EH: W: U? I'UNMIIUIW HEWEUIIG‘ an isn‘t—unv-

THE QPERATIONS 0F MICHEGAN ELEVATOR FARM
SUE: ELY BUSENESSES

 

Tfiesis E09 Um Deg?“ of N1. 5.
MECEIGAN STATE. UNIVERSITY
Arthur J. Pursel
1957

IIIIIIIII IIIIII III III I II

3 1293 00848 9357

J
AfiChigan State
University

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES man on or before ode due.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

L_____

%I— :I

MSU Is An Affirmative ActIchEquel Opportunity Inetltuuon
cmflnO-DJ

 

 

 

 

 

THE USE C? FUKCTICKLL éNgLYSIS
III SILK-"III? 31:3 P335731 N3 CT ICICHIGSJI

'r" t'". "219v \‘ZTT'Y‘TZ'rY “5"71'7'“‘"""‘:"W
.LLlLfgtICR‘:-.lir. udf¢L va-Ll‘-:J~J~)4:JD

By
.23r32U3 J . PURSE

o .- Y"\r"‘
I _.‘_
~J

>-\
A;

3

A x
:1 J.

re-

'...i.CT

Submitted to the College of Agriculture of Michigan
State University of Agriculture and Agplied

Science in partial fulfillment of the
requirements for the degree of

NALTER C? 33 EECE
Department of égricultural Economics

1957

Arthur J. Pursel
ABSTRACT

The purpose of this study was to obtain estimates of the
marginal productivities of the resources used in the oner-
ations of Hichigan elevator—farm supply firms. It was antici—
pated that these estimates would provide useful aids to
elevator owners and managers, boards of directors, management
consultants, research and extension personnel in analyzing
the effects of orooosed reorganization and expansion programs .
The real oroduct of the country elevator is service and
the empirical neesure of this service is gross margin. A
Cobb—Douglas type oroduction function was employed to determine
the marginal value oroductivities of the inouts used in per—
forming this service. This is an exponential equation which
is linear in logarithms. The regression coefficients are

S CHELI'S S .

(’l'

lees

PI)

determined oy the method 0
The marginal value oroduct of each input category was

then determined by the following formula: MVPX1= bi E(Y) or

Xi

 

the antilogarithm of the log bi + log E(Y) — log Xi, where
E(Y) is the gross margin obtained when Xi is the amount of that
inout used in the estimating equation, and bi is the regression
coefficient of Xi'

The data used in estimating the marginal value pro-
ductivities were obtained from the financial records and a
personal interview with the managers of 34 selected Michigan

elevetor-farm suooly firms. An effort was made to select firms

Arthur J. Pursel

which were tyticol in terms of the yrooucts sold. Cons der-
able range with es pect to tie groyor tions of inputs used was
desired in order to reduce the inter—correlation between in—

»reeter reliability of the estimated

(V
r.-
L)

puts and hence to assure
regression coefficients. This in turn increases the accuracy
of the marginal value products derived from the function.

The returns to each category of inputs for the "typical"
organization were found to be £320 for the labor (X1), $.179
for inventor y and accounts receivable (X2), $1.696 for direct
Opereting expenses (X3), s.d $2.68 for investment in machinery
end equipment (X4). The gross margin was estimated to be
$83,674 when he geometric mean amounts of inputs are used.

The marginal value product of labor is not significsntly
different from its rmrrin l f; ctor cost, therefore, it wss

concluded that thi input should not be increased. It was

0')

oelieved the t incr ees ed quality is 3 more appropriate goal
with respect to labor. It W38 concludei the t the inventory
and accounts receivable c:te cry should not be increased be-
cause its FVP wes approximately equal to its If C. The leek
of a In easurins device which would simultuneously me; sure the
interrelated fectors of level, composition and rete of turnover
makes it difficult to eveluete inventory adequately.

The two adjustments which seem most edvissole are: (1)
increase the expenditures on direct operating expenses while
all other inputs constant, and (2) to increase direct

operating expenses end the amount of investment in macIiinery

irthur J. Tursel

and equipment, in least cost combinations. However, the case
for the latter adjustment is not strong when machinery and
equipment have a reservation price of 20 percent. ”he first
adjustment is primarily an increase in utilization of existing
facilities because Operating expenses are those which vary
with the physical volume of products handled by the firm. The
fact that a high rate of liquid capital accumulation is ob-
tained substantiates the case for this adjustment. Liquid
capital accumulation is thought of in terms of traditional
accounting procedures and is net profit plus the depreciation
charge.

It must be recognized that the country elevator is a
merchandising firm as well as a producing firm, therefore,
the instigation of the pronosed adjustments must also be
accompanied with management practices which will increase the
quantity of services demanded from the firm.

A measurement of the demand for a given firm‘s services
indicates that it is relatively elastic. Therefore a major

means of increasing the utilization of capacity is to cut unit

gross margins and consequently increase total gross margin.

.tmproved WWW

Major Professor

Th3 USE OF UIJCTICHAL .‘i-\' -‘LLT'L 313
IN EVALUATING THE OPE RA IICI‘ CF NICHIGAN

EV'TCE--;’N SUPPLY JLQILZJSES

A3 THUR J. PURHE

A ‘I‘HES IS

Submitted to the College of Arriculture of Michigan
State University of Agriculture and Applied
Science in partial fulfillment of the
requirements for the degree of

N?S'T ER CF SCIENC

['11

Department of Agricultural Economics

1957

7wiifi“

4.- .2 z o a:

ACKEONLEDGEHENTS

The author wishes to eXpress his sincere appreciation to
those individuals who made this thesis possible.

