Retail Sales Data by ugd11381

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									Causes of Retail Pull in
Nebraska Counties and
       Towns
         A Thesis
            By
        Rex Nelson
              Introduction
 Motivation for study – to understand rural
  declines
 Improve effectiveness of rural
  development efforts
                  Introduction
            Observations in Rural America:
   Rural population declines
   Rural business district declines
   Declining services available to rural dwellers
   Declining quality of life for rural residents
   Declining job opportunities
   Shrinking tax base
   Decaying rural infrastructure
                Introduction
         Goal: Improved Understanding
   Learn to modify, if not change trends
   Manage impacts
   Focus rural development efforts
   Improved public policy
   Better use of scarce resources
              Retail Trade
 This study uses retail trade as a
  benchmark to measure relative economic
  performance
 It is a net by which wealth is captured and
  transferred to new ownership
   In recipient community: creates jobs and
    economic multiplier effects
   In doner communities: opposite effects
              Retail Trade
 Rural counties in Iowa, Kansas Missouri
 and Nebraska
   15% retail leakage in 1970’s
   20% in 1990’s1
 Lost Jobs
 Population declines


                   (1) Leistritz, Ayres and Stone
     Causes in the Literature
 Central Place Theory
   Distance and geographic area2
   Distance and demand thresholds3
 Population and demographics
   8.4% of U.S. counties accounted for 93% of
    growth 1990 to 19964
   Age and shopping patterns
 Income
                (2) Reilly 1931, (3) Craig et al (4) Rathge
     Causes in the Literature
 Retail environment
   Size and quality5
   Presence of big box retailers
 Transportation
   Highway access
 Agriculture dependence6


                   (5) Darling (6) Yanagida et al
                   Theory
 Retail Trade =
   People
   Money
   A place to trade
                   Theory
 Retail Strength is represented by:
   County Trade Pull Factor (CTPF)
   County taxable retail sales / average of state
    aggregate taxable retail sales
 Measures retail trade coming into or
 “leaking” out of a community
                  Theory
 CTPF = f(CB, BP, RE)
 Where:
   CB is Customer Base
   BP is Buying Power
   RE is Retail Environment




                      (7) Darling
                Theory
           Dependent Variable

 CTPF represents Retail Strength
     Dependent Variables
CB
  POPROOT
  MJRHWY
  DIST
BP
  INCOME
  CIIV
RE
  VALUE
       Theoretical Model

CTPF=f(POPROOT, MJRHWY, DIST,
 INCOME, CIIV, VALUE)
       Dependent Variables
 POPROOT: square root of population of
  dominant city within each county
 MJRHWY: location on interstate highway
 DIST: for communities over 2500, distance
  from major trade center of 10,000
  population
       Dependent Variables
 INCOME: per capita household income for
  residents in county
 CIIV: size and direction of flow of
  commuter income
 VALUE: per capita value of property value
      Dependent Variables
CB              Seitz and Darling 2003
  POPROOT      CB
  MJRHWY          URBMASS
  DIST            MJRHWY
BP                 CIIV
  INCOME       BP
  CIIV            INCOME
RE              RE
  VALUE           VALUE
                   MARKETCAP
      Dependent Variables
CB              Upendram and Darling
  POPROOT       2004
  MJRHWY       CB
  DIST            URBMASS (sq root)
BP                 MJRHWY
  INCOME          CIIV
  CIIV         BP
RE                 INCOME
  VALUE        RE
                   VALUE
                    Data
 All 93 Nebraska Counties
   Includes the three major metro counties
 CTPF from University of Nebraska
 Department of Ag Economics: “Nebraska
 Retail Pull Factors for Counties – 2002”
   Sales tax data
   Values greater than one – stronger than
    average retail sales
      Implies incoming trade
                       Data
 POPROOT: population of dominant city in the
  county – the trade center
   From 2000 census
   Square root used to reduce variance
 CIIV: Derived from U.S. Dept. of Commerce
  Bureau of Economic Research - 2002
   Index developed by Darling at KSU
   BEA Adjustment for Residence divided by total
    income
   Signed for positive index for job centers
                   Data
 MJRHWY: county given a value of one for
  location on an interstate highway
 DIST: Distance county trade center lies
  from nearest trade center of >10000
   Towns under 2500 assigned value of zero
   Towns over 2500 assigned number of miles
                      Data
 INCOME: Per capita income in county
  from 2000 census (1999)
 VALUE: Per capita commercial property
  value, real and personal - 2002
   Includes all retail and industrial property
    Results and Conclusions
 CTPF
  Mean       0.56
  Median     0.47
  Skewness   0.89
FIGURE 1: Pull Factor Histogram and Descriptive Statistics


 12


                                                                                Series: PF


                                                                                Sample 1 93
 10
                                                                                Observations 93




