PROJECTlGN G? 1980 RETAIL FOOD SALES
M MECHiGAN

Thesis for {Ewe Segme of M. S.
MBCHIGAN $3344? "MVERSITY
Kenneth fiaimas‘ Duff
W54

LIBRARY

Michigan State
University

 

Wu“ I61 .‘
A593 1 RA .1

PRMLCTIO} OF 1980 norm. moo Silo IN i'-’_I;‘.‘,;£IGnN
by

Kenneth Delmar Burt

During:the 1950 to 1962 period, the state or fiichigan 03>
perionced over 1 to percent increase in the volume or retnil
food sales. However, some counties doubled their sales during
this same periOd while others increased only slightly.

The problem, therefore, lies in.the Michigan retail food
industry's need to occurately project the potential groan
food sales of a given geographical area (1..., county) so as
to recognise and make the necessary'changoa in their expansion
plans. This need may arise due to the lack of necessary in-
formation, but more often can be attributed to the lack of
knowledge about the aocio-economic causal relationships affcct-
ing changes in the magnitude of an area's gross food sales.

Therefore, the basic objectivo of this study was to deter-
mine relationnhipc and significance, if’any, of economic and
sociological factors in earplaining variations in gross retail
food sale: over time by county, metropolitan area and state.
The cecondary goal was then to formulate basic statistical pro-
cedures that'vould use these relationships to accurately pro-
jcct the potential retail food sales volume for a given area

up to the year 1980.

 

I” II,
\‘:3

Kenneth Delmar Duft

-2.

The technique need to reach the objectives was that of
statistical analysis and projection based on regression equat-
ions.

Multiple linear regression equations were used to deter-
mine flint relationships, if any, did exist between county retail
food sales (dependent variable) and various market character-
iatica such as population, income, etc. (independent variables).
Variation. in county and state retail food salon for the yam
1951-62 were used. Eight independent Variables were used in
the first trial run. After each trial, those independent var-
iables with high inter-correlation and/or a low demo of sign.-
uicanoo were eliminated. County population, per capita dia-
poaablo income, and mambo:- ot retail food stores per county were
the threo independent variablel remaining after the third trial.-
Population was found to be of such great importance that it
tended to hide the relationships or the other two variables.
The dependent variable was then changed to per capita retail
food sales, thereby leaving per capita disposable income and
number of food stores as the independent variables. Retail
food sales and per capita incom were deflated by a food price
index and consumer price index, respectively, to eliminate in-
fhtionary price fluctuations.

Once the affect: of these two independent variables had
been detomined, l limplo curvilinear regression equation was
md to project the expected value of these two variables into

1980 (tins used as independent variable) . These projected

I...

Kenneth Delmar Duft
.3-

values could then be inserted into the multiple linear equation
for a given county and a projection of that county's per capita
retail food sales calculated. Each county's pepulation was then
projected, using a geometric-linear expansion, so the per capita
sales projection could be converted into total county project-
ions. This entire process vas conducted with five selected
Hichigan counties and the necessary data on the remaining 78
counties presented in the appendix.

0n the basis of this research, the following conclusions
can be drawn:
1) The major factor in determining the volume of a county's
retail food sales is that county's population. However, var-
iations in per capita deflated retail food sales are largely
explained (F2 of .13 to .85) by per capita deflated disposable
income and the number of retail food stores in the county.
2) The effect of the number of stores was negative for the ma-
jority of the counties. The magnitude of this effect was
greatest in the northern counties and diminished as one moved
down to the southeast counties where the coefficient was slight-
ly positive. This phenomena is partially explained by the
northern counties experiencing a huge decrease in the number of
small. rural stores, giving the few remaining large stores
greater drawing power. However, the BOUtheafi counties ex-
perienced this sharp decrease in numbers of small stores prior
to the observation period and therefore, the small increase in

number of large stores slightly increased per capita sales due

..-—

.L Kenneth Delmar Duft

to increased product availability, etc.

3) The state, as a mole, was found to have a positive income
effect. Income was expected to exert a positive influence upon
per capita food sales, however, 3b of the 83 counties produced
negative coefficients. Additional study is needed to explain
this unexpected phenomena. Findings showed the income elast-
icity of the demand for food to be lower in those counties

with higher per capita income, therefore, being consistent with
Engel's Law.

h) The significance, magnitude and direction of the effect the
independent variables had on per capita retail food sales varied
greatly throughout the state.

S) The projection technique used in this paper proved to be more
practical, realistic, and applicable when compared to the norm-
ally used simple curvilinear projection over time.

6) Projections indicate a 150 percent increase in fiichigan's
gross retail food sales by 1980.

F 233 .3 ELL"? 10:3

0‘“ 1933 REIML econ 3521,33 11-: fi1x3-213.=t:~1

By
Fenoeth Delmar Huft

Submitted to
eichigen taste University

in partial fulfillment of the requixmmu

to: the degree of

MASTER OF 3C! E‘QCE

Depament of Agriculture Economics

1964

0““...—

9/ 3/5" ¢

amwmtmmm‘rs

The author wishes to express hit oincoro thanks to
tho nmoroua poopio who assisted. advised and anomragod
him throughout the duration at this study.

Acknawl odgunmt in due:

Dr. L. L. Sager and the Department of Agriculture
Economics in appreciation to: their financial assistance.
ocodomic guidance and the on of various departmental
facnitioig

Dr. Luster v. handcrachoid, who gov. advice and in-‘
Spiration throughout the course of the study. 818 sincoro
and unselfish interest in students it an attribute that
will not b. torgottcn.

Dr. Smith Ii. Graig. who qavo important aaaiatonco
and guidanco in tho dwaiomont of tho critical points of
thi. papa.

Dr. Charla: Slater. of tho Department of Marketing,
Transportation and Administration, whoao consultation greatly
helped in tho interpretation of: tho toot raoulto.

Dr. John madam consultant in Demography at mam...
whose advice greatly aided in the handling of population
(Iota.

Mr. W. A. Wharton. monarch Director at the raichigan
Dogortzmnt of Revenue. whoa. amputation made poaaiblo the
collection of much o: the nocusary intonation used
throughout this Itudy.

Minn Yvonne salamin for her preparation of the first
craft 0: this paper.

Thin author‘s wonderful wife, Sandra. without
whose patient-o. understanding and oncourogmmt. this rt-r_.~.dy
muld have been :3 nor. trying task.

11

TABL E C I? CORTES} T3

_Faflo

 

 

1. IntrOdUCtioflooooooooooooooocooooooooooooococooo 1
Race“: StTUCturnl Change. ooooooooooooooooooooo
Identification Of the Problem .QOOOQQQOOOOOOOQOIO
Definition 0: Terms oooooo-ooouooooaoooootono. 13
Basic ObJeCt1V0. doooooooooooooooooouo-oono... 15
General Hypothesifi 00-0000oooooooooooooooooooo 17
flothoda Of Investigation ooh-cocoooooOcOOOOOOo 18

II, Pooaihia Pact Contribution. to this Study ,... 22

III. Justification and Explanation of Possible
Significant V3t13b103 .g..........o.g.... 43
Dependent Variable do...coo-cocoooooo-oooooooo 43
Independent Variahlos .OQOOOQOQOOOOOOOOIOQoooO 44
Accumulattcn 0: Bot. 9.0.0.9..ado-0.0.0.900... 55

If. Ponsihio Statistical Procedure- .............. 62
Ch1‘5quat. 703‘ Goon-coo.ooooooooonoootcooat 63
An.1Y313 0: Varianc. cocoon-900.000.00.00... 64
Regraaaicn Analyais OIOOOOOOOOOOQODOOOOOOOOO 64
ChOiCQ of Statifitical Teak .g........¢...... 63
Time-591163 analysis cocooooooooucooocoooooo 69
Czags'fiecticnal finalyfiia toooooooooooocooouo 72

v. £olection of Significant Variables and Final

. 399393310“ Equation oooauoooacooooo-oocooc 75
Trial Run #1 too-cocooooooocoo-ocooooooooooooo 77
Multiple Linear Regression Analyaio .......... 91

Results. Trial Run #1 cocoooooooooo-oooooooo 91

Result“: T3151 Run *2 Quote-cocooooooooooooo 93

Results. Trial Run ”3 otooooocooooooooooooou 93

Rosulta, Trial Run #‘ oooooooooooooiotocoodI 94

cr°$a-SQCt1°n Equation finalysi. .Q.......... 95
Simple Curvilinoor Rogreaaion Analysis «0.0.00 96

VI. Presentation and Analytic of Coefficient
Eatimatfifl to...oooooo-oococoovoooooa...00.099
Time series MultiPIOILinoor Rogroooion
Equation g...........00000..0000C0.0...... 93
Cross Sectional Linear Regression Equation ...198
aimplo Curvilinoar Regroaoion Equation Co-
‘ff1C19nt EfltimatC ocoocotoooouoooooooo-o 112
Index flumbor Projection cocooooooouoooooooooo 114

Simple Curviiinear Projections of Rotail

«'"H

FOOd 9&108 goo-0.03... CocoooototoooooitO 115
PODUIatiOn PtOJ.Ct1°n fiQEUIte ggggggggggogggg 119

Stattnttcal siqniticanco .................... 122

111

{ratio 0: Contents. Continuoa......)

¢“'*T?fi gfifio
W31. ?IQJ%C1103 FFOCfiCUEG coo-ou-Oocooqooaooooooooao 1?}
tiscuooion ofi Projection Frocofioro ............ 123
Cfmnt? fr‘ififiifi'flm 00.000.000.000.COCOOOOOIO 13‘:
Composition o: Potootiol onloo‘noiumo 0.0.9.0.. 1&2

viil. fiprlicotiafi Of yffljflgtfld Efitfl g...g¢...¢....... 146
- Rfititfi gtatfi gate...ooaootootooooooooooooo 1&5
Matrfirfllitan A39“ ooooootiaooone-toooooooao 1E1

“auntififi cocaine-cono-oo-oocoooooooooooooOQ 1&2

1?!me 3138‘1‘31“? and AER-3:331" Low gagggaofio 15*:
Limitations to Long Run Frojoctiooa 0.00000 1:?

IE. anamory out C0”31u319n3 ooonoonoooocooooooocooo 15d
Roaohing thfl*0hjcctivfi5 cocoon-oooooooooo0ioooo 154
Tasting the fivpothaalfl .ooooooaoooo-ooouoiooooo 17$
CO“C1ufiing Etatamfint ooooooooooooooOOIOOOOQOODO 17$
Rifiliflgrflphy no.o-ooooCocoon.cocoooooooooooiooo 175
Arfiflflfiix coo-loot!on...OOIooooooooooloo000000Od 131

A to.woooooooooooolootoooooCooooooooiooocoo 1?}

B OODOGCIOOOCO...OOIOIiOOCGIIOOIO¢QCCOOUOOG ifié

C ..¢..OOOGCOOCOOOIOUOOOUOO.IIIOOOOOOO..QQ. 1&3

D Dooooncoaovooootoo.cocoooooooayoonooooooo 3”?

E coon-ooooooooooonoooooo¢00039ooooococoon. Ell

iv

 

LIST 0? TABLB3

Total Annual fiichigon Gross Retail Food

5&193 Coco.toooooooQOOOOCOOOiCOOQOOOOOOOOO.

number of Retail food fitoros in Midhigan

1951-52 cocoooooooooooooooo00.000.000.00...
Michigan iood otoro Numbers by Sales Volumo 0..
Michigan Population 1951-62 coo-.oooooooooooooo
Proportion of Tourist: Who Visited hadh

3tét9 Area oso.coooooooooooooooooooooooocbt
“Uri-St.‘ txvendlture DY “£9533 EV ‘51:“ .Q......
Annual Gross Retail Food sales For Selected

COuntiea and Stat. OOOOOOOOOOOOCOOOOODOOOO.
Population for tolected Counties and atotos 00o
Frooortion Non-White Pepulation ...............
Ponulation Density coo.OOOCQO¢OiUOOOOOOIOOQOOOQ
Percent of Total Fopulation‘- Urban ...........
Number Of Retail FOOd Stores ooooouaooooooooooo
Per Capito Disposable Income coco-.00ooooooo-oo
Gross Retail Food tole- Por Food Star. .0030...
Gross Retail Food Solos For Parson ooooooooooo.
Time Series Equation! ocooo-oooohooooooooooooo
Cross Sectional Equationl oo-oqooooo00000-oooo
Income level and Number or Food Store Simple

ProjeCtlon Equations loco-oooooooooonoocoo
C.P.I. and 539.1. FtOJfiCttOfl Egflfitim' .Q.....
60901. aha ?.P.I. Projections OCOOOOOOIOOOOOOO
Gross Rotail Food fialoa simplo Projection

Equat10n3 couooonooocoo-cocooaooonaooooooo
Hiehigan Pooulation Projections ......¢o¢.o..¢
t w'voluo atatiaticol T351. loo-00.00.000.000.
Potential Retall Food Sale. oooooooooooooooooo
Deflatod Retail Food Salea goo-nuooooooooo-ooo
Income BlflBtiCitY .0040...cocoa-ooooooooooooto
Income Elasticity ot the Demand fothood .....
Percent of For Capita Disposable Inoooo

8P°nt on 900d 0-00....oooooooooooooooooooo

155
160

Flooat

18.

LIST 0? FIGURES

 

Average Fooo Chpéhfliture and risyosohlo
InCOmO For Chpita oooooooooooooooooooooooo
Curvilinear Frojection as a Function 0: Time..
Gross Retail Food tales l951~62 (flichigon)....
Michigan [0PU1Lt10fi 1951“C2 ooooooooooooOOOOO.
%.Eon—whito Population 195 ~62 (F1Ch1§&D)Qcooo
Population Lonrity 1251-62 (”ichigmn) ........
fl; firm-m POWIation 1:}51‘52 (it‘lchlgon) .Q.Q....
Number of Retail Food Stores 1951-62
(Michigan) ooooootooooooooooooooooooooooooo
for Caplta Disposoolo Incomo 1951-62
(Nichigan) oo.coo...00.00000000000000000000
salon {or Ltoro 1951-62 (oichioon) cocoooooooo
Annual Saleo‘volumo For Patton 1951.62
(hiChigCn) ooooooooooooootooooooocfiooooooo
500d FI1CG Inoox 1950-30 qooooooooocoooooooooo
Consumer Yrico Index 1952 90 goo-cocoooooooooo
CIDSB boction Equation (R ) 00.0.0.0...C......
Michigan Population Projoctions .noooooooooooo
Borrion County Fooo Solos Projection ...o.....
nioooukoe County food tolos [rejection .......
Ingham County Food tales Projection ........oo
kayno County {00‘ Silég Yrojoction ooooooooooo
Errogo County Food fioloo Projection 3.4.0.0...
State F006 88163 PIOJSCtiOfl cocooboooooooooooo
Percent 0: metal food Salon Attributed to
General Typfl G: 50011 Store ooooocoooQOOOOO
Brookntvon Analyoio, Economies to Scale ......
Percent of Icr Capita Incooo Spent on £90§..ao

vi

$9

90
116
117
110
1?1
133
134

140
141

143.
:n
161

L I 5? CF ELM? .3

F?.<'*e

W

4gro:011tfln #11985 000000.00...OQQOOOOQOOOCOUOQ. 15
‘) erffiflient OE WCGmination cocooonooootti 7'3
1) IWTbGI Of sGOd Store-‘5 QOOOOOOGOOOIOIOOOQI. 132
1:”) Per C pita Iriaposzmla Inomm "nun"... 13L”:
iii-b ) Liqnificanca of Number 011’ 1001 btotaa

1 and Far CGPita DABIUSECLIO “.0033 p.00... 1!: 9
Mar-WIT. breua Ctmutlefi ooouncwuoaoocooooconocic 1-37

v11

LIST 0? APPENDICES

 

8.

nichigan County and State Data on Gross
Retail Food Sales, Rumbar 0! Food
Stores, Per Capita Disposabla Incama
for 1951~62 and Pogulation to:

1951‘80 «cutoootoooloooooo¢OIcuoooouooonoo

Time—Series Multiplo Linear Regression
Equation RBBUlts .aocooogtolaoohbonocoo.no

Crosa~3ection multiple Linear aggression

Equation R6?U1t3 00¢OQQIOIOOOIIOOotniibiot

simple Curvilinaar Regression Equation

'5 .
he3ult5 Q..0000...OOQOQOQQIOOOOOOGO00.0...
uichigan Population Trends ...................

flichigan County Coas fiumhexs ......o-..o¢.-...

viii

9333

173

13:3

192

194
265
212

A PMJECTIOH 0? 1980 RETAIL FOOD SALES If? NICHIGAN
CHAPTER I
IRTRODUCTION

Retail food marketing occupies a very atrategic posi-
tion in the Merican economy. Ite groee annual aalea «-
currently over $56 billion (nationally) - are greater than
than or any other Anerican induetry} Approximately one-
titth at every dollar apent by American conemera ie epent at
a food atore.’ The farming rector or our econouny. aa well as
food processore, ie greatly dependent on the retail food inc
duatry ea a market outlet for their producte.3

within the retail food industry. grocery retailing
conetitutea the moat important aeqment. Nationwide. grocery
etoree accounted tor 13 percent at all retail food atoree and
81 pert-mt of all retail food aalee in 1961. And, grocery

store aalee are growing more rapidly than total (and anion.

_ _A -_ A4._.l . w..-

WW .——_— W‘— w w“

I'Induetryfl defined aa a bunineea Which uploya and:
labor and capital and ia a distinct branch or trade i.e. cora-
pariaon based on the dollar volume at annual retail ealee or
the manuractured product.

  
 

. u » _ . -.- Government Printing
ottice. 1960, pp.18 (a 1 each data are eatimatea tor 1959 made
by the Council of Economic Advisers).

3William F. Mueller and Leon Garcrian,
P! s R a n Univ.- of hire... Madison.

951. pp. 2.

2

‘Ihie increaeing importance of grocery atore buainaee relative
to the entire retail food induatry. in due primarily to ite
expanaicn into a wide uttering of both food and non-food
iteme.‘

Just er the retail food induatry ii of! major import-
ance to our nation'e economy. it is also or major prominence
in the etate of Michigan. The importance of the retail food
industry to Himigaa'a econony ia eecnnd only to the maaive
automobile induetry. Between the yeare of 1951 and 1962.
groan retail food aalee in Hichigan increaeed from $2.38 to

$3.55 billion. or alneat so percent.

Table 1. metal Annual Hichiqan Groae Retail Food Baler. 1951~62
W

(6000)
1951. ‘I' 2. 379,817 1957 . 3,202,872
a .. 2.703.329 9 .. 3,255,939
4 «- 2,852,181 1960 0 3, 374.631

 

 

W ,__‘ m ”M

Thia paper is devoted to a deecription. explanation.
and projection of peat. present and future changee within the
azidxigan retail toad induatry.

 

REGRET ETRUCTURAL dim-GEE:

Despite the immune expansion of groan «in during
that twelve year ebaervation period, the number of establieh.
manta acting ae outlete tor food producta continually decreased.
The number at retail toad atoree in Michigan decreased 2m
16.531 in 1951 to 11.572 in 1962 or 30 percent.

Table 2. timber at Retail food Storea in Michigan 1951.62.

W

1951 '- 18, 531 1957 '5 13.781
3 «- 15.210 9 - 13,011
4 «- 14.543 1960 . 12,505
a . 14.29: i - 12.039
6 *- 1‘.037 1 ‘I' 11. 572

_._‘

m- illuatratea how thoee atoree remaining are an»
perimcinq a continued increase in grease ealee per atore. In
1960, 12 percent of the retaining tood etorea in Michigan
were grocery atorea and 74 percent of food aalea were grocery
etore aalea.

Following ie a liet of additional poeaible reaaone
for the increaae in per etore qroee retail teed aaleas
l) Bee-inane captured by the large food atoree from the mailer
and usually lees efficient food retailer. Table 3 shown how
the large volume atore has become more dominant.

a) Pepuiation increeeee. aa elm in Table 4. (Increase in
population deneity implied)

4

Table 3. Michigan Food Store Rumbare by Balea Volume”

r~*h-n~-n- -'a..— m- “nu—-e- g “’w~—-' .M -—e—-- “........1. n... - ..

 

number Percent Number Percent Number Parent

sales Volume of oi oi or or or
(3) Storee Total Storee 00:41 Storee metal

_~ A 4
w w ___v w w

Up to 500.000 13.071 93.35 12.505 72.92 11.374 90.02

 

500.000 to
1 million 313 2.15 409 3.00 407 3.00
1 million and '

over 303 2.50 555 4.00 052 5.20
Total 14.540 100.00 13,529 100.00 i 12.523 100.00

$101. 4. Michigan Population 1951-623.
W

(000)
2 O 6.662.]. 3 4- 7,532.9
’ . 6.80902 9 - 7. 678.1
5 ‘. 1,097.5 1 . 8.038.‘
5 - 7. 2‘2. 6 2 - 8. 26 5.9

#- 4 Ah. __-.. --_‘ ._ h-4
fifiw v-v w W

 

1Kenneth D. Unit. and Earl a. Brown. 'Michigan'e
Retail Food luau-try . Statietice on Population. Store Numbers
and Salon. by State. Cmmty. and Metropolitan Areas.“
Michigan State UniversitYo Agrimllture Economice Department,

‘12..B

lJ-gflkg er c1011£;..

  

 

S

3) Cranging :ood preparation and buying habits or the consumer.
he... purdaaaee of more costly prepared foods.

Using the claeeical exmple of the ”luv. Dinner.” where
the meal ie prepared except for heating. we can eaeily nee
how the increaeed cent at the retail food atore might produce
indications o: increaaed gross aalee volune. Gone are the
daye when the houeewife vent to the live ohidcen market to
916: out the bird. then take it home for plucking and eviacer-v
ation. Gone are the daye of veahing and out or apinach. take
ing the pail down to the mill: atore. waiting tor the grocer
to W out the potatoee and applet am a barrel}
4) Addition of non-food itama.

{ According to one national atndy. the average food
etore new stoma 13 out 21 major non-food or general oerdaan-
diee lines. Health and beauty aide. housewaree. and mm'e
hoaiery are the three leading liner (handled by over 90 per-
cat at the food "crash: In 1933. 5.20 percent or total
aalee in the average reed atore were derived from the aale of

nom-fiooda.3 In 1963 a etndy by hone eomoeaiete at Purdue

fig 0% A A A A w __— _‘ A —A

"'77 v—V m— “ ——-—.—v v w “w w v—w w‘

"not Book on United Btatee Agriculture.“ 0.5. Dept.
of agriaialture. orifice of Information, March 1963. pp.63-9.

2"mm! Chaine Put the 010 General Store sacs: on the
"“4594. W April ‘0 1959: PP. 93": 99¢

3“?acte in Grocery Dietrthion.’ e v G ‘ g
1959. '

6

University showed that non-foods made up 20 percent at the
supermarket purchases in Lafayette and Indianapolis, Indiana.1

It has often been stated that expansion and progress
are little more than naceaaary hy-producte o! a capitalistic
society. Many. it not most food atore operators feel that
growth or their companies ie an essential alment in continued
business success. One supermarket executive has argued s-
correctly in my opinion - that it booineae does not progress.
it will retrogreae. that it cannot stand still. The reason
for this he argues. in that a store union is not growing
find: it difficult to retain young and ambitious personnel.
but even more important. an enthuaiaatic spirit in often
nurtured by growth and such epirit in hard to gem-aerate in a
statioorganiaation.2

The recent growth in tuchigan's retail food industry
can also be attributed to the exiating market conditions.
he... coopetitive etnxctnre. profits. etc. Economic theory
antenna that industry adjusts. grove. and also declines in

3

order to increase or secure their profit position. Here we

n- ._. ... i...— _.. 1- _._ _-.

A 1 i. 41 .1 ' _‘_ .
w W v—vv— ——w—v —r —— Vic,— —_v. y W

1'Fect Book on 0.3. Agrimlture.’ pp. 00-9.

  

’naipn Caseidy Jr. .

W University 0" "Oran. on " "
Pa e

3m" P0 430

7

wall cite eeverel reeeone enunciated with increeeed mrioontol

integration which eeeme to have e bearing on the eituetion in

manger: during 1951-»62»1

Emmi" 01‘ Scale ~ edventegee such ee epecielized manage-
ment. lerge ecele procureuent ct euppliee. and groator
eaee in obtaining equity end loan capital.

663132391110 Divereii'icetion - integration over e lerge goo-
graphic area increases e tim’e eecurity or emival
power. 1.0.. poor Operetinq condition in one area
may be oomterbelenced by more eetietactory ones
eleevhere.

Prestige .. momqment of large time may deeire to grow ever
larger in order to enjoy the prestige eeeocieted with
operating one of the etete'e lergeet time.

fiafltot Pave: - Initiate). integration may proceed to the
point where it reunite in e high degree of market
ooocmtretiom allowing those larger time to have
eome coutzol at their eellinq end/or procureomt
polieiee.

In Michigan. an we true throughout our nation during
this time period. the mall eized retell flood outlets were
“weaned“ out of buoineee by the large affiliated chains. so
as to inoreeee their competitive poeitione ageinet the large
Granulation. many or thoee mining «all outlete eerged

‘ A AA. “4‘. .i. A. ;_
W V. wh—v .w v W w’v W‘

"mmm with Jan. 1963. W.

8

together. There ere eeverel beeic tectore which made growth

by merger preferable to growth through internal mansion,

market Btructure Coneiceretione on eince it may be extremely
ditticult to open e umber c: etorce in e new mentor;
in e relatively ehort period. e firm deeiring to ex»
pand m en important incentive to do I: through the
merger route.

Financial Goneideretione ~— buying e going concern otten is
eeeier to finance than ie internel growth on e com--
parable ecele.

Tax Incentivee - populer literature on mergere often cites
the tax etructure ee an importent incentive tor
met-gore. Under certain conditions, en ecquiring firm
gete not only the eeeete or another concern. but ite

tax loaeee ee mull.1
In the above diecueeion, I heve presented some basic

data; in conjunction uith e ehort explanation or recent changes
within the Michigan retail food induetry and its market

“mature. During thie period 0: etructurol rwrangtamt,

progra- he been cede end met continue to be made. It hoe

boon ehoun that continued economic progress: cannot be made
within e etetic industry and, ’theretore, we met anticipate
and prepare for many more chengee in the future. This situa-
tion can beet he deecribed by quoting e etetenent from the

.4- A _‘..., _.._ _ w. ——-L-— A - “A. A——-—- ~A—‘A

m W
r erw W w .,_ vqm MW —__"j-_—-—

1"The Merger Movenent in Retail road Dietribution.”
national Meecietion at Retail Grocer-e. axicego 1959. 99.2937.

9
conclusion of Rain}: Casoidy'e text, 'Sinoo no one knows
definitely what will happen next, those engaged in businano
in this field must figuratively be 'on their toee'. This
termites being mentally alert to Change and flexible-uninfiod
regarding the form that end): changes take. In short. those
in this field must be willing and able to move with changing
heals and conditions of those composing the market. because
food buyers will be with ue always. while the food store
might in time be replaced by some other type of organizetiom"1

Therefore, as stated by Ralph Caesidy, the retail food
industry must remain flexible and eble to want ite food
distribution dutiee no no to meet the changing neede end
congenition of those composing the comet; “mic leads us
directly into the primary problem to be dealt with in this
paper ~ that of accurately forecasting those areas of wron-
oion and contraction to which the retail food industry must
make its edjuements.

Roomtly Fm. Curt Rambleu, Director of Resend: of
the fingernarket Institute, while epoaking on the retail food
inouctry'e tenure to accurately predict the potmtinl tales
mine of. tentative food store sites, stated, “Benny two out
of! every three new eupemerkete (62 percent) are doing lees
buoinooe than predicted..." the ditiermce between ectual
and eatimatod gross food sales is quite substantial: in many

cases ranging tree 54 percent below to 49 percent above, Due

“A . .___. A M
A“ A

AA A A
wW :1 W _, V W ~—

‘Cauiay. p.274.

10

to heavy reliance being glaced upon intuition and? rules of
thumb, decisions mnceming future More expansion and site
selection have been made on pranctional differentiation rather
than economic juetiticzamione."1

Even though Mr. tomblau was referring to national
date, thin me prohlm exists within the Richigan retail
food industry.

inf-:g-ITIEI firm}: or 1'21: $2631.32“

The problem. an round in other states as well an
bzidligan. lien in the retail i'ood industry'e inability to
accurately project the potential grooe food onion 0: e give:
geographical area eo as to mercetho appropriete adjuetznonte
in their future expansion plme. This inability may he duo
to the loci: of necessary intonation, but more often can he
ottriluted to the lock oi knowledge about the sociooeoonomio
causal relationships effecting the magnitude of en eree' e
gmas food ealea. Even for those few who have an understana‘
ing of the basic relationshipe involved in determining the
volmue oi potential gross food eelee. there new to be a
lad: oi ability to transpoee thie knowledge into workable.

meaningful, and accurate projections.

# A _-‘ i.

“—w
W

1% Kornhleu, Director of Reeeerc'h, somerto‘t
Institute. from a paper presented on ilov. l. 1963 in the
Kellogg Center. hiohigan State Univereity, Eeet Lansing.
:ic‘higen, to e food marketing miner.

11

A winninono mount of information has beam published
concerning tho optimal otoro location within o given tom or
City. homsr. moot all such writings ssmo tho ores. county.
and city hovo oiroady boon ooloctod and tho decision niromiy
mods to build o now stoi'o.1 Thus. tho main promos still
remaining is that at analyzing tho loco). onvirorment factors
in on ottonpt to igooto Moo noncot characteristics normally
contributing to tho maximization of on area's oxpsctod profit
potential. Littlo regard. it any. is ovor given to determine
ing in what gonoroi srso or want}! on odditionni outlot is
most noodod. oithor now or in tho tutor-o. For omio. s new
retail food otoro may to oatpotiencinq 40 porcont ioso business
than anticipated. fmo otoro may oxist in o city previously
m to two odoqusto solos potential and it may ho located
in m idosi oron. mo probisn horo may to:

1) mass invostiqoting tho saioo potential at this iconic
toiiod to discovox any trmds indicating that tho poten-
tiai solos woro likely to dociino in tho rutnro. or

2) Mo investigating toiiod to oxtond thoir study into on
oroo any largo: than tho city itooit and thus tailed to
aims: an «namely low buying potential in tho county
or gonoroi on: surrounding the city.

In order to ovoid ma: orroro. on ontiro ototo. area and

 

*- 5‘1 “‘— 1‘.— “ AA +‘A——___
m 1- __ w“ flww

1‘4: G. Gibbs. ”How o Pminmt Chain video its storo
Locations. W. Vol. m1 Nov. 10. 1947. DP. 103-9.

la

cavity mot first to onslysod .snd all treads projootod into

tho tutors (st losat 10.15 yosrs) botoro deciding it and mots

manner) (or. mntnotion) is necessary for the retail food
5.11de to moot tho managing dogmas and market conditions.
Othor :slstod problons may ho marital so tollowsa

1) Look 0: bssio long run solos potential data projections.
which airs necessary for ooumi tuturo planning by tho
Midiigm rotoil food indistry.