Special thanks are expressed by the author to his major
professor, Dr. Vernon L. Sorenson, for suggesting the problem
and rendering guidance and encouragement at all stages in the
deveIOpment of this thesis.

The author wishes to eXpress his thanks to George G.
Greenleaf, Coordinator, Elevator and Farm Supply Short Course,
who has given freely of his time and advice when they were
sought by the author.

Financial aid in the form of a research assistantship
vhich was provided by the Department of igricultural Economics
headed by Dr. Lawrence L. Boger, made it possible to carry

ut the study.

Hrs. Arlene King and members of the statistical pool were
of great assistance in making the computations that were
necessary in the empirical portion of this study. Thanks are
expressed to firs. Phyllis Quinn and Hrs. Joann Prendergast
who typed the original manuscript. The writer is also indebted
to Hrs. Dorothy hart for her effort in typing the final manu—
script.

The author greatly appreciates the encourasonent that his
wife, Jacqueline, offered at all times through the course of

his studies.
Responsibility for errors which may be present in the com-

pleted work belongs to the author.

Ch

a.pter

ijectives and F
The Sample . . .
1:3 -.I - 1'1“ 3 -L “12,-".

Operating

The farket Service CuQ

Iatu re of the I
the Elevator-Tc

Rules for Input Categoriz

7 Cr o“*
.4 .‘ ex“:

0 O O
J- 1
onOQS
O O O
n 4" rx‘rr
L .4 ILLL

Relationships

7‘1

jut of he Firm

oduction Function for
m Surply Business . .

Tim retical Eackzrcund

ation . . . .

Optimum Combinations of the Factors

of Production

The Cobb-Douglas Production Function .

{110 ns of th 1e Coob- -Dou<las

E1630 CI ‘fi:11Ciue Q Q

Computation of
Services . . .

Ll
Cf
(1‘
H
C)
Cr
H'
0
CV]
H

Computation of the h

*1 7’1 TR‘Y‘I "WW" ”1min . av
4‘ILTAINKJ LL12; L‘LiuVLIK/i‘l o 0

Results and

Ratio Comparisons . .

Short-Run

Adjustment .

Long—Bun Adjustment .

Effects on Fet

of Increasing Direct Operating Ezzpenses
achinery and

Investment in 1%

arginal

Evaluation . .

Value Products

Profit and Operating Capital

Equipment

and

U1 \fl U4 l-J F4

C9.

10
12

d

16

16

R)
C)

m
U1

V

;;l “. iLfirS 5 CF 123:1 ‘IDTJI I, 1:) o o o o o o o

A Further Comment on the Cperating

Framework of the Richigan Country
Ble’ngtor O O O O 0 O O O O O O O 0

7s {VfiVr ”TU "x‘fer' f-Tr‘u-j‘w
[JIM 1.- -—$-L_L £1-‘D 3L- 0.1.1.11 Q4L’i\~b o o o o o 0

U)

E.' -VDI:{ o o o o o o o o o o 0 o o o

JDILLIC31ifier lY o o o o o o o o o o o o

H
m

C'KI
n,
1

U1 C
H (D

Table

l.

13.
14.

15.

LIST C? FATLES

Percentage Eech Source of Cross Kergin
is of the Total Gross Kargin . . . . . . . . . .

Example: Computation of the Infiex of

Karketing Services . . . . . . . . . . . . . . .
"Usual" Organization and Estimated Kerginel
Value Product of 3Q Elevator-Farm Sugply Firms
in Richigan, 1955 . .

Comparison Between th

e Estimated bi and the
51* necessary to Equete {VP

, end PFC" for the
X: J\.i
3h Elevator-Perm Surply Firms Studied in

.' 1 h .~
1110111,;an o o o o o o o o o o o o o o o o o o o 0

Changes in TVE's for the "Typ col" Greeni-
zation Resulting from Incross r
Cgersting Expenses from gl3,3

Changes in the {VP of Xq and X4 as a Result of
, , .7- , .. ./ . , _
IncresSIng tne gxgenaitures on Direct Cperet-

ing Expenses and Eschinery and Equipment
Investment . . . . . . . . . . . . . . . . . . .

Changes in KUP'S for the "Typical" Orgonizeticn
Resulting from Increases in Direct Operating
Expenses sni Inves ment in Kechirery and
Equipwent . . . . . . . . . . . . . . . . . . .
accumulation of Liquid CCfltcl then Facilities
are Priced at Henlecement Values . . . . . . . .

Comparison of the Sources of Gross Kargin . . .
Compsrison of Capacity Utilization . . . . .. .
v A
Comparison of I? , 1C, and Y . . . . . . . . . .

Eethod of Pricing, Number of Firms and Per-
centage Using Each Kethod . . . . . . . . . . .

Summary of Input and Output Data . . . . . . . .

Components of Gross Rersin end of Each Input

ED

CCitegOI'y o o o o o o o o o o o o o o o o o o o o

Computation of Kerginal Value Products . . . . .

30

33

41

5o
53
53

(J\

O\
(I) O

70

[‘3

List of Figures

L.”
In

(it.

affects on the JV? of Labor for the

”Typicel" Organization Reecltin5 from In—

creasing Direct Coerating Exoeuees from

113,335 to 527,250 . . . . . . . . . . . . . . U2

Trial Combinations of Direct Cgerating
iXUGESeS (X2) and Hechinery and Equipment
Inv

estrent (X4) . . . M5

CHAPTER I
INTRODUCTION

Objectives apd Methods Used. The major objectives of
this study are (l) to measure the returns to various input and
investment categories used in selected Kichigan elevator-farm
supply firms and (2) to estimate the effects of Varying re-
source combinations on returns to these input categories.

