All members of a community, even those with very low incomes, have money to spend. Every household is a consumer of retail products since it must buy food, clothing, and other everyday items. Those retail dollars either stay within the local economy or they leave the local economy. If dollars remain in the local economy, the benefits associated with them will also remain. Furthermore, as those dollars re-circulate within the local economy, more economic growth is possible. Of course, no person can be induced to make every purchase in their own city or town, but the healthiest economies will attract a large portion of local consumers’ dollars.
It should be noted here that this fact sheet is not advocating an attitude of “shop at home at all costs.” Consumers should not be expected to support a local merchant who offers low quality merchandise at high prices. Instead, the purpose is to help community leaders understand that there are some tools available that can help them better understand the weaknesses in their local retail market. Once leaders understand that weaknesses, such as high incidence of out-shopping, do exist, then they are able to plan competitive responses to those problems.
In recent years, organizations such as Main Street have played an important role in educating local citizens specifically in issues of retail competitiveness and in issues of economic development in general. As a result, the nation’s small cities and towns have placed a renewed emphasis on economic development through the retention of local retail dollars.
Efforts in this area have led local leaders to devise various techniques for measuring how area residents spend their retail dollars. Does a city create surplus retail dollars by attracting shoppers from outside the area to the local retailers? Or does the city face a leakage of retail dollars as area shoppers leave the local economy to make their retail purchases? Sometimes this information can be inferred from area consumer surveys. In other cases, secondary data may be utilized to indicate such leakage or surplus.
One such technique for determining retail surplus or leakage is called sales gap analysis. The technique is a relatively simple one. Members of local economic development committees are certainly capable of performing the analysis for their community. (See Bates, 1998.) The following sections describe how to perform the analysis, indicate data requirements, and suggest likely sources for locating data.
What is Gap Analysis?
Gap analysis is a technique for identifying the strengths and weaknesses in a local retail market. Essentially, the analysis estimates how many shoppers are coming to a community to purchase retail items. For example, if a town with a population of 2,000 is attracting 4,000 shoppers annually, the interpretation is that this community is attracting its own residents, in addition to drawing in non-local customers. If the same town of 2,000 people was only attracting 1,000 shoppers, the implication would be that this town is not capturing the retail dollars of its own residents. Out-shopping is probably taking place. Because gap analysis utilizes data from the Oklahoma Tax Commission reported by Standard Industrial Classification (SIC) code for eight separate retail sectors (see Table 1), the analysis allows a community to identify which areas of retail may be subject to out-shopping.
The value associated with sales gap analysis comes from knowing the strengths and weaknesses of the local retail economy. It is a first step. Local residents must decide for themselves whether a retail gap is not acceptable, acceptable, or even preferable. If it is deemed not acceptable, then community leaders should work to devise a competitive strategy for meeting the needs of the community. A common misconception, however, is to assume that if a gap exists, then it must be filled. For instance, residents of one community indicated on surveys that they wanted a retail bakery, and a gap analysis showed a large gap in this market. Unfortunately, feasibility studies indicated that the town’s market area was not large enough to support this kind of retail establishment. However, the information was useful because it did give some local restaurant owners the idea to offer more baked goods for sale.
Table 1. SIC Codes for Oklahoma Retail Sales FY 1998 (With Percentage of Income Spent in Each Sector)
|52-59||Total Retail Expenditures||28.99%|
|52||Lumber, Bldg Materials, Hardware||2.51%|
|55||Auto, Accessories, and Gasoline Service Stations||1.57%|
|56||Apparel and Accessories||1.31%|
|57||Furniture, Home Furnishings & Equipment||2.36%|
|58||Eating and Drinking Places||4.02%|
The first step in conducting a gap analysis is to collect the required data.
1. Current estimate of town’s population – Bureau of the Census.
2. City per capita income (1990 is the latest available) – Bureau of the Census.
3. County per capita income (1990 and latest year available) – Bureau of Economic Analysis (BEA).
4. Sales tax collections for the city by SIC code and city sales tax rate.
Sales tax data is available upon request from the Oklahoma Tax Commission. Census Bureau and BEA data for Oklahoma are accessible from ORIGINS, an electronic database maintained jointly by the University of Oklahoma, the Oklahoma Department of Commerce, and Oklahoma State University. ORIGINS is located at the following Internet address: http://origins.ou.edu.
Table 1 presents the SIC codes for eight retail sectors. Also presented are percentages that indicate the proportion of their incomes that Oklahomans typically spend on retail items. For instance, in fiscal year 1998, a typical Oklahoman spent about 6.31 percent of their income on groceries at food stores.
Several methods for estimating these percentages are acceptable. For example, the National Main Street Center (Joncas, 1995) suggests using Bureau of Labor Statistics data published in an annual Consumer Expenditure Survey. Consumer expenditure patterns are reported for the nation and four regions of the country. The Oklahoma Cooperative Extension Service (OCES) suggests utilizing data available on ORIGINS. Retail sales for the state of Oklahoma are compared to total personal income for the state. For example, in fiscal year 1998, Oklahoma residents received over $68 billion in personal income. In the same year, retail sales totaled close to $20 billion. Consequently, state residents spent 28.99 percent of their personal income on retail items.
There are several reasons why the OCES has chosen to calculate these percentages from state retail sales data as opposed to BLS Consumer Expenditure Survey data for the southern region. First, the OCES has been measuring retail sales gaps for communities for several years. In the past, this kind of analysis has been referred to as “pull-factor analysis”. Although the name is different, the methodology is exactly the same as gap analysis. Continuing to utilize percentages based on state retail sales estimates will allow Oklahoma towns for whom pull-factor analysis has already been performed to compare past studies with present and future ones. Furthermore, the state retail data is more state specific and is probably a better representation of residents’ spending patterns.
