NEW MEXICO MAINSTREET COMMUNITY ECONOMIC ASSESSMENTS

Transcription

1 NEW MEXICO MAINSTREET COMMUNITY ECONOMIC ASSESSMENTS Data, Analysis and Trends Jeffrey Mitchell Molly Bleecker Joshua Akers November 2007 University of New Mexico Bureau of Business and Economic Research 303 Girard Suite 116 Albuquerque, NM (505)

2 NEW MEXICO MAINSTREET MISSION The New Mexico MainStreet Program fosters economic development in the state by supporting local MainStreet revitalization organizations and their work in downtowns and the adjacent neighborhoods. The Program provides resources, education, training and services that preserve and enhance the built environment, local historic culture and heritage and stimulate the economic vitality of each participating community.

3 MAINSTREET PROGRAM Partnership of national, state & local public and private organizations National Trust for Historical Preservation, National MainStreet Institute New Mexico Economic Development Department, New Mexico MainStreet Program (NMMS) Community MainStreet Programs

4 With 27 communities, NMMS is the largest MainStreet program in the U.S.

5 MAINSTREET S FOUR POINT APPROACH I. Organization social II. Promotion political III. Design physical IV. Economic Restructuring economic

6 MAINSTREET S GUIDING PRINCIPALS 1. Comprehensive 2. Incremental 3. Self-Help 4. Partnerships 5. Capitalizing on Existing Assets 6. Quality 7. Change 8. Implementation

7 BBER S PARTNERSHIP WITH NMMS To provide Community Economic Assessments in support NMMS mission in economic development and restructuring. Began in 2003 with Leakage study of Grants (reviewed at BBER Data User s Conference in 2005), and continued for FYs Completed assessments of 19 communities, with 3 more scheduled for Spring 2008.

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9 RATIONALE FOR BBER S INVOLVEMENT Economic component has often been the weak link of the MainStreet Approach goals are long term, results are not always evident. (compare with Organization, Promotion, Design) Decisions by business owners, entrepreneurs, MS leaders are often based on subjective information. Small communities in NM receive inadequate public support focus on smokestacks that yield photoops overshadow community development.

10 BBER s ANALYTICAL APPROACH Economic Geographical Approach In an increasingly competitive global economy, places (neighborhoods, towns, regions, etc) must find and develop their niche matching their unique strengths with their function in the broader economy.

11 BBER s ANALYTICAL APPROACH Town s Role with State & Regional Economy (Location Quotients, Gross receipts Analysis/Pull Factors) Community Profile (demographics, housing, Incomes) MS Role in Town Economy (Demographics, 202 employment & wages) Policy

12 OUTLINE I. Data and Analysis used in BBER/MainStreet Community Economic Assessments (Molly Bleecker) II. III. ESRI s Business Analyst Data and Trade Area Analysis (Josh Akers) New Mexico Special Considerations in the Analysis of Small Towns/Rural Areas (Jeff Mitchell)

13 I. BBER/NMMS COMMUNITY ECONOMIC ASSESSMENTS DATA & ANALYSIS

14 Town s Function within State & Regional Economy (Location Quotients & Gross Receipts/Pull Factor Analysis)

15 Location Quotients

16 Using LQs LQs indicate the role of a local economy within its larger geography. LQs help define the relative strengths and weaknesses of a local economy, measured in terms of industrial, occupational, and ownership structures. This information can inform policies that aim to strengthen weaknesses or exploit strengths.

17 Location Quotients Indicate the concentration of employment of the residents of a given geography relative to that of a base geography ; e.g., Grants in relation to Cibola County. Employment sectors can be industries, occupations, or types of worker (government, private, family, etc). Use Census 2000 tables P49-51: Table P49: Sex by Industry for the Employed Civilian Population 16 Years and Over Table P50: by Occupation for the Employed Civilian Population 16 Years and Over Table P51: by Industry by Class of Worker for the Employed Civilian Population 16 Years and Over

18 Calculating LQs Calculated as ratio of local employment in given industry, occupation, or ownership type to total employment, in relation to same ratio for base geography; i.e., town employment sector / town total employment county employment sector / county total employment LQ = 1.0 indicates that a job is in proportion with the base geography. LQ >1.0 indicates that a job is relatively more common than in base geography. LQ < 1.0 indicates that a job is relatively less common than in base geography.