This study is concerned with the problem of efficient resource
use in the Operation of country elevators.

Probably the major problem in the Operation of elevator-
farm supply businesses is determining the quantities and pro-
portions of resources which are most likely to maximize net
Operating profit. However, country elevators are merchandising
firms as well as producing firms. Therefore market comple—
mentarity among products is also an important factor in deter-
mining the profitability of these businesses.

Elevator owners and managers, boards of directors, manage-
ment consultants, and marketing firm research workers are con-
tinually faced with the question "Will it pay?". Generally,
this question is of concern when a reorganization or eXpansicn
program is prOposed. It was hOped that results of this study
would offer guides useful in analyzing the effects of proposed
reorganization and expansion programs.

Theoretically, the conditions of maximum profit are met,

when the marginal value product of each input is equal to its

marginal factor cost. 178 most logical procedure in adjusting
a firm to a more nearly Optimum economic position is to in-
crease the use Of those inputs which yield the greatest returns.

Cobb-Douglas analysis is used to Obtain estimates Of the
marginal value products Of major input and investment cate-
gories employed in the production of market services by the
firms studied. While Cobb-Douglas functions have been used
in analyzing farm firms, very little use has been made Of
this method in analyzing firms which market the products Of
agriculture and furnish the necessary production items for
farms.l/

The Operating relationships and the nature Of the pro-
duction function for a country elevator are discussed in
Chapter II. A brief discussion Of the Cobb—Douglas function
and a.review Of past studies in which this function has been
employed is also given in Chapter II.

Chapter III deals with four major items. The first of
these is the fitting of the function and a statistical evalu—
ation Of the results; second, the computation of the marginal
value products; and third, ratio comparisons of net Operating
profits to net fixed assets and replacement values. The
fourth item considered is a short-run and long-run adjustment
in the factors of production and the changes in net Operating

profit as a result Of these adjustments.

 

l/ Recently two studies have been completed at Kansas State
College on resource returns and productivity coefficients
for grain elevators in Kansas.

3
Chapter IV deals primarily with an analysis Of the diff-
erences between estimated and actual Operating returns 2% and
secondly, with a further comment on the Operating structure
Of the country elevator.
General conclusions and recommendations obtainable from

the analysis are given in Chapter V.

The Sample. Data were Obtained from financial records

 

Of the firms analyzed and from a personal interview with the
manager Of each firm. Several major criteria were established
in selecting the sample.

An effort was made tO select firms which were typical
Of the elevator-farm supply business in Michigan - typical in
the sense that the products sold and merchandised by these
firms are essentially the same. Organizations with an un—
usual product mix were not included in the sample. Those with
exceptionally low dollar volume (below 200,000 dollars) and
those primarily of the feed store variety were excluded from
the sample. Considerable range with respect to the size Of
business and the proportions of inputs was desired in order
to assure greater reliability of the estimated regression
coefficients.

Elevators Operated by chain organizations were not in-
cluded because Of the overlapping accounting and managerial

services employed. A partial exception to this rule was

 

g/ Actual Operating returns is an index Of marketing services
which eliminates the difference in absolute unit gross
margins taken by the firms studied.

made in the case of elevetors associated with Farm Bureau

'.

Services. However, this was not considered a serious error
because of the decentralized accounting and management pro-
cedures practiced by Farm Bureau Services. Originally financial
records and interviews were obtained from 42 country elevators,
however, due to insufficient information it was necessary to

reduce the number studied to 3#.

CHAPTER II

THE ANAL TICRL FBANEEOBK

Qperating_3elationshins. The elevator industry plays

 

an important role in Nichigan agriculture by meeting a large
portion of the marketing and distributing needs of the farm-
ing community. Elevator-farm supply firms are assembling
points for the movement of grain through the marketing system
and into the hands of the consumer. The country elevator is
also a major distributor of items required in the production
of field crops and livestock products

These firms handle processed and unprocessed grain. The
greater proportion of processed grain is derived from the
elevator's custom feed grinding and mixing Operation, while
a smaller proportion is obtained from retailing "complete"
feed mixes. Feed supplements a e added to a high percentage
of the processed grain handled. Host of these supplements
take the form of protein additives such as soybean, linseed,
cottonseed meals and/or prepared commercial protein supple-
ments. Other feed ingredients such as salt, antibotics, and

grain.

‘1

liquid molasses are also added to 4'he processed
Unprocessed or merchandised grain is sold to three major
classes of buyers: (1) terminal grain elevator companies,
(2) other country elevators, and (3) farmers.
In classifying the market service output of the firms
studied, unprocessed grain, processed grain, and service in-

come are grouped into a single category. The guiding principle,

in grouping these products is the h gh degree of complemen-
tarity existing between them. The greater the degree of inter—
relationship between products, the more reason for aggregating
them into the same category.2/ This principle was also used in
grouping the many other items handled by country elevators into
the sideline category.

The firm which provides a farmer with those commodities
needed in livestock production is very apt to obtain that same
farmer's saleable grain. In this respect, feed and merchandised
grain Operations are complementary in the market.