Conducting a Gap Analysis
After collecting the pertinent information, the next step in gap analysis is to proceed with a gap calculation for total retail expenditures.
Follow the worksheet in Table 2 to calculate the gap coefficient. The sales gap coefficient is an index that will indicate the degree to which a retail market either attracts non-local or loses local customers. Data for an unnamed city are utilized for instructive purposes. The sales gap coefficient in line 12 (.8662) indicates that residents are likely leaving the city to shop for some retail items.
A coefficient of 1.0 possibly indicates that the city is capturing the expenditures of its own residents but is not drawing any trade from outside the area. A number greater than 1.0 might indicate that area residents, as well as shoppers from outside the area, are induced to shop in the local economy. Any number less than 1.0 is an indication that area residents may tend to shop for retail items outside of the local economy.
Any community that registers a gap coefficient below 1.0 should recognize that retail dollars are leaving the area. Leaders in these towns should determine whether or not the leakage is consistent with the community’s plans for economic growth. If not, they should determine if the leakage is large enough to cause concern. If the leakage is large enough to cause concern, strategies to help recapture those dollars should be developed and implemented.
Table 2. Gap Analysis Worksheet
|1||City Population||Available on ORIGINS||2030|
|2||County Per Capita Income 1990||Available on ORIGINS||$13,609|
|3||County Per Capita Income latest year (1997)||Available on ORIGINS||$18,025|
|4||The Percentage growth from line 2 to line 3, then add 1.0||A growth factor used to adjust city per capita income||1.32|
|5||City Per Capita Income 1990||Available on ORIGINS||$8,641|
|6||Line 4 x Line 5||Per capita income adjusted for time||$11,406|
|7||Line 6 x 0.2899*||Average spending per capita||$3,307|
|8||Line 7 x Line 1||Expected total expenditures by city's residents||$6,713,210|
|9||City Sales Tax Collected||1998 data available from OTC||$174,447|
|10||City Tax Rate||1998 rate available from OTC||.03|
|11||Line 9 ÷ Line 10||Estimated taxable sales||$5,814,900|
|12||Line 11 ÷ Line 8||General retail gap coefficient||.8662|
|13||Line 1 x Line 6||Total income to be spent by city's residents||$23,154,180|
|14||Percentage for "eating and drinking places"||Utilize the percentage for the particular category in question||.0402|
|15||Line 13 x Line 14||Demand for category by city's residents||$930,798|
|16||Sales Tax Collected by Businesses in Category||Available upon request from the Oklahoma Tax Commission||$30,658|
|17||City Sales Rate||Available from Oklahoma Tax Commission||.03|
|18||Line 16 ÷ Line 17||Estimated amount consumed by residents in city||$1,021,933|
|19||Line 18 ÷ Line 15||Ratio of total consumed to total demanded - the "gap"||1.098|
* 0.2899 is the average proportion of income spent on retail items by Oklahomans in FY 1998.
Calculating the Gap Coefficient for Specific Retail Categories
Before calculating the sales gap coefficient for specific categories of expenditures, a city must request its annual report of sales tax collections by SIC code from the Oklahoma Tax Commission. This type of data is not generally published and made readily available to the public, but it will be made available to cities that request it. Your city may already collect this information. For contact numbers, the Oklahoma Tax Commission has a web site at the following Internet address: http://www.oktax.state.ok.us/. Assuming that this information has been obtained, Table 3 continues the worksheet begun in Table 2 for an unnamed city.
Notice that the sample city registered a gap coefficient equal to 1.098 in the category of “eating and drinking places”. Because this number is greater than 1.0, it indicates that restaurants in this city tend to attract customers from among city residents as well as from residents outside the city. The same city registered a gap coefficient of 0.087 for “apparel and accessories.” (Calculations not shown.) Literally interpreted, 91.3 percent of all apparel and accessory purchases took place outside the city. Clearly the city was facing a substantial leakage of retail dollars from the local economy in this category.
This paper has discussed a useful tool in community economic development called sales gap analysis. The tool has become popular in recent months due, in part, to the activities of Oklahoma Main Street, which has advocated the use of sales gap analysis by its member communities.
The purpose of this paper was to describe the technique so that community leaders involved with Main Street, the Chamber of Commerce, a merchant’s coalition, an economic development committee, or a planning commission might be able to conduct a sales gap analysis on their own. Data requirements were given and ideas for locating the necessary data were discussed. Sample worksheets for calculating gap coefficients were also included.
Conducting a gap analysis can be a valuable method for identifying the strengths and weaknesses in an economy’s retail sector; however, the analysis only indicates the possible areas of leakage. It does not indicate why the leakage is occurring, whether or not the leakage is desirable or acceptable, or how to stop the leakage from occurring. In fact, these questions can only really be answered by the community itself. Gap analysis provides a starting point only. In order to be valuable, the information must be used to stimulate further discussion, to devise appropriate strategies for action, and to evaluate the progress of these strategies over time.
Bates, J. A. (1998, May 1). “Stop the ‘sales gap’ with a downtown retail analysis”. Downtown IdeaExchange, 3.
Joncas, K. (1995). Step-by-step market analysis: A workbook for downtown business development. Washington, D.C.: National Main Street Center/National Trust for Historic Preservation.
Shaffer, R. (1989). Community economics: economic structure and change in smaller communities. Ames, Iowa: Iowa State University Press.
Suzette D. Barta
Assistant Extension Specialist
Mike D. Woods
Professor and Extension Economist