Consumer Spending
The Consumer Spending 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).
Methodology and Data Sources
The consumer spending 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 2005 Consumer Expenditure Survey data from the Bureau of Labor Statistics. The BLS survey is a comprehensive survey that averages over 7,500 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 396 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 estimates were inflated using detailed consumer price indexes to current year levels. 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 estimates were inflated using detailed consumer price indexes to current year levels.
In addition to providing average household expenditures, AGS also provides total market estimates for use in market share and demand analysis.
Consumer Spending Variable List
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AGS is a trademark of Applied Geographic Solutions, Thousand Oaks, CA