The sources of service income for the country elevator
are: (1) custom grinding and mixing of livestock feed, (2)
handling, trucking and storing grain, and (3) cleaning and
treating grain for seed. Service income, as the above list
indicates, is primarily derived from grain handling and pro-
cessing Operations. Vertical integration of service operations
with both processed and merchandised grain leads to a greater
volume in either or both enterprises. In this respect service
Operations exhibit both technical and market complementarity
with processed and merchandised grain. Technical complementarity
exists because some of the facilities used for service Oper-
ations may be used for grain processing and merchandising.
Market complementarity exists because grain merchandising and

processing volume may be increased as a result of providing

 

3/ Richard Phillips, Nanaging for Greater Returns in Country
Elevator and Retail Farm Supply Businesses, Published by
Farmers Grain Dealers Association of Iowa (Cooperative)
Des Hoines, Iowa, pp. 3b and 35.

the service.

Technical complementarity between unprocessed and pro-
cessed grain is greatest in what might be called the dual-
purpose plant, because part of the same facilities are used
in handling grain as are used in processing feed. The
seasonal nature Of grain harvests and livestock feeding, makes
this type Of Operation possible. Technical complementarity
between these two activities permits higher utilization Of
machinery and equipment, and consequently absorbs idle capacity.
Dual-purpose facilities provide Operational flexibility and
reduce risk caused by shifts in the composition of the grain
volume handled by the firm. ‘It is apparent that an in-
crease in the total volume of grain (processed and unprocessed)
handled may lead to competition for the available facilities.
This competition is not serious in those firms primarily
merchandising oats and wheat, because these grains are har-
vested at a time Of the year when feed volume is lowest. How-
ever, if the firm in question merchandises large quantities
Of corn a competitive relationship could exist, because corn
is normally harvested and sold when the feed business is at
or near peak volume.

A partial answer to the competitive relationships exist-
ing in the dual-purpose plant, is separation Of grain and feed
facilities.IHWhe facilities are separated, the firm can handle
a greater total volume Of business. Separate facilities permit
handling harvest-time runs, and at the same time enable the

firm to maintain its feed volume. However, an expansion program

8

of this type requires increased investment in fixed facilities,
more specialized exployees, and consequently the ne essity of
increased sales volume.

The question now presents itself as to when grain and
feed facilities should be separated. It is extremely diffi-
cult to give a concrete or empirical answer to this question.
The factors which must be considered are: (l) the present
sales volume in feed and grain, (2) the seasonal nature and
type of grain production in the trading area under consider-
ation, and (3) the potential increase in grain volume that

result of increased capacity. If all these

07

might occur as
questions can be answered with a reasonable degree of accuracy,
it would then be necessary to make a comparison of the costs
relationships for each method. Upon completion of the cost
analysis, management would have a guide to the decision of

whether to separate the feed and grain facilities.

The he ket Service Output of the Firm. The relationship
between merchandised grain and processed grain has been dis-
cussed in physical terms, however, it is impossible to devise
a physical index which will measure all the products handled
by these businesses.

Sideline items run the gamut from fertilizer to print
feed bags, out of which farmers' wives make aprons. In con-
junction with the profit motive, the purpose of sidelines is
to increase competitive effectiveness and make use of idle

capacity. Idle capacity may be labor, plant facilities, or

9

managerial ability. Sideline Operations absorb idle capacity
and provide an opportunity to gain additional grain volume
from the same farmers who purchase sideline items. In this

respect, sideline items and grain are complementary to each
other.&/

A substantial prOportion of the elevator's operating in-
come is derived from services which are not associated with
the purchase and sale of a commodity. a service is also per-
formed in handling and distributing the many products bought
and sold. The sale value of any commodity is composed, in
part, of the value of market services performed in handling,
storing and processing. These services are similar to those
performed independent of the purchase and sale of commodities.
The services performed in these two ways then, represent a
homogeneous output of the firm. The dollar value used to
measure these services is the gross margin derived from each
activity carried on by the elevator. The average gross margin
for the 34 elevators studied was $98,56U.

The following table shows the average percentage of gross

margin derived from each source of gross margin.

Table I. Percentage Each Source of Gross Margin is
of the Iota Gross Kargin

 

Nerchan- Pro- Fertil- Petrol- Farm Ser-
dised cessed izer Seed eum Supply vice
Grain Grain Inc.

 

Percentage 18.08 20.09 6.56 5.71 10.08 17.23 22.25

 

 

3/ Joel Dean, Fanagerial Economics, New York: Prentice Hall,
Inc., pp. 119-120.

Table I indicates that grain operations are the primary
sources of service revenue for these firms. The gross margin
derived from merchandised grain, processed grain and other
service associated with grain Operations is 60.4 percent of
the total gross margin. The proportion of gross margin ob-
tained from these three sources is also a fairly constant per—
centage amongst th different firms. Only nine of the firms
obtained less than 50 percent or more than 80 percent of their
gross income from grain operations. In other words, 25 of
the 34 firms studied derived from 50 to 80 percent of their
total gross margin from grain Operations.

Nature of the Production Function for the Elevator—Farm

Supply Business. In the previous section commodities handled

 

by the country elevator were classified into two pritary cate—
gories. In the next few paragraohs a justification will be
develooed for measuring the output of an elevator-farm supply
firm as a homogeneous set of darket services.

