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 sdb1113@okstate.edu susanft@okstate.edu mdwoods@okstate.edu 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 bentonj@okstate.edu ralstin@okstate.edu 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.

"Oklahoma State University, in compliance with Title VI and VII of the Civil Rights Act of 1964, Executive Order 11246 as amended, Title IX of the Education Amendments of 1972, Americans with Disabilities Act of 1990, and other federal laws and regulations, does not discriminate on the basis of race, color, national origin, sex, age, religion, disability, or status as a veteran in any of its policies, practices or procedures. This includes but is not limited to admissions, employment financial aid, and educational services."

"Readers may make verbatim copies of this document for non-commercial purposes by any means."

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

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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.

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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

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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

.

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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.