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Methodology for the ETI Urban Purchasing Power Profiles and Urban Markets Retail Sales Leakage/Surplus ReportsThe University of Wisconsin-Milwaukee Employment and Training Institute provides comparison data on purchasing power, business activity, and workforce density for all residential ZIP codes and the 100 largest metro areas in the U.S. The profiles are designed to help cities, businesses, developers, and organizations assess the advantages of urban density for underserved city neighborhoods. Each year, the U.S. Census Bureau conducts detailed analyses of the spending habits of residents by their household size, type, and income levels. These Consumer Expenditures Surveys are used by marketing firms to estimate expenditures of consumers and to assist retail companies in deciding where to locate and what populations to target for their consumer items and services. In most cases, marketing firms have based their data and recommendations on median household income of residents by geographic locations, while ignoring the advantages of urban density and the concentrated spending that takes place in city neighborhoods. The purchasing power profiles developed by the Employment and Training Institute provide an easy-to-comprehend method to estimate purchasing power for common retail expenditures. Five steps are involved in the process. The ETI Purchasing Power Profiles presented here are based on analyses of 2002 and 2003 Consumer Expenditure Surveys (CEX) and the 2000 U.S. Census. Note: The reports have not been updated for more recent CES or Census data. STEP #1: Using the CEX to determine what households buy.
The ETI Purchasing Power Profiles are based on spending patterns taken from the 2002 Consumer Expenditure Survey, utilizing survey responses from more than 30,000 interviews of households with complete income and expenditure responses. Additional data are drawn from the 2002 and 2003 CEX diary files, which includes patterns of spending by more than 22,000 respondents with complete income and expenditure data. The Purchasing Power Profiles focus on 16 categories of expenditures:
Note: The ETI Purchasing Power Profiles do not include certain high-end purchases often included in national marketing firm reports (e.g., cars and boats), which are better identified through other data bases. STEP #2: Determining expenditures by 5 household types and 5 income levels. The Consumer Expenditure Survey provides data on spending by income levels and family types, which makes it possible to estimate expenditures within communities. For the ETI Purchasing Power Profiles, five types of households and five levels of income ranges by the same family types and income levels using 2000 U.S. Census data were considered in estimating expenditures for each of the 16 retail categories listed above. The five household types are:
The annual household income ranges used are:
In all, 25 expenditure estimates (i.e., 5 household types X 5 income levels) are calculated separately for each of 16 categories of expenditures. The table below presents the estimates, based on CEX data, of annual expenditures for food purchased for the home by the 25 household/income cells. As shown in the table, expenditures for food at home by type of household increase only gradually as income doubles, triples, or even quadruples. |
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| Annual Expenditures by Annual Household Income: | |||||
| $0- | $25,000- | $50,000- | $75,000- | $100,000- | |
| Type of Household | $24,999 | $49,999 | $74,999 | $99,999 | and above |
| Families with children under age 18 | |||||
| With married parents | $4,809 | $4,953 | $5,317 | $5,684 | $6,893 |
| With single parent | $3,685 | $4,117 | $5,126 | $5,488 | $6,141 |
| Families with no children under age 18 | |||||
| With married parents | $3,430 | $3,780 | $4,190 | $4,635 | $5,327 |
| With single parent | $3,159 | $3,665 | $4,108 | $4,329 | $5,065 |
| Non-family households | $1,944 | $2,490 | $2,856 | $3,153 | $3,613 |
The CEX data further shows that a large number of households in the U.S. are in the lowest income category and/or single parents -- groups often ignored or denigrated by marketing firm stereotypes.
| ESTIMATES OF NUMBER OF HOUSEHOLDS IN THE U.S. BY ANNUAL HOUSEHOLD INCOME | |||||
| Number of Households by Annual Household Income: | |||||
| $0- | $25,000- | $50,000- | $75,000- | $100,000- | |
| Type of Household | $24,999 | $49,999 | $74,999 | $99,999 | and above |
| Families with children under age 18 | |||||
| With married parents | 4,893,474 | 2,922,042 | 1,076,752 | 382,633 | 326,974 |
| With single parent | 1,907,308 | 1,729,770 | 771,438 | 317,394 | 171,986 |
| Families with no children under age 18 | |||||
| With married parents | 3,006,793 | 5,325,310 | 5,705,498 | 3,875,143 | 4,406,655 |
| With single parent | 5,107,187 | 6,548,635 | 4,903,928 | 3,209,307 | 3,885,130 |
| Non-family households | 18,174,910 | 7,900,311 | 3,143,023 | 1,086,162 | 1,103,594 |
STEP #3: Determining the number of household types in each income category in each neighborhood.