The commodity inputs can be specified as:

(1) 21 = grain (2) 22 = sideline items

The total value of cutout when measured to include the

value of both the comnodity and narket services is:

Q1 F [(21). X1: ' ' ’ ” X11]
'32 = P832), Xl’ ' ' ' °’ Kn]

The commodity inputs (Z1 and 22) are identities with the

physical outputs and X1 to Xn are the inputs incorporated with

the commodities in the marketing operation. The value change

between the commodity inputs and contodity cutouts arises to

the extent that non—connodity inouts (X1, ....,Xn) add value
through the incorooration of market services with the commodity.
Since there is an identity between the commodity inouts and

the cutout in both a physical and value sense, it appears ir-
relevant to include the connodities handled as a cart of the
output of a marketing firm such as the country elevator. If
this premise is accepted, service is the real oroduct of the
elevator—farm suooly business and the financial measure of

this service is gross margin which includes the difference be—

led, and

Q.

tween the nurchase and sale value of commodities hen
direct charges for service oerformed without the ourchase and
sale of commodities. The value oroduct for the elevator, then,

could he stated as follows:

d
Y =.£;

.1
U

133(plj - p23) + Q = F (x1, x2, x3, Xn|X5,....,Xn) + U.

where Y = index of marketing services in dollars as measured

by adjusted gross margin. Zj = physical quantity of commodities
purchased and sold. P1j = price of a particular product sold,
P23 = price of a particular product purchased, 3 = 1 to d, and
Q is service revenue obtained independent of the buying and
selling of commodities. X1 through X4 are the amounts and/or
values of each variable input used in obtaining gross margin,
X5,....,Xn are fixed, while U represents the variations in

actual gross margin from the functional relationship. These

variations are assumed to be randomly and normally distributed.

12

Gross margin is derived from many sources. These are

~3gregeted into a single output category. Grain and sideline

~

{

Operations, as was the previous categorization Of all the
sources Of gross margin, are complementary tO each other for
essentially the same reasons, that processed grain and mer-
chandised grain are complementary to service Operations, as
well as tO each other. Market complementarity stems from the
relation between grain volume and the ability to provide a
complete or "full" line Of production items needed by farmers.
TO use gross margin as the index Of marketing services,
it is necessary to make certain computations in order that the
index will have the same meaning for all firms. This is
necessary to obtain comparable interfirm comparisons Of the
value Of market services performed. All firms must be placed
on an equal basis in the sense that any differences in the
absolute unit gross margins due to competitive relationships,
location factors and managerial policy are eliminated.- The
computation Of the index is illustrated in the next chapter.
In producing marketing services certain inputs are re-

quired. These are categorized as follows:

X1 = Labor

X2 = Inventory and accounts receivable

X3 = Direct Operating eXpenses

X4 = Investment in machinery and equipment

Xq,.., .,Kn = Unstudied factors Of productions which are

"

held constant

13

Labor (X1) is measured in man months Of productive labor.
This category includes all labor time except that devoted to
management and bookkeeoing tasks.

Inventory and accounts receivable (X2) is the average
monthly inventory, plus the average monthly accounts receivable.
This is used as a measure Of the liquid capital necessary to
Operate.

Direct Operating expenses (X3) are the eXpenses which
vary with the volume Of business done by the elevator. Such
things as power, teleohone expense, and hired trucking are in-
cluded in this input category.

Investment in machinery and equipment (X4) is the re—
placement value of machinery and equipment in the elevator.
These values are engineering estimates Obtained from Michigan
Millers, the agency which insures the physical facilities of
these firms.

(xg,....,x the effects Of these factors on the de—

n)

pendent variable (Y) are fixed at a Specific level.

Rules for Input Categorization. One of the major diffi-

 

culties encountered in carrying out this study was categorizing
the inputs in such a way as to gain a reasonable degree of in-
dependence between the inout categories. The proportions of
individual inouts within a category should be in least cost

combinations to be meaningful from an economic standpoint.

14

Johnsoni/presents the following rules as guides to be used in
categorizing inputs which have a meaningful relationship to
value of output in analyzing farm businesses. These rules
appear to be applicable in categorizing the inputs used by
country elevators.

(1) One reasonable rule for grouping inputs into cate-
gories is to group good complements together and
good substitutes tOgether, measuring the complements
in terms of "sets" and the substitutes in terms of
the common denominator which makes them good sub-
stitutes.

(2) Sets of complements and sets of substitutes can be
grouped into the same category very conveniently if
the sets are complementary to, 9§_substitutes for,
each other.

(3) Ihe converse of the above two rules follows: Input
categories defined should be neither good substi-
tutes nor good complements for each other.

Johnsoné/further states that the above rules have the

following adVantages: (l) the input categories so defined
ordinarily turn out to be the categories which managers have
recognized and named. (2) Managers ordinarily recognize sub-

stitutes and have a name for them which recognizes the common

 

5/ Glenn L. Johnson, "Classification and Accounting Problems
in Fitting Production Functions to Farm Record and Survey
Data", Resource Productivity; Returns to Scale and Farm Size.
Edited Earl O. heady, Glenn L. Johnson and Lowell S. hardin.

pp. 90-91.
fi/ Ibid., p. 91.

 

 

 

15

denominator. (3) Concentrates the analysis on the real prob-
lems faced by managers: The real input combination problems
are not concerned with combining substitutes and complements,
but, rather with combining categories of inputs which are
neither perfect substitutes nor perfect complements to each
other.

There are also certain accounting procedures that should
be followed in grouping individual inputs into categories.

It is necessary to put cash expenditures and investments in
fixed facilities in separate input categories or the marginal
value products will have little meaning as guides for obtain—
ing optimum adjustment. KVP's for cash expenditures would be
underestimated, and the h P's for investments would be over-
estimated, if the two types of inputs were in the same cate-
gory. This condition arises from the expected returns on
different types of inputs.