19 An Example A. B. C. A. Raw data from Census B. Employ Share= (Industry employ)/ (Total employ) C. Location Quotient = Grants share/ ax Share

20 >1 values in relation to Cibola County in wholesale, information, finance, mgt, and accom & food jobs indicate role Grants plays in the region (County Seat of Cibola County & commercial center of the region). Compared to the state, nothing special in these sectors. Arts, entertainment & rec jobs are very common vis-à-vis State, but nothing special in Cibola County. Interpreting Grants LQs

21 Pull Factors

22 Pull Factors Measure the effectiveness of an economic sector in bringing revenues into a community. Can be calculated by major sector (e.g., retail) or by specific subsector (e.g., auto parts), depending on the quality of the data.

23 Computation Calculating Pull Factors divide the community s GRs for a given sector by the total personal income for that community Do the same for the state Then divide the former by the latter, i.e., (Community GR sector / Community Income) (State GR sector / State Income)

24 Data used Calculating Pull Factors, Cont d. Gross receipts data from NM Tax & Rev Dept. (RP-80) Quarterly, by 6-digit NAICS sector Available at state, county, and town level Must be painstakingly formatted Personal income data from 2000 decennial census (SF3) Table P83 (aggregate income for population 15 years and older), adjusted for intervening years using BEA personal income summary data (CA1-3 for communities, SA1-3 - for the state.)

25 Using Pull Factors A value of 100% is break-even point. Values greater than 100% indicate the sector is drawing revenues into the local economy Values less than 100% indicate the sector is leaking money to other communities. Assume that persons in all communities spend income in the same proportion as the state as a whole.

26 Understanding Pull Factors Dividing the Grants proportion by the State proportion standardizes the Grants numbers. A value of 100% means that store receipts are in line with the State average (based on incomes in Grants).

27 Understanding Pull Factors, Cont d. A value < 100% means that stores in Grants are selling less than their share of X in Grants (compared with state average). Thus, Grants residents are buying those products elsewhere. That sector is Leaking revenues. Example: Wholesale Trade in Grants.

28 Understanding Pull Factors, Cont d. A value > 100% means that stores in Grants are selling more than their share of X in Grants (compared with state average). Thus, out-of-towners are buying those products in Grants. That sector is attracting revenues. Example: Gas Stations in Grants.

29 Interpreting Grants Pull Factors Overall, Grants is positive: pull factor of 133%. Retail is the main draw, wholesale is a major point of leakage. Within retail, I40-related and Misc General Merchandise (Wal-Mart) and Eating & Drinking are principal sources of outside revenues.

30 Policy Implications Two ways for a community to grow economically: either be more efficient (technology) or accumulate more resources (land, labor, capital). For resources, either limit the loss of resources ( plug leaks ) or capitalize on strengths. For many communities, retail & services are among the best opportunities.

31 Community Profile (Demographics, Housing, Incomes)

32 Demographics, Housing, Incomes

33 Demographics, Housing, Income Characteristics Give a picture of the community in relation to surrounding geographies and through time. Use data from 1990, 2000, and later for communities, counties, regions, the state. Demographic data: total population, as well as age, race and ethnicity breakdowns total households educational attainment migration

34 Demographics, Housing, Income Characteristics, Cont d. Housing and Income data: Household income and poverty Labor characteristics: employed and unemployed Housing characteristics: housing units, vacancy rate, occupancy type, home ownership, age of housing Housing affordability: value of housing, % of income spent on housing

35 2000 Decennial Census and ESRI ArcGIS Business Analyst Used Census alone or in combination with ESRI in past. Used ESRI alone this year. Pros and Cons for each: Data Sources Census Pros LOTS of data available Reliable Free ESRI Pros Projections for recent years Can aggregate small geographies easier Census Cons Only available every 10 years ESRI Cons? reliability of data, esp. at small scale Less data available, e.g., no poverty rate. $$$$$$$$$$