2) 5830831 lock 0: tnowlodqo nocosssry to undorstand and
mm tuturo trsnds and apply this data in o practical
decision making situation.

3) Ltd: of oroo and county trond data. nooossary in analyzing
tutors potontisl solos ohanos within oonntios and neces-
sary in tood storo mansion. contraction. rs-locstion.
etc. thorwy implied.

4) Love): of trno undaotonding of tho ofi'oct inoomo. market
saturotion. powlotion and othor significant rslatod voti-
nbloo osy hm on post. prosmt. and tutor-o gross rotail
food solos.

DEFINEIOW OF TBMSO

Botoro continuing any tuxthor. it would ho most hono-
tioisl to tho roads: to assay dotino thoso toms that mo
mood sud/or will to usod in this popor.
.. o highly dopastmmtoliaod «can ootsblisl'mmt.
doalinq in toads and other mordzsndiso. either molly
mod or contusion operated. with sdoqusto porting

 

13

we. Ming a minimum of $500,090. business annually.

The gmary dMent. Waiver, must. be on a self--

service bani-,1
’3 f A ‘ a A upoctnc geographical area band an

criteria pmontod in 1960 8.8. Census of Fowlation

and marina 11: W.’

Michigan ha- toa motmpolitm am. (an clawauflafl by
the 0.3, Censu- cntozn). Tho motmpouun urea statistics
used in this study. mu aggregated 13mm thc county data
gal-waited tn the 1960 0.8, Emulation Cancun of Michigan.
Bad: metropolitan ”on continua of tho tolloung county (or
emu-sun).

mm mm:
Ann 5:130: ' Wanhtannw
Bay 31‘? ‘ Bay
Danton waync, onlmd, Mam}:
mint Genus.
Grand Mptdo ' Kent
Gammon Jack-on
H. .A '._: L m u u T__m:;“ #wwmiw

 

 

'Revtud rm “mono. annual. sales in 1961 by tha
8W". Innututc.

"aobm L. moan. and nan-11 9. mm and 3. Larry
Krtstyanam. 'Pmmme and Pracum of. a salon-tad Group

of mix}! Processing P1395.“ acumen 51:110th 193, Unlvornity
at Fit-conch. Jan. 1956, 39.2.

:mampauun Ara Smiths," W
Jun. 10. 1962. pp. 593-5.

Kalamamo Kalamazoo

5311““? Clinton, Eaton, Ingram
zmmn Hunks-gov:

angina: Saginaw

Map Ea. I. locates than ten arms.
W - Th. tollowlng were considered as feed atom
‘catabllfl‘mmtul '
emery uterus «o with or without. meats
Dairy 2mm atom ~ 1911!: mutate
Fruit and Vegetable “or“
Mutants (family) 0
Taverns. Clubs *
bundling”. - candy atom. buxom“, egg and
poultry markets, dellmtcaacn. other.
W o Rotors to the canplox of store: wrounding
the mud “or. locum. When used 1n "taxman
tn dripping canton. it cannot“ tho cumin. range
of star“ withln the 5.1161le mm; Gator.
1mm used in reflux-met to unplanned cites, 1% refers
to tho retail atom locatcd '1,th one—third mile
of thc 3120. when used 1:: raformco to a mall tam.

_.__-. A .‘L

 

w My TV v—v v.— V 1.— WW M W W V 7, Y.

. 10.8. swine” scam, I}. S. repartition: of Gamma.
1949, 54. 58.

mm catagorlu m to he considered only when con»
smearing cal a. «slum. data: not. lncludod 1n amber: a: thorns.

15

 

 

 

I-Ee tropolitag; Are 3

 

Flint

 

 

 

 

 

 

 

 

 

 

 

Lansing

7
\

 

 

 

 

'Iuskegon

 

 

Saginaw

 

 

 

" Bay Civ

 

 

 

Jackso

 

 

 

 

W Ann Arbur

mm Grand pids

Detroit

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Kalamazoo

 

 

 

 

 

WW“ MW
3
OMOIMON ‘1
Map No. 1 ° .
OOOCOIC Ln; f
Michigan's W ....._., |.-

 

 

 

 

' 5-: / a Metropolitan Areas '57:.\ g
5 "m“ 3 . wucouam\"“l~u
u i Imam": G; 'W“ ! '
7.30,. L..- .._.; hm i '1 km“ ‘ c A N A D A ,
I g ‘

' .omml .1. __. . ‘xfim ' hmmer _____ __ - .. ~
J. l . {can t 1 i 4
“4°" F ' ' “ 1:53

' ,noatucg ' r.— ‘1'- I . ‘ ‘ Q \
' O ' /.,- s \ b .
_ i l . n a $3
' mzuoumui l '8 ' "cumvm -
WISCONSIN g \ ‘ g
A‘ \ a
,0 0, V. i ӣ1500:
mamun Q ‘ '

fifiomm , '
'
l. i I E !
“—h ...._ u "—3 Ws:—‘omirfo?c?.—
mom! wwono ramum ‘m ! g
' | s i .1
-- ' - o—v-O -—
mflr— ‘fofiétTf-n'jofislwm' “W
I g ' . L.
‘ g ! g '3}?- a
0"“.-- .*._L-.—f 2.... I

 

 

 

 

 

   
  

060/ am /mosror1igi

   

WOAKULN—i

N'MEKSON flwunfigw! mm: b,
”Eggi Egg/gm gig}: CANADA

 

BERN“! ‘

IA mu.“ .nsim?" "2"

0810 3L :6 to u comm

I 81.10“?“ BRANCH TM
0

mt {smanu'

l
' vtuuufl‘a.‘ .W. M
mourn ‘ T

WW“
V“

F“
i

 

 

 

 

16
it rotors to all of tho rotail stoma Writing tho
business district of the town.

 

. «- Retail food outlet existing with no
other retail storas around it on what is oitsn called
s 'txss standing location.“

W «- Tho sxtant to which salss in a part1.-
cular market at» us channslod through a cartain
tin: or nuabs: or firms.

M - Pastaininq to arsas with no incorporatsd villages of

2. 500 population or mots)

W - Hsasursd by tho umber of retail outlets
within a givn geographical arso.

W "' “‘0 902105 of on. day spent by ons tourist in a

qivso atom,

W - Siapls statistical correlation bstwson
two or mots of tho indopondont variables of a regres-

sion equation.

BASIC OBJECTIVES!

1) To admin. tslations‘nips and significancs. it any, of
mic and sociological factors in uplaininq variations
in gross retail flood sales ovsr tins by county. metropolitan
arsa and stat. (nichigan). ‘ '

M M .. _.._‘ A“ “—4——

y. W wm W ‘7' w

10. a. Population Consul.

2lulaitmolti. P. woli’t. “Estimating the unmet Potential

0! t Plenum: Pond-Mon." Wsiiam July 1954:.
19:12-11.

l1
2) To dotomins significanco oi rolstod factors in oxplaining
variations in gross rotail food solos among mmigan's eighty-
thros oountioo ovor tho yosrs 1951-62.
3) To iomlato basic statistical procoduros that would use
tho rolotionships dotoroinod in (l) and (2) to accuratoly
projoct tho potontial road salos him by county. metropolitan
sroo and stats (Michigan) up to tho your 1980.
4) “no prodict tho proportion of tho projoctod gross annual
sales voluoo which will to “wound with difforont typos of
retail food storos. i.s.. grocory storo, dairy product store,
rootaurants. otc. ‘
5) To dorivo. oxplsin and analyro inoono olsoticity for tho
danand to: toad in Michigan during tho twolvo you poriod
undo: invostigation.
6) To onolyao rooults and convort pi'ojoctions into practical
smootions of how this data night to oppliod by tho Hichigan
rstail food industrios in thoir tutors planning.

CEE‘IERM. HYPO’Z'HESESI

Tho major hypothosis is: Does tho significanco or
ooonooicsl and sociological factors oftocting gross rotail
food solos havo boon dotorninod, statistical concepts such as
mltiplo linoar rogrossion and sinplo curvilinoor rogroooioo
may to sppliod to occurstoly proioct into tho iuturo poton-
tial gross rotsil flood solos by county, astropolitan area

and stats of Michigan. This statsmont. than. posits that
oeourato projsctiono can to nods. soablinq tho rotsil food

la
industry to swaluato and adjust their oxpansion plans on a
scalorlargsr*than a singlo‘businsss district.

To bo mro consistent with normal statistical reason-
ing. tho abovo hypothesis could wall havo boon statod in the
ions Tho offset coda-economic tactors havo on gross ratail
food salos cannot ho determined and statistical techniques
each as rogrossion analysis cannot be appliod to accuratoly
project potential gross retail food also to: a givsn area.

A null hypothosis such as this may use: mots meaningful to
the roadar with a strong statistical backgmmd.

Sons sub-hypothoaos srss
l) Tho pmportion of total gross rotail food salsa attributed
to grocory storos will chango only slightly in michigan'a
hoax tuturs.

2) Hospito tho onormous «aphasia plscod on tho aumnmt of
tho lacuna slasticity of tho demand {or food on tho national
and stats basis. a much aors dotailsd analysis is nocosssry
betors this national noosuromomt can accurstsly to applied to
an individual aroa as small as a county.

3) Tho rolstionships found bstwos: variabls factors and groan
retail food solos varios so grsatly among tho sighty-thrco
Kichigan countiss that an individual county analysis must he
WBM“ to obtain accurats and applicabls results.

ammo 0? nwasrlstrmm
So {or in this dhaptor. I have attsnptad to illustrato
tho importsnco of tho totail food industry and iormulato tho

l9
objectivu and hypothssos of this paper.

In Chaptor II of this paper, short smarios of prov»
vious studios conductsd in tho area of. retail food markst
potentials and other rolatod subjects srs prosantod. It is
hoped that thsso resumes provido background knowlsdgs for a
batter undorstandinq of tho reasoning and procedures used
lator. Each rooms mtains tho goncral purposs of tho study,
a short description of procsduros usod, conclusions or
results, and an explanation of how this study's tschniquea or
results wore applicahlo or holptul to tho discussion or the
problem dealt with in this papsr.

Tho first major prohloxa that must to considsrod is
tho dstormination or which variablos significantly affect the
voltsns or gross rotail food salsa. Chaptor 111 contains a
discussion and oxplsnation of tho possiblo ottscts various
factors may havs on gross solos. Final selection of. those
factors to bo ussd in tho final statistical computations will
to mods on tho basis of trial run statistical rssults and tho
findings of past studios in this particular aroo.

Following this comamt on possiblo sol so dotorminont
foetus. tho tschniquos ussd to obtain tho information secon-
sary for a study of this noturo will he discussod. Explana-
tions will to qivon, uhsn nocossary. concsrning tho validity
at tho data ocmlatsd and ad justsonts nods to rsndor tho
data soro roprsssntativs or o truo situation.

2O

Chaptsr 1V contains an enumeration of tho possiblo
statistical procedures which could to used in such an analy-
sis. Included is a short explanation of tho advantagos and
disadvantages of alternative methods, followed by a justifiv-
cation for tho selection at tho rogrsssion analysis technique.
The basic procedurss. and computations shall then be inter-
preted. For purposes or simplicity. this interpretation will
not omsist of a detailed analysis or tho regression technique.
but will ssploin only those concepts necessary for an under-
standing of tho results derived.

Chapter v doals with tho actual osscution and small--
cation of tho accumulated data to tho statistical routine.
Hers it is shown has over a soriss of “trial runs.‘ the in-
significant variables (rectors) ssrs drappsd. tho inter-corro-
laticn and trend oliminatsd. and tho final tomula dsrivod.
Assertion or expected rosults aro soda to term a basis for
later contradictions and illustrations of the heteroqeneoue
results among Michigan's countiss.

In Chapter Vi tho rosults o: tho tins series and
cross sectional studios. using the multiple linear regression,
ors prosmtsd. Rather than hurdm tho reader with results of
that statistical tests or all oighty-thros Michigan counties,
rive countios (representing geographical and dnographicol
extras”) mo solsctod. For tho moss avid rsodor. data on
tho othsr snooty-sight comtios is availshls in the appendix
oi this paper.

21

The coefrioimt estimates from these same five
molested counties are then analyzed soar to give the render
an idea or the basic procedure used without boring him with
repetitive county analysis. County data is camparod with the
results of. the otato, an a whole, and additional meats
made. cone-owing! Eichitjnn'a ten metropolitan areas.

Following tho presentation and interpretation of
than romlts in Chapter VI, this information is then applied
to a regression equation to form the actual retail food sales
projsctions into the year 198'). Values of. the independent
variables are projected on the basis or simple curvilinear
regressions. and these results applied to the multiple linear
regression equations. producing the projected potential food
sol-cs volume by county, metropolitan area and state tor l980.

Tho uso of these projections in decision making pro-
castes cos-accruing location of and/or need for additional
retail food outlets throughout the state of Michigan is
illustrated in Chapter VIII. host. the limitations or this
type of studyfgare recognised and discussed. suggestions are
made concerning adjustmmts that night eliminate many or the
doiicisncies. , I. _ j

an acceptance or rejection of the major and sub-
hwothosos is made in Chapter IX. It also contains a stunner?
and concluding statoaont pertaining to the otfoctimoss and
applicability or this paper's romlts to the major prohlon as
stated in this chapter. '

CRAPTER II
FC‘SSI?LE§ PAS-T CCRTRIBUTIC‘ES '10 $5313 STUDY

This chapter contains short resumes oi studios pre-
viously conducted that are related to the problea dealt with
in this paper. Hany or these contributions will be referred
to later to provide baccground for various statements.

Poucdot.on 9 -
W _

 

In 1954 hobort forber ot the Department of Economics
at the University of Illinois conducted a study to determine
tho causes of variation in retail sales between cities. Mr.
Forbor hypothesized that factors influencing variations in
retail sales to individual consumers are not likely to be the
cone so those which influence variations in retail. sales boo
tvom cities. Bis objective was to identity tactors influenc-
inc variations in retail sales (food. general merchandise,
apparel. etc.) between Illinois cities and to measure the
relative importance or each in attocting total gross sales.
m multivariate correlation statistical technique (multiple
linear correlation) was used because it permitted identified-
ticn at several pertinent variables at is time and also leads
to a more precise estimate or the influence of any one variable
by extracting its not influence from the interacting of: acts
or other variables. The procedure was to advance a hypothesis

regarding the factors that were thought to influence the
2:

:3
variable in question: translate these factors into correspond-

ing variables: and then test by correlation analysis the
etieot, it any. of each or these variables on the dependmt
variable (gross sales). The results at this study provided a
multiple coefficient at determination (32):»: .92 (.85 exclud-
ing Chicago). referring to the selected tactors' ability to
explain 92 percent of the variation in gross retail salea
between cities. Basra. even .92 was smaller than the .95
derived while analyzing variations between individual con-
more. Almont 92 percent or the variation in total retail
sales was explained by the two variables of population and
distance between cities. Wltlon of standardised regres-
sion coefficients revealed that population was by far the
more important. having an influence on sales more than eight
timer as large as distance. Mr. Ferber then decided to
eliminate the population factor vhid: tended to conceal the
presence or other significant variables. This was accomplished
by dividing the dependent variable by population to derive per
capita gross retail food sales. After this adjustxmt.
reanlts obtained indicated the following: a) contrary to the
previous findings, income turned out to be highly significant
in post instances (regression coefficient at .6 to .7).

b) a high intereorrelatioebetwem income distribution and
incone per capita was discovered and thus it was decided to
use only inooue per capita. c) distance remained an important
variable. however, the magnitude of its effect on sales was

24
no long“ high. and d) tho number of retail Icon. in the
city was an important datum: on per capita tales. These
flamingo point to incur... distance. and number at stores
taut”. to population as major cumming factors an the
tutor-city variation in per capita sales. Bpocutcany with
regard to tot-.311 food “In, tho regression coefficients were
as follows: 15' II 1. 3*" 0.0x" .23 x5 + .4305 with a multiple
correlation confidant: at damnation (32) o! .21 when:

‘1 u- n: Gupta Retail. Food sun (3)
x1 . Distance (Mo)

II Per Capita Dingo-able moon. H)
*3 : wfiaiamfiigfimcintgzx .1 1nd or probability
:- scan-tinny “gunman: at .05 It“). at pmbabntty
In his conclusion. Fatba- It“... '11:. cvldmco 1n
thereforc. fairly clan: that an forces tntlumcinq inter-
any variation: in per mica ulu ditto: granny, and that
a mom or 1“- Indtvtduuuuc approach it needed in “d1
ease."x
Pub-1"- Imdy to applicablo to this paper In the
13011an are”:
1) Pubs: recognized that. an analyst: mt ho conducted of
new larger than pox-Ema. o: a gun city. rather analyzed
variations bum mun, whereas. thin papa: curt“ 1.1:. one
step W by studying variatlma between counties and

alumina an”.

‘A—L‘

¥_‘ 1 L‘A._ ' A 4 m —-—- ...A. ___ .4.“
r_ .v' . -—'—vv “ V? —'——r-' —— W w w. —,v _ WV

‘ 1mm Father. ‘Vanauono in mean Salon Between
Cities.“ Bureau of Economic and Business Research. Departmmt

o: EMCD. Untvuuty or 111mm... W

3313‘ ’u, 53.

25
2) His objectivo was similar to one of. the objectives of this
paper, mt. Femoral» used s statistical toot similar to tho
ono used in this paper. .
3) Fer‘bor's results slowed s lower 82 (explaining variations
in total gross solos) betwson citios (.92) than between inoi.
viziuol consumors (.95); ~' rim this relationship so might
litter-wins expect a. laws: It:
comtiss and to: counties than citios. As shown lasts: in

for, mstmpolitsn areas than

this paper. results tron this study show this to ho true.

4) hhilo analyzing Michigan‘s dots. I also found population
to be and: o great solos dotominont that it had to bo oliminat»
ed to rovosl tho significanoo or other variables.

5) Factors of per capits incoms and number or otorss worn
also i'omd to be significant in this intor~oounty study. time
importmcs of tho distoncs isotor was shown by Potts: to ha
of decreasing imponanco when moving in: intro to inter-city
analysis. Assuming this trond oontinusd, as tho sins of the
axon undo: onslysis increased. distanco was not considered to
be on important factor in this inst-county study and such
data wars not ovon included in tho trial runs. * Forbor's
«motion. pertaining specifically to retail food solos. tmc‘is
to justify this decision.

6) Ststansnts in Poi-bar's conclusion that areas ditto: so
greatly in thsir morsctotistios tint on individual sppi'oodm
is ncsdsd in soch csso, sons to sgrso with the second sub-
hypothosis o: this paper.

26
Adciitional Dotonninants

In 1962 Hz. a. Osborn waits: conductod a study in tho
Chicago-Gary, Indiana am for tho Jowol Tea Co. Tho objoon
tin of this study was to dotsmino tho facilitiss which will
havo to ho sddod by tho totaii food industry to most tho
mantot'o toquitmonts in 1990. sinco tho Joni Tea Co. bases
tho dolls: volmo o: thoir rotail food solos on tho growth of
tho pagination ond tho ability at an; pomlotion to buy
Cinemas). tho procoss was simply ons of pmjocting thoso‘ two
factors into tho your 1990. amor. orojsctions o: income
not oapita vars complicatod by a strong incroasing trad in
tho who: of nonwhits rosidonts of tho srsa producing a
W offset on incomo lovols. In otho: words. it was
disoovorod that this trond toward a highor. ratio of non-thites
to whitos. whilo’ incroasing tho nunbs: of poopls. will inc-
cronno tho food stats potential at o slows: rats. In tho
sums-y it no ststod. ‘This study indicatos that won tho
thirty yea: span from 1960 to 1990. tho population or this
am (Chianti-Gary) will incroaso 52 porcant and that tho
food stors potsntial gross salon will incrsaso 43 pox-cont.
The 4 porosnt differenco is duo to tho increasing ratio or
Wits population with its lower buying m. '1

* —"V ‘—' —-—w———— w— —v—— — v—v 'w WW

19. Osborno Walksr. “A study of Retail Food More
Facilitios which will hood to bo Constructed in Maition to
1960 z-iacilitiss. From 1960 to 1990 in. tho Chicago—Northwest
Indians standoxd Consolidated Aron Rosulting from tho Projected
Incrsnso is .POpulntion and tho Changss in the antics o: if
whito and Whito Segments in Certain Divisions 0: tho Area.“
30031 T“ COQ. Ines. Hay 28. 196:.

 

27

Osborno‘s study has made the following two contribu-o
tims to this paper:
1) Tho tact that this. study was mods for a largo rotail flood
organisation}, illustratos that tho industry is indood anxious
to obtain such long run projoctions. Also, tho interest in
«at tacilitios will ho noodod strongly signifies that such
projections will actually ho ussd in docisions concerning
tutors oxpansion plans.
2) It suggosto that tho porcsnt non-shits population is an-
other factor ma considorinq in an. projoctions o: rotail
food solos volumo. . '

Prosont Location Critsria

in January ot 1960. on artiolo appoorod in tho m
gm M1 magazino ontitlod “Chains Rovoal Rulos oi Thanh for
Choosing stars Locations.‘ This articlo usphosizos tho fact
that s largo portion at tho rotail food industry still usos
”rulo o! thmh' oonsidorotions rathor than oapirical studios
to soloot locations at nos mtlots. Bolov aro listod sons of
tho 'rulo of thumb“ oonsidorations usod in choosing tutors
food storo locations. as subunittsd by a group or largo chain
otors organisations}

‘- Doos tho location nos havo tho nosdsd papulotion within 'a

limitod oroo?

__ A _.4_

A

IL v v-ww W W V "—

l‘Chains Rsvonl Rules of Thumb for Choosing Store
Location-o” W Jan. 1960. pp. 233-538.

28
«- Aro tho road patterns or access routes adequate?
- Competition?
- Fara anchor tenants being placod on tho property to induce
the groatoot amount 0: trottic tlow
~ Curmt volmo of. retail outlota in tho aroo? ‘
- Total numbor of oxioting aquaro foot of food store space in
the area?

It can oaoily ho coon that no rotoronco io node to
that thia aroa'o manctouatico might bo liko in tho future.
to intoroot no oxprooood about tho location'o potential
onloo volmo. All of tho mlo of thumb conoidotationo certain-
ly do contributo to tho ouccoao or tailoro of a retail toad
outlet. hovovor. thoro ia a oincoro nood (or additional in-
quirioo into tho aroa'a ovorall potoutial.

Viowa or Outoido Intorooto

Tho rotail food induotry io not tho only agency that
ohould bo intorootod in mro accurato tomato on to tho
cocoon or failuro o: a pmpoaod outlot. A grant coal of
outaido financing otton io nocoooaxy boforo a now outlot can
to locatod and built. Thus landing ogoncioo oro looking tor
occurato intonation which might nako thoir invootnonto loos
riok'y. Janoo ii. Rouao. o oortgago bankor in Baltimoro.
atatoo that banxor'o in thoir rolo oz tinancing a nmbor of
retail food outloto. havo opont a grant coal or timo attemp-
ting to doviao a method that walla yiold valid oatiznatoo ct

29
the success or tailoro of! a given outlet.

In fir. Rouao'a opinion, thoro aro a number of van}:-
nets-sea inherent in tho proviously usod judgmont approach.
First 0! all. there io no such think an a finito trading area
in an ufiran community. Secondly, tho complain interplay of
emanating rotail food aroaa within a largo urban area in Ego-'-
yond accurato ovaluation bond on Judgments. alone. Thinlly.
there coma to bo ovidant in moat ouch judgnmt-aurvoyo an
unintentionally optimistic biaa in oatirnating mutt of
purchaooo to bo mado at a now Outlot. Orton tho and result
of thooo orroro producoo otoroo that aro unooononic tor their
mmera. tananto. and invos‘torn.1

Thin articlo by Hr. Rouoo aorvoa only to ro—ornphaaizo
that the rotail food induotry. both in Michigan and the notion.
is in nood of a valid otatiotical tachniquo by which oatm-
tial rotail food oaloo volumo can to projectod in tho future.

Along with financioro, roaltora aro also intorootad
in tho narkot potential or on an no that they night to able
to moro accuratoly appraioo tho two valuo of pouiblo food
store locations.

An articlo in tho W writton by Loow h‘.
Ellwood. illustratoo thoir ottonpto to bottor vioualito this
problom. Tho following atatomonto aro typical of thou
charactoriting tho roaltoro' viowa touardo animating poten-

tial salon volma.

A—u w... A .4... _‘ A— __

w w w—V-‘v—vw ‘— W

13am” w. Rouoo. ”Botimatinq Productivity for Plannod
Rethanol snapping Contora." W, Oct.l953. pp. 1.5.

so

«- on estimato of potontial volumo for a proposed now food
otoro oust otart with information ao to tho oxioting volumo
of buoinooa.

a» An ootimato of tho potontial volumo o: a propoaod now food
otoro amat allow for tho componito pull of all othor coo-.-
poting rotail diatricto.

- Sinco moat chapping oxpoditiono atart tron hano. tho optimum
oizo or oach rotail outlot io uaually governod by tho numbor
of homoo to which it in ooro accuaiblo than all other com-
potitivo rotail diotricto.

Hr. Ellwoodo mncludoo by aaying that tho problnt of.
estimating tho potontial volumo‘ of a propoaod now chopping
cutter is ono in which primo tootoro aroo a) oxiatiog volts-no
of trado. b) oxioting chopping tacilitioo and c) accooaihility
of tho propoood location to tho population of tho trado
aroma."

Thio atudy loom quito applicablo to thio popor oinco
data on oxioting volumo or rotail food trado and lumbar or
existing rotail food iacilitioo ooro uood ao dopmdont and
inaopmdont variabloo. roopoctivoly. in tho multiplo linoar
rogroooion oquationa uaod in my atatiotical oozaputationo.

Even though Ellwod'o work doalo with ono particular mopping

aroa thoro io no moon to think thio mid not apply to an

ontiro market ouch or an ontiro county. Humor. accoaoibility

M A h... A.— —— fl... ___.-o_

A
__,_1 w W w w“ _

1Loon W. Ellwood. “Estimating Potential Volumo of

Propoood Shopping Cantor-o." WW. Oct.1954,
PP. 581-587.

31
(diatanco) has previously boon ohown (rorhor'o study) to havo

only limited oignificanco when doaling with areas an largo as

countioa.

Scapulation and Reilly'a Law

A. early at 1949, pooolo. ouch no Edna Douglas at
Iowa stato Unimoity, woro intorostod in rotail food oalaa
potential oatination. niao Dmglao conductod a cross notion:-
al analyaio of a rotail aroa by determining tho location of
the bank- against which worodrawn chad“ dopooitod in a local
hon}: by a group of local rotail outlets. Donpito many problems
arising. i.o.. coma local peeplo had cheating accounts in a
for distant town, and a tonqu not to rovoal accuratoly tho
comparativo intonoity or aaloa distribution betwoon noarby -
and :noro dirtant cannunitioa. oho uaa ablo to aoaort this corr-
clusions ”Ono can concludo, thoroforo. that pOpulation
density in ion useful on a moans o: dolinoating trading areas
than no a moon- of.’ explaining why out or town custozaoro are
morn plontiful from certain localitioa than from othoro and
of providing a booio for honouring intonoity of drawing
poucrfil It var thia atatamont that auggootod consideration
of population dmoity ao ono of tho poooihlo oignificant
determinant tactora.

_ A‘ #4.; . ‘4‘ _l.._ A _ . ..._...._._ __._.. -_- A -. _..a‘ ‘4

WWW V— W. v.— . " WW —_Vw

{Edna Douglas. “Honouring tho General Retail food

Trafiiw Ara ~ A can Study: 11". W Jul?
1949. 14:46-60.

32

M18! Douglas also recognized such now-price {actors
as quality and quantity of merchandise, terms of solo. inn
cluc'iinq such things as tho "turn goods privilogs, credit,
certain smicss. guarantors, stew and selling mothodn, as
well as buying habits and knowledge of the market situation
to be dotminsnt factors. tbs than roctitieo this phenmona
by otstinq that the sits of retail srss hos been provm on
misquote indirect nonsurs 0: thus non-price factors in
retail coiling.

As previously mmtionod. market analysis on a strictly
local basis has bacon. highly dsvslopod.’ For oxamplo, once
tn. decision has boon mods to construct s new rotoil food
storo in s given city or town. the process of analyzing this
local market for the optimal store sits has become fairly
routine. thanks to tho contributions of William J. Reilly.
Eadc in the only 1933's, Hr. Reilly began conducting im-
quirioo in various Texas cities to ostsrrnins a mathematical
oqaotioo which might accurately dolcribo the retail pulling
pow-er between two rstsil markets. From his work. Reilly
devoloPod his “Law of Rotsil Gravitation” which status

'Two local markets attract trade from a third

market in the vicinity of the breaking point
approximately in direct proportion to the popu-
lation of two marksts and in ivorso proportion
to the squares of the distance from those two
markcto to tho third market.“

OR

Logo

Pb

131

A

“a
C’
{.‘b

33

Ems-are: Ba '- proportion of the trade from the third market
attracted by market A

Eh I proportion attractod by market 3
Pa I- population of market a
Pb a poPulntion or market a
no II distance from third oar-int to market A
Db - distanoo rm third market to met 31
Through tho us. or thin tomuls. retails" could look
at a city. nonsurs pomlstion sod dintancu batons: trading
areas, and thereby accurately dot-1min. the area in union
the drawing power at a proposed stors would hays an affect.
Other nan lino P. D. Convoru st tho University at
Illinois imodistoly booms intsrostod in tho validity of
Reilly's Law and conduct“ further studies. Convsrss room-.3
that the law rousinod accurats only «non considering a mall
trading sros. As tho distanoo between markets approached
tmty or more miles. the formils bscamo loss valid, duo to
tho over-onphssis or tbs population factor. Thus, mm

analyzing trod. arms as large as, a oounty, Comoros suggested
2

substituting sn inertia factor for Db in tbs formula:
23 . to. 25... ’
Eb Vb I»:

##.l_‘__4._ -—-— , ‘__ .A

—-———~—— ___,_. w , v

   

1William 3. Reilly. ‘1; -a
New York: William 0‘. Reilly. 31.
2?. D. Converso. “Bow Law of Retail Gravitation.“
r - Oct. 1949, 143379-84.

   

34

there: x II inortia iactor of whatever magnitude it take-o to
maka the formula valid.