Cash expenditures are made on items that are generally
consumed within one period of production. Therefore, it is
necessary that the product resulting from these expenditures
have a value at least as great as the cost of the input. On
the other hand, investment items are usually consumed over
several periods of production, consequently, the return should
be high enough to cover that portion of the asset used in one
production period. Maintenance expenditures and depreciation
should be eliminated from the input categories, then the mar—

ginal value product can be determined for the investment category

16

and equated against a marginal factor cost determined by the
management. The marginal factor cost would include depreci-
ation, insurance, repairs, taxes, interest, and perhaps a

subjective cost for risk.

Theoretical Background. The theory guiding the empirical
part of this study is the theory of static production economics.
This body of theory is deduced from the law of diminishing re-
turns under a set of static assumptions which state the con-
ditions necessary to maximize profits. "The law of diminishing
returns holds that (except in very special instances) the
addition of a variable input to fixed inputs results first in
total returns which increase at an increasing rate, second in
.total returns which increase at a decreasing rate, and third
in total returns which decrease with increases in the vari-

able inputs".2/

Optimum Combinations of the Factors of Production. In
applying the economizing principles to the factors of pro—
duction there are two questions of primary concern. They are:
(l) optimum or most profitable combination of the factors to
use and (2) the optimum amount of all factors to use.

The general equation or expression for a production re-
lationship between total gross margin or the index of marketing
services and the factors of production, labor, accounts re-

ceivable and inventory, direct Operating expenses and capital

 

2/ Bradford & Johnson, Farm Hanagement Analysis, p. l13.

17

investn ent, plus an indefinite nunber and amount of fixed
factors would be:

Y = F (X1, 12, X3, XMIXE, .... ,xn).

This is a oroduction function and may be thouzht of as a
definite relation between gross margin (Y) an a set of input
variables (X1,....,Xn). The index of gross margin (Y) depends
simultaneously uoon the factors (X1,....,Xu) in some definite
way when the factors (X5’°'°"Xn ) a.re held constant. —/

In the operation of a country elevator the manager is
primarily interested in maximizing profit. It follows from

the law of diminishinr

,.
:.
52

returns, that profit will be increrse d

H

as long as the m2 rg inal value product4/of any Iactor of DIO»

duction exceeds its mars inal factor cost.lo/

This concept is illustrated in the following profit

r
,.).:

equation with gross margin dependent upon irect operating ex-

penses (X1) and investment in machinery and equipment (X4),

 

1

I 11:31:30, I). 1220

 

3/ Marginal value product is the change it the value of th,
total product (gross :nar in) as a result of using an

additional unit of input.
In terms of calculus:

MVP = Y-aPY + aY

Where: Y Original output

FY = New price of Y
lO/Marginal factor cost is the change in the total cost as a
esult of using another unit of input.
In terms of calculus:
PX,
MFC-Xi. 3 1 +13}, .axi
3X1 *1 3X1

Xi : Ori inal input

Pxi: Iew price of Xi

 

 

with labor (X1) and accounts receivab e and inventory (X2)
held constant at an arbitrary level and with (X5,....,Xr)
assumed fixed.

__1_1/

(1) 7r = PYY .. PXZXB - quxu _ c - F.C.

when differentiated with respect to X; and X4.

(2) i1?- _ va _ 1ch
a X3 “ X3<Y> X?
(.5) 9 7T 1'
_ ...___ _ VP — 21. FC
3 x4 XLHr) X”

The conditions for maximizing nrofit are met, by setting
equations (2) and (3) equal to zero and solving them simul—
taneously. Interaction between the factors necessitates a
simultaneous solution so that the profit maximizing conditions

(1) what combination of X3 and Xu to use and (2) how much of

X2 and X4 to use, are satisfied. if

The Cobb-Douglas Production Function. The use of this

 

function was originated by Cobb and Douglas in a study con-

f—J

cerned with statistically testing the margins productivity
theory of distribution. The function was used to measure the
effects of labor and capital on gross national product. The
function in the power form was P = bchl-k. It was fitted by
least squares regression and was linear in logarithms. The

restriction that the sum of the regression coefficients be

equal to one was imposed upon the function, thereby assuming

 

_1_.1_/ C = the arbitrary amount of XI and >22 used times their
respective prices.

l9

constant returns to scales.l§/ It was later demonstrated by
Durand, that the assumption of constant returns to scale

could be statistically tested by the F test of variance.l3/
Increasing returns to scale are present, if the sum of the
coefficients or eXponents is greater than one, decreasing re—
turns if the sum is less than one and constant returns to
scale when the sum is equal to one. Thus, the function never
reaches a maximum and can not handle two or nore production
stages simultaneously. The function has constant elasticity
throughout, which means that least cost combinations of two
inputs will be in the same proportion at successive levels of
output. Another disadvantage, as the function is used in

this study, is that it must intersect the Y and X axis at Y = O.
h. 0. Carter has developed certain modifications which do away
with these disadVantages.l3/

However, there are several advantages to this function
which make it a useful tool for determining the marginal value
products of input categories. In logarithms the function is
linear and easily fitted to empirical data by the method of

least squares. It takes the following form when fitted in

 

12 Charles w. Cobb and Paul H. Douglas, "A Theory of Pro-
duction",.American Economic Review, Supplement XVIII,
pp- 139-165.

13/ David Durand, "Some Thoughts on Marginal Productivity with
Special Reference to Professor Douglas' Analysis," Journal
of Political Economics LXLV), pp. 740-758.

l&/ H. 0. Carter, "Fodificstion of the Cobb-Douglas Function
to Destroy Constant Elasticity and Symmetry", Resource Pro-
ductivity Returns to Scale and Farm Size. Edited by
Earl C. Heady, Glenn L. Johnson and Lowell ”. Hardin.
pp. 168-174.

logarithms:

Log Y = log a + bl log X + - + bn log Xn.

