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AE-02197
ANALYSIS OF RETAIL TRENDS AND TAXABLE SALES FOR NORMAN, OKLAHOMA AND CLEVELAND COUNTY
Suzette Barta, Extension Assistant, OSU, Stillwater (405) 744-6186
Susan Trzebiatowski, Student Assistant, OSU, Stillwater
(405) 744-6186
Joe Benton, Agric./4-H & Interim CED, OSU, Norman (405)-321-4774
Stan Ralstin, Area Community Development Specialist, OSU, Enid
(580) 233-5295
Mike D. Woods, Extension Economist, OSU, Stillwater (405) 744-9837
OKLAHOMA COOPERATIVE EXTENSION SERVICE OKLAHOMA STATE UNIVERSITY
December 2002
Analysis Of Retail Trends And Taxable Sales For Norman, Oklahoma And Cleveland County
Suzette Barta Susan Trzebiatowski Mike Woods Extension Assistant Student Assistant Extension Economist Room 527, Ag. Hall Room 527, Ag. Hall Room 514, Ag. Hall Oklahoma State University Oklahoma State University Oklahoma State University Stillwater, OK 74078-6026 Stillwater, OK 74078-6026 Stillwater, OK 74078-6026 [email protected] [email protected] [email protected] Joe Benton Stan Ralstin Ext. Ed., Agric./4-H & Interim CED Area Ext. Comm. Dev. Specialist 601 E. Robinson 205 W. Maple, Suite 610 Norman, OK 73071-6674 Enid, OK 73701-4011 [email protected] [email protected] ABSTRACT
The goal of this paper is to provide an analysis of taxable sales for Norman and Cleveland County. Basic data is used to provide estimates of trade area capture and pull factors. Reported sales tax data is also used to analyze trends in the county and area.
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1
ANALYSIS OF RETAIL TRENDS AND TAXABLE SALES FOR NORMAN, OKLAHOMA AND CLEVELAND COUNTY
INTRODUCTION
Oklahoma communities have been concerned with all aspects of economic development
for the past several years. Creating new jobs and additional income is of concern to rural
communities and urban areas alike. Often, retailing is viewed as a "service" sector dependent on
the "basic" sectors such as oil, manufacturing, and agriculture. Export sectors produce goods and
services sold outside the local or regional economy. Service sectors tend to circulate existing
local dollars rather than attracting "new" outside dollars. The retail sector is important, though,
as retail activity reflects the general health of a local economy. Retail sales also produce sales
tax dollars which support municipal service provision. Many local communities are promoting a
"shop at home" campaign to keep local retail dollars in the community. It will not be possible to
stop all out-of-town spending or sales leakage’s for a local economy. Opportunities for
improvement do frequently exist, however. Key areas can be identified for improvement.
Analysis of retail trends can identify emerging trade centers. Local leaders in Norman requested
the following taxable sales analysis. The specific objectives of the study are:
1. Utilize reported sales tax data to analyze trends in the county and area,
2. Provide estimates of trade area capture and market attraction, and
3. Provide estimates of market attraction, broken out by SIC code.
2
METHODOLOGY AND DATA SOURCES
A trade area analysis model frequently used is "trade area capture." Trade area capture is
calculated by dividing the city's retail sales by state per capita retail sales. The figure is adjusted
by income differences between the state and relevant local area. The specific equation utilized
is:
Where: TACc=Trade Area Capture by city, RSc=Retail Sales by city, RSs=Retail Sales for the state, Ps=State Population, PCIc=Per Capita Income by county, and PCIs=Per Capita Income for the state.
Trade area capture figures incorporate both income and expenditure factors, which may
be influencing retail trade trends. An underlying assumption of the trade area capture estimate is
that local tastes and preferences are similar to that of the state as a whole. If a trade area capture
estimate is larger than city population then two explanations are possible: 1) the city is attracting
customers outside its boundaries or 2) residents of the city are spending more than the state
average.