36 Demographics Example ROSWELL CHAVES COUNTY SE NM Region NEW MEXICO POPULATION Total Population 44,654 45,451 61, ,551 1,819,046 Households 16,208 17,089 22,559 61, ,032 Household Size (Average) AGE Under 5 yrs 8% 7% 7% 7% 7% 5 to 17 y/o 22% 21% 22% 22% 21% 18 to 64 y/o 54% 55% 56% 57% 60% 65 yrs and over 16% 16% 15% 14% 12% RACE & ETHNICITY White 82% 70% 72% 72% 67% Black or African American 2% 3% 2% 3% 2% Native American 1% 1% 1% 1% 9% Hispanic or Latino (of any race) 36% 45% 44% 41% 42% Speak Spanish, Linguistically isolated* 5% 3% 3% 2% 2% EDUCATIONAL ATTAINMENT Less than High School graduate** 31% 26% 27% 28% 21% High School graduate; and some college 49% 51% 50% 52% 49% Associate, Bachelor's, or Graduate degree 21% 23% 22% 20% 29% MIGRATION Moved to new house in County since 1985/ % 27% 26% 26% 24% Moved into County since 1985/1995* 23% 18% 17% 15% 20% Source: US Census Bureau, 1990 and 2000

37 Housing Example ROSWELL CHAVES COUNTY SE NM Region NEW MEXICO HOUSING CHARACTERISTICS Total housing units (#) 18,242 19,286 25,647 71, ,579 Home ownership (%) 67% 67% 70% 68% Owner-occupied housing units 11,188 11,760 15,986 44, ,435 Vacancy rate (For Sale) 3.1% 3.2% 3.6% 2.5% Renter-occupied housing units 5,007 5,350 6,575 16, ,536 Vacancy Rate (For Rent) 14.8% 13.6% 16.6% 11.6% Median age of Housing Structures na 23 HOUSING AFFORDABILITY Median value of Owner-Occupied Housing (1999$) 57,924 55,800 56,700 na 94,600 Median costs of homeownership (% of income) 19.4% 20.2% 19.8% na 22.2% Median Rent (1999 dollars) na 503 Median cost of rental housing (% income) 28.5% 25.8% 25.0% na 26.6% Source: US Census Bureau, 1990 and 2000

38 Income Example ROSWELL CHAVES COUNTY SE NM Region NEW MEXICO HOUSEHOLD INCOME & POVERTY Real per capita income (1999 dollars) 14,454 14,589 14,990 14,980 17,261 Median household income (1999 dollars) 29,189 27,252 28,513 na 34,133 Households with earnings 73% 72% 75% 75% 80% Households with Social Security income 34% 35% 33% 31% 25% Households: interest; dividends; or rental income 34% 29% 28% 26% 30% Households with public assistance income 10% 7% 6% 6% 5% Households with retirement income 18% 18% 17% 16% 17% Persons below the Poverty Line 9,386 10,003 12,778 32, ,933 Poverty Rate 21.6% 22.6% 21.3% 20.0% 18.4% LABOR CHARACTERISTICS In labor force (population 16 yrs and over) 18,642 18,407 25,361 69, ,632 Unemployment Rate 6.5% 9.7% 9.0% 8.3% 7.2% Source: US Census Bureau, 1990 and 2000

39 MainStreet s Role in Town Economy (202 employment & wages)

40 ES-202: MS Businesses, Employment, & Wages

41 Covered Employment (ES-202) Data Give a picture of the distribution of businesses, employment, and wages in various geographies, e.g., MS, town, county. Allow us to see role of MainStreet in a community. About the data: from NM Dept. of Labor (BBER has access through a confidentiality agreement with DOL) Includes establishment-level data on employment, wages, industrial classification, address includes both x/y coordinates and addresses. BBER cross-checks these.