1
When transforming into natural numbers it is necessary only

to place the coefficients in the exponent position. It gives
immediately elasticities of the product with respect to the
factors of production and permits the phenomenon of decreas-
ing marginal returns to come into evidence without using too
many degrees of freedom. If errors in the data are small and
normally distributed, a logarithmic transformation of the
variables will perserve the normality to a substantial degree.
Even if errors are not normally distributed and not independent

the best linear estimates will still be provided by the method

of least squares.l§/

Applications of the Cobb-Doualas Technique. Considerable

 

work has been done in fitting value productivity functions to
cross sectional data of farm firms. In most of these studies
the Cobb-Douglas function has been used in determining the
marginal productivities of input and investment categories.
One of the first studies of this type was that of Tintner

and Brownlee who fitted a production function to farm record
data.lé/ Earl Heady used a random sample of Iowa farms in an

analysis measuring the returns to the factors of production.lZ/

 

lj/ Gerhard Tintner, "A Note on the Derivation of Production
Function from Farm Records", Econometrica XII, No. 1,
January, 194k, pp. 26-44.

lé/ Tintner and Brownlee, "Production Functions Derived from
Farm Records", Journal of Farm Economics, Vol. 26, 1944.

lZ/ Earl Heady, "Production Functions from a Random Sample of
Iowa Farms", Journal of Farm Economics, Vol. 28, 19N6.

21

In a series of progress reports at the University of Kentucky

Johnson used a purposive sample in fitting value productivity

functions to farm data.l§/ In the more recent past several

studies of this type have been done at Michigan State University.

R. V. Wagley, in 1953, determined the marginal value produc—

tivities of input and investment categories on a purposive

sample of Ingham County Michigan farms.lg/ C. Beringer used

a multi-equation model in determining the marginal produc-

tivities of input categories for 27 Illinois dairy-hog farms.g9/
While many empirical studies have been made to analyze

the economic efficiency of resources on farm firms, only re-

cently have the analytical techniques of production economics

been employed to study resource use in agricultural marketing

firms. Within the last year two studies have been completed

at the Kansas Agricultural Experimental Station on the

elevator industry in that state. The first of these studies

is entitled, "Resource Returns and Productivity Coefficients

in the Kansas COOperative Grain Elevator Industry".§l/

 

18/ Glenn L. Johnson, "Sources of Income on Upland EcCracken
County Farms", 1951, Progress Report No. 2. Kentucky Agri-
cultural Experimental Station.

19/ Robert V. Wagley, "Narginal Productivities of Investments
and EXpenditures, Selected Ingham County Farms, 1952".
(Unpublished Master Thesis, 1953), Nichigan State College,
1953-

gg/ ChristOph Beringer, "A Rethod of Estimating Marginal Value
Productivities of Input and Investment Categories on Multi-
ple Enterprise Farms", Unpublished Ph.D. Thesis, Nichigan
State College, 1955.

gl/ Paul L. Kelley, Henry Tucker, and Kilton L. Manuel, "Re-
source Returns and Productivity Coefficients in the Kansas
Cooperative Grain Elevator Industry", Technical Rulletin 84,
Agricultural Experimental Station, Kansas State College,
October 1956.

22

The second study is entitled "Resource Returns and Productivity
Coefficients in Central and Western Kansas Country Elevators
of Fodern Construction".g§/

In the first study the Cobb-Douglas function was employed
to estimate the productivity of resources used in 215 c00perative
elevators in Kansas for the 1949 wheat crop year. The variables
were classified as follows:

Y = Value of output in dollars

X1: Labor services in dollars

X2: Operating expense services in dollars

X3: Capital services in dollars
The value of output (I) is sales plus ending inventories less
beginning inventories less purchases plus income from storage,
grinding, commission and other miscellaneous income. Patron-
age refunds and recovery on accounts previously charged off
were excluded. (X1) labor services was defined as salaries
of managers and office help, wages of plant workers, commissions
paid, directors'fees and employees'pensions. (X2) other
Operating expenses were defined as office supplies, plant
supplies and other incidentals essential to elevator Operations.
(X3) capital services included repairs, water, light and power,
telephone and telegraph, gas and oil, depreciation, rent and
railroad lease expense. Taxes on prOperty, capital stock taxes,

corporation taxes, insurance, interest, auditing expense,

 

gg/ Paul L. Kelly, John H. KcCoy, Henry Tucker, and Virve T.
Altan, "Resource Returns and Productivity Coefficients in
Central and western Kansas Country Elevators of Rodern Con—
struction, agricultural Experimental Station, Kansas State
College, Narch 1957.

 

\

23
licences and bonds, legal expense, bank service charges and
bad debts were excluded from the function.§3/

Functions were first fitted to data stratified by three
risk areas of the state - Western, Central and Eastern Kansas.
Secondly the data of the same firms were sorted by degrees of
diversification to determine whether the more diversified
plants were more productive in the use of various resources.