Trade area capture figures can be utilized to estimate the amount of sales going to outside
consumers. To do this a pull factor , which is a measure of an economy's retail sales gap, is
derived using trade area capture figures and city population:
Where: PFc=City Pull Factor, and Pc=City Population.
PCIPCIX
PRS
RS=TAC
S
C
S
S
CC
PTAC = PF
C
CC
3
A pull factor of 1.0 means the city is drawing all its customers from within its boundaries
but none from the outside. A pull factor of 1.50 means the city is drawing non-local customers
equal to 50 percent of the city population. A pull factor of less than one means the city is not
capturing the shoppers within its boundaries or they are spending relatively less than the state
average. This is considered leakage of retail sales or a retail sales gap. Additional discussion of
trade area capture and pull factors can be found in the references cited in this report (Barta and
Woods; Harris; Stone and McConnon; Hustedde, Shatter, and Pulver). The Oklahoma
Cooperative Extension Service has been conducting pull factor/gap analysis and sales tax
analysis since 1991 (Woods, 1991).
City pull factors and trade area capture figures are calculated for fiscal years 1980
through 2002. Data used were sales tax returns as reported by the Oklahoma Tax Commission.
These figures do not include all retail sales (only taxable sales) in an area but provide a proxy.
Population data were obtained from the Oklahoma State Data Center and were consistent with
figures from the1980, 1990, and 2000 Census. Income figures were taken from Bureau of
Economic Analysis estimates for counties. Similar income data for cities were not available so
county income was used as a proxy.
4
TAXABLE SALES ANALYSIS
Sales tax returns as reported by the Oklahoma Tax Commission for Norman are listed in
Table 1 for the fiscal years 1980 to 2002. Sales tax returns are important to a city because they
reflect the general health of a local economy and also represent significant revenue for the city
budget. In FY 2002, Norman collected over $36 million in sales tax at tax rates of 3.0% (for 5
months) then 3.5% (for 7 months). Figure 1 plots estimated taxable sales for the same time
period in both actual dollars and inflation-adjusted dollars. Sales are estimated from the sales tax
returns and the sales tax rate that is reported. The Consumer Price Index is used to adjust for
inflation. When taxable sales have been adjusted for inflation, Figure 1 shows that “real” sales
have increased steadily since 1988.
Table 2 lists trade area capture figures for Norman from 1980 to 2002. The trade area
capture for Norman was at a maximum of 113,026 occurring in 2001. This means that in 2001
Norman “captured” the retail sales of 113,026 persons. Figure 2 presents a graphic of these same
trade area capture figures. With the exception of a few small “dips,” growth in trade area for
Norman has been quite steady since 1980.
Table 3 lists pull factors for Norman for the years 1980 to 2002. The pull factor for
Norman ranges from 0.921 to 1.203. Recently, these pull factors have tended to be about 1.80
The interpretation is that Norman is capturing the sales from persons within the city's boundaries,
plus is capturing additional shoppers equal to about 80% of Norman’s population.
Table 3 also shows the pull factors for other cities and towns in Cleveland County with a
reported sales tax. Figure 3 presents this information graphically. Norman clearly shows up as
the community in Cleveland County with the consistently highest pull factor, generally between
1.0 and 1.2 over the past two decades. Second in line would be Moore, whose pull factors have
grown since 1995 and are now around 0.90. Noble and Lexington have had similar pull factors
5
over the years, but Noble has been ahead of Lexington since about 1988. Hall Park and
Slaughterville both post pull factors below the 0.20 mark.
Figure 4 shows pull factors for 461 cities that have sales tax return information available.
The pull factors are presented as a group average by city size. The highest pull factors fall in the
size categories 5,001 to 10,000 and 10,001 to 25,000 and 25,001 to 50,000 in population. The
smallest pull factors fall in the range for cities less than 1,000 in population. Figure 5 plots
Norman’s pull factor compared to other cities with population greater than 50,000. Norman
posts pull factors that are very similar to the average for other cities of similar size, but has
pulled above the average since about 1996.
