chain supermarkets, chain drug stores, and discount stores within your geography: name, address, annual sales volume, selling square feet, annual sales per square foot, parent company name, and number of parent stores. Mapping capabilities are also provided for these datasets. Each company listing is fully updated annually and the Chain Store Guide research staff revises the database as changes in the industry occur.

The Chain Drug Stores, Chain Supermarkets and Discount Stores in this site are licensed by Chain Store Guide - A Lebhar-Friedman Company. © Copyright 2003 Business Guides Inc. (BGI). All Rights Reserved. Unauthorized use of the Data is expressly prohibited.

Traffic Counts

Dynamap®/Traffic Counts provides detailed information on the two-way average daily traffic volumes nationwide, with in-depth coverage in the metropolitan areas. Using information from state departments of transportation and local government agencies, Dynamap/Traffic Counts provides more than 400,000 points nationwide for the most complete and current coverage available. Designed to complement GDTs complete line of street network products, Dynamap/Traffic Counts overlays with other Dynamap street network products.

Aerial Photographs

Complement your DemographicsNow MapGuide maps with Aerial Photography from Aerials Express. Aerial Express used Earth Resource Mappings image processing software ER Mapper, to process all the colour mosaics of all major U.S cities. Aerial Express used high altitude mono photography of very large areas and software to match photos together perfectly. Colour balance and density were controlled so the finished mosaic looks like a singe image. ER Mapper's ECW technology allowed Aerial Express to compress approximately 50 Gigabyte images by a ratio of 20:1, thus reducing them to a manageable size. Aerial Express also uses Earth Resource Mapping's Image Web Server to serve this compressed imagery across the Internet.

Consumer Expenditure Detail

Business Summary Report

The core source for the Business Summary database is BusinessCounts from InfoUSA. BusinessCounts is a geographic summary database of business establishments and employees for over twelve million companies and one hundred and ten million employees. The InfoUSA Business Database is built from a careful integration of commercial databases, compiled white and yellow page directory data, city directories, corporate annual reports, and securities filings.

The BusinessCounts 2000 file is current to January 2006. Several additional sources of national and state level estimates from the BLS (Bureau of Labor Statistics) and the Census Bureau were used to verify summary counts in the final database. In general, the database agrees substantially with these estimates.

Consumer Behavior/Product Potential Data

The MOSAIC segmentation system creates clusters, which group households having similar demographics, spending patterns and behaviors. At this time there are 60 MOSAIC clusters that describe all American households.

The MOSAIC system then assigns each block group in the United States to one of the 60 clusters based on how closely each block groups households match the clusters compositions.

MRI surveys thousands of American consumers to obtain information about where they shop, what they buy, what they believe in and so on. Each survey respondent is geocoded to determine which block group they live in. Individual survey respondents are assigned the Block Group's dominant cluster.

Profiles of all survey respondents are created for each question asked in the survey. By looking at the clusters of respondents they find a % penetration of households that "own a dog" or "bought tires at Sears" for each cluster.

These profiles are then used to project data locally and nationally to all levels of geography. When looking at a specific area, the cluster counts are multiplied by the respective % penetration of each cluster to calculate total estimated households that "own a dog" or adults that "bought tires at Sears".

Major Malls

This database includes information for all malls within your geography: mall name, county, gross lease-able area, mall type, mall shape, presence of food court, number of stores, site acreage, number of parking spaces, nearest city with mileage and nearest mall with mileage. The information is provided by the Directory of Major Malls® (DMM), a directory of shopping centers concentrating on the primary centers in the industry with a Gross Leasable Area of 250,000 square feet and above.

Financial Summary

The primary source of this database is the 2001 Survey of Consumer Finances, issued by the Census Bureau. The survey includes a wide range of demographic attributes related to consuming units (generally households), which have been modeled separately for each discrete expenditure category. The older surveys were first inflated to current price levels using the detailed consumer price index series. For each individual expenditure category in the survey, summary statistics were calculated for each separate element in the list below. In several cases, it was possible to utilize cross tabulation data (e.g. income by age of head of household).

These variables are listed below:

·                  geographic region (Northeast, South, Midwest, West)

·                  metropolitan status (metropolitan, nonmetropolitan) and size (e.g. > 4 million)

·                  housing tenure (owner or renter)

·                  age of head of household (<25 years, 25-34 years, 35-44 years, 45-54 years, 55-64 years, 65- 74 years, and 75+ years)

·                  size of household (1 person, 2 persons, 3 persons, 4 persons, 5 persons, 6+ persons)

·                  household income (<5000, 5-10000, 10-15000,15-20000, 20-30000, 30-40000, 40-50000, 50-70000, 70000+)

·                  race (White, Black, American Indian, Asian)

·                  number of vehicles (none, 1, 2+ vehicles per household)

For each item, a series of adjustment factors were derived for each unique demographic attribute. These adjustment factors were then applied to the block group level using the same demographic variables in order to create estimates at the local level, which are consistent with local characteristics. Consistency checks were undertaken in order to ensure that the results at the block group level were consistent in the aggregate with overall published estimates.

Crime Statistics

CrimeRisk, from AGS, is the result of an extensive analysis of over seven years of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. The AGS Crime database provides indexed crime data for your geography. It provides indexes for assault, burglary, larceny, motor vehicle theft, murder, personal crime, property crime, rape and robbery. It also provides an index for total crime in the area.

MOSAIC Cluster Distributions

MOSAIC is Experian's geodemographic segmentation system. AGS demographics are an integral part of the MOSAIC system within the United States. The MOSAIC Cluster Distribution add-on will enable users to evaluate cluster groups within any geographic area.

Retail Potential

The Retail Potential database, from AGS, consists of average household and total market potential estimates by each of sixty-eight retail store types. The store types are based on the NAICS classification (examples: 44111 New Car Dealers, 44211 Furniture Stores, 44312 Computer Stores, 44511 Grocery Stores, etc.).