42 Example: Employment by Industry and Geography, Grants, Grants MS Employment Transport & Warehsing Admin & Support Information Manufacturing Prof, Sci & Tech Svcs Other Services Public Administration Finance & Insurance Real Estate Arts, Entertain & Rec Wholesale Trade Utilities Accomm & Food Svcs Education Retail Trade Health Care Source: NM Department of Labor, ES-202 (Covered Employment Statistics), Calculations by BBER, 2007.

43 II. ESRI/BUSINESS ANALYST 9.2 TRADE AREA ANALYSIS

44 ESRI ArcGIS Business Analyst

45 Available Data Sets OUTLINE Defining Geographies and determining scale Spatial analysis tools Gravity models & Trade Area Analysis The features in Business Analyst allow for quick aggregation of data for various geographies. Spatial analysis tools allow us to capture the data behind geographies utilizing variables of distance and competition.

46 Why Business Analyst for MainStreet? Data and tools tailored toward mapping trade areas Demographic Projections for communities of any size Drive Time function allows for analysis to mirror travel times instead of linear distance Designed to identify marketing opportunities (Trade Areas) for businesses Economic Development a stated goal of MainStreet project

47 DATA Census Data Market Profile Business Data

48 1. Census Data Demographic, Income and Housing Geocoded Analysis at Block Group level possible SF01 (Complete count) for Demographics SF-3 (1 in 6 sample) for Income and Housing

49 Projections and Estimates ESRI uses three primary data sources for inter-census projections of population & demographics, income, housing, consumer spending. 1. Acxiom s InfoBase household database (ABA) 2. USPS Residential Delivery Statistics (delivery stats assigned to Census 2000 block groups) 3. Hanley Wood Market Intelligence, for residential construction (75 top housing markets) 4. Undisclosed ancillary sources

50 Margin of Error ESRI measures error rates for population estimates using historical projections. Mean Absolute Percent Error for projections over 10-year period between U.S. 2.45% State Mean 2.66% New Mexico 4.08% County Mean 3.47% Census Tract 6.80% Block Group 8.87%

51 Margin of Error (cont.) As geographical area shrinks, miscounts of smaller populations increase the margin of error ESRI s Evaluating Population Projections: The importance of Accurate Forecasting. is available at

52 2. Market Profile (Consumer Spending) BLS Consumer Spending Survey National patterns projected Census Block geography 730 items grouped into 15 categories Adjustments for local income patterns Retail Goods and Services Report ID: 0 1 Description: 0-3 Summary Population 4,679 4,681 Households 1,872 1,902 Families 1,310 1,303 Spending Potential I d Average Amount Spent Apparel and Services 46 $1, $2,339,124 Men's 49 $ $470,156 Women's 43 $ $750,444 Children's 54 $ $451,383 Footwear 25 $ $236,011 Watches & Jewelry 60 $ $209,230 Apparel Products and Services 81 $ $221,901 Computer Computers and Hardware for Home Use 63 $ $264,838 Software and Accessories for Home Use 64 $20.20 $37,825 Entertainment & Recreation 63 $2, $3,868,868 Total

53 1. InfoUSA 3. Business Data Gecoded Sales Volume Employment Numbers Business Status 2. Directory of Major Malls Total Sales Volume Leasable Square Footage

54 Geography / Scale for MainStreet Trade Area Analysis

55 Scale for Analysis MainStreet Boundaries defined by municipality/ms Board Walking Distance Buffers ¼ mile around Main Street 30-second drive time

56 MainStreet and Buffer

57 3-Minute Drive Time Scale for Analysis (cont.) Short and convenient route from home or hotel Town Region Generally drive times are used. Future direction is to use Gravity Models to define trade areas inductively.