Figure 6 shows pull factors for Norman and other selected cities. Highest on the chart is
Stillwater (population 39,000); lowest is Broken Arrow (population 75,000). Norman
(population 95,000) is primarily third on the chart, but has drawn up even with Enid (population
47,000) in 2001 and 2002. Edmond (population 68,000) has shown remarkable growth since
1988. Midwest City (population 54,000) has primarily declined since about 1988. Lawton
(population 93,000) shows a fairly large drop in retail pull after 1999.
6
Table 1 Tax Returns, Norman, Oklahoma, FY 1980-2002
Year Collections Tax Rate 1980 $5,736,291.46 2.00% 1981 $6,735,487.43 2.00% 1982(1) $595,242.48 2.00% 1982(11) $10,688,437.80 3.00% 1983 $12,947,063.07 3.00% 1984 $14,127,154.59 3.00% 1985 $14,503,238.93 3.00% 1986 $14,364,491.23 3.00% 1987 $14,049,444.14 3.00% 1988 $13,875,141.80 3.00% 1989 $14,775,335.79 3.00% 1990 $15,584,647.98 3.00% 1991 $16,392,611.28 3.00% 1992 $17,578,495.47 3.00% 1993 $18,097,023.09 3.00% 1994 $19,281,164.30 3.00% 1995(3) $5,101,437.17 3.00% 1995(9) $17,007,312.07 3.33% 1996(3) $5,951,301.59 3.33% 1996(9) $16,518,459.29 3.00% 1997 $23,666,418.64 3.00% 1998 $25,292,033.27 3.00% 1999 $27,081,629.55 3.00% 2000 $29,545,484.25 3.00% 2001 $31,699,132.25 3.00% 2002(5) $13,693,628.19 3.00% 2002(7) $22,566,170.90 3.50% (1) Data are for 1 month of the year
(3) Data are for 3 months of the year (5) Data are for 5 months of the year
(7) Data are for 7 months of the year
(9) Data are for 9 months of the year (11) Data are for 11 months of the year
7
Figure 1. Estimated Retail Sales for Norman, OK, Actual and Inflation-Adjusted, 1980-2002
$0.00
$200,000,000.00
$400,000,000.00
$600,000,000.00
$800,000,000.00
$1,000,000,000.00
$1,200,000,000.00
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Actual Adjusted
8
Table 2 Trade Area Capture, Norman, Oklahoma,
1980-2002
Year Trade Area Capture Population 1980 63,725 68,020 1981 63,787 69,250 1982 71,344 70,900 1983 80,142 72,500 1984 83,146 73,900 1985 86,417 75,050 1986 90,559 75,250 1987 89,882 75,200 1988 84,492 75,000 1989 87,637 77,300 1990 88,284 80,435 1991 91,076 81,718 1992 94,522 83,300 1993 93,075 85,004 1994 94,325 86,932 1995 95,742 88,387 1996 100,191 89,562 1997 106,905 91,921 1998 108,554 93,073 1999 109,279 94,193 2000 110,265 95,694 2001* 113,026 95,694 2002* 112,672 95,694
* Based on 2000 BEA income data.