The major deficiency in this approach recognized by
Converse was the fact that inertia factors more highly aub—
Joctive and varied in magnitude not only among various dio-
toncos, but also bstwsm marksts. Thus, this leaves no
definite pattern provan applicabls to market areas in general.
This also seams to be the opinion at R. n. Reynolds following
some Iowa touts.1 '

As might be expected. results of tests like those of
:“er‘ber‘o. have shown pepulation to ho a major factor in
determining potential gross retail food sales. Likewise,
regulation is moot important in other areas of our soonony.
Boopits this phmmma. it com extrmely alarming to this
author that economists have in the past tended to dismiss:
their acknowlodgcnont of our nation's papulation trends by
passing on those problems to demographars. ”ms prominent

ccnomiot, Fulton Friedman, admits to this occurrence by ony-
ing, “Population, it was said. depends primarily on a host of
non-reconornic considerations which are not within our
(economists) compstcncs or field of intsrsst. Only rocontly.
have economists ranswsd their intarsst in pomlation theory
and hsvs home again ooncsrnod with reintegratinq the theory
of population with soonomio theory ~ I devalomont that in to

A A“ A” A LA— .- _-—;_— A _____....‘_

‘w' ,._

‘21. n. Reynolds. “A Test of the Laws of Retail
Gravitation.“ W. Jan. 1953. 173273.71.

35
ha encouraged.“ Less justification than this is needed to
approve the one o: the pomlation tactor in this study.

Income and Engel'a Law

Income levels. however. unlike pOpulation have always
hem maintained ea an integral part in economic writings,
since much literature is available on inoome'e effector: ooh-
mor's Whores on food, I shall attempt to only mmtion
writings of. particular interest to this paper.

Income street on the habits or individual oonsmar's
actions at the market can beat be illustrated in these state-
masts!

. First. low income housewives have a slightly greater tand-
mcy than those with higher incomes to respond to a hypo-
thetical general food price level orange and a corresponding
hypothetical moons change as though they are synonymooa.

- second. the consumer with a higher income has a greater
money than those with lover tomes to tollow habit
patterns in wrduasing food.-2

a true scam-mist dare not dismiss income's street on
food put-amass without recognizing Engel's law. In 1851,

4 ‘— .4 a“ - __ 4 “AL A

__ . 7,— 7 WV...“ ‘w—w W W _V

Mlton Friedman, W University or Chicago,
1962. p. zoo.

 

36
Ernst Enqel stotflied the expmditurea of families of all levels”
of: incone in Belgium and Barony. his data showed a consistent-6
1;: higher percentage of total expmaituree going for food coin-
cifiont with lower average incomes- par tamily. he ooncluflozi.
”ti-ho roorer a family, the greater the proportion of total out.
go that must he used for £004.“: 11: ll to be noted that
Engol's analysis was mtined to we period in time. Because
of.” thin. many economists have tended to discount the valiflity
of local“ law that attanptlng to apply it to a agnostic
oitmtion. Marguerite C. Burk ettaaptotl to test the valifllty
of Engel's Law in a static vs. d3mamic situation and arrived at the conclusion
that. 1::— r3al' a Law probably applies reasonably well to all tho
rotationahipe of. average income and food expenditures throiegh
periods in which no aubotantial antigen take place in popula-
tion patterns, cistribution of incoae. manner or living. and
mamotinc practices. mat is to say. it applies under malic-
tirmo that are relatively static....'2
margusrite C. 3113'! study is extranely relevant to
this paper since both static (cross-sectional) and dynamic:
' {ti-ma caries) analysis are conducted on lame and tood

.‘4 “-1 1.1 A #A.‘ , , _ ‘5 ._ .

v—rv'v—r—v—v ‘W W— WW WW

1"tlt‘r‘mnsmlatot‘l tron page 26 «- DIE Lfi’iwaimiim 981.131.; 11:11
AP." ”*7“? at» Fri ”12.11211 1211131131 13213 JET: ST - 1112211111.? :11?ch5 121:2. "L” 1 “““ 1 «-
15.11.1112“? 1‘Hxn..::1., I. a -: r A,
Ila-124, ill. 1895.

 

21my:inherits C. turn. “a omoy of Recast Relationchico
’Mtwoon income and Food fimditurea.‘ 11.3.1303” 4 ._

 

 

37

wmmditures data. Thie will make possible the testing at the

existmce and validity or Engel'e Law within the state or

tiiaiaigan under both etatic and dynamic mediums.

marquerite c. Bum has written many other articles on
lame-food relationships. Major findings or these articlaa
may be amused ee rollover ‘

l) “are ettectcr real income on quantity of food consumed has
changed only elightly in the lest 20 year...

2) The level of use at food market emicee bee risen eigni~
ficantly with men of the change ocmrrinq in 1939-41 and
1945-47.

3) This change in level or food market ear-vitae resulted in
higher postwar levele or market value of ell teed consumed
and thmtere. of dollar velue food matures in rela-
tion ta immune eleeticitiee tor the road value measures.

4) Analyeie of curvey date ehcwe that major increeeee in the
dented tor mainly produced food and for food whet-
ing emicee in relation to income have came primarily
among term and rural non-fare household: and lever inme
urban hmeeholde.

5) Increase: in eves-age nonemption or flood true all eources
resulted from higher incomee whereee the nee or toad
marketing eervicee hue exceeded expectatione based on

‘ USMC-mm“ ear-vice reletienehipe in prewar yam}

L..___ -1 ..__ Lu 1“. A. h . A

.__‘ w ‘v—w— www— W

1m:l.'-gmmrii'.en c. Burk. “Same Analyeie at Income-Food
naletionehipefl , , a . - . _-

 

37

amendituree date. Thin rill make possible the testing of the

existmce and validity of focal“ Lew within the state of

Michigan under both etatio and dynamic conditions.

Marguerite C. Burk hoe written many other articles on
inane-toot! relationships. major findings or these articles

may be summarised as follower .

l) The effectd real income on quantity of food consumed has
manged only elightly in the int 20 years.

2) The level or one or food met eervicee hee risen eigni-
iicently with lunch of the change occurring in 1939-41 and
1945-47.

3) This chmge in level or food market eervicee resulted in
higher partner levele or market value of ell food consumed
and therefore. of dollar relue food expmditnree in role-
tion to income eleeticitiee tor the food value measures.

4) Analysis or eurvey date ehowe that major increeue in the
denend tor mainly produced food and for toad marketa-
ing emioeie in relation to income have come primarily
mono ten and rural non-tern humid. and lower incane
urban honedaelde.

5) Increase. in ever-age contraption or food tram ell roux-cos
rmlted from higher inoounee whence the use or food
marketing emicee- hae exceeded expectatione breed on

3 income-merit». eervice reletionehipe in prewar yearn»1

MA 4 A... AL“. A \.1 __ ._. _._.1 .1. _ _‘___1 .1

W w ivy—w w...

1'11aurg‘uerite C. Burk. “some Analyeie of Income-Food
Relation-hips,“ . , -_-.. . _ _ 3 1. - '

 

33

anther study, testing the neasitlvity oz mmfiitum
to insane changes used ae a mafficient the average per-emit
d'aimrja in expenditure per one percent 6132159 in dimsa‘bla
par cagita income. balding canstant the effect of trend.

The reaulte are an fallow:

Expan§lture Senaltivity
coefficient
1. Tctal consumption expenditures .35
ll. Burable goods 3
boate and pleasure aircraft 3.1a
radios. phonographs 2.5?
new automdbilee 2.00

(a: 22 durable goode groups, only
2 shaved maiticimte which are
lean than 1.0 and for the majority
01 than, the sensitivity measure
wan 1.4;) or higher)

III. Hon-ucmrable (mode
food purchased for on praniae

dining 1.69
food purchased tor of: premise

coneumption .95
33103: .Ea.)

Iv. Services

but: tare: . .7371
automhile insurance paymmtl .6)
teleplwne .423)
galollne .2‘)
electricity .Zfl

In general. therefore. the durable 90655 were found

ta: be aime average in aeneitivity, the non-durable: a»

ave-raga. and the services - balow warm-5&1

A A l . . . .4. ‘4‘ A.....;

__-—‘—~4 ~ A; ‘ .-.

‘Clmnt flatten and Mabel A. with. “lame
l

fieacltivity a: Conamption Expenditure.“ W
W. January 1953. pp. 11-20.

39
Tourist Effect

Before proceeding into Qaepter In and e more detailed
inquiry of poeeible determinant variables, e short diecusaion
ie neceeeery concerning a dxeracteriatic of hichigen which in
cufferent from that of the average etete. mie Macteriatic
toquixee that certain adjustmente be made when analyzing the
northern portion of this etete. The northern one-halt of
mangan ie characterized by e large influx of eunmer tourists.
The men. reeident population (relative to the annual tourist
poyulation) o! thie aree only tends to add to the inecmracy
of food eelee date ee it appliee to e 'gim county. For
”mole. the date on 'annuel groee retell food ealae per
person" will be en overeetimate o! the true value... This
come became total gran retail tood enlee data includes
nix-chem eede by the treneient population. whereas population
data include only permanent residente of the area. True, to
raider theee date more acme-ate. they ehould be deflated by a
'touriet index” . which with exieting information ie relatively
meant-able.

Accurate marketing appraisal ie etetietically diffle
cult in northern Michigan. eince the tourist patterns are
geogmhicelly and functionally mingled with the resident

pomlece.

 

3’)- Annual retail Food

 

11
t :- tine. yeare (i e 1951-62. 1 I mtiee (1.83).

43

The yearly buying power of a floating ponulation is I
inwmony respects fiiffaront iron that of the resident populnoo.
For instance. the vacationers in a tourist area uaoally noon:
moro than the resident on the some level of income and his
noonaing goon into different items or consumgtion.

In general. one may assume that annual tourist days.
rultiglied by'mean daily spending will yield the figure‘oz
aggrogato buying power at the filoating papulation. however,
in many area: thermean spending is likely to‘be eobject to
large anneal-ml fluctuationa. Since the data one: in this moor

a all of an annual nature. seasonal fluctuatione will not‘ho
m- 5.121 <11 h .

Mao the consmigation o: the floating populatim,
especially travelere. ie fiifferent from that.o£ the roeiéont
or pormanont population. with respect to retail food sales
for instance. it ie unfieratandable that a touriet group in
likely to buy lose food in grocery stereo but ligand mre in
restaurants than the rosiéant papulatioo.1

A recont atufly acne in Hichigan by the Bureau of
mneinoae ano Economic Research at Michigan state Univeroity
{Infiucad the following data which aid in describing the ontoot
ofi tourinm in Miohigan.

Even thouththe nuober o: tourists visiting the upon:
paninsula ie not the largeot of any state araa, the effect of

w— W W wr—

laeinhold. P. Mitt. “Estimating the Market Potmtirl

of 43 Floating Papulation. W My 1954
19:12-17.

41

Table 5. Proportion of Tourists Who Visited Each State Area1

 

(% of Respondents)

Deotination
W an L? e 45 ll #4? )3

gap“ m. j
Western e ]
Eastern j
225.2033 I
Estimated total food purchases by tourists in the

upper peninsula
1962 s 32. 348,475,002

1.1. ‘7 ~— w wiw

tourism is much greater because of the extreualy small
resident population, relative to the other three state areas.

Table 6 illustrates that those tourists visiting the
northern portion of the state tend to spend more money and
thereby increase their effects.

M A _. A ____ ._ l

w

1

W. harm of amino-a and
Econaaic Research, Mic gun State (In v... p. 29.

"charm Trends.“ WW Vol.
6. No. 2, Bureau of Business and conom c Resear . ' chigan

state Univ... Feb. 1964.

w w— w—v.

42

 

 

 

 

 

 

Table 6. Touriet’e Expenditure by Areee Visited}

‘w ___W Median Emmditgg A 7 Am w

mtg; gen, we: W W. A 3179,08 {before the matinee bridge)
. “Eaten __ W___ 176.79

M *4 1......3...” "

mi . is e ‘EML

 

_.___ 4A. A 4_ M __ k .4

lMic‘higen mm Survey 1957.

CH£?TER III

JUSTIFICATION AfiD EXPLARATIDN CF PGSSInhfi SIGEIFICAKT UkfilkfiLBS

93.333“? VARIABLE:

3’31:th all the etetietical analytic, gross retail
foo-El sales data is need ae the emendent variable. The first
portion at statistical analysis represents an attempt to deter-
mine which factors are significant determinants of the volme
of gross retail food sales. The time eerie: study will dieter-
mine the importance or these selected factors in explaining
variations in axon retail food eeles by country over the
twelve consecutive years. The arose-sectional study will
detezmine the importance of these factors in exPleining vari-
ations by year among counties.

In the final analysis and pro jection. the eetimted
potential retell coed sales to: the state and counties are
calculated. It in hoped that the tedmique used in this
paper will prove reliable enough eo that the estimatee may he
need. with covariance. by the Michigan retail food industry
in their plans for future expansion and new store locetlaono.
Since these estimates will be noetly on e comty basis, they
can suggest only the gmeral ereee o! the state having in-
creasing (or decreasing) opportunitiee and normally cannot be
used in the market analysis of an area as email an a city.

An encqation to thie would be in cities such an Detroit o:
Lansing where e large portion of e county’s buying power ie
43

44

located within the city. Even though all gross sales data in
in the tom of dollar volume, it is assumed that the indumry
will be able to convert this dollar value into data referring
to the additional store facilities that will be required in
the future to adequately handle thie increased (or decreased)
amend for food products.

I: 1:” 3...; Dir-3T VARIABLES :

A large amber of factors have been mentioned as
effecting the food sales or an area. It would be virtually
hngaosslble to discern each factor mmtioned as a possible
food sales determinmt. Instead, only tl'mse tactore {mind to
be significant in other studies of. thie nature will be die-
cusoed. Following the emulation of Hichigan data on these
variables, numerous trial me were conducted. By the one of
regression analysis. it was determined which or the independn-
cnt variablee were significant in Michigan and union to
eliminate. I

W: as we so clearly illustrated in Femer'e soggy,
mulch it oi! the greatest importance in determining the
groan toad eelee volume or a given area. Ite importance is.
well wreeeed in the statenwt, ”The wonderful thing about
food from our point or vim ie that everybody ones it - and
'1 This food retailer'e state'nent illus-
tratee the unique type of built-4n obeoleecmce tint food

uses it only once.

4 w .__4._ ‘. _. A. .4“. .u 1...

WWW r W “-— fiv— —— v—

1"'l‘ootl That Isn‘t Food.“ W June 2, l961.
Pe 9e

45

products pone". Ite utility ie not of a long lasting nature.
and once command. can never be done eo again. As unique as
this quality may neon. it emu to partially explain why
population in no closely related to retail food ealoe.
Americane oanme about 1500 lbs. of food per capita
per nnnum. which rQortedly hoe varied little in mt over

e considerable epan or yeere..1

Food, unlike eome other con-
mar producte. in an absolute requircnmt for hmnn exiotmco:
hence the calling job for the generic product is not an overly
difficult one. Moreover, food in needed not just once in a
while. en in the one or most oomditiee. but at frequmt

and regular inter-vale. One or the chmcterietice or food
itona, therefore, is that they are procured on e repeet-
purchaso'bauio.’

Thus. the relationship betvean food eelee and papula-u
tion. alone. in partielly phyeioel rather than eoonanio. The
relationship ie diroet one positive in nature. indicAting
that en inoreoee in the papulation will. out or physical

necessity, produce increased food uelee.

AA A A‘.‘

w w _ W ~—

I'Concontrntion and Integration in notailing,‘ ggggg
was“ “a .1; fed; a Trad r . .3? r . ‘I' " 9:43."! .mu' 1 “a. if
.;--.:.:.a on. v n. 'nr, 1. Govt. rrinting Office, Hashington,
‘6“ Jan. 6 . p. . A

2Ceeeidy. Pe 3e

‘6

Even within the general mpulation criteria other
characteristic- euch ee distribution. parent nomad-mite. etc.
are found to have an effect on food ealaa. For exonple.
airing” in population oonpoeition and family size have been
ehown to have an effect on the lame elasticity and donnnd
for food.1 In a limo! by W Herman. it no ehovn how the
per family income elasticity for the denand for food increased
from .68 to .92 ae the eire of family increeeed from 2 to 6
people. In forecasting the dunno for food. Hermon euggestod
that one ehould recognize that larger faniliee ere more
{W‘NO to income changee than a mailer family. other
nomination ohenctuietice mach an education level. ethnic
hadrground. religion. etc. we found to produce no eignific-
cant differ-wee in food expendituree per oepita M income
and family eire were controlled.2

walker‘e etudy of the Chicago-o
Gray market area revealed the moortance of another phase of
population mopoeition. In this etudy. the increeeing porcont

 

 

H 4;. ...i . A A“ L M
w v. . v , ,__

1% finer Rex-man. 'An Investigation of Differenoaa
in Income Elasticitien of banana for Food in Hmooholdn of
Differing size and empoeitionfl mohiqan state University.
3961-0 Pa 53¢ .

2'mmnae Heil Hone. “Sane Reletionehipe of selected
Bocinoonomio Pactore to Food Goneunption and Expenditures.“
Michigan State Univereity. 1952. PP. into-41. ‘

47

non-white pagination vae found to exert a domwerd influence
on potential groee retail food ealee of the area. other avail-
able infomation" on the effecte of race on food expmdituree
em: to indicate that the influence of this factor may be
dreaming. m: differencee do exiet, between white and non-
uhite consumption behavior. tend to disappear as the inane
level of the non-venue ie increased.2 Negro fmuiee were
found to me more at the eeme level of current income than
om white femiliee and Negro houeeholde were lerqer than the
mite householde in most cases. Average empenditure for food
was famed to be generally larger in white than inhegro tonne-
holds at e given income lone}... the difference being greatest
at lower inme levele.3,

no exteneive infomation on none-white Ming habita
in the etate of Hichiqen could be found. However. we basic
eonmptione on be made: i

1) Difference in non-mute food Marine behavior can be
1‘3:ng attributed to inme levele. rather than teeta or '

‘J A___ ._ __.____ A ._._ m L #7 i_. 4-.-

,_._. w‘vv— w... _,_._.._, ._.__

"willard N. Cochrane. and Carolyn a. Bell. m
.n , 3 _ i. _ .. Nee York: McGrev Hill. 1956. pp. 199*-

 

 
 

2u. a. Department of Agriculture.

51mg?“ 3 if thg n.9,, Report No. 1, want: :1
fig 0 £1c0g 9 6. P. 190.
3artist-M11153! of Pennsylvanie.8

iigggg. 121mg; figg sexing... Vol. 111.: tebul ed by the Bureau
o Labor Static or or hem rtonSdaool of Finance and

Guarantee. 1956.ppw. 133.140.

48
preference dieparity. end
2) Regardless of the attributing factor. a trend~ toward 3
humor percmt non-white pepulation will have a deflationery
effect on an area'e potmtial retail food ealee, with thie
effect decreasing over tine ee non-white“ inconee rieoo

 

Another factor highly
related to population composition ie the rural-urban distribu-
tion. nidxigan county population variee from being 100.90:-
cent rural in the northern countiee ouch ae Mieeeukee and
Home to over 90 percent urban ea in Wayne oomty. Due to
this heavy oonomtration of thie etate'e population in the
routhern met counties. it may be described as an urbanized
Stete with elightly leee than 15 percent of the etate'e total
pooziatioa living in urban areae in 1960.

‘ Food commotion of rural reeidente hee been found to
differ from that of urban dueliere for varioue reaeone.
first. the rural family will two to eat a larger quantity of
food ae well ae more high calorie footie. Thie ie attributed
to the greater amount of phyeioel exertion required in the
daily routine of the rural reeidmt. compared to the urbenite.
secondly. the rural family will eat a larger proportion of
haze-grown foode. a lower proportion of a fanily'e total
food conmpticn is manned et a etore and thie night canoe
retail food eelee data to be an underestimate of true consump-
tion. 'ihirdly. income level ie aleo interrelated to this

49
factor. in that rural residents generally have a lower annual
insane level. thereby inducing than to buy more of the lower
priced food products.

Generally‘speaking. then. one could say that a otenfiy
decline in the percent rural residents. as Michigan has ex-
porionced in recent years. would have an inflationary effect
on future potential food sales in an area. this trend is
not only characteristic of the state of Michigan. but of the
tirelo notion.

W213”. The last population claracteristic. to
he omsidered as a possible food sales determinant. is

population density. The sord dmaity refers to the inhabitants
pa equsre mile. Population Guilty can be considered en in-
diract measure of the-"distance factor mentioned in ferber’e
study. For example. when analyzing a county such as Wayne.
me finds a population density of 4. 392 persons persquare
mile. (1960) This indicates that on the average. a new
food outlet mid have a population of over “000 within a
one-half mile radius. The factor of distance would thm be
of little importance since a large portion of the store’s
wtmers will live within walking distance of the store.
However. now locking at the population density of e ominty
like Keweenev is only 4.4 persons per square nails. ‘ here a
store' s more existence may depend on the male county's papa-
letion. uho may have to travel twenty miles or acre just to
read: the store.

50

i A complicating rector in this analysis is the recent
construction of huge Ihopplnq centers. Traditionally, fir-no
choose locations on e heeis of independently made decisions,
but some time now prefer to locate along with other non-
annotating stores in e shopping center. thus obtaining the
advantage resulting from the drawing power of several merchand-
ising institutions rather than juet one. It eppeers that the
attraction or any individual store within e mopping area is
enhanced by the fact thet other stores providing e renge of
different products or services surround it. Thus. it is
often postulated that in the case or e shopping center or
retell cluster the combustion of stores possesses en ettrece
tion to the customer that is greeter than any ot the stores,
token individual: end thereby exerts en additional influence
to thet of en eree’e population density)

W: “m- nm- factor to be con-

eldered is the number or retail food outlets in e givu tree.
Food store numbers considered an indirect measure of market
concentration. saturation. and competition. Bernard LeLondo

conducted e Michigan study to determine the importance of

2

store size or store complex on per chopper sales. Store

complex was considered to be the number of outlets in the

_A-_‘ A... _.__.__ .__-i4..-——‘ A A __..A AA .4.— *'_._._.___.

‘— *—
———* w w —-< w

2martini-d Joseph LaLonde. 'Diti’erentiel in Supermarket
Brewing Polar and Per Capite Sales by Store Complex end store
Size.” Michigan State University. 1961. p. 119.

51

local market area studied. Store size was measured by tho

ncnber of products offered for role per store. Results of

LoLonde's etudy indicated:

1) fitore complex was an important influence in determining
the drawing power end per shopper soles of the food ctoroo,

2) store size was not on mportnnt variable in determining
For crapper sales. and

3} there existed distinct end significant petterne of per
mapper sales which could be isoleted end quentitstively
analyzed so e basis for future location dismeeion.

Soon addition“ conclusions were:

1) he the product offering increased. drawing power increased.
but per shopper sales decreased.

2} influence of store coupler on per shopper soles bet-mun
quote: or the distance from the survey store increased.
and ,

.3) there one no systematic end relieble connection between
store size end per snapper sales from which any ecmomic
dieoassion could be hand.” .

Market concentration can be measured in one of the
following three ways:

1) Volume of sales eccounted for by serious numbers of atoms,

2) umber of persons served per store. or

3) number of stores.

 

. n . L _4_. “i_. -i- _ A ._... A
M Wei ._~__._ W __ W ._ w

1Wd.. pp. 139-”.

52
market concentration becomes quite important when the industry
in evaluating an area (city, counties, or etete) for future
expansion.

In addition to size or the area, papulation growth
affecte the degree of concentration. Mpidly growing areas
attract new entrente and hence make it more difficult for
existing time to expend weir share or the market. There in
a tondmcy for ealee concentration in the retail food incactry
to be highest in the emeller markets. Thie reflecte the
i'act that chaine which are relatively unimportant nationally,
oftm are very important in their local markete)’ '

While the quantity of grocery iteme available at
retail food locatione at any one time normally ie a: little
eignificance, the number of food etoree ie an eigniiicent
factor which can often have He revere eti'ect on both price and
non-price competition. _Reletive tevneee enomregee concerted
bohavior, evenin the abeence of collueion. with the result
that such industriee behave leee competitively than when

nmnbere are larger.

W: The relationship between inme and food or.
pmditure hae been expreeeed by econominte both in the tom
of lame-expenditure elaeticitiee or amend for food and an
angel curves repreeenting food expendituree et verioue levele

Of inOGDOe

A...‘ A _____ . __ M 4.— _ ._._

w
—~_. .._ w w w...— -—‘_w w— ,

1Mueller: and Garcian. p. 33.

53

Inconecexpenditure elasticity is defined as the retio
off the percentage change in menditure to the percentage
chem-go in income and in oxpreeeed methanaticolly am"

2‘1 25
cx’!

Where: Y I food expenditure
x I- income

The Bagel curve for total food expenoiture ie related
to the ehove since the elape of the Bngel curve. 91, ie port
of the mathematical expreeaion or income electing; however.
it must be remenbered that the original lee applied to a
static condition and not to changer in income levele over
tine.

People like Robert Ferber, Herguerite C. Burk and
George R. Rockwell have long been presenting unpirical proof
cf the relationehip between income and food expenditures.
rather round the relationship to eniet only eiter the into:-
acting influence at other variables (population) had been
removed} Likewise, namerite C. Burk cede acme important
diecoveriee about the chengee in the incoee elasticity of
(la-mend for food over the pest m yeere. The following dia-
gram will beet describe thie change.

._._ e... A

7—..— V“ ——

"Wold, hereon. and Jureen Lare. W
(new York: John Wiley and Gone. l953) p. 8

2Ferber. p. 303.

54

Figure 1.
Average Food Expmditure and Diepoeeble Income Per Capita

1940

1954
1950

i

 

Food Exp. Per Capita $

 

; DieperIe Income Per EapIta

Figure 1 illustrates that during the period of 1940-
50 the line beoune more elaetio. however. beginning in the
1.950% the whole line began to ehitt upwarde due to increased
nee of prepared food- of higher caste. At a given income,
changes beginning in the 1.950% mold indicate e trad towards
a slightly more inelastic income deeand for food prodnoimi:l

George R. Rockwell contributed to thie general die-
oueeion by eteting. ”The percentage change in denomination per
pereon in relation to the peromtage change in income per
person. or income elasticity, is ooneiderably different for
various kinds or food. There are also wide variations in the

income elasticities in low. medium-b. and high—income houn-

holda. " 2

..__..__. A. - A‘—

1nunc. p. 89. _ w
George R. Rockwell, Jr. I e d 8 n
d V mi.

 

55
In general. one may say that rising incomes have a
positive effect on gross retail food sales, the extent of
which varies greatly between areas and type of food purchased.

Hie-e“ Lacy Assuming the reader has the economic knowledge
of the basic product price-demand relationship. little on.
planation is necessary to describe this relationship between
the food pricelevel and food purd'naeee. For purposes of this
study. construe: toad prices are secured to be constant for
all comtiee during time periods or less than one year.

Price changes over periods or one year or longer will be
taken into account by the use of a food price index diamond

later.

RC?" T—ilHu‘I-TION OF DATA!

8 " 5a - raw data on the dollar volume of
annual retail food sales is not published either by county or
metrOpolitan area. however, the state of Michigan levies a
4 percent sales tax on all items sold in food stores1 and
this information (tax receipts data) is published by county

A—. ___._ AA .L‘ M

w“ W —-v
ww— a—V 1—

l"”I‘here is hereby levied upon and there shall he
collected tron all persons engaged in the businsns of making
roles at retail. as hereinbefore defined. an annual tax for
the privilege of engaging in ouch business equal to 4:6 or the
gross proceeds thereon. plus the penalty and interest when
applicable as hereinafter provided. leee deductions allowed
in sections 4 and 4a“. - first paragraph or Section 2. of the
r-tiohigan Sales Tax Act, Act 161. an. 1933, as amended.

in the ann*

 

as >33: rtnsoot ogevmcc.

Sales tax data was collected; from this report for the
aims 1951-52 and converted into gross retail food sales by
the following computations:

1951-60: (X + 3) - 100 =- 22'.

1961: [Xx . Q.4§7‘£1 7 . 100 + [‘5 - §9,§? 11 7.193 a

1962: (x e 4) 3e 100 I z

Saxon-ca K :- total retail food ealee ten
2 In total gmee retail food taxable aalea

Approximately ten percent of the food etore sales are
non-food iteme. Thie uould indicate that the derived data is
not a truly accurate indication of food ealea. However, :zr.

£4.51. Wharton: etated that approximately ten percent or total

toad aalee were not included in the food ealee tax data becaus

these We were cold from placer other than those classi-
fied as food storee. i.e.. gee etatione, drug stores. depart-
mint stores. etc. The ten percent lore and ten percent mis-

ellocation then tend to offset each other. leaving the

.3

derived data "moderately accurate. Gmee retail food sales

I . . A.“ 4 M M “A AA—I—__ _# A

w —-—— WW W

1Prior to Jan. 1. 1961 the ealee tax law read ”$42".
During 1961. often called the “dirty year' by tax analysts,

(-13.45% or annual tood sales were taxed at 333. and the reminder

2
Rev mu a.

acmeidered by ma. Wharton to be 3'- 22: or true food

mice for a given area.

Research Director of the Michigan Department of

J.

o

57
6:911:31 was 1:129:99}! accumulated for the state of P'ic‘aigan my}: its
2’33 992911-9199 1'39: the twelve 3999.:- pariofl of. 1951—62.

'1‘:91*1a 7. Annual. Gross: Retail Food Sales for Enacted amt-29199
and Stata’.
W
($000)

Earaqua «11533115100 Burden 1199219999 Kayne 999-123

‘www m WW 7—.

 

 

1

19:1 1.995 993 47.337 69.379 1999.495 2379.917
1993 1.937 1.114 53,999 79.779 1199 391 2933.929
1959 1.99 1,194 54,591 79,291 1159.999 2:99.99

1993 2.234 1.593 63.109 91, 939 1151,002 :294.439
199:: 2.397 1.593 59.119 95.193 1021,h62 33.97.9999
1992 2.599 1.339 653.178 99.239 1015,5391 3:97.993

 

E3 cannula- arc ”0.119191. 1.11 the 8.8. Census at Michigan $9311“
191-91911. hawovct. thin data 1. only published at the beginning
of; every (39911930 1940. 1950, 1953, ate. Luna to: the inter»

”annual

 

cannua years was obtained from
5111119993 cf Buying Puma" published in July of each year.

A: shown in table a, Michigan“ powlauon has been
increasing at approximately 2.23 percent. per year, comm-9.99-
91913: 912an the nvsmgo increasa of 1.83 percent. rewxaeé £9:

thfi nation an ‘ “13.

M A— _._n...._

LA.— ..LA... A. _. A j

'Daea derived from sales tax data - information £9:
:9 919112;: 73 counts” can be found in Appendix A.

58

Table 8. Population for Selected Counties and State'.

“Mayna- .‘n W-‘""_ «M

 

~-_ av ' .~ - -. ,>""_h -.

 

 

:5 arson M 1 "nukes Big-Kin Ingram Wayn- state
1951 ‘7.943 7.391 119.1 176.9 2459.3 6516.9
1963 7.7771 7.256 126.0 194.4 2594.5 6999.2
1955 7.594 7.121 132.3 192.1 2559.3 7997.3
1959 7.329 6.919 143.0 293.6 2929.1 7522.9
1990 7.151 6.794 149.9 211.1 2696.3 7923.2
1992 6.994 6.661 169.9 229.3 2717.1 9265.9

. _ M . - A... ’ A _..__._

_.___... W ———-——— ‘—

 

«- slightly less than ten percent
oi 91161191111“ population 1': non-white. This proportion 1199
been growing ctoadfly at: about. .22 percent per year. Over
one-#191! at tho non-uh“. population 111 the northern most.
part of tho stat. cannot-rot 11161311.. «1111. flegrooo are
pmnmtn‘ the pouth'o nonwhito pépnmuon. flowing from
poi-1:11 to south and from out. to out. who pore-lat Mite.
9191191101111191903308. , fl 9 ’

Tan. 9 11111321999.” Marthe pardon: non-whit. paptna-
tion 13 increarmg 111' the southern mutt“ «1:11. 1.: 1-

dacreaaing in can. of the northern on”.

