Analysis of Retail Trends and Taxable Sales For

AE-04027

ANALYSIS OF RETAIL TRENDS AND TAXABLE SALES FOR MOORE, OKLAHOMA AND CLEVELAND COUNTY

Suzette Barta, Extension Assistant, OSU, Stillwater (405) 744-6186

Susan Trzebiatowski, Student Assistant, OSU, Stillwater (405) 744-6186

Leah Wall, Ext. Ed. Comm. Ec. Dev., 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

May 2004 Analysis Of Retail Trends And Taxable Sales For Moore, 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]

Leah Wall Stan Ralstin Ext. Ed. Comm. Ec. Devel. 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 Moore 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." ANALYSIS OF RETAIL TRENDS AND TAXABLE SALES FOR MOORE, 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 Moore 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.

1 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:

RS C TACC = RS S X PCI C PS PCI S 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:

TACC PF C = PC Where: PFc=City Pull Factor, and Pc=City Population.

2 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 2003. 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.

3 TAXABLE SALES ANALYSIS

Sales tax returns as reported by the Oklahoma Tax Commission for Moore are listed in

Table 1 for the fiscal years 1980 to 2003. 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 2003, Moore collected nearly $11.3 million in sales tax at tax rates of 3.0%.

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 since about 1992.

Table 2 lists trade area capture figures for Moore from 1980 to 2003. The trade area capture for Moore was at a maximum of 40,621 occurring in 2003. This means that in 2003

Moore “captured” the retail sales of 40,621 persons. Figure 2 presents a graphic of these same trade area capture figures. In 1993, trade area capture reached a relative low point, but then increased from 1994-1999. Trade area declined in 2000 and 2001, but rebounded in 2002 and

Table 3 lists pull factors for Moore for the years 1980 to 2003. The pull factor for Moore ranges from 0.573 to 0.929. Recently, these pull factors have tended to be about 0.93. The interpretation is that Moore is capturing about 93% of the sales from persons that live within the city's boundaries, but does not attract non-resident shoppers. This is not exactly true. Moore probably does attract some out of town shoppers; but the effect of these shoppers is more than offset by the out-shopping by Moore residents. The result is a pull factor that is less than 1.0.

Another thing to note about Moore’s pull factors is the increase in pull factor value from

1999 to 2000. A glance back at Table 2 reveals that Moore’s trade area capture actually fell from 1999 to 2000. Why, then, did the pull factor increase? The answer is that the Census

4 population for Moore for 2000 was significantly less than the 1999 estimate (about 4,000 people less). The result is that the lower population figure drives up the pull factor value.

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 very close to 1.2, and recently going beyond that level. Second in line would be Moore, whose pull factors have been rising steadily over the last few years. Noble tends to remain fairly consistent around the 0.50 mark, while Lexington has dropped well below the 0.40 mark in recent years.

Hall Park and Slaughterville are both below the 0.20 mark.

Figure 4 shows pull factors for 460+ 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 Moore’s pull factor compared to other cities with population 25,000-50,000.

Moore posts pull factors that are consistently well below the average for other cities of similar size.

5 Table 1 Tax Returns, Moore, Oklahoma, FY 1980-2003

Year Collections Tax Rate 1980(2) $153,949.65 1.00% 1980(10) $1,501,099.94 2.00% 1981 $2,315,701.86 2.00% 1982 $3,015,394.31 2.00% 1983 $3,033,300.24 2.00% 1984(3) $818,841.62 2.00% 1984(9) $3,514,928.97 3.00% 1985 $4,856,041.88 3.00% 1986 $4,739,114.53 3.00% 1987 $5,103,529.91 3.00% 1988 $5,291,450.39 3.00% 1989 $4,813,156.13 3.00% 1990 $4,885,106.83 3.00% 1991 $5,026,422.95 3.00% 1992 $5,086,841.20 3.00% 1993 $5,254,485.98 3.00% 1994 $5,617,142.01 3.00% 1995 $5,995,696.93 3.00% 1996 $7,002,985.42 3.00% 1997 $7,893,307.27 3.00% 1998 $8,478,176.36 3.00% 1999 $9,175,259.00 3.00% 2000 $9,643,868.59 3.00% 2001 $9,771,090.60 3.00% 2002 $10,992,748.00 3.00% 2003 $11,289,946.91 3.00%

(*) Denotes number of months of the fiscal year that sales tax was collected at the tax rate shown.