The 2000 U.S. Census data are used to obtain estimates of the number of households in each of the 25 cells identified above at the zipcode, census tract, and block group level. U.S. Census Bureau definitions of geographic units are used.
STEP #4: Applying expenditure estimates against household/income data for the neighborhood.
Once the number of households are determined for the 25 cells (5 household types by 5 income levels), CEX expenditure patterns for each retail area are applied against the population in each of the 25 cells for each neighborhood. Separate calculations are made for each of the 16 retail categories, based on the findings of the 2002 and 2003 Consumer Expenditure Survey studies.
STEP #5: Calculating expenditures per square mile.
Emphasis on average household income by major marketing firms misses the significant spending by this large population of lower income families, and particularly the aggregate spending that occurs in dense urban neighborhoods. First, as seen above, families with lower incomes spend much higher percentages of their income on common retail purchases. Additionally, these families are often clustered in very dense neighborhoods while many upper income families reside in sparsely populated suburban or exurban areas.
The land area of each geographical unit is used to calculate density per square mile for the ETI Purchasing Power Profiles.
STEP #6: Calculating urban markets retail sales leakage or surplus.
Some neighborhoods are underserved by retail establishments and residents purchase many of their goods outside their community. Those census tracts where neighborhood retail sales fall below the estimated purchases of residents are said to have a retail sales leakage. That retail sales leakage is calculated by comparing the sales levels estimated from retail employment data with retail purchases from the purchasing power profiles. Retail sales surpluses occur in other tracts where retail sales estimated from retail employment data exceed local resident expenditures. These communities may have retail establishments attracting customers from outside the neighborhood, e.g. shoppers attracted to particular retail businesses, in-coming commuters, or stores serving metrowide markets.
Estimates are developed for all census tracts in the 100 largest metro areas in the U.S. to gauge retail sales activity in each neighborhood. To determine the extent to which existing retail businesses are capturing retail spending of local residents, consumer expenditures were estimated for 15 categories of consumer spending. All of the expenditure categories in the ETI Purchasing Power Profiles except for food-away-from-home (which is not in the NAICS retail sector) are included in the estimates for each census tract. This total is compared to estimates of retail sales derived from comparing employment in retail sales work by census tract with the total employment in retail sales for the metro area. Average retail sales per retail employee were calculated for each of the 100 largest MSAs by dividing the sum of the 15 categories of consumer spending estimated for the MSA by the number of retail workers in the MSA from census place-of-work tables. This average is then multiplied by the number of retail workers in each tract using place-of-work tables to get the estimated sales in the tract. Differences are reported as estimated retail sales "leakage" or "surplus."
In Milwaukee, the University of Wisconsin-Milwaukee Employment and Training Institute partnered with the City of Milwaukee Department of City Development to provide purchasing power analyses using current CEX data and income data more recent than the 2000 Census by using detailed ZIP code and block level data from the Wisconsin Department of Revenue on the most recent income tax year filings. This advanced methodology allowed the partners to adjust for changes in the economy and employment by neighborhood. These data offered comparable estimates for Wisconsin areas. At the same time, the nationwide statistics are available for comparisons with other metro areas throughout the U.S.
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Free Purchasing Power Profiles, Retail Sales Leakage/Surplus Reports, Place-of-Work Drill Downs, and Workforce Diversity Drill Downs Available Online
How to Find Census Tracts in Your Community You can locate the census tract for a specific address at the U.S. Census Bureau Factfinder Advanced Geography Search page using the GEOGRAPHY "address search" or "map" option. For maps of census tracts in any community, go to the www.census.gov/geo/www/maps/descriptwindows/outline.htm. Click on "Census Tract Outline Maps 2000." Select your state, then county. Then select the PDF file for your county or select the first PDF file to locate the tracts for your part of the county.
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