W331i! 9 generally 89mins» papulation density
in financing in tho northern count“: of aichigan and worms-

1m; in the southern count-.109. A

, . A..__ A.-

w' -—v . W W V w

'Addzlttonal information in Appmdix A.

59

Tablo 9. Fraportmn mom-mun Population.

(Percent. at Total)

 

Bongo Milo-aux" Bordon Ingram Wayno state
1951 5.76 .57 6.45 2.19 14.52 7.33
1953 5. 20 .51 6.95 2.57 15.76 7.70
1955 4.90 .45 7.45 2.95 17.00 0.25
1950 4.09 .36 6.20 3.52 10.66 6.94
1960 3.60 . 30 8.70 3.90 20.10 9.40
1962 3.12 {24 9.13 4.07 21.19 9.00

.4 .4‘ ‘4‘ , ___.__ -——.‘—— “L.

v—w v—v—w w v—v—w WW .7 VFW w

Tablo 10. Population beauty. 9
W
‘ ‘ (Poroono/Squoro H110)

 

1962

 

__

qua 1114660206 6422166 1691:» Woyno 61.620

w _.. , 99 A 1 7W 1:
1951 3.00 13.06 205.39 316.26 4049.97 114.25
' 1953 8.60 12.84 217.17 329.98 4126.11 119.35
1955 8.40 13.60 228.95 343.70 4202.25 12‘445
1953 8.10 12.24 246.62 364.28 4316.46 132.10
1960 7.90 13400 258.40 378.00 4393450 137420
7.70 11.76 270.19 391.72 4460.74 142.30

r W W

. oouthoru P11631191!!!

mun oro olowlr homing noro urboolzod. mayor. many of

tho northorn oountho 42111 hm no Moorporotod 0111.94

largo «tough to be oonoidorod an urban am.

6O

 

Tdblo 11. Pare-at of Total Papu14t1on . Urban.
W
06:69: M1unnukoo 0622160 Inqham Reyna Stat.
1951 O 0 50.23 78.68 96.96 70.97
1953 0 0 50.09 79.44 97.08 72.05
1955 0 0 49.95 80.20 97.20 72.05
1953 0 0 49.74 81.34 97.30 72.86
1960 0 0 49.60 82.10 97.50 73.40
1962 0 0 49.46 82.86 97.62 73.94

v w ———

W ~ during the “-1" you purlod of 1951-

62. every county in Mtdh1qan cxpcrtoncod a docraano 16 th-
uumbot of tot211 toad.out1oto. Th1. tutormatlon an. extracted
tuna tho 0.9. Bus1noun Census. Data to: tho 1ntor~ccnsul
yon:- wnrc dortvod by 11noor 10torpo1at1on. It must be noted.
hon-vex. that a docrouoo tn the number’ot tactlttto- 1- often
nts1oadin§ u1nco tho-croutlott rumatntng havo gonora11y 1n-

area-ad 1a .12..

 

24h1o 12. Ruabor of £01.11 Food Store...

062096 Miouaukoo Borrton Ingham wqync Stat.
1931 13 23 321 11 351 6495 16531
1953 16 19 299 322 5959 15210
1955 14 10 292 303 5522 14292
1950 14 '19 265 291 5010 13529
1960 12 18 247 270 4552 12505
1962 11 17 230 251 4110 11571

A #— *L‘w“ A.

w— W w
Vflfi w W V “1* ww— ‘—

*Addit1on21 tutormatton 1n Appendix A.

61
‘inggmg_§ggglg_- tncomo data wa- 6120 nxtrnctod from the
“Annual Survoy'of Buytng Faust“ published each July by fig1§§
‘figggggmggt. Th1: nag-zinc 42:19.0 at than. 14941. by taktng
a survey of 4465 county ul1nq afl11 qnoat1onna1ron and person.
41 1ntorv1cum. I chat. per capita d15posdblq 1ncomo (total
earned tacomo 1454 taxes) bol1ov1ng it to to tho boat 166106-
tton of fund: ava1lablo for food purchase-o '

Tdblc 1!. Par Capltn Dioposablo lhcomo.

062696 Mitsaukoo 84:21.6 'Ingham Wayne State

W—w—fi *1 wwfi—

1951 1466 938 1517 1799 1406 1610
1953 ‘ 970 679 1439 1637 113 1641
1955 967 374 1571 2026 1212 1615
1956 111 , 1154 1635 2026 1322 _ 1610
1960 1202 1251 1636 2374 1434 2224
1962 1232 1162 1963 2140 1512 2000

w *. ____ M —- .4.“ M
w—v— w— Fw—V w w—v— _.._ 7——

909 that I‘hcvo‘l1utod. oxp141nod. and llluotratod
that. factors whxdh at. to be countdcrod.as pelliblo actor»
minant variublol. 1 dhnll ptolont a short deucrtptton of the
atat14t1ctl tout. avalldb1o'to dot-rm1no «hteh at that. tact034
at. u1gn1£1clntly'1mportant 1n M1chlgnn. Chaptor IV will
63:016. tho alternattvon ava11nblo and descrtbo thn It6t14t1eal
tcdhnlquo t1nally duos-n. '

CHAPTER IV
POSSIBLE STATISTICAL PKDCEDURES

no. that oonoidorauoo. o: to... vaz1abloo montumed
1n Chaptot 11. ha. 19... juottflod. ototiotlcol toot. V111 11.
no.0 to dotorulno which of tho... tactoro. 1: any. ha. a
16.6mm. otfoct on tho vo1un. o! omoo rotau food ooloo at
. opootflc t1m. vlthtn tho otat. of 14101119611. 1t moot ho
notod. hovovor. that tho oo1oct1oo ot a 919.11 vanablo. shown
to havo o oigntncant ottoct 1n 111421119611. dooo not mount.
that an. om factor .111 hovo a “tuna: oftoot 1n othor
aroao or undo: d1t£otont o1tuotlono.

1o amoral. .tatiotlcal onalyolo tnvolvoo tho touting
or o hypothooto. much for purpoooo of th1o 21m procoduro
ohall 13.4 141 11.. no ottoct on qrooo rot—.11 food oaloo of o
91... aroa. Tho potpooo o2 tho otat1otxoal toot 1. to accept
or 1'ij tho (6911) hypothouo. and to '46 oo 40111. 3.16161.-

1119 tho 1... tune‘flou.1

4w A __._. ##4— M .__.__‘ ___._.__

x1. I at 71010 "2°:

1. In total .xpoctod looo
i I probabntty o! Typo 1 orzot (rojoctton .ot
bull hypothoolo whoa 1t. tax.) 4

3 I pmbab1l1ty of Typo 11 .2263 (acooptane.
oi null hypothooto whoa 1t. taloo)

. prlot probabnlty that null hypotbouo 12
two

2' p210: probabutty that 111111 hypothooio 1.

£614. and altomativo tn.

:1. ooot of Typo 1 .11.:
2- out o! Typo 11 om:

Ii’1
P

62

63
Tho following oocttoo mount. a ohoxt atocuouoo of

tho commonly uood otottoucal toot pmcoduroo.

W1 Probably tho oimyloot techniquo which is -
and to dotommo tho dopondoncy hotom x1 and grooo flood
ooloo io tho ch1-oquoto toot. Tho basic procoduro involves
touting tho dopondoncy botwooo on. lodopondoot and on. depend-
.ot vatioblo. Th1. toot can b. appltod whoa dot. for both

1 61660 tho data obtained

96216111.. or. qual1totiv. in oaturo.
111 mu. otudy at. all quantitativo. tho on of tho ch1-oquaro
toot would b. on unnocooouy amplification. Juot oo tho
daiaoquaxo toot uooo tho oughtoot amount o: lotricato data
and dotoil 1n 1t. poocoduto. 1111.91... tho tooulto or. of
only tho ollqhtoot voluo rolotivo to thooo of tho 10110271110
two otatiotical tooto. Tho chin-mar. toot dooo ootablioh
tho tolatlooohlp. 1: any. hotwoon o dopondoot and indopondoot
variablo. hooovot. it providoo 642 auction ooaouroooot of:
thlo rolotioooh1p no: 60.. 1t provido any moirical data from
chich projoctlono can to «1.0..2 Also. analyoio of on no.

on wall oo a county. oould toqutro annoy dato 1m vatious

w. A k A ‘1 A. . M

‘w w ——
Ww " w—w www—

11. v.9HondoroCho1d. 'An Introductlon to Statlotlcol
Tooting.“ Aquculturo Economist. 74110.. 867 - rovlood. 2.13.
196‘. pp. 6.8.

f 2Fm'odonck E. Ctoxtoo and Dudley J. Gowdon. 52211.99.
W. Franco-8611.. Inc... Enqlowod Clltfa.
3.43.. AP“; 1956. pp. 681-693.

64
areas within tho county. Thus. tho information proomtly
696110.131. would only allow tor a otato onalyoio. with county

data oorvinq ao oboorvotiono within tho otato.

 

‘ V 1 Th. hypothcoio generally tested in tho
analysio of variant. tochniquo i. tho oquality botwoon tho
mean. of «veal group. of data. ouch .1th by 6 different
" An 1661;21-
dual county onalyoio io poooim. within tho map. of this

dogro. of influonc. of an indopondont variablo.

analysis. homor. Just oo in tho on. with tho chi-oquaro
test. data tron variouo oroao within tho county at o giwm
timo would to nocoooary. aowovor. it oboorwoticno woro made
ova-r aporiod of timo. thio would not to nocoooary.

Tho onalysio of variants. requiroo that at tho loast
the dependant variablo ho quontitativo in naturo. . Juot on
the onalyoio of "none. roquiroa a more dotoilod procedure
than 00.. tho Ohio-quot. toot. it aloo providoo nor. precise
result... hwortholooo. thio toot also provides no numerical
moomr. at tho rolotionohip botwoon variabloo. nor doe. it
exhibit any haoio from which projoctiono could to undo.

Whil. tho firot two ototiotical tocho

 

w Wm W—w v—fi ———""—-"

101m. hili’roid 0.. and Fronk J. Mooooy .72.. mm-
.9 - . ~ o 2nd to. NcanufiillBock

  

65
they are 0! oxtromoly limitod valuo whon ootimating tho
effects of. independent variabloo on o dependent variablo.
z-Iooover. tho rogroooion onnlyoio tochniquo io oopocially suited
to this typo of computation. Tho typical tom of. tho regres-
sion oquotion in

Y . “ "‘le * 32X: . oooooooooo ‘finxn " u

Whores Y o oboorvntion of o dependent variablo .
o factor which io ottoctod by tho ina-
dependant voxiobloo in tho oquotion.

xi:- (i :- 1nd!) II observation on indepmdmt
variable of oooociatod independent vari-
oblo tot-tort I) which ottocto tho depend-
ont vorinblo, but io not otfoctod by it.

(a oonotnnt pogilotion pomoto:

piti :- laoon)‘ rogroooion coofticiont roprooontinq tho
nognitudo at tho relationship between x
and Y: to: every unit change in X thor‘
will bo oooociotod with it op change in Y,
coming x2"... x n nzo conatnht.

u I- oboorvotion of tho random orro: torm.

It vo now mo thot all voluoo o: a oboorvod oro
independont tondon votinbloo, vo thoriobtoin tho fiollowing
A
estimating oquntiom Y II o '0 15131 O bzxz o- ..." o bnxn

Whorou- 9 o ootinotion or calculator: value of Y:
o and b oro ootinotoo ot-tondfi

Additional romlto ooy bo obtoinod from tho nomal

1

rogroooion analyoio toot. sono of tho otho: intonation

obtainod includo tho multiplo correlation cootficiont (a),

.4.‘ A.“ ._.__ ; A A A A A __._ M M

linen. 9.2.. and mi. Rublo. “I-‘ozmuloo noon in cons
Nino.‘ Add. Program Doocription l2, Oct.ls, 1963, pp.4-9,
Michigan Stoto Univoroity Computor Labototory.

68
the standard error of ontimato ($y.x), standard orror of co»

efficients ($121). t-valuo for testing it tho 1'9:£ in different
1m zero (1’3), rooiduolo (at) and coefficiento of multiplo
doteminntion (32) olong with othoro. when:

R2 o 5311 son I own of aquaroo oxploinod by rogresoion
TSSM rssmo total on or oquaroo oftor mean

2 _ .

R

oorroctod for dogrooo' of. freedom 1- Ez- l-Nc-L o(1~R2)
d1

:3 II numbor o: obomntiono
£2 io otton protorrod to R2 oinco 32 given tho oxact
oplit. of tho vorionco of Y2 nto orploinod ond an-
oXploinod variance whereas R splits tho mm oi?

oqunroo.
a - fit:
a wrroctod tor dogrooo of troodoa a 3 In El:
317.: o G:

.52 II ootimotod variance of dioturbonoo I SE

383 :- mo of oqunroo of orror
onto 51:: o {:1 .82

oi I- i th olomnt of tho invoroo o: tho some
of oquoroo

T3 II tb o 2% Y o truo voluo o: oopondont varinhlo
s
i

no A i
“t o 7: «- Yt Y .- ootimntod value 0: dopondont
vorioblo

'i'hio outhor will not nttmpt to oxploin tho calmlationn
involvod in tho typical rogroooion toutino oinco dotoilod ’
oXplanotiono of this routino nro readily availablo} Also.

_....._ “h __.._. - A

W “—7 w W W

’xm, 9.2;; and w. mm... ”Calculation or Multiplo
Regroooiono. Uoo of. CORE Routing" 3.3.8. 310931: Doooription 4.
8.9%; 30. l963. Michigan Stoto Univoroity Computor Laboratory.

67

the availability of computar sot-vices makes an understanding
of the calculation toohniquo unnocaaoary.

no can to roadily notod. tho rogroaoion analysis
todmiquo involvoa moh noro intricato calculations: than
either tho chic-aqua" or anal yaio of varianco tosta. It also
providoo moro detailod rooulto from which a noro couploto
analyoio can to aado. It nakao it poooiblo to nmorically
monouro tho magnitude ct tho ottoct an indopondmt variablo
hao upon a dopmdent variablo ao well an anabling tho noor
to mako projoctiono on tho aomption that thou rolationnhipa
dctoctod will rmin conotant ovor timo. Alon, tho'i‘B value
associated with each independmt variablo my to comparoo
with tho tavaluo at tho t otatiotical toblo and. givon
éogrooo of troodoa (N-k-l. whoro H II oboorvationo and I: 'I
paranotoro), it can to dotorninod ohothor or not that parti-r
cular variablo io otatiotically oigniticant in ito ottoct on
the doomdont variablo. For oxamplo, it can) twaluo.
given doqrooo o: {roadom anod- lovol. than tho variablo is
accepted as being otatiotically significant} '

Hanover, this torn 'aigniticant; mot not to nio-
intorprotod. Statiatical oignificanco may voll how a oomploto-

cly éiitoront connotation from that o: oanomio oigniticonco.

A i , A A ._4_. L w... A ‘_~ A w; A_.__ A

_..—, vm — w w ‘— —-——— . rfi

"Tooting tho oignificanco of tho hypothosin that
variablo (I). Xi hao roro otfoot on tho dopondont variablo.
(using a ono-tailod toot).

63

For NZMple. the arbitrary usa o! .35 loval of at may have no
economic moaning if tho difference in retail food sales is
only $130 per county. Likewise, many factoro may ho ocono-A
mically oignificant and yet ahow a T3 toolow to qualify as
being otatiatically significant. For this roaoon. factors
were ooloctod. for thoi: importanco oo a dotorninant factor.
on tho haoio at tho ,‘noot‘ oiqniticnnt (alto of TB) rathor
than using tho TB é twaluo critoria.

 

In omnary, tho regroaoion analyoia proceduro was
chonon ovor thooo of chi-aquaro and analyaio of. variouo for
the following reasons:

1) Data on both dependent and independent variation are

gzontitntivo in nntnro and thus. can most ottoctivoly be
nalyzod by tho regronaion techniquo.

2) It provider numerical nonouromanto of tho ralationships

between tho variabloa and anablao determination o: those
factoro amid: aro “nost‘ oigniticant.

3) It onamoo tho our to tormlato projoctiona.

4) Providoo odoquato roaulto from which o bottor ovorall

annlyaio can to undo ao command to tho othor altornativo

methods.

5) It allowo for individual county analyoio, uoing availablo
information, and illustratoa tho hotnrogonoity batman

countioo.

69

6) Emotion noaourononta aid in tho oconmic intorprotation
of tho relationships that may oxi at.

 

Timo sorioa Analyoio

Tho firot rogroooion oquation to to and in thin
atudy io callod tho tino oorioo mltiplo linoar rogroaaion
equation} Whoro a dopondont variablo io ini'luoncod not only
by a oinglo indopondont variablo. an in tho rolation of. Y to
:5, not. aim by too or m. indopondont voriahloo. thio

relation can to roprooontod symbolically by tho tollowing

multiplo linoor rogroooion oquatiamu2

Y o o o hlxl-khzxzo u... «I- hnxno u

Hhoro: Y :- tho dopondont variablo
81',2""“"n . indopondllt Vattablefi

M proviouoly otatod. tho tirat ohjoctivo to ho
roachod in thia otndy io to dotornino which at tho factors.
it may.- dooorihod in Chaptor III. havo an opprociahlo ottoct

.4 A- - A“ “A A A ‘4

.—_w. , w— “'7— __,V wfi w.

1"Tho torn “mltiplo‘ io addod to indicato that it out--
plaino Y in torma of too or moro indopendont variahloo atrza,
".3: o Tho coottioionto b and h aro tormod not roqroa‘ i
coofgicionto. Tho torn 'n " io good to indicato that they
show tho rolation of Y to and x .v‘roapoctivoly, oxcluding
tho aooociatod influoncoo o tho indopondont variable
or variation."

’9“, Karl a, and Enokiol Mordocai.

" ‘ ' ‘ ._ ' -' a. Jam Wu” ‘ m.g "Inag"§w

   

W199. p.152. '

70
on tho gmoo rotoll food ooloo of o county, motmpollton arm.
or tho ontlro ototo of Michigan. Tho multiplo llnoias "groo—
olon tomala will ho mood to accomplloh thlo task in tho
tollowlnq my.

mm. lt boo already boon montlonod that tho ama—
uaxt mlnblo of. thlo partleular aquatlon lo tho moo totall
food «loo o: a. gtvon area. slnco tho first toot ohall be a
tlmo ooxloo otudy, tho annual volumo a! “toll road oaloo in
“County A" for tho tvolvo your pol-lad of 1951.62 bomoo the
valuoo a! Y 1:: tho aquatlon. leovloo. tho doto on tho 1m»
dapmdmt variabloo prudently diocuaaod (powlotlon, lame,
#33 food otoroo. otc.) bomoo tho valuoo o! 35.32"...)5‘. The
equatlon to: County A thou lento llko: Y :- o+b121+b2x2+ ...+
has“. L

mun: Y o annual gm" rotoll food onloo l95l-62

to: County A

13.x)..."xn o memo. populotlon. etc. 1951-
62 to: Cmmty A.

Onto tho data to amngod in tho abovo manna. it to
oubjoctod to trial m calculations. nooulto of thlo trial
m should om tho porcont of vulotlon tn Y «or tho twelve
you period that to oxplalnod‘by 11.x2.....xn. ‘32,. tho magma-
tudoand dlroctlon at tho otfoct an 1! of oodh figxrooooofiao
(121,132....h), tho lovol of oignlneanco of ouch Mopondent
variablo (T3131, ”by"... rah“), ond o grout dool o! oddl-
tlonal lutomuon not at partlmlar lntoxoot in em- study.

71
Those variabloo with low lovolo or significance at high inter~
correlation aro thou drappod and tho calculationo again made.
Eventually, on acourato oquotion io found mowing the magnia
two. aiqniticonoo, and porcaot or variation in Y oxplainad
by thooo variabloo oolootod. Thia procooo no oomplotod for
war of Michigan“ 83 oomtioo and tho otato to: the twelve
year 993104.

The following diagram may old in tho roadar'o undon-
etandinq of tho ditroronco between tho time-«arias analysis,
just described. and tho cmoo ooction analyaio. ooon to be
discuoaodc

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(on) ‘ '
. (For Comment")
2.2.3.... F - 5 - flow-ow:
Av‘fl M‘“ “1...:“‘ MW A “i...“ ‘—
......i o a A i: ’ .1 ,_
_ .......§A A J h W
._...§ » A a A __ A— W
,1 A w J. J *_ “To
Jo” Mo to _ o J; ~~~~~
, g __ o ____A;__M A of w
m; “A“. A «A ”*W# *1”-
m 4 ““1;
4 - ‘Tw—AvWT‘“ “ w. I M TL“ ““‘

 

 

 

 

 

Tho tino oorioo analyaio involooa tho calculation of

84 multiplo liaoar regroooion oquationo. too to: ouch of tho
CDLUE‘EJS of data. Tho crook-action analyoio. Woo. involves

72
tho calculation o! 12 oquotiono. one for each of. tho Roses at
data.

emu Sectional Analysis

aux-t, o cmo—ooctional otudy is conducted. Tho-
otatiotiwl pmcoduro in much tho oamo. except ouch oquaticn
represents vuiation in food men between counties to: a
given year. rothot thou vorioticns m: o two potted (11
years) for o givm county. Whereas tho timo sorioo equations
we and to deocribo chanqoo in gran retail food oueo over
timo for ooch county, tho croonooction oquaticmo now doe-
criba variation batman countioo for my 91m you batman
1951-62. Tho voriabioo and mo truso found important in
the timo o‘otioo analyoio.

simplo Cmuihoor Rectonion Equation

Onco tho oignificont factual hovo boon detomined.
one major otep main: Moro pmjoctiono can to undo. By
taming thou roloticnahipo round in tho mitiplo linoar
:03:qu oquaticno will main constant two: time. numbed
values at “1‘”2””"‘n to: o tututo you may to piocod into
the aquatic!" and on oatmatod value at Y. for that you,
mlmlotod. am“, tho occuocy of thin: estimatod or pm-
Jectad Y dopendo not only on tho accuracy 0: tho oquotion,
but also on tho accuracy of. tho ootimatod voiuoo at 31.82pm"

Rn «stated in tho colanatioho. 'Iharoton, tho major step
now being couoidorod, io tho accuracy of: tho projactod values

73
of the selected indooohdoht variables.

Sinco tho cannon behind the vaiuo of o given indo-pmd-
ant variahlo is not of particular interest, these rotatory
projoctiono hood only to mado oo o function of timo. For
oxmnplo. Figuxo 2 illustrates tho situation now faced.

Fiqoi‘o 2
Curvilinoor Ptojoction oo o Function of Time:

(7)

 

 

'193’1 " “"1562 “““ Rafi-J

votiouo todmiquoo oto ovaiiobio for ootimotinq tho
waldo at 3‘ in o tutu“ timo potiod, troohond, wing over-
ago. or loo-t oquoroo trond lines may ho drown thieugh tho
given voiuoo of at" and extol-mod outward toward tho future
you of intuoat. 'Bowovoi'l. moro occui'oto trend line: may
often ho obtain-nod by using o oimplo curvilinear regression
«motion oo ohoum ' '

Y .. ' ‘ hm * ”2*?

than: ‘2 o afloat-d independent variable (3:1 in
Figaro 2)

:11 C time

74

mathematical curvoo will have a distinct advantage
over froetumd and other methods when there io o logical basic
for expecting o curtain typo of relation to‘hold. when thoro
in a logical booio tor using o given tormula, tho constants
at tho oquotion oorvo no on oxplanotion of tho nature of. the
relationohip. In moot othor cocoa, the mathematical curve is
no moro rolioblo than tho othor methods)

Il‘ho ohovo oquotion io calculated for each of tho
oeloctod*varinhloo tor ooch.ot tho 83 oountioo. Roaulto o:
theoo calculutimo will ho similar to than of tho multiple
linear xogrosoion. Onco o. bl and b2 havo hm determined.
the valuoo for tho opocific tuturo your io incorporated into
tho oimplo mnilinoor oquation and on occuroto «timoto of
tho voluo or ovary-ax“ io dorivod and thooo valuoo thou
placed into tho multiplo linoor oquotion to obtain tho poten-
tial rotoil food colon of o givon county in o qivon yoor. In
the following choptoro. thin ontiro process will be illusa
troted in detail for fivo ooloctod countios, and o.moro
detailed understanding thorohy dorivod.

A“ A ._ “A _‘___ .....__- _¢._. 4.. .. _ .

W w-F ‘ _.__r ‘r v w w... ..,_._

lFox and Eastiol. p. 109.

WEE V

551.2:me CF 5mm: ".1033? \«MIAELL 132:1)
9mm. anemones: EQUATIOEI
no stated in the previous chapter. the important votin-
esaloo aro ooloctod on, the hosio of test results using multiplo
linoar equation in a series at trial run calculations. This
chapter explains tho procoduro used to "loot the final voric

ohloo and regression equation.

W

Rathor thou conduct on W involving all of
Eichigao'oBS mtioo, iivo ommtioo mo ooloctod to
rmroooot moot of tho variouo typoo of oountioo round in tho
state. Thooo tivoxoountioo could than to carafullyanalyzod
and tho rooulting variahloo uood in conditions for tho cater
723 ommtioo. ‘ ' V

Mop a: illuotratoo tho location of tho five selector
Wm...
M - Thio county io taprooontotivo of tho oountioo in time
0999! Poninoula. 'lto rooidonto an primarily rural dwellers
with low incomoo. Tho county io vory oparooly papulated and
has o largo touriot influx during tho mar months.
W .- m. county io typical of countioo in tho mm
portion at tho Lava Poninoulo.‘ Horo. oloo. moot at tho
pooplo oro rural rooidmto rocoiving a low income (run their

15

76

Map #2

Selected Counties

 

 

 

 

 

 

4 Code # Countz
n. 7 Emmga
§\. (57) S7 Missaukee
ll Berrien
g3 Ikghmn
2 W
Michigan ayne
\
n (33)

 

 

 

82>

 

 

farming or logging enterprise. It has a relatively high
summer tourist pepulation. '

Berrien - This county was selected to represent the south-
western portion of the state. Here the pepulation is more
dense, incomes are higher and the rural-urban papulation is

about equally distributed.

77
13“"111 a3. - This county represents central r-uchigan and is
characterized by a ugh per capita income, fairly heavy
population density and, a high percent urban population.
Wax :3 . This county reproéents southeastern Michigan. It is
the most heavily populated county in the state, it has a man
percent mnowhite population and almost all of its residents
live in urban mmmities.

The above tiva counties represent statewide variations
in geographical location. pow-lanes, population density,
percent rural-urban malatioa distribution, income level.
percmt non-vuhito population. etc. By analyzing these
typical counties, it is easier for the radar to establish
limits within max tho discussion will remain valid. Even
tlmgh only tho tivo ooloctod counties will bo discussed in
detail. regression equation results tor all counties on
prorated in the appendix no that the reader, specifically
interestod in one of tho remaining 78 counties, can perfom
an analysis oimilar to tho ono discussed in this papor, on
any particular county or group of comatioa. Throughout the
remainder of this paper. the discussion shall pertain direct-
ly to tho tivo solectod countioo. motropolitan areas, and the
State on a whole.

W:
' Tho first calculation used tho following equation.

78
Y I o it 131211 0 132:: o ...... a» 13939 9 u
Where: '2 o‘ 3
‘xfl’ioo

:1 I population donsity
a: II also volwno per otoro
x a sales volmao per person

3
x4 .(§3)100. (deflated disposablo per
4 capita income)

35 .‘ 5) . ‘dflflatad diamabl. per
:4 100 family income)

86 I percent non-hito Motion
in, I t urban pep ation
"B I- umber or food otoroo

I

I

39 pepulation
grooo retail food oaloo

git food price indox. ism-loo
3' pct capita disposablo incomo
:31 “II oonsmor prioo indox. 1950-100
”15" portamily diopoooblo inmao
:- roam orror
~‘rho abovo equation shown. how shoot all factors
national in Chaotor ll! voro conoidorod in tho firot trial

Mo

W

Baton continuing. tho uoo of tho food prico and tho
constrnor prico induoo must to oxploinod and justitiod.

an index io mot often dotinod no a nmorical device
used to compato tho magnitudes or two or nor-o relatod factcro.
To be non procioo. tho indoxoo in this aquation woto used to
doflato tho oxioting valuoo of gross solos and imo no as
to mo ottocto of managing prico lovolo. Binco all sales
data aro proomtod in tormo of dollar valuo. currently assist-
ing in the year roproomtod, any projoction or this data into
the futuro would to oxtmoly misleading whoa compared to

79
present prico levels. Boforo tho past, present and future
sales voluao data can accurately represent tho physical vole
mac implied. tho inflationary offocto or price riaoo mat be
eliminated. Likouioo. inm lovolo must be adjuotod so as
to depict its true purdxaoinq power.

To accomplish thio adjustment. a food prico index was
used to dorlato tho prico of. iced and o oonouaor prico index
was used to rmdor incono lovolo noro roproomtativo of its
true paramoing W.

m conmor prico index. em... rm tho Buroau of
Labor sta’tziotior1 is a otatioticol nounro of changes in
pricoo of, tho good- and oorvicoo bought by common. it
meamroo only mongol in pricoot it tolls nothing about
chmgoo in tho kinda and amounto of goods and aorvicoo con.-
sxruero buy, or tho total mount spent tor living. or tho
differ-anon in living costs in dittoront places. It uses the
“comet tomcat approach“ in dotormining that products on
priced. Tho indox market bamot in an oatimato of tho goods
and sonic" bought by tho conmor to coo. roploco and add
to thoir pooooooiano to hoop up their lovol of living of a
aim haao you. sinco this index roproomto tho dances in
tho prico incl at mama’s mark-t bonnet. it than booms:
an indicator or that consuaor'o purduoing pom ao catapulted

to a hero your.

M “..A . M _._. _.e.. ‘ ._._

no... . - - .
._.. r. VJ v W 4—,— _...e W w r__,

1“Wiring. willord W.- “Tno Conowaor Frico Index." U.8.D.L..
Bureau of Labor statiotico, January 1959. p:- l.

82)

The food prico index it o meamro of tho prico 612mg“
of! only tho toad prosaic“ within the markot hookah It thm
[amides o numerical ammo of tho food price chongoo over
time and motion can to eliminato tho inflationary portion of!
9:039 onion, ioavinq data onto roproamtativo or actual
pmroioo). voiuno at £0063 comparod to o baa. period.