9
Figure 2. Trade Area Capture for Norman, OK 1980-2002
60,000
70,000
80,000
90,000
100,000
110,000
120,000
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
10
Table 3 Pull Factors for Cities and Towns in Cleveland County
1980-2002
Norman Hall Park Lexington Moore Noble Slaughterville1980 0.937 0.251 0.511 0.573 0.521 --- 1981 0.921 0.200 0.399 0.592 0.424 --- 1982 1.006 0.150 0.443 0.738 0.406 --- 1983 1.105 0.187 0.426 0.731 0.413 --- 1984 1.125 0.394 0.426 0.709 0.413 --- 1985 1.151 0.243 0.430 0.722 0.481 --- 1986 1.203 0.334 0.403 0.743 0.486 --- 1987 1.195 0.365 0.458 0.818 0.474 --- 1988 1.127 0.291 0.428 0.816 0.431 --- 1989 1.134 0.217 0.441 0.725 0.481 0.067 1990 1.098 0.170 0.470 0.686 0.519 0.147 1991 1.115 0.185 0.448 0.683 0.536 0.131 1992 1.135 0.230 0.448 0.658 0.541 0.090 1993 1.095 0.200 0.402 0.637 0.500 0.104 1994 1.085 0.127 0.384 0.637 0.526 0.097 1995 1.083 0.111 0.401 0.644 0.571 0.087 1996 1.119 0.113 0.412 0.725 0.531 0.090 1997 1.163 0.188 0.404 0.795 0.486 0.094 1998 1.166 0.130 0.453 0.804 0.528 0.099 1999 1.160 0.113 0.425 0.815 0.554 0.106 2000 1.152 0.130 0.369 0.875 0.507 0.086 2001 1.181 0.147 0.340 0.847 0.522 0.084 2002 1.177 0.134 0.326 0.911 0.517 0.094
11
Figure 3. Pull Factors for Cities and Towns in Cleveland County, 1980-2002
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
NormanHall Park LexingtonMooreNobleSlaughterville
12
Figure 4. Average Pull Factor by City Size,1980-2001
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
Less 10001-55-1010-2525-50Grtr 50
13
Figure 5. Pull Factors for Norman vs. Other Cities with Population Greater than 50,000
0.800
0.900
1.000
1.100
1.200
1.300
1.400
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
Norman Greater than 50,000
14
Figure 6. Pull Factors for Norman and Other Selected Cities,1980-2002
0.500
0.700
0.900
1.100
1.300
1.500
1.700
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
NormanLawtonMidwest CityBroken ArrowEdmondStillwater*Enid*
*Population below 50,000
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SALES GAP ANALYSIS FOR NORMAN, OK
For purposes of this study, a sales gap analysis refers to a pull factor study that has been analyzed
by SIC code for the 8 retail sectors. Sales gap coefficients may be interpreted in exactly the same
manner as are pull factors. See Table 4 for Norman’s sales gap analysis. Table 5 provides a detailed
description of the 8 retail SIC categories.
For Norman’s Building and Gardening Materials, the number of shoppers has increased from
81,478 in FY 1998 to 107,151 in FY 2001. (The 2001 value, however, is down from 1999 and 2000
figures.) Norman's population is about 95,000; thus, in 2001, this sector of the Norman economy was
capturing a number of non-local shoppers that was equal to the town’s population plus another 12%.
The category of General Merchandise tends to be dominated by Wal-Mart. Wal-Mart reports all
its sales under this category (even though it sells clothing, grocery items, etc. as well). In general, towns
that have a Wal-Mart will post sales gap coefficients that are greater than 1.0 for this category. Norman
is no exception to this rule. Norman does have a Wal-Mart (two actually), and their gap coefficient in
this category was 1.484 in FY 2001. This category shows consistent growth over the four years shown.
Grocery stores in Norman had a gap coefficient of 0.762 in 2001. Consumers tend to appreciate
the convenience of shopping for groceries close to home. In addition, most residents outside of the city
limits will travel into the small town grocery store to shop; consequently, it is common to find that even
very small towns post high gap coefficients (over 1.0) for this sector. Why then is Norman’s coefficient
less than 1.0 in this category? This is easily explained by the dominance of the two Wal-Mart
Supercenters in Norman. Many grocery items are purchased at these two stores, but are “hidden”
because they are reported under SIC 53, General Merchandise.
SIC category 55 is difficult to interpret because motor vehicle and gasoline sales are exempt from
municipal sales tax in Oklahoma. Most of the sales tax collection reported under this category appears
16
to stem from auto parts stores and other retail sales from gas stations. For instance, most gas stations
sell snack items, tires, some auto parts, oil, anti-freeze, etc. Sales tax collections for Norman in this
category indicate that these types of businesses attracted about 94% of the residents of Norman in FY
2001.