      8                                                                         Mean              0.555616


                                                                                Median            0.471172


                                                                                Maximum           1.452413
      6
                                                                                Minimum           0.027183


                                                                                Std. Dev.         0.323374


      4                                                                         Skewness          0.892797


                                                                                Kurtosis          3.352427



      2
                                                                                Jarque-Bera       12.83614


                                                                                Probability       0.001632


      0


          0.0      0.2          0.4         0.6         0.8   1.0   1.2   1.4
     Results and Conclusions
   Profile of retail sales underlying CTPF:
 Three metro counties capture 61% of retail
  sales
 Top six counties (6.5%) capture 71%
                                                                        Nebraska Retail Sales by County

               7,000,000,000



               6,000,000,000



               5,000,000,000



               4,000,000,000
Retail Sales




               3,000,000,000



               2,000,000,000



               1,000,000,000



                          0
                               1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93
                                                                                           County by rank
                                                  Frequency
             10
                   ,0
                      0




                                     0
                                         5
                                             10
                                                  15
                                                       20
                                                            25
                                                                 30
                                                                          35
                          0,
                            00                                                    40
             50                  0
                   ,0
                      0   0,
           10               00
                  0,
                    00           0
           25            0,
                           00
                  0,
                    00          0
                         0,
           50              00
                  0,            0
                    00
           75            0,
                           00
                                0
                                                                                                     County




                  0,
                    00




Bin
       1,                0,
         00                00
                  0,            0
      10            00
           ,0            0,
              0   0,
                           00
                                0
                    00
                         0,
                           00
                                0
                                                                      Frequency
                                                                                       Histogram of Nebraska Retail Sales by




                          M
                           or
                                 e
                         FIGURE 2: Scattergram of County Trade Pull Factors

               1.6


               1.4


               1.2
                                                                                             P
                1                                                                            F
Pull Factors




               0.8


               0.6


               0.4


               0.2


                0
                    0   5,000   10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000
                                                    Population
TABLE 2:                Pull Factor Regression Re sults
Dependent Variable: Pull Factor
Method: Least Squares
Included observations: 93 after adjusting endpoints
      Variable        Coefficient   Std. Error    t-Statistic       Prob.
        CIIV            0.188308     0.062330     3.021145        0.0033
        DIS T           0.003271     0.000602     5.436691        0.0000
      INCOME            1.43E-05     1.99E-06     7.194395        0.0000
     MJRHWY             0.175576     0.059764     2.937844        0.0042
     POPROOT            0.000509     0.000277     1.838572        0.0694
       VALUE            2.80E-05     8.15E-06     3.431658        0.0009
R-squared               0.748940    Mean dependent var           0.555616
Adjusted R-squared      0.734511    S.D. dependent var           0.323374
S.E. of regression      0.166620    Akaike info criterion       -0.683858
Sum squared resid       2.415321    Schwarz criterion           -0.520464
Log likelihood          37.79939    Durbin-Watson stat           2.224826
     Results and Conclusions
 Adjusted R-Squared         73.4
   The model is effective at explaining retail
    trade
 All variables significant at the 10% level
 POPROOT was 66% correlated with
  VALUE, all others <55% in correlation
  matrix
     Results and Conclusions
 DIST: coefficient positive and significant at
  1% level
   Relatively large
   A trade center city 50 miles from another
    trade center could surmise that 0.16 of CTPF
    was due to favorable location
    Results and Conclusions
 MJRHWY: Coefficient positive and
 significant at the 1% level
   Location on interstate may add 0.17 to CTPF
    all other things being equal
   Highway investments have and will continue
    to impact trade patterns
     Results and Conclusions
 POPROOT: Coefficient positive and
 significant at the 10% level
   Larger cities do have a significant advantage
   Managing for population growth may improve
    retail pull over time
     Results and Conclusions
 VALUE: Coefficient positive and significant
 at the 1% level
   The value of commercial property gives some
    measure of retail performance
   Investment in the retail environment may
    improve retail trade
     Results and Conclusions
 INCOME: Coefficient positive and
 significant at the 1% level
   $10,000 increase in INCOME may cause
    increase of 0.16 in CTPF
   High income cities may draw less outside
    trade than CTPF indicates
     Results and Conclusions
 CIIV: Coefficient positive and significant at
  1% level
     Results and Conclusions
Retail Trade:
 Is a function of Customer Base, Buying
  Power, and the Retail Environment
   Customer base can be represented by
    population, interstate highway access and
    distance to trade center
   Buying power can be measured as income
    and commuter income
   Retail environment can be represented by
    value of commercial property
             Further Research
   Longitudinal Study
   Alternatives to CTPF
   Testing model on other state data sets
   “Big Box Retailer” variable
   Demographic variables
   Agricultural influence
   Finer highway grid
   Define study boundaries by trade areas rather
    than state borders

								
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