1. The Challenges of a Dynamic Retail Market in Kansas Presented By David L. Darling CD Economist And Sandhyarani Patlolla Department of Agricultural Economics Kansas State University Manhattan, Kansas

2. Community Functions and Assets Community Function Human capital Financial capital Engineered capital Social capital Natural capital Living Economic Government Service Social and Cultural

3. Economic Functions Consumption activity Production activity Investment activity

4. Sources of Income Communities and functional economic units (regions) rely on three sources of income. 1. Earned Income from the export of products and from the income of commuters. 2. Captured Income from transfer payments, property income, and inheritances. 3. Made Income from the income multiplier effect.

5. Made Income In order for the income multiplier to be substantial i.e., 2.00 or greater. Retail communities must hold on to local trade i.e., minimize leakage, and pull in trade from outside. This results in pull factor greater than 1.00.

6. Formula of Income Multiplier (IM) IM = 1 / (1- (PCL * PSY)) PCL: The proportion of new, after tax household income, that is spend locally. This can range from 0.3 to 0.90 in Kansas communities. PSY: The proportion of household income spent locally which remains in the area’s economy to support other households. This usually ranges from 0.25 to 0.65 for non-metropolitan communities.

9. Counties with high Pull Factors Johnson: 1.55 (TAC =717,040) Pottawatomie: 1.44 (TAC = 26,280) Saline: 1.37 (TAC = 72,618) Ellis: 1.32 (TAC = 35,517) Shawnee: 1.20 (TAC = 198,917) Sedgwick: 1.20 (TAC = 540,860) Source: The FY 2002 K-State Report #210

10. Cities of the First Class City NameCity Pull Factors(PF) Trade Area Capture(TAC) %County Trade Wichita 1.28 437,745 80.90% Overland Park 1.78 271,861 35.45% Topeka 1.57 186,048 93.49% Olathe 1.60 153,073 19.96% Kansas City 0.70 101,909 89.19% Lawrence 1.10 87,101 93.17%

11. Cities of the First Class (cont’d…) City NameCity Pull Factors(PF) Trade Area Capture(TAC) %County Trade Lenexa 2.05 82,253 10.72% Salina 1.52 68,529 94.33% Shawnee 1.18 59,809 7.80% Hutchinson 1.45 54,492 84.03% Manhattan 1.18 50,035 89.42% Garden City 1.24 34,312 83.06%

13. Average % Market Share by Region In Kansas RegionAverage % Market Share RegionAverage % Market Share Northeast43.6%Southeast5.4% North Central10.9%South Central30.9% Northwest3.5%Southwest5.7%

14. % Market Share Regional Growth Rate RegionRegional Growth Rate RegionRegional Growth Rate Northeast1.19%Southeast-0.58% North Central-0.75%South Central-1.06% Northwest-1.30%Southwest-0.57%

15. Model for County Retail Strength County Retail Strength = f(CB,BP,RE) Where  CB stands for the customer base served  BP stands for buying the power of the customer base  RE stands for the retail environment

16. Pull Factor Regression Analyses Dependent variable: Pull Factor. Method: Least Squares. Included observations: 93.

17. Variable Names, Predicted Values and Description Variable Name Expected Value Description PER CAPITA INCOME + Measure of the 2002 per capita income in every county URBAN MASS + Population of the dominant city(s) within each county. VALUE + Measures the per capita value of commercial property in all its dimensions: both real and personal property. CIIV + The size of the flow of commuter income. MJRHWY + Indicates whether a county is on a major highway

18. Pull Factor Regression Analyses (contd…) VariableCoefficientStd.errort-StatProbability CIIV 0.148820.053212.7965 0.0064 INCOME 0.021270.006693.1775 0.0021 MJRHWY 0.071310.035602.0029 0.0483 URBANMASS 0.002594.37E-45.9300 0.0000 VALUE 0.000275.61E-54.9496 0.0000

19. Pull Factor Regression Analyses (contd…) R-squared0.7574 Adjusted R-squared0.7434 Sum of squared errors1.4315 Log likelihood62.1226 Mean dependent variable0.61075 Schwarz criterion0.02062 Akaike Information criterion0.01751

20. Economic Development Strategies and Resources STRATEGIESHuman Capital Financial Capital Social Capital Engineered Capital Environmental & Natural Resource Capital Retentions & Expansion Firm Creation Local Linkage Capture Dollar Attraction

22. Thomas County Example: Thomas County Popl’n 2001 Pull Factor Trade Area Capture % of county Sales Colby5,2511.387,24880.24 Brewster2800.20570.63 Rexford1560.09140.16 Gem950.022 Menlo570.0530.03 Rest of County2,0690.821,69218.73 County Data7,9621.139,032100.00

23. Thomas County Retail History Measures2000 Census 1990 Census 1980 Census Population8,1808,2778,451 Trade Area Capture (FY) 9,1049,84511,328 Pull Factor (FY) 1.141.181.35

24. Firm Marketing Choices 1. Expand market share with the current product line. 2. Enter a new market with the current product line. 3. Develop a new product for the current market. 4. Develop new product and sell in a new market.

26. Further Research Needed If retail sales are a derived demand, what do retail sales measure? Who are the stakeholders in a successful retail community? Should local governments subsidize it? Should economic developers spend their time and efforts assisting retail businesses?

27. Policy Issues Should retail sales be taxed? If so, how should we tax Internet and catalogue sales? Should government subsidize small retail operations the way it subsidizes farm businesses? Why? Why not?

28. For more information go to: www.agecon.ksu.edu/ddarling