Apparel sales are reported under SIC 56. It is very difficult for small to medium sized towns to
post high sales coefficients in the category of apparel. Many small towns have nearly zero sales in this
category, and it is common to see sales gap coefficients that are less than 0.10 in these towns. Cities
with large malls tend to be the most successful at capturing the market. Norman is home to the Sooner
Fashion Mall, and thus does very well in this category. Apparel stores captured a total of 188,316
shoppers in FY 2001 (nearly double the city’s population) for a gap coefficient of 1.968.
SIC 57 reports Furniture and Home Furnishings. Also included are appliance and electronics
stores, drapery and floor covering stores, and music stores. This category is generally viewed from the
perspective that most furniture purchases are made in either Tulsa or Oklahoma City. Oklahoma City,
for example, has a large cluster of retail furniture stores centralized in one geographic area. Although
the value of this coefficient has been growing over the last few years for Norman, it is still below 1.0. It
does seem likely that many Norman residents are purchasing furniture in Oklahoma City.
Eating and Drinking Places, SIC 58, is one of the most straightforward retail sectors. It contains
restaurants and bars. Restaurants and bars in Norman captured 150,228 customers in FY 2001. This
number has been increasing since 1998. Restaurants in Norman tend to attract a number of non-local
shoppers that is equal to about 57% of the town’s population.
SIC 59, or Miscellaneous Retail, contains a host of retail activity, including pharmacies, florists,
liquor stores, and antique stores. Norman's pull factor in this category increased from 0.784 in 1998 to
1.112 in 2001.
17
Table 4 Retail Sales Gap Analysis by Standard Industrial
Classification (SIC) Code, Norman: Fiscal 1998-2001
Trade Area Capture Sales Gap Coefficient*
FY 1998 FY 1999 FY 2000 FY 2001 FY 1998 FY 1999 FY 2000 FY 2001
Building, Gardening & Merchandise (52) 81,478 115,625 118,398 107,151 0.875 1.228 1.237 1.120General Merchandise (53) 67,600 90,216 118,394 142,015 0.726 0.958 1.237 1.484Food Stores (54) 75,698 96,271 80,906 72,921 0.813 1.022 0.845 0.762Automobile Dealers & Gas Stations (55) 61,072 85,067 82,574 89,878 0.656 0.903 0.863 0.939Apparel & Accessory Stores (56) 116,488 167,947 168,422 188,316 1.252 1.783 1.760 1.968Furniture & Home Furnishings (57) 53,551 74,809 79,134 85,952 0.575 0.794 0.827 0.898Eating & Drinking Places (58) 97,102 134,850 136,575 150,228 1.043 1.432 1.427 1.570Miscellaneous Retail (59) 72,982 99,256 98,687 106,421 0.784 1.054 1.031 1.112
* For purposes of this paper, when analyzed by SIC code, the pull factor is referred to as the sales gap coefficient
18
TABLE 5 TYPES OF BUSINESSES
DESCRIBED BY THE RETAIL SIC CODES 52 Building Materials 58 Eating and Drinking Places
Lumber yards including home centers Paint and wallpaper stores Glass stores 59 Miscellaneous Retail Hardware stores Drug and proprietary stores Retail Nurseries Liquor Stores Lawn and garden supply stores Used merchandise stores including antique Mobile Home dealers stores and pawn shops
Sporting goods stores 53 General Merchandise Stores Book stores
Variety stores Stationary stores Department stores Jewelry stores Warehouse clubs Hobby, toy, and game shops General combination merchandise stores Camera and photographic supplies stores
Gifts, novelties and souvenirs 54 Food Stores Luggage and leather goods stores
Grocery stores (Supermarkets) Sewing, needlework, and piece goods stores Convenience stores both with and without gasoline Catalog and mail order sales (includes e- Meat and fish markets commerce stores) Fruit and vegetable markets Vending machine operators and direct selling Candy, nut and confectionery stores establishments Dairy stores Fuel oil dealers Retail Bakeries Bottled gas dealers
Florists 55 Automotive Dealers and Gasoline Service Stations Tobacco Stores
Motor vehicle dealers (new and used) Newsstands Tire stores Optical goods stores Auto supply stores Cosmetic stores Gasoline stations Pet and pet supply stores Boat dealers Hearing aid and artificial limb stores RV dealers Art dealers Motorcycle dealers Telephone and typewriter stores
56 Apparel and Accessory Stores
Men and boys apparel Women’s apparel and accessories Children and infant’s wear Family apparel Shoe stores Custom tailor and seamstresses
57 Furniture and Home Furnishings Stores
Furniture stores Floor covering stores Drapery, curtains and upholstery stores Pottery and crafts made and sold on site Household appliance stores Radio and TV and consumer electronics stores Computer and computer software stores Record and prerecorded tapes stores Musical instruments stores
.