58 Short Drive Time and City Boundaries

59 Regional Scale

60 TRADE AREA ANALYSIS Why use trade area analysis? Estimate market capacity Delineate market areas To capture the data behind it

61 DEFINING TRADE AREAS WITH ESRI BUSINESS ANALYST 9.2 To define trade areas, BA uses 3 variables & data sets: Competition (Source: InfoUSA or others) address referenced with revenue projections. Distance Drive Times (using road & street data) or Linear Distance ( as the crow flies ) Consumer profiles -- Census data on Block Group scale, demographics, income, spending

62 DEFINING TRADE AREAS WITH ESRI BUSINESS ANALYST 9.2 no competition equal competition weighted competition calibrated competition Ring (Euclidean) Simple ring Gravity: Theissen Gravity: Simple Huff Gravity: Advanced Huff Drive Distance Drive Distance NA NA Drive Time Drive Time NA NA Gravity: Advanced Huff Gravity: Advanced Huff

63 Simple Rings No measures of competition As the crow flies distance from a particular point Allows preliminary analysis of markets and trade areas when customer data is unavailable User specifies number of rings and the distance of each ring

64 1. Grants Simple Rings

65 Comprehensive Profile Grants Simple Rings Demographic 0-1 Miles 0-3 Miles 0-5 Miles Income (2011): Median Household Income $39,331 $39,957 $39,667 Median Family Income $49,320 $44,406 $43,831 Average Household Income $48,193 $50,219 $49,727 Average Family Income $57,302 $55,837 $55,166 Per Capita Income $19,382 $19,726 $19,348 Net Worth (2006): Median Net Worth $56,873 $46,542 $44,497 Households by Net Worth (2006): < $15, ,472 1,747 $15,000-$34, $35,000-$49, $50,000-$74, $75,000-$99, $100,000-$149, $150,000-$249, $250, , , Households by Disposable Income (2006): < $15, ,037 $15,000-$24, $25,000-$34, $35,000-$49, $50,000-$74, $75,000-$99, $100,000-$149, $150,000-$199, $200,

66 2. Drive Time Polygons Uses actual street networks Approximates Drive Times Advantages Models how people actually travel

67 Grants Drive Time Polygon

68 Gravity Models Equal Probability (Indifference Curve) Trade area break points are weighted based on variables such as sales volume or number of employees Parameters can be entered manually based on predictor variables in your store layer. An example, competitors nearby have sales volumes between $1 million and $2 million per year. You choose $1.5 million.

69 3. Equal Competition Assumes customer will travel to closest store Estimates store trade areas Lines are drawn halfway between stores Theissen Model Uses include pizza delivery and direct mail

70 Equal Competition Grants

71 4. Gravity Models: Simple Huff A gravity model assigns trade areas to competing markets. Two Variables involved Unequal competition; i.e. Attractiveness of the markets The Measurement of Distance

72 5. Advanced Gravity Models Advanced Huff Modeling Empirical calibration of Distance Decay Function Observed behavior Market Survey Measures of distance Standard Euclidian distance Drive Time Drive Distance

73 Advance Gravity Model: Albuquerque

74 MAINSTREET QUIZ

75 Guess that MainStreet Community: Community 1, Clue 1? NM 2000 SELECTED SOCIAL & DEMOGRAPHIC CHARACTERISTICS Education Educational Attainment: Less than High School 2, % 2, % 21.1% Educational Attainment: HS graduate; and some college 4, % 3, % 49.5% Educational Attainment: Associate, Bachelor's, or graduate degree 1, % 2, % 29.4% HOUSING CHARACTERISTICS Occupied: Owner-occupied housing units 3, % 3, % 60.8% Occupied: Renter-occupied housing units 1, % 2, % 26.1% Vacant housing units % % 13.1% Median value (dollars) $48,400 $87,100 $108,100 Median costs of homeownership, with mortgage, as percentage of household income 24.6% 27.5% 22.2% ECONOMIC CHARACTERISTICS Per capita income in 1999 (dollars) $7,515 $12,619 $17,261 Median household income in 1989/1999 (dollars) $18,023 $29,797 $34,133 LABOR CHARACTERISTICS Labor force (population 16 yrs and over) 5, % 5, % 61.8% Unemployed % % 3.3% 4, % 5, % 96.7% 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

76 Educational Services Information Guess that MainStreet Community: Community 1, Clue 2 Transportation & Warehousing Retail Trade Construction Wholesale trade Health Care & Social Assistance Hospitality Finance & Insurance 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