 

Dospito almoot constant xovioion. thou indexes are

3 Thoy no ”one: to tho many kinao
o: iimitatima that on alwayo prose-1t in ototiotical calcar-
iatiooo. in tho language at tho ototioticion. thooo limit-v .
ationo oro oniod "'ox'aro~x*o4_‘."3 Thin ohouid not ho intotpraod

not exact ooaouromonto.

to mom that thoy on autonomond. to: purpoooo of thin
stmhr. tho indoors: oto “mod to bo accurate.

Also. naming that m arm at Hichigan no oqualiy
affected by any national. inflation (or donation), tho two
national. index“ mo appliod to ”a: oomty'o data. so on
to who this uniform to well no applicablo to tho timo period
being otndiod, both indexes mo adjusted to tho base year of

 

M _.‘A_L_ -_... A“ u _. __-. L “A; “A _. A.“ W

1volunoo otiii unocto tho inoraaso in toad mica
value duo to inaouod omiooo in product.

 

3'c.p.1.,' February 3. 1964. p.22.

 

SUM”. Olivo E. ”An appraioal of tho 3.1..3. 0on-
mo: Prico Indu,‘ W, octoboz 1953, 18:
1%!»

8.1
1950. Below are listed the values used for oach your 1951.-
62o

CON 5 U”; E

 

 

YES-1.53:3
1950 100.0
1951 108.0 ‘
1952 110.4 1959 121.1
1953 111.2 1960 123.0
1954 111.7 196 124. 3
1955 111. 3 1962 126.7
1956 . 11 3.0

   

 

Bororo dimooing tho toot motto of trial run (fl.
it might ho holptul to illustrato tho {actor trondo in tho
various oatmtioo and mention mo rolationohipo that might be
orzaoctod to ohm up in tho tomato. :

Rot-ail Food Saloo . Tahlo 7. in Gupta III. ohowo how gross
retail food ooloo incrooood in ooch county during tho twelve
year period: Inghom county loading with almot o 50’ percent
incroaoo. Thoro io o noticoohlo drop in 1955 mid. may to
attrimtod to o sharp national rocoooioo in the oorly port of
that yoar. Aloe, thoro io o notiooablo lovolingeott o: the
incroaao during tho noro roost yam. noun 3 illustrates
tho trond for tho ototo oo o uholo.

Fomlotion - ‘robloo 8—11 in Chapter III illuRrato tho trams
in the population maraotoriotico of tho voriouo oomtioo.
Figuro‘ illustratoo tho otato trend. Botioo tho regularity of
this incroaoo along with tho alight upward-bonding tenancy.
This phmommo io certainly oxpoctod, when oonoidoring tho

($000,

h.0

3.5

3.0

2.5

2.0

1.5

IaO

.5

0.0

82
geometric expansion concept of the Malthusian Theory. It is
expected that the population data would have a positive.
effect on gross retail food sales.

000,000) 5'1 3
gure

F Gross Retail Food Sales - Michigan

 

 

1 j l o o l l l _o 1 l

1950 51 52 53 5h 55 56 57 58 59 60 61 62 ‘

Percent Non-White - Figure 5 shows a distinctive increase in
the percent non-white pcpulation. As explained in the Jewel
Tea study, it would be expected that this factor would'have a
slightly negative effect on gross retail sales.

Population Density - Likewise, Figure 6 shows a fairly con-
stant increase in the pepulation density of Midhigan and this
is expected to have a positive influence on gross retail food
sales, since, as was previously discussed, increased pepula-
tion density indicates an increase in the size of the local

market.

(000,000) 83

F1 re 4
9.0 r 9“
POpul ation - Michigan

8.5 ~

8.0 ~

 

705 ‘

7.0 -

6.5 -

 

(z) a-.- .-_i._._...._......._....._.._._.,___i..
Figure 5

Percent Non-White Population - Michigan

 

900 "’

7.0 ”-

 

1950 51 52 53 5h 55 S6 57 58 S9 60 61 6f

84

 

 

(Persons/Sq. Mile) Figure 6
1h; r Population Density - Michigan
m -

135 -

130 "

125

120 -

115 r

110 -

105 -

lOO

 

F‘va 1

l 5 l l l I l l I j l I

O
1950 51 52 53 Sh 55 56 57 58 59 60 61' 52

.._ s-‘-- L,, _

Percent Urban P0pulation - Figure 7 shows almost a linear in-
crease in th~ percent urban residents. However, this increase
can be expected to taper off slightly in the near future.
Nevertheless, it is expected that increased percent urban
residents will produce a positive effect on gross sales.
Number of Food Stores - No estimate of the effect can be made
here since past studies and economic reasoning differ in their

resulting effects. While general marketing theory might

85
Figure 7

”Percent Urban Population - Michigan

v-M-”"‘-‘*“F— . y... ..., .. _. u v 7 _,_ 7 .fly._ __..._ _‘

73 '

fififiv

 

O 1 1 1 1 1 1 4 n A A a 1

1950 51 52 53 5h 55 56 S7 58 S9 60 61 62

indicate that an increase in food store numbers would slightly
increase total food sales, past studies in this area show a

negative effect. Additional iinformation will be given later
in this paper to illustrate whether the trend Shown in Figure
8 produces a positive or negative effect on gross retail food
sales. Table 12, in Chapter III, shows a general decrease in

store numbers for each of the five selected counties.

Additional Population Characteristicl- Among the most dramatic

 

1Beegle, Allen J., Phadtare, Hambir, and.John F.
Thayden. ."Midhigan Population 1960, Selected Characteristics
and Changes,” Department of Sociology and AnthrOpology, Special
Bulletin 438, Agricultural Experiment Station, Michigan State
University, E. Lansing, Michigan, p. 7. .

86

changes in Michigan population is its growing centralization.
Twenty-three counties account for no more than one-third of
one percent of the total pepulation. Wayne, Oakland, and
Macomb counties, combined, on the other hand, account for

nearly one-half of the state total. Approximately one-fourth

 

(Nmflnr)
:Fignume 8
17000 f
Number of Retail Food Stores - Michigan
16000 ’
15000 _'
1h000 ’
IKDO '
12000 f
11000 ‘
10000 '

 

0% 1 1 _L I I 1 1 I i 1 l 1

1950 51 52 53 Sh SS 56 S7 58 S9 60 61 62

(22) of the counties have no urban population, that is, no
place having as many as 2,500 peOple. At the other extreme,
approximately one-fourth (23) of the counties are more than
Inalffcuflaan. . "

Population growth or decline is a result of a combina-
tion of the balance of births and deaths and of selective

migration. Differences in rates of change between county

:37
units in a state, for instance, are more likely to be due to
no effects of migration than the effects of natural increase.
Eighteen counties actually experienced losses in their total
nguatime between 1950 and 1960. ‘ 1
Due to the expected inportance of theeffect of pom-

lation on retail food sales, additional population maps are
presented in Appmdix B to simplify the reader’s understanding
of. téidaigan'e population composition and trends.

lame - E‘igure 9 shove e generel increase in per capite dis-
1303331310 lame and this else would be expected to exert a
positive influence on are" eeiee. 'rahle 13. in Chapter 11:,
illustrates how me insane level in lower to: the northern
meaty residents. .

Sales Per Store - Sales per store was included in the trial
mm is"). as e mum“ of market concentration. the greater the
degree of market concentration (per-cart of arse sales handled
by one store). the walls: the potential food sales expected.
also, any market which is highly concentrated gmerally pro»
vides :3 strong entry barrier to any prospective retail outlet.
Tamale 14 and Figure 10 illustrate the present trend, which

is demoted to have a negative effect.

salee Pet Pet-eon - This factor wee included in the triel run
to act u an indicator a: the trend in per capite food me-
ituree. annually. en increase in food eelee per person
would have e genitive effect on total food eel". Table is

(S)

2300

2200

2100

2000

1900

1800

1700

1600

19X)

1h00

1300

1200

1100

 

88

Figure 9

Per Capita Di-;osable Income - Michigan

0: 1 l 1 J 1 1.1 L 1 1.1 n

1950

 

 

51 53 SS 56 S7 58 S9 61

Table 14. Gross Retail Food Sales Per Store.61
Baraga, Missaukee Berrien Ingham' Wayne State
1951 93.9 59.8 109.3 ' 141.5 109.1 143.9
1953 105.7 63.4 129.9 ' 168.5 127.3 177.7
1955 117.5 67.0 150.5 195.5 145.5 200.0
1958 135.2 72.4 181.4 236.0 172.8 241.3
1960 147.0~ 76.0 202.0 236.0 191.0 269.9
1962 158.8 79.6 222.6 290.0 209.2 290.2

 

62

89

(3000) Figure l0
3m3*r Gross Retail Food Sales Per Store -.Michigan

273 w
250 *-
225 -
200 ~

179 ~

 

150 -
12 S ‘-
100 -

é

 

O n I L I 5 J l j 3 l 1 3

1950 51 52 53 51. 55 56 57 58 59 60 61 62

and Figure 11 show an increase in per capita food expenditures.

Note, however, that this data does not necessarily indicate an
increase in the quantity of food consumed, but' may be the
result of increasing food prices and/or increased purchase of

the higher priced foods.

($3)
th

1:30

h20

h10

boo

390

Table 15.

Gross Retail Food Sales Per Person.

 

($)

 

 

Baraga Missaukee Berrien Ingham Wayne State
1951 206.40 168.30 279.90 268.60 276.60 365.00
1953 217.20 174.90 291.70 283.80 287.80 397.00
1955 228.00 181.50 303.50 299.00 299.00 403.00
1958 244.20 .191.40 321.20 321.80 315.80 433.00
1960 255.00 198.00 333.00 337.00 327.00 431.00
1962 265.80 204.60 344.80 352.20 338.20 406.00

Figure ll
Annual SalesVolume Per Person - Michigan
TI. ‘ --~* ~ ,
t

 

58

59

6l

 

62

91
In emery, the previous dismssion found the possible
determinant factors to mibit the followings.

 

29m W
Population Up 4»
$5 Hon-white Pepulstion Up ..
Pogulation Density Op ~ «5
2% Urban Papalation Up 4»
#1 Food Stores Down 7
Per Capital Income Up ' «5
Sales per store . Up ‘ ..
Sales per Person Up e

14111.net: manna REGRESSIOH 15.11.1519

19811:: new

New tn“ the components of the possible regression
eqzmtion have been disclosed. the sctusl test con be emanated
and further progress made towards the final selection of varia-
813108.

In trial m #1. es expected. negative ooefficimts
(bi) were found for the following variables: Bow-White
repuletion (:6); Sales Volme Pet store (8,). Although not
anticipated. e negative coefficient wee she found for the
factor. mates of food stores (are). the remaining variables
were preceded by positive coefficients. indicating e positive
effect on gross retail food soles. es wee Wed. Boomer.
the magnitude and the significance of each factor could not
be metely measured with the use of the test results. this
was because of the extremely high degree of intemsreletion

 

4.....4' .1. “4.. A. “AM __ M .1; AJ- _—-‘ - ‘a—A A
__.. m w w i __;I"

wr‘ “W , 1 —v— V

‘0 Increase in factor value increases gross retell
food sales.

.. increase in factor value decreases gross retail
flood selee.

92

bemoan eone of the varieblee. nearing the existence of e
singular matrix. which ie mathematically unusable in thin;
type of calculetion. nigh degrees of interoorreletion were,
fomd between the following eete or groups of variables. in.
Meeting the fomulel'e inability. to eoourately attribute, an
effect on Y to either of two or more feature.

I ( ) x Eon-White Pomletion .99$-.999
(x7) 73 Urban Population
i ) Population Deneity
2) Population
1 l
i l

11 Per Family lnoone “Rafi“; 990...”:

Per Capita Income C

In Group I. all five oomtiee end the etate almond
high intercorreletiooe between mletion end the three
population composition ohareoterietioe. Thie ie not unusual
einoe population data, alone. directly effeote the veluee of
the three moment» Thur, it one decided to drag the
three papuletion ohenoterietio variablee from the equation
and use only papuletim.

”m Grow I!“p per family end per «pita insome were
also found to be high interoorreleted. Thie, eleo. eee not
totally unweoted eince average family eize within the, state
doee not fiery greatly over time. Time. per. family income was
also dropped from the equation. leaving per capite income.

Following the above edjuetanente the equation now
reads an follower

Y "' ””2": ’ I’3":=I ’ ”4’4 ’ ”8‘s " ”9’9 5' “a

93
This «motion ”I then used in the calculations of
trial m «a.
W' saw
no in trial run #1. the following two groups of vari-
ablos were found to be highly interoorrelatoda

I (:2) Sales Volume Per store .993-.997
(:8) number of Food Stores
1: (:3) sales VolIsae Per Person ‘ .99.~.993

(x9) Popoletion

Again, Groups I end I: vere more or less expected
since sales volume per store was directly relsted to the
number of stores end eeles volmne per person was directly
related to pomlstion. Mil. both Isles volue per store and
par oepits were elinineted. leaving the following equation
to be calculated in trisl run #3.

Yeseb‘r‘ebexaebgfieua

The results‘of trial run :93 were similsr to those in
Porter's study. where population (19) use found to be of
no: greet importsnee. both in magnitude and in simifioonoe.
that it completely ooooeeled soy relationships that might
have existed between Y end per capits income (2‘) and/or
amber of food‘stores “a”

as previously mentioned. the relationship between
population end food seles is primsrily e bio-physical one,
with mntribotes extranely little to any eoonomio discussion

9‘

that might be of interest in this paper. Therefore, following
the procedure of Father. the papulation factor is recognized
on being of primary importenoe and sdjuetumats are made no -
that other relationship can, appear. This edJuMent simply
involves dividing pomletion (3:9) into groan retail food
solos (Y) to derive groos retail food sales per person. pro-
viouoly coded as :3. w A _

The equation that eppeors one follm for the fourth
trial run. A? ' f '

n: I e e 1341‘ 0 base 9 o‘

wheres at, e I 0 gross retell food sales per person
39 ‘ .
3‘, ’8 e no listed under Trial Run fll

Boom.” W‘

The results from trial run #4 overs much more condo-v
eivo arming no major trend interfermoe and only e nominal
doom: of interoorreletim. Both factors "0‘8, were found
to have to effect on gross retail food sales per person. Hou-
ovor, the nmitude. direction and significance of this
effect differed between the five counties end the mu. The
rooults, ss are shown in Chapter VI, were considu’od valid
enough to suggest use of the following equation for all 83

counties 8

100 (a: ) e e “+12 figs-112%: loo 9)}
r}: “Sq
5m

:- groee retail food eelee (previmely 3n)

n food ptice indent (previously 1112)

:- papulation (pteviouely x )

I number of! food etoree (pl‘viouely )

e per cepite diepoeeble income ( ev sly :13)
- ooneueer price indent (previou y a”)

II countiee no. 1-83 and state

:- yeere 1951-62

there:

‘“ “Jui‘e'd'uu

Bed: equation empleiued the verietioee in per oepite
grace meil teed eeleeby mtyeveecheceelveyeex period.

W!

aieee the feeder new elee he lamented in vetieuooe
Matinee-ell eebeeveellyeete. emee eeetieeel
Myeie eee elee emcee end e eieile: mingle linen:
Wu eels-tion In need. However. in thie Win.
theveluee e! menthol“ eppliedeo eon: county to: e
givenyeet. mmmunammeeimmty. "in
the title eeelee. In ehieeeee. the minions undid ere
time new We new then one use.

mmuuWumm toeeecholche
twelveyeueeemeeueeeeveilehle. Moment-uno-
pieiue miecieee in pet oepiee retell teed eelee along the
83 melee he end: you 1951-62.

The mericel teenlte of both the time eellee end
ozone eeceienel undie- eee peeeeeeed end interns-end in

Ma Vie

9 6
F PDJECTICKL' P303231. 5' C R EXI'LAZUXI'O KY FACTORS

Coefficimte. alone. are not adequate information for
making projection. Also necessary. are «Heat» 0: the in-
dmdeat variable. By coming the relationship tound in the
time eeriee enalyeie to remain oonetant over time, the esti-
matod grace ealee can eaeily be calculated for each caunty
if, and only if, accurate projected values of the independent
vorioblee are included in the mmtation. Thur. the valueo
of the two selected independent variables must now be ecoaratn
oly projected into the future. Since the exietence or
factore effecting the values of the two independent variables
ie not of particular interest in this paper. extrapolation of
the valuee mine time ee the determinant factor. eeene quite
euffiicient. Figure 2 in Chapter Iv will illustrate this tech-‘-
niquci the objective being to compute an equation capable o:
accentely projecting the value of an independent variable to
a given year. The followiaq two eimple curvilinear motions
were canputed for each or the 83 countiee and the state. as a
whole.

3‘ O cl 9 b413,: e 2343:;

"s "’ '2 * ”51":- * Itn";

Were: a!“ II umber of food storee

it, C per capita diepoeable name
I? I you (time) 1951 e '51.". etc.

Emerical resulte of these equatione and their inter-

probation can be (and in Chapter VI.

97

a projected county powletion is also. necessary be-
fore the projected per capite sales volmne can be transfozzzzaed
into projected total county groae retail food sales. However,
ample geometric ertrapoletion will he need for this rather
than e regreeeion equation. The geometric expansion was
found by Dr. Thaden. Demogrepher at michigau State University,
to be sufficiently accurate. Further discussion on this
topic will be timed in Chapter vn.

CHAPTER VI
I"; ‘liTETIO’I REID MLPLYSIS CF ODEYFICIBZ‘IT ESTII‘EATE3

Time series Hultiple Linear Regression Equation:

Preemted below are the time eeriee calculation
resulte tor the five eelected countiee and the etate or a
whole. Note the variations in the reeulte betwem counties.
amplete enelyeie or all equation ie presented following
each table.

Equation used:

 

 

 

' (2)
e ml x‘ +132 {100 "6 10 e
sq 4
”q a zq 1:
Table 16. Time Series Equation»
3:
Code (Igtegifi ‘73):
Comty e Corr. a b b 2
Efraia , c :- . '6 . “t: e- ~< Xe". . ’h‘t' .: 3L, .
settler: ll «8133 .132 652.4423 ~.3563 «1.268 «1.7063 1.8967
Ingham 393 c.4726 .353. 335.8499 «3604 .0675 4.5495 1.3432
1519531113” 57 .10“ .828 63.4942 ¢7e‘910 e2578 *2.9356 6.4352
Wayne 82 «.1455 .293 122.7371 .0097 .1296 1.2331 2.3992
State 8-4 «597 .053 250.5143 .0016 .0553 .3705 1.4349

98

99
Inter-correlation varied among the five selected

counties from a high of .81 in Berrim to a low 0: .10 in
rcioomzkee County. Generally speaking. only Berrien Comty
had a high mough interact-relation no that no accurate eati-u
mate could he made ee to the relative effect each independent
variable had upon per capita deflated gross retail food solos.
{the state, no a whole. had on intercorrelation of .60 indicat-
ing a tendency for the analyaie or the etete to be leee
reliable than an enelyeie of an individual {3th within the
state. _

32 or ‘52 repreeent the percent of. variation in food
sales that wee “explained hy'2 the two independent variables}
Table 16 ehove Baraga to have the high 152 eith .85 and Berrien
County the low with .13. Again. the etete enalyeie move
poorer reeulte (32. .05) than that or individual counties.

Map 2 ehowe the county reeulte o! the entire etate.
Generally. there are greet "mm. in 3’ throughout the
state. vith the only noticeable pattern being in the meth-
veatere portion of the lower penineule. where a high a: is
evidmt. Other than thie. no relationehip la ehouo between
geographical location. papuletion. income. etc.

A‘ ‘ M L A .‘A - m .A ._ A A M ALA-A- AA —--

W ' w W ——-W W fl "— W.— W v-r-v

hi2- nz adjueted tor the degrees of trudge. '

Q'Explained by“ in ueed rather than 'caueed 131:“
since only economic phenomena can actually “canoe” these
voriatione.

10.0

 

 

 

tg'VPILLQLMuo \ a v men 0 .

 

  
  
        

WISCONSMI

 

 

 

W"?

 

 

 

 

 

State ' .2
% 80-9
§ 60 9
[DIN 140-9
20-9

C: 0-19

 

 

0110 ea

30 80 90 60 em:

"-2-“ \
fj/F/IL\\\\\
// \ ‘

 

Map #' 2

Coefficient of Determination

 

 

 

 

 

 

 

 

 

" ' /".§‘ \ b
I. 7 -/l
'\ M f‘cuu v u ..

        
   

 

/17c«muvw\m

)16//T‘ts

\\!MON 5T\i: .ALrw ~_

'm—e-ow

Q62 \ g-EE.

 

      

 

2] \ \‘\)' __ ‘~‘ .
313 I ._§_L§\.&~\g.j/ ° __[‘_..__.. h ‘“ “"4
mtmflin 'f‘mu (IMAM ,
--—.-_._18_.._::.-$ ‘ y 3!“. 6!..1‘7 ‘ .05 ‘
:i'“__‘\ K I “”5 Milk?” .__....|..
.9“ W qumuo \q'iicxs aim ‘ if" ‘ Ayflf
‘_ l“? §:\V\.B \ Tr
\ K!

   

%\§

3050“ !\\6 and»

W!

"“ 3‘7\° . 7+
LE halite—:— “P":
k 039—- 4‘1}... 5 '0'
fume: [Leon mu “WEAR \ O

--—-J W8
fiflfil‘i} .0

u Poeu'n. .aostm
meuees {VS-’9" a

INDIANA . °

 

 

 

101

The ”a” (Table 16) represents 3 constant 1n each
equation and lto value indicates little other than the inter--
cept o: the regression llne on the Y or vertical axle.

The “131' (Table 16) represents the dollar magnitude
of the change in e county's total deflated per caplte retell
food oolee associated with 3 one unit Change lo ttmt county's
metre: of food storee. naming all other lndependent vari-
ables are content. Table 15 shown vulntlone 1n h1 1m #13.
(decreaee of $13.) in Baraga to .009 (looteeee o: 3.009) to
Wayne County. The etete, ee a mole, ehove e ellghtly pool.
tlve enact. flap 3 above n distinct pattern of. bl“

Map 3 shove e aletlnot pattern whereby the negative
ooefflclent le proalnent lo the northern portmne of the
otate end the potluve effect more noticeable in the eouthern
oomtlee. Alto. the oegetlve effect to much lerger 1n the
moat mrthexn oountlee. end deoreeeee in magnitude m mov-
ing mthmrd. Thle negatlve coefficient indicates: thet on
store manage decree“. per ceplte retell flood ealee increase,
while other vex-lob}. ee ere cement. For example. to Baraga
Cmmty. no the who: of food etoree to the county decreosea
by one, annual pet ceplte denoted, retell food eolee loci-ease
by $13.90. however. to e eouthero county like Wayne, en lo-
cmee in per ceplte food eelee 1e pertlally explained by an
increaee lo the amber of. food etoree available.

An explenetlon or thle pettern my be as follows.
First, tho-e food etoree going out of huelneee 1n the northern

102

 

 

 

 

(OPII‘fiIU DV 3‘" p g"

 

 

 

 

 

 

 

 

 

 

J .
6M —. “:9 ~
on: - . . g ‘ - . I ’606 ""
'sw .--+--L.- 217‘ ~ - 530%
i I ' ./' o ‘ . .
MEMMlutti- l '8 0 w E
WISCONSIN b g \ - cuuovone
- .73 ,A.‘ o N ’2’ 9 .936 a:
lumen: ' Q x V . ‘ ’7°5i'sao
6.17"“. -___'.._:5-1_8}...-
mm, mom- .mm
0%“ :19 mm 'Wmoo WWW" ,l
53‘ -7.8 1-6.02!-15;1!_.f_°.7__-
EL? km}; f3fififom ‘MONA
‘ ' oomvmt' , ' .
_:§:6j_.6.6 é-lh.9!-12.l! -10:_§.:°.6i
“331:4 wfirTnE {in-15332? . 55:35:; iofiiw resent-)0
23:1;23-23-h!-7-h9! 40-14%," '
MASON 1 m.— {oi—€65" {"5 _éu"5'@&:' W .
--'-‘.._..-:__._.» . .t- W .
State .. .001639 “WM! unwevoo‘uuosu%\ - mowi _ a)
-lo93le 2 32.146 $4.12 ‘ . '“WW‘ 'muc'
o "’0 30’ s ”.rfi'_’ '
'2‘; fihfifigioufia‘r‘mumw L‘! 4.38%. ’1'28
‘\\~‘\ . . . ufimggfia?“' -2.1?'1'52i "31‘29..L_r_3“"11
K0 : Foaltve Store Effect “,3 \\9§\ . «<"5‘mm‘ mun ._..._..
. . m\ \mzflmar ». 2%} 02):— gm“
' 'A \V f. -2e3 ‘9102
Negatie Store Effect ”\K i'1'9ht39hé&®_mm‘—Emaq
. uni». 'mm 'Tsitou'Tioum. “\mosw «201$ “:66
4.21; 2-1.81i-m51i -.26 13‘
ememma‘ attai- were; fie.mtu.w‘f{m§
‘79-..321-0991‘: "e63 i'eOh6 r'1e056 \‘1 CANADA
-—--eeL—-_. ' . 71
ms smosarfi"""“"'"‘“"" ' form
.3 I lumen «we»: . ' \_
.e?mqj.-l.lLl.l6i-'3s ! _.66t\ {Q
“ m“’“""""7“”“ (“am 'Fafilru'm-wmé ° «7
INDIANA 5 e -

 

Map#3

‘ Coefficients of Food
Stores Variables

(bl) \

 

 
   
 

'7 -13.21['

-3005 Lo... .-

 

 

 

 

w x a t:;:;:\"l'.
we I ? °'
[-5.314 mm“ { CANADA

0

 

 

 

 

 

-m-':'"T- ‘W'mfn‘: VI" 0"

e-vv

 

103
part 0: the state are the mall cutlets (country stores)
located in rural arena. Those atoms remaining in Operation,
tend to be located in the more heavily populated areas of the
county. These stores can etill be found in the shopping dias-
trict of the small town (lose than 2. 500 people). nan}; have
moi! into a new shopping canto: which may nerve the entire
oomxty‘e pepulation. negardleee. tho-e remaining outlets can
he found in an area outmoded by other: retail establistnnenta
so they might take advantage of the increased drawing pmzor.
therefore. cmmty midmte can trove). to one major retail
trading area and porchaee many different types of retail
goods. Such an axea certainly poeeeeeee e larger motmt of _
drawing power emanated to W atom. This would coin-
ciao with the findings of. Bernard Joeeph LaLonde. previously
mentioned) when the existence of e shopping center etoro
maple: had a poeitive influence on delving power and per
oustome: aalee.

Seoond. those etoree remaining are generally the
large aimed outlete able to uhihit 0: stock a much greater
hunter of food promote. Homolly. an the availability of
dimeified food products increaeee, so doee the per capita
food ealele

Second. tho-e etoree maining are generally the large
sized outlete able to «hint or etocx a much greet“ when

 

‘ A...‘ . H A A .‘r‘ ‘4“ ___-.._ .e.._ ,
‘v—‘w— W7 T m , w W W W w V'— Vvv‘v

Imahomle. p. 120.

104

of food pxoducta. Romany, ee the availability of divuaie
file-3 food producte increases. so éoea the per capital food
sales.

Third. the northern oountiee are not only experiencing
a decrease in the number of food stores. but also an increase
in the mt of annual tourism. Tourism ie a factor not ina-
cludod in the computation of “2:1" and therefore producee e.
bias due to thin omitted variable; Since en increeee in
tourism normally would cause e rise in food eelee, thie trend
toward increased tourism in the northern emmtiee would tend
to inflate the effect new attributed to e decreasing ember
of food etoree. Therefore, the “1:1“ in the northern cmmtiea
would tend to be large: compared to the southern countiee. w

Fourth. in the mthern part a: the etate it ie such
more heavily populated and the existence of large modern shor-
piug enters are more men. In general. the well mtry
state had been eliminated prior to the ebeervetien period of
1951-62. The email positive effect tuned in some of these
southern counties may then be attributed to the greater
availability of more expmeive prepared (code and other food
producte. 'l'hie euggeete that the 'etore ettett' will be.
positive in more counties in the future as more are“ advance
to the present etetue o: the eoutheuetern Michigan counties.

The mall “tire effect derived from the etete. as
a whole. ie attributed to the heavy weight. pieced by e mty
such as Wayhe on the‘etate date. For example, 50 percent of

105

tha state's tatal retail toad aales occur in the Detrcit
metropolitan area. consiating of the three cemnties - Oakland,
I-Iayna, and macaw: two of which have a positive b1 coefficient.

The “b2“ represgnts the magnitude of change in den
flat-.321 per capita food sales attributed to a one) unit change
in cicaflated per capita disposable tame, manning other 121-
c‘legandent variables are constant. For example. in Missamcea
County, an menus at $1. in denatod pot captta disposable
meme would increase deflated par capita food sales by $.25,
assuming; other variables at. constant. Table 16 am 132
varying 1m .23 in Missaukec to «512 in Berrien Comty. Que
malt?! normally expect to find a posit“. maummtp betmm
income and food “In nine. an menace in mean. level. memes
pnaaiblo an increased upgrading on :11 items, including toot!
gamma“. Whil- analyzing the unto, an a whole, a positive
coefficunt (.05) was tound.‘ Normally tfln would b. unlvarsalu-
1y amlted to and!) and ovary smut of flu abate. timer.
as flap {I no explicitly illustratga. thin practice mule: seem
to be in error. than analyzing tho atato on a enmity by
cmmty has“, an and: not only variation: in the magnitude
of the coefficient, but also in the direction of the effect.
For WP]... nap ¢ chow: that 34 of tho 83 counties have
negative rather than pasttlvo coefficients.

Thu. negativg coefficuntl vary from «.003 to «.126.
Those counties showing nogntivo relationships com to be
evenly located tin-oughout the stat. with no Manama pattern.

. .106

 

 

 

 

SWEERA

  
   

 

‘ Xmaommn

(or m:- m iLnuo E39“?! Sonya“ Sungaggm-TK

Map # h

Coefficients of Per Capita
Disposable Income Variables

(b2)

 

 

 

 

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_ x ‘ \ \
“L" \ '"OOBSI mm "15“ \n\.
.o a\\ ‘ Q
\ o./"o 3 vb
. ME 0M.nu;\\\ I 78 "g“icgv Yo» ‘
Wiscomsm \\;\&\ g , \\
.’E‘: V. \K [ratsook
nun um . ‘ \‘
§ .'..02---\ u\\\
NW iJAONTVO

ANTS!“

Max.

\. KMJ‘ASKA \rHM’NORO! “600‘ l ALCOI'M

OVStGO I é."{rh\\
"‘“ffl Q; 0145 __!_\ WK

"'I‘h on "was:

3931;:- :.12.é- .021i -.O°Sé: 293-21’-.01\
may“! WIIJWWJ §OGEMAW to
-.068 Tori-.001 [\Qéx -013!§‘\§\\

MASONM foggiou CURE it?“

  
   
    

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W-.OSB

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Stat- - .05526

é‘

I.--.Il.0

  

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151' .KCLAIR

 

 

:cu-Tfi KAS'T‘ “Qt-loch 17 \
332M ‘ , ‘ \,
~4- ‘\ \ ‘~\\

-T‘ *.