19
BUSINESS DEVELOPMENT STRATEGIES
Retail trade trends reflect the overall health of a local economy. All out shopping or sales
leakage cannot be stopped. Often, larger economic trends (State-National-Global) overwhelm
retail opportunities. There are programs and actions that can assist retail trade activities,
however.
Concerned leaders and business persons can focus on business development by forming a
business assistance committee to begin implementing some of the assistance activities or
working with the existing chamber of commerce. The following activities were in part of a retail
trade improvement program. These activities can improve the climate for business and show the
community's commitment to support local business.
1. Analyze the local business sector to identify needs and opportunities to be pursued by the
program. Businesses often do not have the resources to study the economy (local, regional,
and national) and how they fit in. They need practical data and analysis that will help in
their individual business decision-making. In particular, economic analysis can identify
voids in the local or regional market that can possibly be filled by expanding or new
business. Examples of analysis include the pull factor analysis reported here and consumer
surveys to identify needs and opportunities.
In addition to economic analysis, information is needed on the needs or problems of
individual businesses and of the business district as a whole. As needs are identified, action
can be taken to improve the situation. For example, a business may need help in preparing a
business plan to qualify for financing. Perhaps the appearance of buildings and vacant lots
is detrimental to attracting people to be business district, or perhaps poorly coordinated store
hours are a hindrance. Once these needs are identified, a business development program can
20
initiate action. A periodic survey of local business needs can form the basis of a business
development program's work plan.
2. Provide management assistance and counseling to improve the efficiency and profitability of
local businesses. Many local businesses are owner-operated, earn low profits, and have
difficulty obtaining financing. Businessmen often need additional education and training in
improving business management skills like accounting, finance, planning, marketing,
customer, relations, merchandising, personnel management, or tax procedures. This
assistance and counseling can be provided through seminars and one-to-one aid. Sources of
assistance include the Service Corps of Retired Executives (SCORE), Small Business
Development Center program sponsored by the Small Business Administration,
Universities, Technology Centers, Oklahoma Department of Commerce, and the
Cooperative Extension Service. The intent is to aid small businesses in becoming more
competitive.
3. Assist new business start-up and entrepreneurial activity by analyzing potential markets and
local skills and matching entrepreneurs with technical and financial resources. Establishing
a business incubator is another way to assist new businesses. An incubator is a building
with shed space or service requirements that reduce start-up costs for new businesses.
Incubators have been successful in many locations but are not the right answer for every
town. A successful incubator must have long-range planning, specific goals, and good
management in order to identify markets and entrepreneurs.
4. Promote the development of home-based enterprises. Home-based work by individuals is
increasing because of the flexibility offered and because in some areas, it may be the most
21
realistic alternative. Home-based enterprises can include a great variety of full or part-time
occupations such as food processing, quilting, weaving, crafts, clothing assembly, mail order
processing, or assembling various goods.
5. Provide assistance in identifying and obtaining financing. Small businesses often have
difficulty obtaining long-term bank financing for expansion because they lack assets to
mortgage, cannot obtain affordable terms or rates, or cannot present a strong business plan.
A business development program can identify public loan programs and package them with
private loans to make projects feasible.