6 Figure 1. Estimated Retail Sales for Moore, OK 1980-2003: Actual and Inflation-Adjusted

$400,000,000.00

$350,000,000.00

$300,000,000.00

$250,000,000.00

$200,000,000.00

$150,000,000.00

$100,000,000.00

$50,000,000.00

$0.00 2 3 4 8 0 4 5 6 0 1 2 0 1 5 6 7 9 1 2 3 7 8 9 3 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 0 0 0 0 8 9 9 9 9 9 9 9 9 9 0 0 0 9 9 9 9 9 9 9 9 9 9 9 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2

Actual Inflation-Adjusted

7 Table 2 Trade Area Capture, Moore, Oklahoma, 1980-2003

Year Trade Area Capture Population 1980 20,096 35,063 1981 21,930 37,050 1982 27,864 37,750 1983 28,164 38,550 1984 27,916 39,400 1985 28,935 40,100 1986 29,877 40,200 1987 32,650 39,900 1988 32,222 39,500 1989 28,548 39,400 1990 27,673 40,332 1991 27,926 40,904 1992 27,353 41,554 1993 27,024 42,427 1994 27,480 43,151 1995 28,126 43,679 1996 32,075 44,241 1997 35,655 44,859 1998 36,389 45,233 1999 37,164 45,431 2000 35,553 41,138 2001 35,025 42,231 2002* 39,729 43,739 2003* 40,621 43,739 * Based on 2001 BEA income data and 2002 Census population data.

8 Figure 2. Trade Area Capture for Moore, OK 1980-2003

45,000

40,000

35,000

30,000

25,000

20,000

15,000

10,000

0 2 4 6 8 0 2 4 6 8 0 2 8 8 8 8 8 9 9 9 9 9 0 0 9 9 9 9 9 9 9 9 9 9 0 0 1 1 1 1 1 1 1 1 1 1 2 2

9 Table 3 Pull Factors for Cities and Towns in Cleveland County 1980-2003

Norman Hall Park Lexington Moore Noble Slaughterville 1980 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 1.165 0.113 0.426 0.818 0.556 0.106 2000 1.138 0.129 0.365 0.864 0.501 0.085 2001 1.168 0.147 0.340 0.829 0.519 0.083 2002 1.220 0.142 0.343 0.908 0.540 0.097 2003 1.256 0.128 0.330 0.929 0.553 0.093

10 Figure 3. Pull Factors for Moore and Other Cities and Towns in Cleveland County, 1980-2003

1.000 Norman 0.800 Hall Park Lexington Moore 0.600 Noble Slaughterville 0.400

0.000 0 2 3 9 0 6 8 9 1 4 5 6 7 8 1 2 3 4 5 7 0 1 2 3 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 0 0 0 8 9 0 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2

11 Figure 4. Average Pull Factors by City Size, 1980-2003

1.00 Less 1000 1-5 5-10 0.80 10-25 25-50 0.60 Grtr 50 0.40

0 2 4 6 8 0 2 4 6 8 0 2 8 8 8 8 8 9 9 9 9 9 0 0 9 9 9 9 9 9 9 9 9 9 0 0 1 1 1 1 1 1 1 1 1 1 2 2

12 Figure 5. Pull Factors for Moore vs Other Cities with Population 25,000-50,000

1.600 1.400 1.200 1.000 0.800 0.600 0.400 0.200 0.000

0 2 4 6 8 0 2 4 6 8 0 2 8 8 8 8 8 9 9 9 9 9 0 0 9 9 9 9 9 9 9 9 9 9 0 0 1 1 1 1 1 1 1 1 1 1 2 2 Moore 25,000-50,000

13 SALES GAP ANALYSIS FOR MOORE, 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 Moore’s sales gap analysis. Table 5 provides a detailed description of the 8 retail SIC categories.

For Moore’s Building and Gardening Materials, the number of shoppers has increased from a low of 11,271 in FY 1998 to 21,582 in FY 2003. (See top half of Table 4.) Moore's population is about

44,000; thus, in 2003, this sector of the Moore economy was capturing a number of non-local shoppers that was equal to about 49% of the town’s population. (See bottom half of Table 4.)

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. Moore is no exception to this rule. Moore does have a Wal-Mart, and their gap coefficient in this category was

1.674 in FY 2003.

Grocery stores (SIC 54) in Moore had a gap coefficient of 0.753 in 2003. Consumers tend to appreciate the convenience of shopping for groceries close to home; consequently, it is typical to find that even very small towns post high gap coefficients (over 1.0) for this sector. Moore is something of an exception to this rule, but if the Wal-Mart Supercenter in Moore attracts many grocery shoppers, their purchases would not be captured by SIC 54. It is also likely that the Wal-Mart Neighborhood Market reports sales under SIC 53 as well.