 
 

iainnv
-.Olé\ :\.

.G-J-:|T.

 

Positive Income Effect ‘
-001

 

 

 

\Ekflfigfl

 

 

 

Ne;.tive Income Effec . ‘ LKD .
.12 Ems i‘1503\‘>“r influx
smmzu' -.021 -.0h1 i‘-.126

9

O

0*

u POQK‘SI. Joan. ‘Cknnutf F3“! IGCL l'tul‘"
O

INDIANA

Wax. ‘\

'IWJOI

Q!" :o no do so count:

 

 

 

 

107'

It is oxtzonoly difficult to explain why lo certain
axons of: the state an increase in per capital food solos mold
ho attrimtecl to a; decreasing per coolto loco-no level. Ono
possible wlanatlon may ho that as income levels increase.
the pooplo decide to gnu-chase -a high cost curable good own
no a no: car or a house. The nubsoqmnt loan repaysamts won
reduce the portion of lncom previously used for food; porn
dmoon It 1: my opinion that thin phenomena may be apply
cable to a mall portion or a oounty’o population. Mover,
its ottoct wound to too mall to alto: tho dltoctlon 0: on
mtiro enmity. It 1! theretore obvious that amltlonal study
13 noodod in this am. .

mbl and Tab: on molt-own“ of tho atatlotlcal
oiqnlflcnnco ot the two lodepondent variables. A: previously
stated, than two melopmdont variables were ooloctod as ho-
ing the two variables “moat“ almltlomt rather than whether
or not they mo 'mtlatlcally' significant} fimrtholooo,
it my be of mo value to coupon the «4 levels, at which the
variables are statistically significant. among oomtlosc
Table 23. also in this chapter. provides the twolm from
midi tho statlctlcal algnlflconco may to dotlmlnod. to:
mangle. both indepondmt variable: on otatlntlcally algal-
ficzmt for Mlosaukoo county at .02 level of ac . but only at

A __... M‘ r . A A. .AA—A. #.

__4 ”A
m w—— Yv-vr ‘ J ——————v w— , W W _._‘ T W W

’sutuucal olgnltlcanco rotors to tho 2.1.1:th o:
the: hypothoau that tho valuable. havo zero effect on retail
food Gala.

108
the .20 level of .c for Berrien Comzty. Again. it is mticofl
that both varieties are generally not on significant to: the
state as they are for on individual county. Map 5 illuo'troteo
how the value of. 'I'Bbl and T3152 may vary wrong the 83 counties.

9:33.151, there is no noticeable pattorn in those values.

Cross Sectional Multiple Linear Regs-onion Equation:

Tho amputation o: voriationu in "can toad Delta
among all 83 countiu to: a given you ptoducod the following
The same tom 0: oqmtiou mod in tine tori“ cala-
oulations woe applied to the cross ooction analysis.

rooul tn.

 

'i‘oblo 17. Cross sectional Equations.
WWI—W
Year (1:33:23. E2 A_ a w b1 _1 1{"52 * rib). 1:832 __
1051 .3x32 .457 46.0735 .00 34 .1327 .4447 7.8035
1952 . 3703 .1 30 201.155: .0139 .0716 1. 3906 2.7215
1953 .4504 .157 196.8754 .0108 .0907 .9742 3.1433
1954 .4604 .105 233.1527 .0147 .0671 ’ 1.1974 2. 2341
1955 .4320 .111 221.9543 .0130 .0694 1.0308 2.4209
19:36 .4370 .107 236.4623 .0140 .0745 1.0070 2. 3827.9
1957 .4019 .073 253.0069 .0153 .0585 1.1175 1.3337
10 33 .460 3 .008 314. 4194 .0191. .0062 1. 3381 .163 3
1959 104557 *0003 341.6622 ‘ .019" ’001‘3 102950 “a 333
was .4651 «.014 333.5122 ‘ .0142 .3027 .7696 .0754
13:31 .3351 «.003 310.6831 ‘ .0134 .0120 .9111 .3327
1052 .3819 «on 359.1792 .0156 -.0302 .8836 «8609

10.9

“I

 

 

swarm . Map # 5
A -.16
oucmo

Significance of Number of Food Stores
-5, 6 and Per Capita Disposable Income
-,3

 

   
    

r. (obi)
H A.

I 1.577I I ____~ ITO I g .
HIE—55L- “I "giés III-GE I III :828; .cumsm
I- -2. 29 I---'7 I

-2 o O
oxcxmsou I h— Iscnmcnm

 

 

 

 

 

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MEMMINE‘I I '
wxscoxsm -7 0'?

..... "§?I 1‘ i

 

-212“ "150%: 7
‘ 5’ ”j.- ' "1.033;

IMORENCV I“! ‘
o ANIRIM I0 013360 I
Ll! RM!

2% ; -E9fi%1'§t§3I :3dIII. 2637

KALKASKA 1M“;fiI-m6

ALCONA
6w9eIcomAvus¢I _h OlI-S 81I'2065 SI-7,88
ffikskg “EI; .hlSI .___1_. 30.-. 4.91 @912.

mm MI'TsEAuTuI ‘IM’; “foccgaw 6Icogc032
“I
-11. 6' -2. 98I-1M11 -1
j'lélI: 03__:_L_I6___. h3__I 91.292" 1' ’
94:30» oscaBLT ELI: IGI-ADWIN‘ h 9.?”
-7. 10-2. ‘510—6. 35 “3 27 .1052 I A1 .4030”
-.§£L3.76I.5880I-1.h1.336 .x;

own I newAmOI '''''

macs“ martian mouuo- -1 23 -1 2

-l. .16I-,23 .44. 7 I178 I-2.2 .9 I 63 wfifijifit’dc'

State a .3785 cTBbl '2925 6. 73 I__ oSSL-I. .1280 _."___-_I-_L_3l.1- -- I-2. .95 I-S.89
"mmAw _

.1, . T8132 1. 1-1E mf'fw: EIWWTI _1. 61 . 1. oar-11. 856
uum:o§,xmL I3 207I -2 gé 110256“

01;... I1 166

' IC‘WOI Ismamss “1va _3 2Frc3‘1538
"38I2 2312!... 4441.121;th
'17; I3. ii hh66I._2_858I1 918 tall-:31 582

_. W'L'T «ng ragga“;
name may ”e310“? Imam- F-NWOSTO -. 9213
-l.608 I-l. .515! -.?~23I_1 SSI Fivh287'1. .2231 I 10’
.1632 -.133I. 276°IL 3343* 1. 9&5! _....c

91;: 38%??? 24?-3?¢.¢Ilf§—1fflo-—I.mafiifl_fik¥lt

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3311:8I.1h37I0530 I-l 13 I.I.2019 I
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2 39 ADA
T H ''''' 4- -r- --r! -.
”“3"?! -°32§I:I::8§883r° ”Lama-{I “5:531 I.3°'é“6°7
-0 -0 -2 61.02 .9680. .779
roq'n'In. .JO‘I'H—‘n rum! [uo‘r .5; .5733}; I:

'00 g—I-‘O' Oh ”—Fk.;
mourn m" I” ' '

 

 

O ‘19 20 I. 40 ’0 06 Ill!"

 

 

 

110

The cross sectional analysis was conducted to determine
what effect, if any, the number of food stores and per capita
income level had on variations of gross sales among counties
in a given year. Therefore, any discussion must be based on
years rather than individual counties.

Intercorrelation over the lZ-year period remained fair-
ly constant, ranging from a low of .33 in 1951 to a high of
.48 in 1956.

-§2 followed a distinct trend over the lz-year period.
In 1951, over 45% of the variation in gross sales between
counties was explained by the two independent variables.
However, immediately after the year 1951.32 decreased to .13
and then slowly continued downward until after 1957 the two
independent variables were found to explain little or none of
the gross food sales among Midhigan's counties. Figure 14
shows how after 1957 the equation loses all its ability to

explain variations in the dependent variable.

 

 

 

§2
Fi e 14
. so - gut .
Cross Sectional Equation
E?

.hO '

.30 "

.20 '

.u) '

O l A l L J.

1950 51 . 52 53 Sh 55 56 57 58 S9 60 61 ' 62

11].

£0 explanation of this trend is reaaily available. ‘Uow-
ever, it may be attributed to:

1) £3 insignificant éiffierence in per cap ta food sales anang
counties to: a given year.

2) an insignificant éiifiezenca in the number of sod stares
of: per Capita incmm among counties for: a given. year.

2) the two indepmctant variables have no effect on the vari-
ation in gross food sales ‘99th counties during the 19- 57-62
pexiofi.

a.) 1“: combination a: 1, 2. or 3, above.

5) Unknown factors.

Data used prove numbera 1 and 2 to be untrue in this
particular etudy. Therefore, «lithe: :1wa 3 is true ans/or
there are other factors. still unknown, which do affect u-zeae
variations. Regardless. results for the yeaxa fallawing 1957
must be interpreted as an explicit inability of the tun independ-
ant variables to explain variations in grass sales among
wtmtiefio

Table 17 chow both bl and b: to be positive throughsut
the: 1951-51 period. The major fact mt}: noting. with regard
to thus results, is a poaitive 122 which is also less than: 1.0
m»: therefore, illustrate: that Engel's Law does. indeed.

hold mm. in Michigan mac: “static" auditions. For magpie,
in 1951. a "b," of .13 indicates that peeplo in county A,

" V w v... _.fi rt...— ww _......fi “.7— p—‘

1usuatm: tofu. to dung” dating a loyal puiod since
data and are moi-ago our 1 year.

112

twaivirxg a $1.. higher per capita diéafnzable iguana than til-3
{ample in county :3, viii Spend $.18 more on par capita fear}
Eangfliturea than those petunia in County :3. ‘X‘I‘zuz‘eioze, if
the people in both comztiaa were oziginally weanling 3:“: of:
their dimaable inmme cm food, the higher income peagle in
Cozmty A mu amend a 10m percent. of their income on foam
than do tha {160916 in County B. In easmce, Engal's Law
KELLICE, inc-.9962, apr 13! to the state of I'ic'xigan under static
CGnditiOhs.

'ffsbl and Tab: vary among the years 1951—57, however,
ca flat; ed per czzpita éiaposable income in morn significant

tam the number of toad atores in each of the seven years.

Shy-la Curvilinear Regressiafi Equation Coefficiom Estimates:
'Iho tanawing two equations mu used to project the
wine: or the two indepmdent variabloa. lumbar of food
storm (:4 ) and par capita diapaaahle incano (:5).
2 4
1’ ”4 "' a1 ’ ”41 ‘1’" ”42"?

.. 2
I“ "s " a: ’ ‘351 "r’ 735232-

In, the amp)... projection at the saint: of £13. inch-spear}-
am; variables, T5131. 13 than: a E2 tagging from .239 {per I
.czztpita income) :60: Baraga cast}! to .996 (umber, of food
stores) far way‘n‘io Cpunty. caudally. "52’. me .600 or
higher, indicating that. «manage in mambo: oz toad stores a:
' mama levels tend to we in clean approximation with time.

113

’1‘ 3.119 19. Single Cur-rilineur Projection figuacion £01: 1116131116
Love). and Number 02 food Stores.-

 

_w “23“" :2 _ _. 441:? :11“— :2“ #14:):1- A z
Baraga. I .884 91.5339- _ -2.1880 .0144 3.9663 .7175
11 .239 26520.9579 .995.1z13 6.9959 4.9619 1.6796
Bertie-'1 I .992 940.410! 015.883? .0720 ~2.G:‘313 1.0661
11 .953 13471.2333 «63.7755 4.5762 ~4.o1674.4347
inghzm 1 .965- 1215.9961 ~14.5229 .1436 4.1.4349 .9632
11 .742 415373656, 431.3574 «6.4815 1.5132 «1.3616
i-iiosawcee I .363 151.6450 4.5118 .0380 «1.4173 1.3486
11 .133 74.160: «6.7050 .3174 «or; 31 .1565
some 1 .996 215614.531: ~367.6108 1.4146 -2.4599 1.0664
11 .649 4.867536!” 702.7629 -s.9161 1.3164 4.2943
state 1 .617 ~13335.$4$9 495.2266 3.6446 .9?E;2 «.6569
11 .965 249.1592 -6.4433 .0722-1.7624 2.2323

_..1‘. - ._‘ A A M 1 A. A __‘__‘ _ 3.. _ ..

_...-— www— WW w _.v‘.

*I=II rumba: of food stat...
Ila per capita disoouhln income

since timo was used. as the independent. miabla in these
eqmtions, tho magnitudooz 1:1 or 1:2 presents little infomation
for ooonomic discussion.

Again. the tender will notice a quot deal of variation
in 'mbl among the :19. selected counties and tho atato.

1.14
121624914 1313.92.49: i? to 3 eat ion 4
in order: that the projected food sales and income level
435,..129 could be graperly deilatod. both the food price (F.P.I.}
11:13. the consumer price index (C.P.1.) had to also bi projoxéd in-
t') Elva“: year. - h ' t ’
EQULti0n3 noojs
1114 1:??? al+b11xi+b1214§
:2;- “C111. “2‘1’21‘1' o 112sz
Both F.P.I. and C5351. projection. or. applied to each

of: the 83 count“: and tho state.

Table 19. 5.13.1. and 12.1.1. Index Projection Equation...

 

$116914 fl: ‘ I ‘ b1 ‘ b2 15%
b1 ”2

. _... 4—_—-‘_ A“ “

_W m _... W‘— F—vw

1:1(F.p.1.) .766 £18.3032‘~11.7335 .1122 ~2.0039 2.1652
1 (9.9.1.) .965 249.1592 6.4439 .0722 “1.7624 2.2323

-‘A- _....1 A A $4... “— ._._ . _.‘h A“ A . 1... _.._ .__..__i A — __

V _w w v...— w _...—W W y—w—w W “— v——-—

Generally speaking. an of the equation remit. preamb-
efi. in Table 19 indicate that tho pmjoction linen fairly
nooaratciy depict. tho trend- of.' both indexes over time. The
resulted! projections are presented in Table 20. Figaro 12
99:3- Figuzo 13. The roaéo: should not £911 to note the use of!
1950 as tho’baeo period. Thurston, 4111 food 99199 coo income
data are donated to reflect changes in both tho physical
«:1an of food and the real purchasing power of pot capiea
incurs. a. oompoxcd to rolationuhipc ”ti-ting in 1950.

115
Table 20. C.P.I. a 1.7.1. Index Plojoouonu.

1 I .

3.9.1.
1950 - 100.0
1951 «- 111.3
1952 «- 113.3
1953 «- 111.6

. 195‘ * 111.3
‘I 1955 .. men

0.9.1.
1950 «- 100.0
1951 ‘I- 108.0
1952 c- 110.4
1953 - 111.2
1954 - 111-7
1935 «5 111.3

1956 .. 119.5 1956 . 113.0
1951 . 113.1 1951 - 111.0
1959 ~ 119.9 1959 «- 120.2
1959 . 117.9 1959 . 121.1
1960 «- 11s.: 1960 - 123.0
1961 - 119.7 1961 - 124.3
1962 . 129.3 196: «- 126.1
1965 «- 129.3 1963 . 134.:
1970 - 145.1 1910 - 150.9
1915 «- 168.3 1975 - 170.9
1990 «- 195.1 1990 .. 194.4

 

AT

ample mum.» nos-cum of 1mm. Food an».

In order to W the moon“. method of subjection.
mod to thin paw. with tho utopia probation on! tho. tho
allowing aquauoa not aim cumnaa.

1 16

 

meH MNmH Chad
11 .q d1 a u m J 1 q 1 1 — q q 1 q M
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\\
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\ 1
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\

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moofiuomnoum xmocH mowum coom

ma 925;

OOH

OHH

ONH

ow...”

.9:

OH

8H

own

8H

own

00w

116

 

owma mwma chad
all .. 1 . . m a q H 1 :1 — fi q 1 -W
\\\.
\\
\
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\
\
\
\ l
\
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1
\
\
\
\ ‘

 

mooauomnoum xmooH mowum coom

NH 8531

OCH

0......“

ONH

oma

.oqfi

oma

8....

0:

8H

0mm

00m

1 16

ommH

mfima

chad

 

 

mooHuoofionm woooH moaum ooom

Na 88m;

2H
8H
on“
. 2H
oma
8a
05H
8H

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com

‘117

83 £3 95 Mad

 

moowuuofioum XoooH ooaum umESmooo

ma musmam

 

 

03”

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ném

119
V' ‘93 " ‘ " ”1%“2’:

Tablo 21. Simplo 0111171111143: No joct1on Equouon tor Gross

Codo __
“’th w 9’ o b1 1"2 w:

Bmga 7 .915 14191976. #94919. 4959.1 2.1861 2.4763
m 11 .961 «415834368. 1712672. 41069.3 1.8806 ~1.3967
199mm 33 .999 .519491499. 19515329. 4375453 3.9199 ~3.2914-
1519992119“ 57 .815 49412356. 688394.41 «5653.9 3.5101 94.3399

I

 

 

993999? 92 .999 «13042.5 490.9 «4.2 5.5539 «5.4513
State" 94 .999 9729224. 432794. 2530.5 «2.1579 4.9479
‘A 2.. Z... W ‘* _‘h‘w ‘“ M A“ A‘ wwwwvj 4“

 

 

 

 

Wood oaloo doto bod boon rodncod by ($000,000)

Doto 111 ram. 21 on uood to empato on. Ounpooito mum
at pmjootton oz toad on» nood to thio popo: wtth tho may
used ammo mutant pmjoctton toolmtquo. nu.- ma. pro-
jection toemtquo to ottn uood to projoot doto nuns than as
tho independont outoblo ond mug no ottost to dotomlno mat
factoro ottoct thuo dung“ ova than. 11.1. no” woo first
need in can popor to projoot tho muo- at tho indepondont var!»-
abloo loto: uood to tho Canpooito mothod. Aqua. data 1:1
ratio 21. tom! to ladle.“ that tho projocttoo no“ no quite
«11 to tho toad moo dot: at tho 12cm ported. Honour.
than pmjocuon cannot bo judgod until 1: 1o compared otth tho

119
Comaosito nothod bung tootod 1n thio paper.

Populotion Projoctton Result"

in order to oomort poo oop1to data into total pot
mty projoctlono. tho county powlottoo woo oloo projectofi.
using o o1op1o goonotnc 11am upon-ion. Tho :omlto ore
am 111 Toblo 22. 1

A omplo aux-V1119»: mroooton oquatton no not use:
to projoct tho county and ototo population auto to tho year

1930. 991109999 o unmouoo on}: Dr. John F. m.o
donogzophor ot Monsoon Stoto Unmorotty. it no 9.9mm not
to uoo o xoqtoouon oqmuon omoo tho month]. tom.
gonordly wood. mold toad to incroooo papal-um data bayond
reasonablo 11919.. Tho won-known gmotno tondonco of
madam gmth moo 2111- typo projootm om non
mmablo with tho population vorlohlo than otth tho other
9911313108.

Comet“: Linux Projection «- Mo pmoduro involvoo tho

automaton of out: omnty'o ovooogo annual pot-mt Mono

(0: deem”) to 9991191199 over tho 12 your period 1951-62.
Projoctlono no undo uotnq tho following oquottonot

Population; 1964 “d... Pomlaiimt:1953

.‘OO.
CUOC‘O

8......

vopulmuoa':£ 1980 1' Populationhwn

120

Tablo 22. Mtdugon County Papulouon.
W
(000)

 

Your Baraga Borneo Inghgm niooamoog Emlyn: Stat. “ -4
1951 7.948 119.1 176.8 7. 391 2458. 3 6516.9
1952 7.860 122. 5 180.6 7. 323 2481.4 6662.1
1953 ‘ 7.771 126.0 187.4 7. 256 2504.5 6809.2

19 54 7.633 129.4 168.3 7.188 2527.7 6952. 3
1955 7. 594 1 32.6 192.1 7.121 ‘ 2550.8 7097. 5
1956 7. 505 136.2 195.9 ‘ 7.054 * 2573.9 7243.6
1957 7. 417 1 39.6 199.8 6.986 2596.9 7387.8
1958 7. 328 143.0 203.6 6.919 2620.1 7532.9
1959 7. 240 146.4 207. 5 6.851 2643.2 7678.1
1960 7.151 149.9 211. 3 6. 784 2666. 3 7823.2
1961 7.072 154. 3 215.9 6.722 2691.6 80 38.4
1962 6.994 158.8 220.8 6.661 2717.2 8265.9
1965 6.764 173. 3 235.6 6.482 2795. 3 90 33.9
1970 6. 398 200.4 263. 2 6.19 3 2930.1 1068 3.8
1975 6.061 231.8 298.7 5.917 372.6 1 1116.6
1930 5.723 268.0 327.8 5. 653 3221. 2 16435.4
m_ x». a. 2...... A; . -mfixfi; - W v. 14......

 

 

Whoa-o: 1 I ooamtloo 61-83

a o ovorogo annual porcoot moron-o (or doom“)
, 1n popu1otioo .

Tho odor odvantogo o! tut tochniquo to that it norm-o
onto the two goomotno tendency oz papaotlon growth whilo

F414

H
U10\O\-<l

SESSSGEEEH

H
O

O\O\\1'\1 CDCD\O\O

121
also taking into consideration those counties decreasing in

population.
Its major disadvantage is that it does not explicitly

take into account the effect of inf and out-migration on a
county's population growth and also assumes that those counties
losing pepulation, do so in geometric fashion - which is not
necessarily so.‘

Dr. Thaden suggested the use of the Geometric Linear
projection, assuming its accuracy to be sufficient for the
purpose of this particular project.

Figure 15 illustrates this geometric expansion in
Michigan's population.

’6
E

2

Figure 15

O
I

Michigan Population Projections M‘_fl_#nm

lie—«~- - /
Vi...
fl...

-_ _ lug--. ,

O O O

c>v1c>uxc>ch>U1c>vxci
I
\

.
U'L
I
\

O
1
\
\

10.5 - . /’

c>c>vxc>u12>Cn<>\n<3
j

 

l
'V

l 4 A l L A 1 A 1 l l

1955 1960 1965 1970 1975 {580

‘r-

H
1%
O

122
statistical Significance:

In analyzing tho importanco of tho 26b: va1uoo pro-ontod
in on. tho oquotiono, tho following toblo in given so that
stationed oigniticanco can to measured at various love:-
of pmhobuity.

not» Moron-ion mottioiont io ototioticony oigni£i~
cent 1: my. «Nagy. «goo at) '

Tamo 23. (too-toilod) twaluo statistical. Tablo.

woes-assesses.

so 2.646 2.360 1.99: 1.667 1.29. .341

 

A_._ __

_. _l _. .-. _- _. _.
_Lw m .. _r ‘_._-_rwm

“AA‘i—A .Al
r—V—Wwwlwww

Hero. again. it :- Immoly pointed out that tho tom
”statistically significant” is otton omtuood with rogoxd to
tho mm in which thoy oro coma. rum... tho ulootion
of on 041wo1. ot which tho oignificanco is tootofi. may also
5. gamma... For Mp1» by "looting o .05 ion). tor-c .
one 9.9 specifying that ho unto only o fivo percent chance or
one... o factor so having o oignificnnt effect on tho
dependmt variahio. ohm in fact. it does (miting o Tum I
error). This ooioction cannot bo arbitrary. but moot to mode
in on. respect to tho probability a: a Typo n orror and aim-
imizotion of tho omectod loco tum.

CRAFTS}! VII
F‘RDJECTIDN PEECED‘JPE

flow that coofliciont estimates havo boon proamtofi ma
expiainod. tho tinai otep rmining io tho an of tho results
in the actual projoction o! potmtiai qmoo rotaii food sales.
90 as not to butdon tho undo: with a complicatod description
of tho pmjoctim pxocoduro. mo county has boon ooiocted
(Earn-ion) to bo- uooed in o 'oampio dmnotwon. A malote
ems details! projoictian of potontioi gmoo nun toad sales,
in 1965 will ho mado for Berrien. County and each atop will. ho
dismsaod no that tho mdorwili undontand tho procedure
as well no tho corroct use of tho ostimatos presumed in
Chapter VI. 7 ,

Potmtial Grooo Rotaii food Solos :- Bezrion County 1965
Stag is Projoctod road rue. Index was I

The first otop io tho calculating at tho ootimuod food
prim index for thio your. Thio invoivoo tho an at tho
aimpio curvilinoo: oquation and tho toot malts mud in
Tablo 19 of Gupta: v1. ainco thi- indox win bo oppiiod to
an countioo, tho subscript "i" taprooazto countioo 1.83 and
stnto to: tho your 1965. I

2
Km ' ‘1 ‘ bu“: ' ”21": um " ‘2’

t, t d. . 2
Fult‘lges ‘ 4.18.3032 . 31.133531. . Jinx}.

123

124
1' 413.3332 * 11.73333‘65) - .1122C4225)
. 413.3032 - 762.6775 + 474.0450
ll 129.6707

they» 2: Projector! Cox-23mm: E‘rica Ina-3.x

Thio otcp io oimila: to Stag) 1 in that it involves the!
calculation 0: an ostimatod index number to: the year 1935.
Rare, 5130. tho index amber is oppiiod to on 83 mmtiea and
thereby need not be calculated for oach individual cmnty.
Test results are also found in Table 19 and mmlto at the
calmiationo or both food prico and ammo: prico index for
the years 1965. 70. 75 and 80 no found in Tabio 20.

. ' 2 ‘
5cm " ‘2 "' biz": " ”22"”: ‘xcn’ " "6
".‘J-b . ' 2

. 249.1592 4 6.4438(65) o .onzuzzs)
. 249.1592 - 413.9470 4» 305.0450
o 135. 3572

Step 3: Project“ timber of Food storoo in Bunion Cmnty
1965

Test rooulto from Tabio 18 no new mood to utimate the
number of: food otoxoo (3‘) that will oxiot in Berrien Cmnty
(Coda Rumbotii) in 1965. In thio equation :4 in tho dammi-
ent variablo. boomer, onto the ootimatod vaiuo is dotoxminea.
it will then ho use: a. mo of tho two selected indapmdmt
variabioo at tho multipio linear pmjoction oquotion.

, 2 .
. o it! o x? o count #-
3491; . ’1 blag zq 1"qu zq :- yon: Y

125

- 2
i?511.1965 o 940.4102 15.8832X 0 .072037

T
3 940.4101 “’1$.8832(65) O .0720‘4225)
O 940.4102 - 1032.4080 9 304.2000

' 212.2022

Step 4: Projoctod Pot Capita Dispoooblo Incomo in Bottien
County 1965

Bozo. oloo. o oimplo curvilinoor oquotion io uood ta
dototmino tho ootiuatod pot copito diopooabio incomo "'5’ in
Bonion County in 1965. Toot tooulto prooontod in Toblo la
aro nood to calculoto thio ootimto which lotor boom“ part
of tho oocond indopondont voriablo of tho multiplo linoor
projoction oquotion.
35m I on o 191”me o 192“):ng

2
PCD:11,1965 3 13072.2333 0 463.7750XT 0 4.57623

’1'

C 13472.2383 - 468.77%(65) O 4.5762(4225)
I 13472.2383 I ”470.3750 0 19334.4450

'3 $2336.31

Stop 50 Projoctod Doflotod For Capita Diopoooblo lncomo in
Borrion County 1965 '

aoion thio ootimotod valuo of pot capito diopoooblo im-
oamo (as) can to uood no on indopondont vorioblo in tho final
pmjoction oquotion. it muot ho doflotod by tho ootimatod
mama prico index in 1965 to undo: it mo roprooontotivo
of. ito txuo manning povor (no comporod to tho haoo period
1950).

X
99:13:11,196: '(fpoo
6

126

DPCEI -(£92511 1965
11.1965 CPI1'1565 100

'fiééfioo
- $1.130.

step 62 Projoctod Dotlotod to: Capita Grooo Rotail Food salon
in Boxrion County 1963
Now that otopo 3. 4, and s hovo boon complotod, tho
ootimatod voluoo of tho two indopondont votiabloo ($3811.1965
and D?c0111.1965) con to plocod into tho~multiplo linoor poo.
joction oquotion and tho potontiol dotlotod pox capito groan

retail food salon {100 (f1) dotomlnod for Box-tion
8
County in l965. Tho x coofticionto to: this
2 11.1965
calculation oro found in Tablo 16.
100.:L x
o o
{:3)aq ' a blqu‘zq ‘b22q(ioo (i2)zq)
a: 6
100 1L, _
x; .
DPGGRF511.1955 ‘ ‘ * blfiysll.1965 ’ hzfipcplnaess

. 552.4422 - .3563l212) .'.1268(l730)
- 652.4422 ~r75.5356 . 219.3540
- 1351,5425

stop 10 Ptojoctod Pot Capita Grooo Rotoil Food Saloo in
Boxrion County 1965

l2?
1: tho toodor io particulorly intorootod in tho hoo-
dotlotod voluo of potontiol pot copito qtooo totoil food
ooloo. tho following poocoduro io followed.

”6835511.1955 ' ”PG°“F’11.1965- ’P31.1965
- 351.5425 . 129.5701
- $460.33

Ste? 8: Pmojoctod Dotlotod Total Grooo Retail Food Saloo in
Borrion County 1965
Thio_otop involvoo tho tronotorootion of potontiol

5311.9,“ pg; coplta qmoo totail food ooloo (DPGGRE'811.1965)

into potootiol dotlotod total grooo totoil food ooloo for
Borrioh County in 1965 (DTGRFBli.loas" Thin io o tothor
simplo procooo in which tho pox copito datum io‘multipllod'by
tho ootimotod 1965 Borrion County papulotioo (lt?op.11.1955)

to dotivo tho total county potontiol. Tho population ootimo-
tion procoduro woo doocribod in Choptor“v1 and projoction
tosulto of tho tivo ooloctod oountioo and tomoihing 78 oountioo
can bo found in Toblo 22 (Choptor'VI) and Appoodix.o, rospoct»
‘de.

DTSRP”11.1965 ' DPGGRFsll.l965 ' E°P°P'u.1965
- 5357.54 . 173311
- $61965614.94

stop 9. Projoctod Total Grooo Rotoil Food Saloo in Dotti-n
County l965

128
Main. juot oo in atop 7. tho dotlotod data can to
charagod to a non-doflotod ootioato by uoing tho tollowing
procodm.