77 Guess that MainStreet Community: Community 1, Clue 3 This hotel anchors the community s MainStreet. 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

78 Guess that MainStreet Community: Community 2, Clue 1 1,200 1, Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming Agriculture Mining Utilities Construction Manufacturing Wholesale Trade Retail Trade Trans & Warehousing Information Finan & Insurance Real Estate Prof & Scientific Svcs Admin & Support Svcs Educational Svcs Health & Social Assist Arts, Entertainment & Rec Accomm & Food Svcs Other Services Public Administration Remainder of? MainStreet

79 Guess that MainStreet Community: Community 2, Clue 2 This community has a poverty rate of 20.1% (in 2000), and its MainStreet program has a $1.5 million endowment. 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

80 Guess that MainStreet Community: Community 2, Clue 3 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

81 Guess that MainStreet Community: Community 3, Clue 1 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

82 DEMOGRAPHICS Guess that MainStreet Community: Community 3, Clue 2 MAINSTREET? NEW MEXICO Educational Attainment (2000, 25 y/o and over) No HS Diploma 9% 6% 21% High School Degree 17% 17% 27% Some College or Associate Degree 23% 27% 29% Bachelors Degree or Higher 51% 51% 23% INCOME Per Capita Income (2006) $38,989 $42,651 $21,756 HOUSING Median Home Value $285,897 $256,549 $94,594 Housing Units by Units in Structure (2000) 315 3, ,579 Single Family 84% 85% 66% Multi-Family 3.5% 3.3% 15.3% Mobile Home 12% 11% 19% Source: ESRI ArcGIS 9.2 Business Analyst, using U.S. Bureau of the Census, 2000 Census of Population and Housing. ESRI forecasts for Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

83 Guess that MainStreet Community: Community 3, Clue 3 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

84 160, , , ,000 80,000 60,000 40,000 20,000 0 (20,000) Guess that MainStreet Community: Community 4, Clue 1 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming ENGINEER AND ARCH DRUG STORES HEALTH SERVICES WHOLESALE TRADE FIN, INSUR & REAL ESTATE PERSONAL SERVICES AUTO RENTAL, REPAIR BUILDING MATERIALS HOTELS, MOTELS, MISC VEHICLE & ACCESSORY APPAREL STORES MOTOR VEHICLE DEALERS RETAIL FOOD STORES EATING AND D RINKING MISC RETAILERS MISC BUSINESS SERVIC ES CONTRACT CONSTRUCTION TRANSPORT, COMMUN, UTILITIES 000s $

85 Guess that MainStreet Community: Community 4, Clue 2 Public Administration Professional, Scientific & Tech Services Information Wholesale trade Transportation & Warehousing Other Services Retail Trade Hospitality Health Care & Social Assist Admin & Support Services 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

86 Guess that MainStreet Community: Community 4, Clue 3 This community is known as the place to buy Native American jewelry. 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

87 III. NEW MEXICO ANALYSIS OF SMALL TOWNS & RURAL AREAS

88 1. Trade Area Analysis in a Small Town What s unique about a small town? Transportation network is not dense. Population (market) is unevenly distributed. Competition is unevenly distributed. These factors increase the sensitivity of models to key variables, particularly the density of the transportation network.

89 Grants New Mexico

90 Euclidean (Crow Flies) Distance Grants

91 Drive Time Distance Grants

92 COMPARING MODELS

93 GRAVITY MODEL CHICAGO

94 2. HIGHWAY COMMUNITIES IS GROWTH A ZERO SUM GAME? For otherwise isolated highway communities, highway businesses is a quick way to increase gross receipts. But is one town s gain another town s loss?