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 to stem from auto parts stores and other retail sales from gas stations. For instance, most gas stations

14 sell snack items, tires, some auto parts, oil, anti-freeze, etc. Sales tax collections for Moore in this category indicate that these types of businesses attracted about 67% of the residents of Moore in 2003.

Gap coefficients have been growing in this sector since 1998.

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. Moore is a relatively large community in Oklahoma, and it does fairly well in this category. Apparel stores captured a total of

27,674 shoppers in FY 2003 for a gap coefficient of 0.633.

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. Moore probably does compete with this Oklahoma City furniture cluster. Moore’s gap coefficient for this sector was just 0.39 in 2003.

Eating and Drinking Places, SIC 58, is one of the most straightforward retail sectors. It contains restaurants and bars. Restaurants and bars in Moore captured 34,494 customers in FY 2003. This gap coefficient has been growing since 1998. Currently, restaurants in Moore tend to attract a number of non-local shoppers that is equal to about 79% of the town’s population.

SIC 59, or Miscellaneous Retail, contains a host of retail activity, including pharmacies, florists, liquor stores, and antique stores. These are often the downtown or Main Street merchants. Moore's pull factor in this category was 0.376 in 2003.

15 Table 4 Retail Sales Gap Analysis by Standard Industrial Classification (SIC) Code, Moore: Fiscal 1998-2003

FY FY FY FY FY FY TRADE AREA CAPTURE 1998 1999 2000 2001 2002 2003 Building, Gardening & Merchandise (52) 11,271 14,425 25,441 13,734 22,054 21,582 General Merchandise (53) 63,438 68,465 60,152 65,445 76,074 73,205 Food Stores (54) 29,415 27,933 25,188 21,766 22,840 32,921 Automobile Dealers & Gas Stations (55) 20,571 21,249 20,588 23,006 26,411 29,367 Apparel & Accessory Stores (56) 33,585 29,492 27,474 28,064 27,831 27,674 Furniture & Home Furnishings (57) 18,041 17,689 17,567 15,981 18,350 17,071 Eating & Drinking Places (58) 32,093 32,919 30,737 31,413 33,859 34,494 Miscellaneous Retail (59) 19,355 17,538 15,626 15,683 15,677 16,462

FY FY FY FY FY FY SALES GAP COEFFICIENT * 1998 1999 2000 2001 2002 2003 Building, Gardening & Merchandise (52) 0.249 0.318 0.618 0.325 0.504 0.493 General Merchandise (53) 1.402 1.507 1.462 1.550 1.739 1.674 Food Stores (54) 0.650 0.615 0.612 0.515 0.522 0.753 Automobile Dealers & Gas Stations (55) 0.455 0.468 0.500 0.545 0.604 0.671 Apparel & Accessory Stores (56) 0.742 0.649 0.668 0.665 0.636 0.633 Furniture & Home Furnishings (57) 0.399 0.389 0.427 0.378 0.420 0.390 Eating & Drinking Places (58) 0.710 0.725 0.747 0.744 0.774 0.789 Miscellaneous Retail (59) 0.428 0.386 0.380 0.371 0.358 0.376

* For purposes of this paper, when analyzed by SIC code, the pull factor is referred to as the sales gap coefficient.

16 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

. 17 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

18 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 19 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

20 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.

21 SUMMARY

This report has analyzed taxable sales trends for the city of Moore and Cleveland County.

The level of taxable sales in Moore has grown significantly in nominal terms since 1980. After correcting for inflation, taxable sales have still grown since about 1992. Located off Interstates

35 and 240, Moore is “sandwiched” between Oklahoma City and Norman. Norman is the county seat for Cleveland County and is clearly the center of trade for the county as well.

Leaders in Moore might be disappointed that the pull factors for Moore are less than 1.0 and that Moore performs below the average for other cities of similar size. The other side of this, however, is the significant growth in retail pull that has occurred in Moore in recent years. Since

1992, real sales (adjusted for inflation) have increased nearly 70%, and nominal sales figures have increased 122%. Pull factors have increased from 0.658 (in 1992) to 0.929.

General merchandise (the Wal-Mart category) is, by far, the sector that attracts the most shoppers to Moore. The retail categories that appear relatively low are building and gardening merchandise (reflecting that there is apparently no large home improvement center in Moore), furniture and home furnishings, and miscellaneous retail (often the downtown merchants.) These all attract less than 50% of the local shoppers in their respective categories. Food stores is also relatively low, attracting about 75% of local shoppers.

22 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, , 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 2003. (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 2002. 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 2001.

Woods, Mike D. Retail Sales Analysis in Oklahoma By County, 1977, 1982, 1987. Bulletin B- 801, Agricultural Experiment Station, Oklahoma State University, October 1991.