TGRPS

11.1965 ' DTGR?9

11.1963“ prl.l965
.- 561965614.94 - 129.6707
II $799 35642.06

'rho ohovo nino otopo ohall horoby ho roi’mod to ao tho
Commoito Mothod ci' Dotomininq Potmtlol Rotail Food Salon.
Thio method can now to compared with a proviouoly and and
cozmnonly occoptod mothod. 'i‘ho mothod. to ho mmporod with
tho Compooito Mothod. lo tho oimplo curvilihoar projoction of
food ooloo ova: timo. Thio oquotion in of tho oomonly used
form: '

xrs"’bixr’b2x;
Tho rooulto of tho calculationo of data on tho tivo ooloctod
mutatioo‘ oro ohm in Tahlo 21. Although thio oothod dooo
not tako into account tho ottocto of my indopondont variables.
ao dooo tho Compooito Hothod. it lo tho only tochniquo camou-
ly nood in making projoctiono or thin naturo. ihotoforo,
thio tochoiquo oholl aloo to and to provoct potntiol dou-
tlotod and non-doflotod totol groan rotoil food ooloo for
Botrion County in 1965. and tho rooulto oomporod with thooo
of tho Compooito hothod.

stop lo: simplo Projoctod Valuo o: Goon Retail rood salon
in nortion County 1965

1 29
2

V ‘ " 344‘ ‘ c- 2
oPJGR. 911.1965 3 9215834368. '0 7772672.}L, 51066.3125kr

' “215334368. 9 7772672.‘65) O 51.066.3125“225)
. $7353‘1‘2o

Stop ll: Simplo Projoctod Valuo of Gran Retail Food salon
in Bottim county 1965 (donotod)

Juot no in tho Componito Mothod. thin datum in now
doflatod by tho food prion ind-x oo that it will to non
reprooontotivo of tho truo phynical volumo of food involved,
an mnporod to o hono you of 1960.

, swoon
:5930113311‘1955 II ”111.196.511.196” loo

112mm, 190
129. 6707

- 357169000.

Stop 123 Comparioon of Counpooito and Siopln Gunilla»:
Room-ion Romltn
‘lhio otop can boot ho occomplishod by plotting tho
rooultn or both onthodo and thou dociding which in non accept-
ohlo. Thin watt-nod in and lotor in thio daaptor. I

Diomonion of. Projoction Procoduto

All tvoivo ntopn, proviounly dooorihod. on now
ropoatod to: tho yooro 1970. 75 and 80. Thin mot thon ho
ogoih topootod for ouch of tho tomoininq 82 countioo and tho

otato on n oholo. to: tho roooor who in intorontod in arm

130
specific county. tho onto nocoooory to oomploto tho twlvo
otq: pmjoctlon pmcoduro lo loontod no follows:
Ptojoctod FPI valuoo .1 Table 20 Chapto: VI
ttojoctod CPI voluoo II Tnblo m Chnpto: VI
Simplo Curvlllnonr Regression Equation Coottlolonto {on
(1‘) to. of Food storoo , o Appmdlx D
(as) Dlnpooablo Pot taplto Income o Appondlx D
(3“) Compatod Mott-sod of Grooo
solo: Projoctlon II Appendix D
nultlplo Llnoor Regan-ion Equation Coottlolonto ton
Final Projoctlon Equation
(Wt. Minted; o 539;:me 3
For purpoooo of thin paper. tho patentlal deflated and
nonudotlatod totoll good onloo mo only calculatod for tho
tlvo oolootod count“... Hwortholou. thlo provldoo outfl-
clout information no that tho Gunpoolto Mothod may now ho com.
pared withltho simplo cuzvlllnoor rogroonlon oothod and its
rolntlvo voluo thoroby dotomlnod.

County Dlocunolon

Tablo 24 pro-onto tho projoctlono at tho dotlotod and
non-donut“ :otnll food solo: to: tho tlvo oolootod oomtloo
and ototo on o molo. dorlvod from tho emponlto Projoction
Method. Tho dotlotod doto to probably of moro voluo to tho
food industry olnco lt ollmlnotoo tho unloading ottoct of

prico tlooo.

Tohlo 24. Montiol Rotoil Food Boloo.

131

 

 

 

 

 

($000)
wBilwwog'ei FIanukio Borrfon ¥ngham tit—[no State
1965
Non-dailotod 2.757 1.582 19.936 116,812 1,269,323 3.018.325
l970
Non-dotlatod 3.325 1.504 90.212 142.551 1.197.340 4.039.900
Doflow 2. 278 1.071 65.940 97.633 83.596 2,767,110
1975
Ron-deflntod 3,954 1.377 115.649 173.195 1.016.899 5.663.771
Dotlatod 2. 354 819 68.839 103.092 605.297 3. 371.292
l980
Non-ooflotod 4.035 961 137.645 211.312 713.453 0.311.003
Detlotod 2.365 491 10.227 107.043 364.000 4.240.339
Toblo 24 ohm o projootod doeroaoo in potential 9:000
retail food onloo to: hioooukoo and woyno caution. wilo

50:090. Eamon. and Inghno oountioo oxo than to havo on in»

crooning potential :otnil food onloo.

Thoto io oloo o largo

inmaoo indicated in tho ototo‘o potontini. Thou Composito
Projection tomlto will now bo oompoxod with tho oimplo
curvilinear poojoctiono to flow which tedmiquo prov“ to be

most rotionol. f
Berrien Comty - Figaro 10 ohowo non-donuts! gnu rotoil

food onloo incroooing ovor 50 poroont botwoon tho yooro of

l962 and 1900.

Homo. noto how nioloodinq thio booomoo

ohm tho inflotionory otioot o1 pkicoo io_ :onovod. Tho deflated

132
potontinl zoom to ho lwoling off, morons tho non-donated
potential continues to rise rather rapidly.

Tho oimplo curvilinonr projection method ohowo om.
éoflotod potential food solos loveling of! at alightly loss
than 80 million dollnrolond doflotod oalos decanting after
1965.

Elna. Box-tion Cwnty io located in tho oouthorn portion
of tho otnto whoro population in continually inomoing. one
would «poet food ooloo [to incroooo in tho tuturo wth in
dollar voluo and phyoicol voltmo. Mouton. tho Conpooito
Mound noon: to to mono moonoblo in ito probation.

#:isnankoo (unity - ln Figuxo 11. both nothodo ohow o «amoral
doom" in potmtinl xotnil toad “loo. This docroooo in
futon “loo volmo is not totally unnxpoctod. Miooouhoo in
o rural county with low pot capito inoomo lovol and o declin-
ing populotion in tho tvolvo roan of tho obomation period.
However. again tho prooito projoction ooono to to auto
rooliotio oinco tho pxojootod docroooo in not no oxtonoivo as
tho oimplo mnilinoo: projoction which in no inaccurnto that
it projooto on inpoooiblo nogotivo Volume of salon to: tho
yearn oftor 1975.

lnghm County «- Figaro l8 chow: n diotinctivo dittoronco ho-
twom tho two pmjoction todmiquoo. This dittoxonco prom
to ho o strong ondatoomont for tho too of tho mposito method.

lnghm Camty has not only has: an continuously growing

133

 

 

 

 

 

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\ 1 mNH
\\\. madam noon Hnmpmm amono.ompmfiomm Hmsoo< 1:. . omH
mmawm ooom Hflwpom mmonu oopmammmscoz_amppod . m
\ MCOHpOmnoa UmeHHQQ QHQEMHW .04. o v on. o o. oo- .o m H
chflpomnonm oopmfimmmucoz mamewm ...III..|II»:II: gr 04H
mCOflpoowonA Umpmamoa opwmomEoo :II..II..II:.III
.::||.: 11:...1: flooo.ooomv

macavoononm copmamoancoz opfimoasoo

hpcsoo cowahmm

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Aooo.ooowv

135
population. but also has ono of tho highoot pox capito incono

lovela in tho ontiro otato. Continuod urbanization. along
with many other ouch trends. point toward: on incooonnt in»
crooso in potontinl retail food salon. Ramos. any xotoil
food firm using tho oimplo cuxvilinonr method. would arrive
at results ohowinq on o-vmtunl dfiocroaso in both doflotod and
non-denoted potentiol food “loo. Thorotoro. tho composite
methoo again om: to man occuntoly coincido with oxioting
and expectod conditiono than do“ tho oimplo method.

tinyno County - Figuro l9 shown an docroooing potential volume
of retail toad colon and. again. in justifinhlo. fioyno Oounty
is not only tho induotzial center of. Hichignn. but in oloo
the mat hoavily papulotod wunty. Home. tho tmdoncy in
the loot two docudoo has been for o largo portion of tho
poogzlo to now out at tho city of Detroit and into tho
surrounding ouhurbnn areas. In. response to thin gonorol
movement of pogulotion. retail food ctoroo have aloo moved
out of." tho cm-uzdod domatom district and out into tho mmuno-n
ing axons. Many havo located in tho largo [10103002 or showing
centers recently built in tho ouburhan trons. Finding a
retail food store in tho downtown cropping district of Detroit
in now almost on much an oddity no finding o “Coho Hall‘ in

a submit}: like Famington. An thoao retail. outlet: movo out

of tho city of Detroit. thoy xo-locoto in tho thxoo ourmmad-r

ing counties or Oaklond. Macmb and Wuhtonow. Thoxotoro. .

tho docrooto shown in Figuro 19 docs not coprooont o coolining

136

8a....

ofimH

. moma coma mmma ommfl

 

 

Cam

 

hpnsoo EmngH Aoooqooowv

ma opswflm

136

owmd

m RH

ohma

 

 

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h92500 Snow:
H 88.808

ma opswflm

137
Detroit retail foodmarket, but rather a movement of this mar-

ket out into the surrounding counties. Map #6 illustrates

this movement.

Map #6

Detroit Area Counties

._ - m-—-—.«-~ u--—A- —-*
___ _...

 

 

. Oakland Macomb
Livingston

 

 

 

 

 

Washtenaw

 

 

 

—— -— —-)' Food Store Movements
W... Detroit City Limits
County Lines

The Composite method, again, is a more realistic esti-
mate, particularly on long run projections, since the simple
projection technique shows a negative volume of potential
retail food sales for the period following 1975. ' A decrease
in the potential can be Justified, but results like those

derived from the simple projection are beyond any rationaliza-

ti on.

23 . $2“ 8a was an .

 

02...
coo-
com-
cos-
com:
com-
cos-

 

138

L. 0
8H
mango 0833 v . cow
as shaman com
.. . 8;
oo no: , .. COM
/ .. . . 08
../ . . . w . cow

./ .. .. . A . 00m

,1..uuy4.. ...... ex A com
. . . .o . .. . 4 80H

8HH
OONH
L OOMH

Aooo.oooev

 

 

. 139
Baraga County «- Baraga is the only uppor pminsulo county
included in this fivo county analyeis. Sincs this county has
such a small rosidont papulotion (approx. 6000). it is es»-
pectod that the some: influx of tourists has a huge affect
on its over-all economy. Likewiso, it is oxpoctod that the
annual voltsno or retail food sales is highly responsive to
the amber ct ’tourist days‘ oach your. floors 20 show both
deflated and non-donated potmtial sales increasing, using
the simple method. Bomor, tho Composito nothod shows only
the nonodoilatod potential to ‘bo increasing to any extent.
The deflated potontial, which is moro raproaontativo of the
physical voluno or solos, is shown to inmaso only slightly.
This slight increaso seems to to most easily justiriod bo-n
cause, despite the fact that tourism is oxpoctod to increase,
the rasidont population is steadily docroosing. Thus. the
Composito motlwd is again minors in accordanco with anticipated
conditions.

In ooch o: tho tivo soloctod oountios, tho Composito
method of projoction, describod and and in this papor, has
been shown to havo o much moro sound basis in economic logic.
Even i: the ootimatod values aro not perfectly accents, the
Cmpooito method can still to used with some degree of con-o
fidmco by tho retail food industry in comparing tho counties'
relative potentials for determining tho most Optimtl area of

man- an s ion .

'lho

 

 

r3500 owonom

om mnemae

1 mom

4 06

 

88688

lhl

OmmH

mhma .

oumd mwmfl coma

 

 

gamete: .. mods eooe Sate

aw seamed

A 08;
.. 08m
.88.
.. 0005

.: 000m

 

.i 000m

800.808

142
state - 01! additional intorost to the rotail food industry is
the potential saloo of tho stats as s wholo. as sham in
Figuro 2l. tho simplo projoction again prosonts an unrealistic
foturo trend. Evan it tho physical volume or food sales in
Michigan rousinod constant. general prico risoa would cause
increases in tutors dollar volume of solos. Therefore. the
decroaso in both deflatod and non-doflatod potontialo. derived
from tho ohnplo curvilinear projoction, is almost impossible
to justify. Eowovor. tho composito rosults indicato an inn-
croaso in both tho dollar and physical voluuo or tuturo retail
food sales. This can be justitiod by incroooing population,
income lovols, urbanisation, product availability. otc.,
much again ondorsoo tho Composito nothod;

Cooposition of Potatiol solos volumo

Tho emposito Mothod or projection ostimstoo tint
potential food sales in tho stats of Michigan will increase
from 3.2 billion dollars in 1962 to 8.3 billion dollars in
1930. This 160 par-cont incroaao in toad solos will occur to
the food industry as o whole. Some importanco is gonorally
placed on an ostimation or what proportion of tho potential
sales volumo will occur in tho various typos of food stores.
For purpoaos of! this papor. tho food industry has boon divided
into six gmorol typos or food stores. riguro 22 shows the
percent or post annual total toad solos mulch mo rwtod

by tho six ditroront typos or toad otoroa.

143

 

 

 

Figure 22
Percent oz Total Food Solon Attributed to General Type of Food
storo
Emma .
V '"'" ootou~ ' "
Dairy Fruito & rants Taverna Miscelo
Yoor’ Groceries Producto Vogotobloo (tomily) & Clubs lonoouo
1951 59.80 5.50 1.16 14.20 10.93 8.41
1953 60.69 5.56 1.16 13.36 11.01 8.23
1954 61.43 5.42 1.02 13.17 10.83 8.07
1955 61.62 5.32 1.73 13.19 11.27 6.87
1956 62.36 5.13 1.51 13.11 11.14 6.74
1957 64.15 5.28 1.13 12.76 10.62 6.06
1953 65.92 4.96 .94 12.37 10.17 5.64
1959 66.72 4.66 .93 12.27 9.86 5.56
1960 66.51 4.40 .86 12.57 10.05 5.59
1961 68.14 ' 4.38 .36 11.38 9.29 5.94
1962 63.38 ’ 4.05 .87 11.32 9.35 6.02

7.

As might to omctod. tho porcont oi total rotoil

food oolos taking ploco in grocory otoros hoo incrooood over
tho twolvs yoor period whilo tho dairy product. fruit and

vegetablo otoros hovs booooo loos important.

this is duo. of

oouroo. to o docrooss in tho nmohsr or null spociolty food

stereo and o tondoncy for tho grocory storso to swollow up

their solos.

I! this trond continuoo.*by 1980 almost 00 por-

cont of total food solos will occur in qrocsry stores and

loss than 3 porcont in spociolty food stores.

w

w— W

1

w

1Projoctiono oodo using oimplo linear oxtropolotiono
based on twslvo yoor proud. ‘

144

It would normally be sxpsctod that tho relativs
importancs of food solos in restaurants had incrooood during
tho tvolvo yoar psriod. Bowovor. so shown in Figaro 23. cos»
pits o 20 percent incrooso in tho obooluto volumo or
restaurant food solos.x tho proportion of total food solos
occurring in tortouronts cocrssssd from 14.2 to 11.3 porcmt
(luring tho obsorvotion poriod. Normally. cs ono'o por capita
looms iocrsosos. ons toads to sot o grootsr proportion of
meals in rsstouronts. Thorstoro. rsstsuront toad solos m
not exported to amp holes 10 "potent or totsl rotoil toad
color by 1980. _ ‘ . _ _

This snoxpoctod cm in tho rslstivs importonoo or
rostourant toad solos may to partially Justitiod by tho
tram: tousrds incrsssod constroption or My prsporsd food
which hoods only to ho hootod borers sot-vino. Yoors coo.
acting st s rootouront providsd utility. in tho torn 0: con-
voniooco. so you so s sociol sxporionco. . But mo. in tho
cm or tho ”Noninnsr.' tho convonioncs merit hos boon ,
Wot oliminoto’d. It now bomos Just as conveniont to
' pots or dinnor into tho ovon so to sot in s rostouront. and
smot chsopor.

Tho slight docrooso in tho proportion of total food
sales sttributod to mod solos in tovorns may ho tho romlt
or s dociino in tho omhsr of tovorns. Also. it my bs tho
result of tho svorogs patron's incrsossd thirst sod ascroossd
hmgofl unortholsss. tho trend indicator 4: turthor drag to

M. L.— _._.¥ ___4_ k A _A _n.

1K.D.Dutt and $52.; 3...”... p. 18.

145
about tivo percent in 1980.

Tho remaining two porcont or total 1980 retail food
sales will be tho result or solos in miscellaneous stores
such so delicotsssons. candy stores. etc.

Since “ratio 22 rotors to tho stats so an tools. these
proportions will vory smonq individual counties. For entangle,
tho touriot trods would tend to increono tho rolotivs unpert-
once 0: restaurant solos in northern Michigan countios.
particularly thoso intho upper ”11181116. 3130. WWW
fwd otoros (dairy ‘product storos. fruit ond vegetablo markets.
etc.) will be less important in thoso muntios with no large
urbanized communities and acts 'importont in thoso counties
with o highly concmtrotod population. i.s.. hoyno. Inghoo.
etc. Groosry stars solos will to relatively nors important
in rural camtiss shore thsrs sro tower spsciolty food storss.

QIAPTER VIII
APPLICATIOH OI" PmJECTrZD 22am.

Before oven tho most accurato projections can become
useful. they must be applicablo to tho situation under mnh- .
ination. The validity of the projections nods. can only be
tested as tins passes and tho actual solos volume tor a
futuro yoar compared to tho projoctsd volmo. Wordless. a
projection procedure now oxist's and furnishes information
for managerial decisions. Table 24 (Chapter VII) shows the
abooluts dollar value of tho projections. The absolute value
of the projected incrosso (or docrosss) may to misleading
oincs' it does not describe tho increase relativo to the hand
period. Tabis 25 shove the projected percent increases in the
deflated solos volume and is 01' mars value who: applying this
data to problem solving discussions.

The data in Ta‘blo 25 show that tho volums or retail

food solos in the stats of Hichigon will douhlo tron 1950 to
1990. This has amorous implications to the retail food in-

dustry.

Entiro Stats

since the data in Table 25 has been deflated. it
represents s doubling of the physical volume or tood involved

146

147

in tho cal“. In order to handlo thin incrmod volumo of
food sales, additional facilities will have to bo mado avail-
able. This io highly inconsistent with tho protont trend.to~
Vflréo decreasing numboro 0: food otoroa. Thin trend io can
posted to lovol of: within tho near tuturo to yours) and tho
number o: food stereo than incrooso slightly towards tho and
of tho 1980 projection poriod. Rovortholooo. tho major trend
will ho o continued inoroaoo in tho oizo of! tho ovozago
grocery otoro. Howovor. it must to noted that variouo recent
otm‘iloo havo m that the Optimum oizod gloom not.
(profitvwiao) lioo hotvoon $1.5 to 2.0 million annual gross
sales,1 Still othor studios havo‘produood data thawing inu
creasing returns to ooalo to tho oito imrmn.’ At proomt.
boom“, tho ovorago Hichigan flood otoro is much mallet thon
this limit and ban plonty of room to: uponoion.’

Figuro-la illuotratoo thooo‘rooulto. Boon as tho
avorogo sin of tho gmcory otoro inoroaooo. this oxpmoion
will not outplotoly moot tho oxpondod noods of continent. and
this remaining volmo may oupport tho racontly incrooood

_L_ _.... . - H __. A_—..—

—-v v— —— w w—w— fl .7... _.— __ W ———-

, I‘Mmial study.“ W; January 1964.
Po CoIZo A

aluminum General Food. otody. control Foodo corp-
oration. October 1963, p. 13, Exhibit lo.

3m“. and Brown. Table 12.

l48

nmoZoor of! omollor ”superottoo" or oo—collod “convenience
atoroofl

Food retailing will ronoin on industry or large numb-om
in opito o: o pronounced decline in otors numbers oinco 1950.
Tho grocory otoro will booomo ooro important relative to the
mtiro food industry on ohown in. Figaro 22. wherefore, the
retail food chains, ottiliatod and unaffiliated indopmdmt
retailers will bars to unto amorous decisions concerning
future expansion possibilities. We: it tho oxpahoion doci»
aim is made. further consideration will ho necessary to
deems whether this oxpanoicm will ho vortical or horizontal:
local. regional or onto-«wide: conductsd by merger: or new
motructiom otc. There exists almost a certainty that food
rmmuo will hovo to mats major organizational changes in
tho tutors. As s result. tho rstailoro will hood to revise
their marketing progromo and mothodo. Regardless of mot ouch
chemgos will imply. tho first and most important information
nooflod it tho markst potontinl changos within tho stoto.
Even it tho physical voluno of retail food soloo dooo double
in tho stats of hidxigan. tho tood industry is at o loos
trying to moot thus incrsaood dmonds, unloss it knows years
of advance, just «has. within tho ototo. thoso changso will
ocwr and tho oxtont of thio change. It is this typo oi'
infiomation that tho Composits County Projoction Teamiquo,
describod in this papor. was oonotructsd to tarnish. However.
those Wits oalss projsctions should not to used by tho

149

Tabla 25. Donated Retail Food sales.
I I ,I , II , I I

 

 

 

($1000) I

, it or % of % oi”

County 1931 1951 1962 1951 1965 1951
Baraga 1.522 100 25075127., 2,137 111.3
I'llSSOLIKGO 89‘ 109 1.143 123.5 1.226 137.1
Eorrien 42.531 100 36,439 132.7 61,966 145.7
Inghom 59,639 100 82,151 137.7 90,552 151.3
¥~£oyna 925,345 100 989,899 196.9 983,971 3.36.3
State 2,138,200 100 2,779,642 1%.!) f2, 339,797 109,4

3 of a: at 32’- of

County 1970 ‘ 1951 1975 1951 1980 1951
alarm-3a 2.273 140.4 2. 354 145.1 2. 365 145.9
Missouri“ 1.07]. 119.8 819 91.6 491 54.9
fiezrléfl 65,094,153.1 68.839 1c1.9 , 70.227 1c5.1
Inghmx 97,638 163.7 10 3,092 172.9 107,843 130.8
Wayne 823,596 88.6 605,297 65.4 334,009 39.3
Stote 2.767.110 129.4 3. 371.292 157.7 4. 240. 338 193.3

retail food industry as tho only critcrion on which expulsion
decisions are boned. this composite technique only considers
tho population amber or road utoroa and income tutors and.
thorofloro. in not designed to prumt a mploto picture of a
given mark-t plum.

Tho pro jocticn "cult- uhould than be used as one
of many factor: to be ccnuidorod in a complete mark-t analy-
oia. Tho mm o! «aphasi- that should be placod on the
projections. thorotorc. depends not only on the particular

150

Figure 3

Break-Even Analysis, Economies to Scale1

Revenue & Profits
($000)

Total Revenue//’

Grossznz;gin 22.0%

hOO l /////’ Tot oats

BreakéEven Point

Variable Costs

200 ‘ ’////

1 Fixed Costs

 

 

 

 

3100 . ZXK)

Sales ($000)

 

lDuft, Kenneth D. “Profitability of a Transition
Point Derived from Technological Changes in the Physical Dis-
tribution and.Handling of Retail Food Products,“ MlS.U.,
December 5, 1963, pp. 24-25.(Unpublished). - '

lSl
situation involved. but also on the availability of istoma-
tion on ths other important factors.

Metropolitan Areas

Michigan is musctsrissd by having s large amber

o: mall regional food main organizations Moll storss) as
well as many of. ths national «amiss.1b Where as the national
mains are interested in evaluatingsll the sunsets through.
out the stats. but the rsgiohsl chains and affiliated independ-
snts are more interested in analyzing ths metropolitan area
in which they Upstate. Hichigsn annulus ten msmpolitan
areas and each can he snaiyssd and projections ends in s
owner similar to that 1:an with the five sslsotsd
cotmtiss. The metropolitan areas. consisting of! two or more .
muss. can be studied by naming individual county data.

Even within an metropolitan ares. special attention
should to given to the outlying rsums behind certain comy
trmds. For exampls. Wayne County, alone. presents he sat--
trendy misleading description of the Detroit Metropolitan
Areas The projections show s dscrssss is the potential food
sales in wsyns County. Mover, this decrease is over-weighed
by the amending Met of the ”standing counties.

ihs study ”ducted in the Chicago-nasty metropolitan
Area mowed how the potential rstsil food market is moving

AAA—A “_... r;- A A .g... ‘__‘_____ A 7 MA A

W
__ *v- 1 ~« fir, Ww—W—w—w _ __ fl _...... wr—

xDem: and Brown; Table 16.

152
towards tbs suburbs and toads to tollow the major traffic:
arteriss. Sines this is not just trus for lugs cities liks
Chicago and Dstroit, it produces unique pzoblms whsn analys-
ing a metropolitan am. Thusfors. svsn within a metro-

pol itnn at“ thsrs may hs variations bstwssn countiss.

Countisn

A county by county projsctim and analysis. lixs that.
performed for ths tivs sslsctsd ommtiss. is idsal to: tbs
lugs national toad chain. m. givss ths industry it
plenum at potsntisl sslss thxougmm tho sntirs stats.
132an of inorsnsing (or dscrsnsing) sslss potsntial can In
determined allowing turthss docisions concerning tutu" s24-
pnnnim plan. How ths "tail food industry knows uhsrs
(within ths stats) this doubling of 100:! sales will probably
om.

One would sxpsct that ths southsrn csmtiss will sx-
parishes s gusts: incxssss in Mars “tail food sslss than
will the northern counties. Wu.this qsnsralizstion is
not vnlid snough to bass major nansqstisl dsoisims on.
Retuxning to Tahls 25. ms tinds s mthsrn county such as
i-znyns shoving s 1980 potsntisl msil tood sales wlms only
39 percent at that in 1950 and s northern mty such as
Baraga with almost a so psrcsnt inst-sans ovsr 1950.,

Tho importancs of the Wuyns comty trends should not
be underestimated. Tho mgnituds of Rnyns County food sales

153
clone. indicatss ths importancs of. this county in determining
the entirs stats's projsctions.

Tho 9:010:th 1980 Wayns County food sol” mts need
faiths: wimstim. Tbs pmjsctsd moo voltms m a
rather sharp carcass iron than 3.950 volums. This tuna, dine
(savored dating tbs 1951-452 obsnvntion [>er is Justitiobly
nttrthsd to tbs amount at Bstroit's populatim out of the
city and into ths suburbs. mentors. ths 1980 projections
are based on tho ”motion that urban tmswal and the present
Watlm novsnents will .omtinus. This sssmption. slonn.
creams limitations uorthwhils of additional consideration
and mast.

For mp1s. I won recent phamsm is ths tmdoncy
for the upper looms papls to movs back into tbs city once
the“: (311.1633! havs left ham. 7316" ml. novs into a Bacall
anal-dummy ultra oodsrn spam-at in ths sidocity when the
husband is within walking distancs from tho attics and the
wife nssd only ml}: across the strsst to tho dmtmm trimming
district. Although this lstsst tuna is s is: on: tron the
magnituds oz tho mass sxodus sapsrimcsd in tho 1950's. it
my bs ths hsginning or! something of grout consumes within
our metropolitan srsas. masters. ths Wayns County projec-
tions srs ”trendy dependant on population tuna assumptions
ans: the projected accrues in potential salss may hs an over-
nntimnts in visit of tho diminishing trend o: Detroit‘s papilla-
tion We:

154

However. a detailed study such as this furnishes
available information on the proper location of new facilities
and oz-panaion o: thouo mating facilitiea.

'mo productivo life 0! a new and moon retail food
outlot. of supermarket also. in about twenty years. There-
foro. baton tho 1mm on status or this naturo can be
moo, on analysis at tho max-Rot to: that twenty-you period
must bo conduct“. Botoro a loqitiouto roturn on an invest-
mmt can bo anticipated. tho oonomor defiant: moat oxiot not
only now. but also in tho tutuo.

It must ‘bo not“. Wot. that thin study'o projoctions
in no way dotract from tho toquimont that ovory Mailer
moot out tho task of carving comma-o moro «actively.

For this io tho bout of any mmmriontod ominous such
as food totalling.

Incomo Elooticity and Engol'o Law

meme Elasticity (a)

Bafom tho projection technique and its results can
be diamond in relation to ammonia theory. tho equation co»
efficients (especially by associatod with deflated per
Capita aisyooahlo incomo) mum: ho analyzer: with regard. to inn
coma elasticities and/or Engol'o Law.

mo emotion manually usod in dotamining the slope of
12516363.. a mum am! the homo elasticity is of the tom:

Ytoai'tbxi'u

i 1

155
«more Yi in tho per capita expenditure on tho iath malty
weaving is included on a macdity) and x is per capita moo-ac.
in: . o zb‘ - 1 '
so that tho sum of tho expenditures on individual oomvoc’titioo
is argon). to total incomo. i.o. Y1 o x at all lovelo o: inn
cornea}

_ V the final technical cutorion in tho choico of a
functional form to approximate tho Engol mo in one. of
nmoxical oatmation. This criterion loads to o profexonco
fox floms fluid) are suitable to: morooaion equation. oath-zeta
tion.2 ’

mo multiplo linear equation need in this paper was
basically of the tom: ‘1' o a «- 251x1 o 112:2 «a where Y is pox:
omits: deflated retail food sales, x1 in the number of food
stores. and a: is collated per capita disposable income. the
income elasticity o: thin aquation is ootermined as shown in

Tobi Q 25o

Toblo 26. Incomo Elasticity’.

marginal Prom oity . Income Elaoticity

 

3° 60:16me a
9;! x . 3
Equation ‘3‘": 1' MP: “2.9" l ,

_.4- , A _A A _— ”_......—
—._..

Hamn: Raga rOmor. p. ’5.

2&1”. 3.6.9. and Aging m1”. F333 . '
(”1012:3011 School 0! Economics and Politic Sc moo: 3m"
otatiotico and Scientific Mound." Hod London: Staple: Prong.
1935); pp. 1-59.

3810:2138“. Po 8). o

 
 
 

  

156
Table 27 shows the) result of the ”E“ calculation to:
Em five aalected countiaa and stata.
mm. 27. lama Elasticlty or the Demand to: Food (E).

X X b

 

Cmmty Code 2 ‘ ‘Y ' _1 2 E
L. A 7“ 7 _ g; l A” Y __ ' A m __*
€57 167. 60 61 31 . 6769 3. 29 .0 384 . 20 3
£51 81.0550 25.8249 301‘ 02577 .309
£311 87. 5973 12.1350 7.22 “.1263 ”915
#32 10.8.9785 22.9792 A 4:74 .1296 .614

state (2234) 113.822! 13.2014 9.32 .0552 .542

.. A. l___. A‘_ < _ ‘4; ..__‘__ - A...

w v.— w “,1— w—v—V rfl‘ W W

Tabla 27 shown an lame elaaelclty of the demand for
food (3) of .542 to: tho It“... as OMC. when mating
this with past studies, this sous-fines hlgh. It indlcates
that an 'pm' «plea dean-d Disposahlo income incl-Gama by
ton pmt. par caplta deflated retail food mum 13¢
cream by 3.42 parent.

mu any h. attributul to the Mg. weighting effect
vague Coth (3 u .614) has on the mm, as a «solo.

flower. lt mun nlao be muons! the 3 cannot be
consumed tho true lam. elasticity. Two income {bustle-u
lty 18 based on the tampuon that "all“ other variables
an bald eon-cant. In tho boglnnlng portlon at this paper
the summation at nmorma variable: than an. equation under
consideration was described. “mentors, now that: many af

these variablu an no longer under 'conudetatlon, and cannot

157
539mg that they are rm-alnlng constant. Also a talatlvaly
high inter-correlation for the state would am to reduce the
accuracy of E...