95 RATON VS. LAS VEGAS COMPETITION FOR TRAVELER MARKET TOTAL TAXABLE GROSS RECEIPTS LAS VEGAS RATON TRANSPORT, COMMUN, UTILITIES 143% 55% GASOLINE SERVICE STATIONS 73% 326% MISC VEHICLE AND AUTO ACCESSORY 122% 284% EATING AND DRINKING 228% 141% HOTELS, MOTELS, 52% 152% AUTO RENTAL, REPAIR 184% 213%

96 3. Location Quotients in Remote Areas Employment location quotients use Decennial Census data (SF-3), tabulated according to RESIDENTIAL location. For Residential Communities (e.g. Corrales), LQs indicate little about structure of the local economy. For more remote areas (where most work in the town where they live), LQs tell us much about economic structure (types of occupations, industries, public vs. private).

97 COMPARISON OF OCCUPATIONAL LQ Clovis Corrales Mgt, business & Finance Production & Transportation Extraction Maintenance Protective service Agriculture Sales & office Building & grounds maint. Professional Healthcare Personal care Construction Food service Location Quotient Location Quotient Extraction Agriculture Healthcare Protective Services Building & Grounds Maint. Food Services Personal Care Production & Transp Install; Maint; & Repair Construction Sales & Office Professional Mgt, Business, Finance

98 RECURRING THEMES IN NEW MEXICO MAINSTREET COMMUNITIES 1. STALLED TRANSITION FROM RETAIL & SERVICE CENTER MainStreets were once the retail and service center of the town. In many towns, retail is mostly gone, some professional & personal service remains, most public service remains. The 9-5 MainStreet.

99 RECURRING THEMES IN NEW MEXICO MAINSTREET COMMUNITIES 2. DESTINATIONS RATHER THAN PEDESTRIANS Businesses survive only as destinations (Bernalillo s Range Restaurant, Grants El Cafecito, Farmington s Three Rivers Brewery). Little or no pedestrian traffic (Bernalillo, Corrales, Hobbs, Grants) Need to develop clusters Need to integrate multiple markets (MS residents, town residents, destination visitors, travelers, etc) Need to incorporate Residential development as part of revitalization (Gallup, Clovis, Las Vegas, Farmington, Hobbs)

100 RECURRING THEMES IN NEW MEXICO MAINSTREET COMMUNITIES 3. THE WALMART DILEMMA Wal-Mart generates Gross Receipts taxes. Wal-Mart doesn t kill MainStreet, but it buries it. Wal-Mart as an opportunity. Competing with Wal-Mart or Surviving with Wal- Mart. Yes: Gallup, Grants, Farmington (2), Bernalillo (coming soon!), Las Vegas (2), Clovis, Roswell, Hobbs, Artesia, Carlsbad, Las Cruces, Silver City, Deming,. NO: Chama, Raton, Clayton, Tucumcari, Santa Rosa, Portales, Corrales)

101 RECURRING THEMES IN NEW MEXICO MAINSTREET COMMUNITIES 4. ABSENTEE PROPERTY OWNERSHIP Important buildings are vacant or underutilized Often owned by old inactive families or out of town speculators. Farmington, Gallup, Raton, Clovis, Silver City. Hobbs property owner recently made available several buildings to MS for redevelopment.

102 RECURRING THEMES IN NEW MEXICO MAINSTREET COMMUNITIES 5. TOURISM LAST RESORT Without exception, every MS community sees tourism (or retiree residential development) as their great unplayed card. Few understand the market, effectively identify trends, invest strategically. The importance of the local market (stop leakages) The legacy of High School football & the failure of regionalism

103 Guess that MainStreet Community? 1. Gallup 2. Grants 3. Farmington 4. Chama 5. Bernalillo 6. Corrales 7. Las Vegas 8. Raton 9. Clayton 10. Springer 11. Tucumcari 12. Santa Rosa 13. Portales 14. Clovis 15. Artesia 16. Hobbs 17. Carlsbad 18. Roswell 19. Las Cruces 20. Silver City 21. Deming

104 USEFUL LINKS National MainStreet New Mexico MainStreet Visiting NMMS Communities NMMS Directory UNM-BBER NMMS Community Economic Assessments

105 New Mexico Data Users Conference 2007 Jeffrey Mitchell Molly Bleecker Joshua Akers November 2007 University of New Mexico Bureau of Business and Economic Research 303 Girard Suite 116 Albuquerque, NM (505)