6. Provide assistance in undertaking joint projects such as:
• improved appearance
• improved management of the commercial area
• building renovation
• preparation of design standards
• joint promotions and marketing
• organizing independent merchants
• special activities and events
• fund raising
• improved customer relations
• uniform hours of operation
Undertaking these projects requires cooperation, good organization, and efficient
management. These projects can improve a business district's competitive position and
22
attract new customers. The Oklahoma Main Street Program provides many good examples
of towns working together for economic revitalization. The Main Street Program developed
by the National Trust for Historic Preservation, is built around the four points of
organization, design, promotion, and economic restructuring.
7. Develop a one-stop permit center. There is great deal of red tape involved in starting a
business including registering a name, choosing a legal form, and determining what licenses,
permits, or bonds are needed. Other concerns include internal revenue service requirements,
unemployment insurance, sales tax permits, and state withholding taxes. Having this type of
information available in one location will make life easier for potential businesses.
8. Involve active organizations and the media. Groups such as the chamber of commerce, civic
clubs, etc. can encourage a healthy business climate. The local media can also support small
business and aid in developing awareness of the importance of local business.
23
SUMMARY
This report has analyzed taxable sales trends for the city of Norman and Cleveland County.
The level of taxable sales in Norman has grown significantly in nominal terms since 1980. After
correcting for inflation, taxable sales have still shown impressive growth since 1980. Located
right off Interstate 35, Norman, the county seat of Cleveland County and the home to the
University of Oklahoma, is the clear center of trade for residents in Cleveland County. Moore
has shown nice growth since the mid-1990s, increasing from about 0.64 to over 0.91 in 2002.
Cleveland County is one of the 14 metropolitan counties in the state and its growth is
indicative of metropolitan growth in both population and retail sales across the state. It is one of
only four counties in the state that has more than one Wal-Mart Supercenter. These stores tend
to have incredible retail pull. Sooner Fashion Mall is probably another strong source of retail
attraction. However, this success does not mean that Norman retailers face no competition.
Norman’s proximity to Oklahoma City almost guarantees some degree of retail leakage.
Furthermore, the outlet malls in Gainesville, Texas provide an undeniable pull on Norman
residents as well.
24
REFERENCES
Barta, S.D. and M.D. Woods. Gap Analysis as a Tool for Community Economic Development. WF 917, Oklahoma Cooperative Extension Service, Oklahoma State University,
<http://agweb.okstate.edu/pearl/agecon/resource/wf-917.pdf>, 2000. Harris, Thomas R. "Commercial Sector Development in Rural Communities: Trade Area
Analysis." Hard Times: Communities in Transition. Western Rural Development Center, WREP 90, September 1985.
Hustedde, R., R. Shatter, and G. Pulver, Community Economic Analysis: A How To Manual.
Ames, Iowa. North Central Regional Center for Rural Development, 1984. Oklahoma Department of Commerce, Research and Planning Division. Population Estimates for
State, Counties, and Cities, Oklahoma: April 1, 1980-July 1, 1989. December 1990. Oklahoma Tax Commission City Sales Tax Collections Returned to Cities and Towns in Fiscal,
1980 to 2002. (Fiscal Year End-June 30) Stone, K. and J.C. McConnon, Jr. "Trade Area Analysis Extension Program: A Catalyst for
Community Development," Proceedings of Realizing Your Potential as an Agricultural Economist in Extension. Ithaca, New York, August 1984.
Tennessee Valley Authority. "Focus on the Future," Workbook provided at RedArk
Development Authority Symposium on Economic Development Leadership, Shawnee, Oklahoma, June 1986.
U.S. Department of Commerce Bureau of The Census. Resident Population by County, 1990 to
2001. http://www.census.gov/populations/extimates/county/ (June 2002) U.S. Department of Commerce, Bureau of Economic Analysis. "Personal Income by Major
Source and Earnings by Major Industry," Regional Economic Information System, 1980 to 2000
Woods, Mike D. Retail Sales Analysis in Oklahoma By County, 1977, 1982, 1987. Bulletin B-
801, Agricultural Experiment Station, Oklahoma State University, October 1991.