Rota that just". as fir. Earmann fmmd gran variations
in E betwem different sized muaahcléa, Table 27 shows great
varlcztlma in 8 mg tho five selectad muss. '

Again. tho' nagatlvo E shown for Berrim County ls
most-1t Guzman to uplain unless 1: la attributes to the high
examint of intercomlatlon pravlcusly mentiontd. In the
remaining four counties. the 13 varies {1:335:03 in Baraga
Cmmty to .809 in 241nm“ County.

Generally 396314.139. as would be impacted. the E 19

hid-her in than mantles with lower income levala.

 

1. 1mm " #33 ' . 307
2. Wayne *‘32 .614
3‘ Baraga £37 0 2'3 3
4. filseaukoo #57 .809

Food mmmm show a low lawn of zaoponu m in»
coma level dung” ln Baraga County {4.203) humus. of the
magnitude. of the tourism effect on food males. Had the
1:911:13: affect been relieved, l: in capactod that Baraga mulfl
be found consist»: with 11110 other three mantle: which allow
that. as lacuna level inc-mus, its effect. an Ema mama-
taxes docs-oases.-

Engel's Law

A 192 coefficient. of less than 1.0 to: cash or the 84

time series mluplo linear :egressmn equations illustrates

158

ammo endorsement of tho existence of. Engol's law undo: QMFPEIC
COIkEtLOflS. The preceding few paragraphs. which show a
blame: E for lower lacuna counties. also tend to show that
Engol'o Law does exist under dynamic conditions. Both of
those findings follow the basic hypothesis that poorer tam-
lioa somd a larger percent of their total income on food
tE-mo do the higher incomo families». However, a negative 122
was fiouml in many counties. 'Ehio pha‘mona still coincides
with the basic rowing-ant that as income incroooeo. a lower
percent is spent on toad, but on: not agree with the com

magnet: that Engol'n Cums is positively slorsod. moro-
fore. under (1:,ch conditions, Engel'o Law does; not perfectly
apply throughout the state of :rzichigzsn.

The static conditions.- illuotratod in the cross
Soctioxml analysis. provided a b: which is not only 193$ won
1.3, but also positivc in nature. is was discussed in
Gupta: VII. tho mating of those two toquirazzenta indicated
that angel's Law m apply to the stat. of aidaigan under
static conditions, similar to trace under which it was origin-
ally formulated. '

Porcmt o: loom: Spent on Food

or additional interest to the economist lo infomotion
on the pom-out of! total income opont on food during the
twelve year period. Table 23 and Figaro 24 present adoqnto
data from which the roadie: may visuallzo the amoral trend,

2’19th 24 best illustrates the 1:91qu towards a
decrease in tho parccnt or income spent on food. This, of

159
comso, coincides with the general incl-coco 1:: income levels
tt‘mougm-ot the state. assuming this general trend continua-2:3,
by 1930, less than fifteen percent of the average Michigan

reoidont's per capita income will be spent on food.

Limitations to Long Run Economic Projectiona

Economic projections are widely used by bucinoco-non
16303:an to new mars-zeta and croca of mantle oayanoion. :-
virtuolly insatiable: amour! for a poor. at the future - evm
if clmmod by unccrtainty - has given rice to a host of
longm: run economic appraise-11$. Unfortunately. many of the
more detailed studies consist largoly of collections of data
for past years and ”numbers" projected on the basis of post
trends.1

Some of the basic limitationc or deficiencies of long
mm projections. such as those made in this paper, are as
follows:

1) fi'iIeithor the economist not anyone else can foresee the
futuro. The communist must. therefore above all, apyrociote
the limitations o3 his tools and procadums.

2} Elaborate, cetailod economic projections gonomily toga-giro
mo time and effort than can to justifiod oven in on ailment

moiety ouch as ours.

_ , _.... _.... a. A , .47 ,..J__ . A__.__;_ A- __ m

_.— , w w -——-v ——- fi- w

A lMYi Rex 9. "Long-Run Economic Projcctionm A
review and Appraisal.“ Agr. Economics Resoarch. Vol. :33, no.4,
CCf-Obaz 1963..

160

Table 23. Percent o: Per Capita Disposable Income Spent on

 

 

F006.
W
county (2‘?) 1951 1952 1953 1954 3.955 1956
Elam-{mafia ‘57} 17.91 18.93 19.91 20.02 18.69 19.11
Berrien (11) 18.45 19.82 29.29 20.19 19.35 19.74
Efli-Jofilédn (33’ 14.95 16.05 15.41 15.“ 14.74 15.18
Reyna (32) 19.51 24.59 25.83 25.81 24.61 25.21
state (84) 22.57 33.10 24.19 2‘.” 22.20 23.68
minty”) 1931 ”so 1959 1960 1331 _ 1963 Average
mam-'13 (7) 22.50 21.92 23.51 21.21 20.8"! 21.59 22.25
Berrien (11) 19.27 19.63 13.29 18.12 17.55 1.7.59 1.9.03
1mfimm(33) 15.15 15.39 14.97 14.20 16.39 16.65 15.40
£9322:ka (‘32) 23.94 23.83 22.21 22.30 23.24 2.35 23.59
State (84) 23.33 23.92 21.59 1993'? 21.13 273.333 23.33

‘— A _.- _...;

W w _— W - W

3) 3909': long run decisions have many faceta - economic,
coci'fil, welfare, national security, etc... and no economic or
other analytical frmmfic can be ospoctod to give unequivocal
concluaionu regarding the mole picture or the future.

The economic projection attmtc a view: oz! the futures
moon primarily on prooont kmlwqo and rolationohipa of! the
rec-mt pact, fiscally the ntratogic acomptiooo are given and
much of tho projoctlon follows logically from those assump-
tions. Accordingly. the projection is not an tmconditional

“forecast“ on. the future. but in an appraisal based on a

25

20

161

Figure 24

Percent of Per Capita Income Spent on Food
Michigan 1951-62 ‘

 

 

1950 51 52 53 5h 55 56 ‘37 58 59 60 61 62

, _..7 ._ ..-___.é 7-fi__.._..

number of Specific assumptions.l Such assumptions make the

projection jdb manageable, but Just as often as not, they are

 

1Da1y, p. 114.

162
a (image ‘mich simplifies the job and limits its usefulness.

The long ran emnmic projection, consecmently, can
be little mre than 0 tough sketch of future growth base! on
past trencie and econmic relationships. Such projections
solfim reveal new prc‘ol em areas. but help to quantify those
kncnm problems.

The commute method of projection, as aiscussed in
this paper, :7er contain a limitation mlich is uxmoticea‘fale
unc’ior average conditions. Emmet, it might become more
e".*ir.'.‘ent if projections are made for all of the :33 counties
rather than for just a selector. few, as“ was done in this paper.

me to the characteristics a: the expotmtial aqua-
tion need in the composite process, the sun of. the 83 ootmty
retail food sales projections will not neceesarily man; the
state projection to: a given year»1 Altmugh this phenomena
teem to give the camposito technique an unrealistic character,
it is not totally myielding in nature.

The meet conventional way of correcting this "error"
Boone to be as follows:

i) assume the state projection to be correct since the state
data will have averaged out those counties with rather ex.
trim-we treads.

2) Kieternine the percent the aim of the county projections in

above or below the state projection, anal

_‘A—Afl ——_.______.___-A AA— #-

w w. w w w ‘-— —v
#77— w “v v

12121:; is also true of. the ample regression technique
and other: except to: a purely linear projection.

153
3) nubtroct or afifi this Hercont of ouch covnty'o projection
to tho original county projoction go that no sum of the
county projections equal the stats projection. Boopite the
fact that this ofljuotment 15 most arbitrary, it seams to he

the boot correction device presently available.

CSLFTEQ Li
SUM?” MY Al? 3 00:2 31.13310733
71113 cfimpter will consist of Summaries av} conch; 35,0115
oi the results. Each of these objectivea of the atudy are

again stated. £0110we§ by a short exylanation of findings of
thin study as they pertained to that particular goal.

Reaching tho Objoctlvoo

fietermine tha relationship and signifiicancc of

 

ecanomic and sociclagical factors in explaining variaticns in
grass salsa over tire‘bv counties. metrOpalitmn areas, and
state.

Chagter‘v explains the prccess (time-aeries multigla
11n@.ar regression analvsis) 1n «h1Ch four trial runs were con-
ducted to detemino the factors that have the major efiiect on
variations in retail toofi sales. Following the elimination
of thgsa factars with a hiq‘1 de3ree of interccrrel tisn or :
inaijnificant affect, it was fauna that population was of

us; great 1: ports nee. both in magnitu e and in 31g .ifiicanca,
that it car cealei any relat13¢.sh1ps that might axis t Let .200
food 33135 and other factors.

' In the third trial run it was dacided to :amove the

effact o: pepulation from tha regrasnien equation by converting

164

165
the total retail {cod sales into per capita retail flooa sales.
In the fourth anfl.last trial run it was discovered that hath
umber of toad stores and deflated per Capita income had an
effect on deflated per Capita retail {cod sales. The results
of a five county regression analysis presented in Chapter $1
show great variation among the counties. ‘32 variat from a
high of .35! to a low'of .132 and T3 from 3.1355 to .3735.
Generally. it was found that tha numfier of £005 stares in a
ccunty had an inverso relaticnahip to that county’s retail
5303 sales. The magnitufié at this relationship was greater
fo? the nexthern Miéhigen cc~ntics and was attributed to tha
aacrease in the number a: small ccuntry stares, leaving only
the lfizgar and more efficiant atorea whidh innate in a cantral
retail sales area Where the drawing payer 13 incraaaad.
In a majority of the counties it was found that (as

is normally oxyected) the 19931 of pa: capitalinccmo has a
direct effect on par capita food sings. qweuw. as 81mm in
tap 34, many counties showed income ta'hava an inverse escact.
.::q:lanation 0:3 this; phma is bE‘fC-nt: the scape 025 this
away, but aces mama“ an are: in winch further study is

groatly needed.'

a Batu-mine the .nigniflunco a: muted tactotu

 

1n explilning variation: in gross sales among the 83 counties
far the years 1951~62.

166

Table 17 in Chapter v shows the teaulta of the cross
sectioned multipla linear regression analyata. Thin cross
sectional analysis was conducted to determine what affect.
it any. the number'ot flood store: and per capitn income level
had on variations of gross sales among counties in a given
year.

The equation results show that both factora'had a
significant effect on food sale. ouz1ng tho years 1951-57.
Howevot. during this ttmo period. the percent of variation in
gmes retail food sales explained by the two factor:- (2.2)
docroased from 45 percent tolonly 7.3 percent. During the
first aawcn year: of the observation period (1951-62), both
tho number'ot stores and per capitn income level unto found

to have a positive and fairly stgnlttcant street on gross
retail food sales.

gbjggggvg 33x Formulatc a basic statiatical procedure which
W15 as. tho relationships determined in (1) and (2) to pro-
Joct the potential food cola: volumo‘by county, metropolitan
areoa. and state to the year 1930.

Chapter VII proaentn a detailed oxplanation or the
atatiatical pmocuduro advocated in thin paper. Its step by
step process can bc summarized as tollowan

Step 1: projection of tho food price 1ndex:number
uoing a stmpl. curvilinear rogyeasion equation.

stop 2: projection o! the consumer price index also

using the aimplo curvilinear regression equation.

1E7

atep 3: projection of the number of fooa stores for
a given county, again using the ainple regression equation
where time is the inflapendent variable and number-of {00$
stares the depenfient variable,

step 4: projection cf per Capita disgosable incmne
level in a givcn county using tbs simplc curvilinear regres~
eion equation and projecting the fiata over time»

Step 5: transforming per capita disposable income
data into deflated per capita disposable income'by divifiing
the non-deflated flata by tha.projected consumer price inaex,

Step 6: prajectlon of the doflatad per capita gross
retail food sales tax a given county using a multiple linear
regression equation,

Ste? 7: projection of the nonadeflatad groes retail
foofi sales for a given county by multiplying the projectad
deflated per CApita sales data‘by tho projected food price
inflex.

Step 8: projection of total deflated gross retail
toad sale: for a given county'by multiplying thajprojectafl
fieflated per capita sales data by the projected pepulation of
that partimlar county,

Step 9: transfomaticn of tho deflated county retail
food sales data projection! into nonndaflatod projections us—
ing the prajectod food price index as it was used in the

seventh step,

168

Step 10: projection or gross retail food.aaleo for
a given year using a Iimplo curvilinear regression equation
as in stops 1 thru 4 so that tho result: of this Bimpl. prOo
Joction over tion can be compared with those of the Composite
nothod (Steps 1 thru‘Q) developed in this paper.

stop 11: transformation of this simple projected
food aalol datum into a deflated value again using the pro.
jcctod food price index.

step 12: th. actual comparison of the composito-
method projection: with tho simple curvilinear projections
over time no that both methods may be evaluated and the most
realiatio and applicable technique selected. Following a
detailed analysis in Stop 12 it was concluded that in ooch.of
the five selected counties and the state, the Caizyaoaito
fiothod of projection.wao tho most realistic and applicable.
Its accuracy can only be determined over the time period for

much projections were mafia.

majggtivg fig: Predict the proportion of pro joctod retail food
ooloa which will bo associated with the different types of
retail food sales.

In Figure 22 of Chapter VII, data is given which shows
the percent of total retail food color which occurrod in each
of the general typos of food stores during the observation

period.

169

is might‘bo capected. tho percent of total retail
food sales taking place in grocery stores has incronoefl over
the twelve your period, while the proportion of sales attriw
butod to the other types of food stores decreased. Assuming
thia trend continues, by 1980 approximately $3 porCént of all
retail food sales will occur in grocery stores.

Relatively unexpected. howevor. is the alight coolino
in the relative importance of food sales in roatooranta. The
aota thou that despite a continued increase in the oboolute
volume of food sales in restaurants. tho importance of ttio
soleo volume rolativo to total retail fooo sales will slowly
ficclina until it reaches 10 percent in 19:3, whom it in exc
poctod to lovel off it not increase slightly.

Sales in specialty food otoroa such as dairy product
otoroa and truit or vegetable markets is expected to aeoreooo,
relative to total food solos, until it is loss than 3 percent
in 1930.

Also. by 1983 retail food solos in taverns and clubs
are oxpoctod to decrease to approximately 5 pcrcont of total
sales. The remaining 2 percent of total 1930 projected
potential retail toad color will ho tho result.of sales in
miscellaneous storeo such as flolicatoooons, candy stores. etc.

in summary, the grocery store will eventually become
the oominant outlot for all food sales. Therefore. the
grocory store organizations should be the primary sector of
the retail food infiuotry which is interootod in solos volume

projections.

170
Objggtivg £5: Derive, explain, and analyze income elasticity
of the demand for food in Midhigmn during the twelve year
Observation period.

Table 26 of Chapter VIII illustrates the prcccflure
uscfi to canvert the per capita income coefficient of the
multiplc lifiear regression equation into a numerical measure
of the incame elasticity of the demand for £005. Tahlo 27 of
the same chapter shown the results of the conversion as it
was applied to the regression equations of tha fivc selectad
cmmties and the estate as amola.

The teaulta show that thc incamc elacticity of the
eafland for toad tot'tho entire atate:ot midhigan is .542.

The elasticity of the five selected ccuntiea varies somewhat.
Rowavcr, once those ccuntiea chewing a negative income co~
efficiart are disregarficd and the tourism effect in removed
from the upper peninsula counties. theta is found a consirtenCy
in those ranaining counties whereby those cnuntiea with the
highegt level of per capita income alga hava the lowest in-
Cfiflfl elasticity. Thin seems quite logical since it is norm~
5113 expected that as one'a inccma level increases, he will
cgcna a cteaflily dacreaaing prOporticn c: that increase in

incame on fooi products.

 

Ch active £6: Analyzo the results and convert the projec»
tions into suggestions of how this data might be applied by
the retail food indunttios in their future planning.

171
Chapter eight deals with tbs interpretaticn of the

teat results in the context of applying projections to tha
rctgil E003 influstry and its overall market analysis.

The size of tha crganizaticn interastefi in the Gfitv
(lccxl, regional, or national mewhsrship) lfirgely determines
the: nit-«3 of? the market 0'! which these projrsctiansa are maxi-3:2.
Far example, the small locrl retail food store association
mry only be interested in tha projections for onc particulflt
ceuntg, whereas a regional group may need to use and avply
ant: from a large metrnpolitan area and anational food chain
be interestcd in a county by county Pnalygis and campariaon
thraughout the entire etata.

The prajcctiona shcw a 150 percent increnco in {he
acllnr valume of retail fcofl 3:193 in ridhigan fram 1950 to
1933 aha a 109 percent increase in the phyaical vclume of
£333 products being handlefi. ?he retail food inéustry muzt
eciie in what areas of the state theta increases (0r
decreases) will be mast pronounced so thfit aflditional facili~
tins can be antnhlished to cape with thia increawefl prnfluct
fiznvnd. Regaréless of the direction, if this prOFOEEd er—
pcncion of retail food marketing facilitiae is t9 he horimnn~
tfil, vertical, enlargement or existing cutlets, or the afidifi
tian of neW'outlets, the industry must first knOW'th. area of
this yatential increasad salea before any deciaions can be
mafia on the expansion process. It is in this area that tha
prc acted potential retail food sales of a given area (or

areas) can ha most apprcpriately applied.

172

Testing the Hypothesis

The final discussion will deal with the acceptance or
rejection of the hypotheaeo presented at the beginning of this

 

Once the significance of factors has
been determined, statistical proceoures such as a multiple
linear and simple curvilinear regression analysis may be
applied to accurately project into the future potontial gross
retail food sales by county, motrOpoiitan area, and state.
Even in all duo respect to tho complexity of the
genoral hypotheses, it is acceptod.on tho following bases:
1) Two factor! wore round.to hnvo a significant effect on the
volume of retail food sales and those relationships were
later used in the projection todhniquo.
2) The Composito Method of regression analysis and projec-
tion, used in thin paper. produced pmojoctions of retail food
sales more realistic «no applicable than the most commonly
used techniquo.
. 3) The Composite method is basically justifiable by economic
and statistical theory a: well no logical roaaoning.
4) Deopit. coma unexplained irregularities. moat consumer
behavior pattornn were consistent with the test results. 1.6..
Engol'a curve.
5) Final evaluation of the accuracy of the projection: must
to delayed until the time. for which the projections were

made. has passed and the actual sales volume determined.

173
fig? Pvfiopheggg~§;;, Despito‘tho emphasis placed.on the
measurement of the incomo elasticity of the demand for foofi
on a national basis, a much more detailed analysis 13 necea~
sax? befaro this national measurement can accurately‘be
&pplied to an inéividu&1 area as small as a onunty.

This hypotheses to also accepted on the‘basia of the
infnrnattm presented in Table 27 which ahows that income
elasticity varies graatly among countlea. 836 the income
elasticity for the state (.542) been apgliad to aadh infiiviu
anal caunty, the raeultl woula‘be extramely misrepresentétive.
Likewise, therefaro, 1t 13 alao‘highly inaccurate for anycna
ta arply the national income elasticity to any one indivifiual
gtpte. A detailafl analysis must be made of the apecific area
uhficr cansideration,beforc 1: can be determined if that area's

firm inmc Masticmty coincides with being apglliead to it.

muh gynntueggaߣ?u The prOportion of total gross retail isod

 

tfilfifl attributed to qmocery stores will Change only slightly
in Pithigan's naar’tututo.

This hypotheaeo is rejected on the §asia of the trends
shown in Figure 22 of Chapter VII. As was previously fi1$~
cursad under abjectivo #4. the trend inexcuted that by 1939
almcet 80 percent of all retail food sales will occur in
gracery stores. This is almo&t a 33 percent increase in the
rrohcrtion shown in 1950 and a 17 percent increase tram that
prwyortion shown in 1962. This aeans to be a rather signifi-
crmt Change and nerves as justification for the rejection of

tha'hyytheses.

174

055 gvn¢+hegee 5 3 Relationships found betxaen variable

 

factors and gross retail food sales vary so greatly among the
83 "ichigan couztiea t} zat an in: vidu~1 cmunty 55513515 555t
be confluctad to obtain accurate and applicable results.

Intcrmation presents: in 5553 2 thru 5 in

in
:‘71
(‘7
Q
N
A

rrcvide the basia on which this hypcthe 515 15 acc eptad.

31110 te*5t1ng the affect of the n""or of foo‘ 5t.or 55 553 the

‘3

par cspit5 dispos5.le income h55 on deflate: per cvpita

retail $535 55155, 52 wws found to vary frmm .21 to .9€, El
varief iron 6.3 to «18.87,? .2 varied 1:55 - .167 to . 57 :55

T? varied from -15.5 to 6.73 in the rultigle 11555: regrcnsion

equation 5555 to project: €551 atefi for 553155 53th 11 £505

55155. T515 vxriation: in the imrcrtance, 55351tur35, flirtation

555 significance of the effect the two inficpnnflent varitfilmg

have on the fiependont V5riablo, illustrates the valiCity mi

the'h"po hoses. Eefore 5n accurazta a n5 553115*?m1...5rkct

55515515 can be made, a county 5y caunty study must 55 can~

ducted no 55 to talze into conr1:.?er 5: on intra-county differ-

GKCGS.

Concluding atatenent

Tho 555d for lonqwrun economic projactiona as an aid
in policy formulation is fairly obvious. Host ecanomic
decisions, whether to invest in a haw retail food outlet.
build a dam,o or'to continua ono‘o evocation, involvo ju33ments

about the future. 55 the extent that it 15 effective, the

long-run appra1551 may be proven incorrect, 1: problem 5:555

175
are rnrmw1~5 and action taken to correct them. ?cr as 1:.
13:33.3 once stated, 'Eccnoflc projections, in influencing 1661:.

run judgments ana galley farmulation,_mcy genergta the con61~
t5 “oz-1:3 1:511 51 rrove them 1131736.").

335115111 food mane-1.13113 15 a "11361;! (“1.61351 131.191.518.13.
T66 Easters effactinq prafits are almost ceuntless: the
r:'::‘.“t1031'2 1pc; ‘rpetx-J'een them are intric‘xte. Weil 2111213133 3363-:

new states is vitally important, as is pricing, contrnllnng

labor exnenae and making superior merchanfiising decisionn.

I?

{1:13.113 55:01:11 13: e 6:32: 3:55) to 36110511' hes-33 3611113115: 35113303131-
firizztions 13251113:an tar-7:5-ts 1.49 615551131111.

These unifitia con5itione 6efine the fund3fient3‘
eccnswlcs 91 fihis 1 6d"try nnd.h66ce shape its h-“6336366t
33337 33:37. 511-311-6332 13‘3“? ire-ere Of these fierce?” harm-332$, 1:3,
‘33.3T“.‘TI}’ nut 531313123351. "53.21.13.111 r11} than 61:11 :;5-é?ter'v1.n 17133 1111:3353

wtrtljr their 1525.317th on gfirr-fitn and other market conditin'x;

1." 191531: 1.1-: 516352666 in take 1th"? 631*170pr1'3te entry}. In 33236333617117.»
163 Q61. pn-er,1t hfis keen mv o“ject1ve tn cmnt just 066 61
5:112:39 1:»ro';..-le'i;3 613.1! rw-gxiirezxe'rzts: 1:1 :11 n (2311 11.3122: - a more =1“..”‘..‘._‘.Ct
li'ht - an that bet 6 695131066 can be mc5e 63 better 16*

'crr..ct--.‘i ovyucwvva r" '1' ether 1.63.1 wit’ain the f’wni 3331 tot? 1.1

ffiafi influwtry.

lazily. p.11 3

BIBL 1013335321?

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State University Feb. 19’4

 
   

  

University of Pennsylvania. Stua o
Inoom AA and Savingg. Vol. III, tgbu atAa by :96
Eureau oi Labor Ltatiatics for tho tfha.xt on School of
Einanca and Commerce. 1956. pp. 133-140.

  

 
 
  

 
 

Vaughan, olive E. “An Appraisal of the B.L.8. Consumer Price
Infiex.” gougggl of margetigg. Oct. 1953. 18:13AA145.

Ainstcn. Clement and Mable A. Smith. ‘Income Sensitivity of
Consumption Expenditures. » E Carl 8 ¢ megs,

January 1950. p. 1703m

   

Wolff. Reinhold P. "Estimating the Aarket Potential of a
Floating Population.“ al of Na «at he, July 1954.
19:12-17. ’

   

 

Daft, Kenneth D.. and Brown. i;ar1 H. “Michigan's Retail Food
mfiuAtry - Statistics on Ponulation. Store Lumbers and
Eales, hv State. County And.AAtr0politAA ALAAA.“
Aicnigan Atata University. Agriculturn Eleonomica
Bepartment, Juno 10. 1963.

Daft. Kenneth D. "Arofitability at a Transition Point
Derivoi from Technological Change in the Physical
Diatribution and Handling of Retail Food Products."
M.L.V.. M.T.A. 831. Bee. 5. 1953. pp. 24-26.

Herrmann. Robert Omar. “An Investigation of Differences in
Income Elagticities of Demand for Food in Aouseholfis
of Diffiering Size and Composition.” Michigan State
University. 1961. p. 63.

Kiel. D.F.. and Ruble. W.L. “Calculation of Auitiplo Regres-
sions. Use of CARA Routine." A.E.S. Progria Descri"-
tion 4. Sent. 30. 1363. bzidhigan State University
Computer Laboratory.

KiAl. D.F. and Ruble. W.L. “Formulas Used in CORE 9outina,'
A.fi.fi. Program Description 12. Oct. 15, 1963, pg.
4.9. Aidhigan AtAtA Computer Laboratory.

153

Kornblau, Curt, Director of Research, Sugarmarket Inatitutc.
paper presented on Hov. 1. 1963 at Michigan State
University in & foaa marmeting seminar,

LaLcnde, Bernarleoseph. “Sifferantlal 1n Supermarket Brcw-
1ng Power and Per Capita Sales by Store Camplex and
stora Size,“ Michigan fitate Ucivarsity, 19%1, p. 119.

Mandarscheid. L.V. “An Introduction to Statistical Testing.“
figticulture Economics Himec 867 - raviaaa, Feb. 1953,
99¢ 6‘90

Vocs, Thomas Neil. “Some Relaticnabips of Selected Socion
Economic Factors to Food Consumption and Expenditures."
flichigan State University, 1952, pg. 140~é1.

'Thc~Mezget Movement in Retail 800d Distribution,“ National
Association of Retail Grocata, 1955-53, Chicago 1959,
pp. 25-7.

Walker. 3. Osborne. “A Etufiy of Retail Food store Facilities
Which Will Head to be Conetructed 1n Addition of 1960
Eacilttias, From 1960 to 1993 in the Chicago-fiorthwest
Inaianu Stnnéard Conaolidated area Resulting from the
Projected Increase in Pcpulation an& the Changes in
the Ratios of Non-Whita and White Segments in Certain
Siviaions of the Area." Jewel Tea C0,, Inc., May 23,
19520

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31

VIII
l’.5'
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Percent of total population urban, by county, 1960.

213

 
   
     

    
 
   
 
   
  

   

Q

I

.ss
\\‘s

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5.6

Lawn Quartet
Second Quarter
Thu-d Outta

Rub“: Quarter

\u

Into 0 11A!

 

Percent change in rural population, by county, 1950 to 1960.

 

 

 

 

 

lat-2.000,“...

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

k” ....-.L.) 1 (Extribution of rural population outside places of 1000 to 25

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I I I
1...... ...... 5.. .9... 17...}... 19.2 ....
I I I I I I I I I I I I 4 _
w " I‘ A": A V luv /
///II//’:u’I’:-Il;‘r:/ 593/
50.5/ 1.7.2“ ’19,0' 1945' 4.5.0' . - ,
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’ , U - 'wl / .. 1.9.7 10.7;
’ ’ ' ’ ' / °// / ‘ ’
5., I r/ 50.0 /50. 51.8 w“ :z:
/ 4/4/sz .A
52.5 - ‘////// 53.8 51.1
50.8 51.7 49.7/ 50.3'
.v‘ // 53-0
I I I I I I ‘b- ~‘ / 53.7
I 49.4.! I 51.1. 51.0‘1 55.3 50.5
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50. 55.0 54.5 55.5 60-1 5“"
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53.21 50.5% 52.1 51.5 51.1 50.9 51.6 .
/// ..

 

 

 

 

   
 

Percent 18 to 64 years of age, by county, 1960

 

’ I
E] ‘0'." We 13 z 9.7/
V ' v/ l ’ I I I
II], “coal Quartet 1‘2 2. . ’ ’ .
“‘1'“ 9““ 12.8 p 12.1 11.2 13.1 13.3 10$

 

 

 

 

 

“a. . 0.11 11-6 11.3

11.7 -

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7, 11.5

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t . I I 9'2
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.. I"; 5" I a I I v '

12.5 ' ', I I ggll /

2 22.21%: g in.

531%" 11.5 1 “794/
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”...-3:431} RH unno- n‘ nfin a...) an"... I... ....._l... Innn

   

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. t It I I
' 0.3/ ’ 6.0’ , 0.133
“5 “Quarter 23 1.3 (’I;’__’_
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Pea-gent :acnwlxitex- bv countv. 1960.

216

....p1

D unCmGAN. 1950

 

 

 

 

 

 

 

 

 

 

- 4
5 some“. use ’55 ”—“1‘
I' ‘
[—v 70.14 '1
65-G9t

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Age-sex pyramid for Michigan, 1950 and 1960.

I'17.2 .
I
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III
I I I,
40.6
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‘29.3.;"31-"' .9 -
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Percent change in total population, by county, 1950 to 1860.‘

217

30.
A.
2.

 

 

 

 

 

 

61.1

 

60.0
39.7

 

 

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Percent under 18 your: of use, by county, 1060.

APPENDIX F

MICHIGAN COUNTY CODE NUMBERS

2'19

 

 

 

 

 

 

 

 

 

    
   
 

rL_.L«_.

I a
l

MENOMME!

55.

WiSCONSIN

“um"?!

0010 3L 20 u :0 count:

...-“-

a e 17 . . C
_,__3 77 .Lfiiixmsc J‘1____.__, _l : E;
‘ can ' I 149'. . .,

corvagumnv gun: AIM) ? C if v s'm A )

APPENDIX F

County Code I‘Mmbers

 

 

 

 

LUCE ! ?
'l “8‘ !‘ 'X

CHIPPEWA

 

   

12,

i SCHOOLCRAFY

21. l

 

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