The results showed that in general labor had been Optimally
allocated among the area and diversification alternatives.
Capital services were substantially more productive than
labor services in this industry. Capital services, on an
area basis, appeared to have been optimally allocated. How-
ever, on a diversification basis capital services in the
medium stratum were more productive than in either low or high
diversification groups. The analysis, in general, indicated
that the firms studied exhibited constant returns to scale.§3/

In the second study a sample of 22 elevators was drawn
from a suspopulation of western and central Kansas elevators
with licensed storage capacity of 95,000 or more bushels and
of uniform type of construction. The subpopulation was
stratified into four size groups. Elevators in each stratum
were picked at random with proportion allocation. Data for
the 1951 wheat crop year were collected by personal interview

and from office records. Cobb-Douglas production functions

 

23/ Kelkw, Tucker, Manuel, 0., cit., p. #6.
24/ Ibid., p. #0.

24

were fitted to sidelines, storage and rain merchandising

S
operations as well as for total plant operation.gi/ The
classification of variables was essentially the same in both
studies.

Estimated marginal productivities, measured at the geo-
metric means of output and inputs, showed that efficiency
could have been increased in sidelines and total plant Operations
by adding labor inputs relative to operating eXpenses and
capital service inputs, and in storage by increasing Operat-
ing expenses and capital services relative to labor. Tests
of interfunction differences in marginal products indicated
that transfers of resources between elevator activities would
not have increased total economic efficiency. Constant re-
turns to scale were indicated in grain merchandising and

total plant functions. Increasing returns to scale were in-

, .
dicated in sidelines and storare activities.g9/ X'

C)

 

Kelly, HcCoy, Tucker, Altan, op. cit., p. 1.
Ibid., p. 2.

(\J N
O\

25
CHAPTER III
FITTING THE FUNCTION

Computation of Index of N rketing_5ervices. The data
collected from 34 elevators was summarized to determine the
gross income and the amount of each input or investment cate-
gory used in obtaining gross margin. Gross margin was then
converted to an index of marketing services by eliminating
any differences in absolute unit gross margin that occurred
between firms. a weighted average unit gross margin was com-
puted for every commodity and item sold by the elevators. The
actual unit gross margin times the quantity sold was calculated
for each firm, this figure is the total gross margin obtain-
ed frcm that product. These figures were then summed and the
total divided by the sum of the quantities sold, to obtain
the weighted average unit gross margin. The weighted average
unit gross margin was then remultiplied by each firm's quan-
tity to get the index value of marketing service for that
commodity or service. Ihe individual index values were then
summed to get an aggregate value for the index of marketing
services. Lack of information on the number of bushels of
grain handled and warehoused, necessitated the use of actual
gross margin values for these services. This was not con-
sidered a serious error because of the small percentage of

total marketing services that these items represented. An ex-

ample may help to clarify the computation of the aggregate

f\)
0\

value of the index of marketing services.

The following table shows the type of data obtained from
the questionnaire that was answered by the managers of the
firms studied. A check on the total gross margin computed
from questionnaire data was made (not index of marketing ser-
vices) for each firm by a comparison with the total gross
marginZZ/indicated in the Operating statements. The com-
parison revealed that in certain incidences discrepancies did
exist. These discrepancies were due to inaccurate answers to
questions on returns obtained from merchandising grain. Since
nearly all of the firms aggregate individual grain margins
into a single account, it was impossible to determine in which
grain or combination of grains the discrepancy had occurred.
It was possible to determine however, that about 85 percent
of the total error occurred in nine firms. The index of
marketing services for these nine firms was adjusted by add-
ing or subtracting the difference between questionnaire data
and Operating statement figures. Upon completion of this ad-
justment an aggregate discrepancy of only filU,056 or approxi-
mately .43 percent was not accounted for.

An: Statistical Results and Evaluation. The method used in
fitting the Cobb—Douglas function was least squares multiple
regression and correlation. ‘1e normal equations were solved

to calculate the regression coefficients and their respective

 

22/ This is total gross margin adjusted to exclude non-
Operating income such as patronage dividends, rent revenue,
etc.

i7

 

 

 

 

 

 

 

 

.msam> NowaH HmpOp esp so va QESHoo mSHQ Aiv gazaoo mH Amv QESHoo .m
» .ssHa some so Amy OOHOQO:
thuQmsw esp mmadp smog mo Samsse mmosw pHQ: ommhm>m wopzmfioz mg» ma Amy QESHOO .m
.Uoow Log SstmE mmosm pHQS
mwmsm>m dopflmHmz map mamswm Amy QEDHoo a0 ESm $39 an Um©H>a© ARV SESHoo mo ESm $29 .m
.Uoou soak :Hmsms mwosm 0p mamswo
dam va QHwLmE mmosw pHQS esp moEHp Amy Umamgmx comm mo mpHanzw ms» mH ARV QESHOU .w
.Eng Somo an AHV U®H©S®£
apapsssw on» mmaHp ssoo mo :Hmsme mmosm uHss mmmso>m copsmams map ma sz QESHOU .m
.ssoo pom :Hmpms mmosw pHss
ommso>m wousmHoz esp mdmzwo Adv sesaoo go saw map a9 UoUH>aU Amy sazaoo mo 55m mze .:
.Qsoo scam sHmsms mmosm HapOp mamswm
was Amy sHmpms mmosm qu: mgp moaHp AHV voHUan Shoo mo apHpsmzv on» mH Amy sesaoo .m
.wmom
dsm Shoo soup msHmeo ELHM Sumo pmsp mussmE mmosm 9H2: on» cam va was ANV mQESHom .m
.EsHa some an Umadsss doom was choc mo mmeHpsmsv mzp msw Amy was AHV msszaoo .H$
OOmm om OO.smm om:
mm Om aOH mH w O0.0 OO.m OO. omH m
mmH ONH mm O NH OO.NH OO.OH mO. OON m
OOH OOHs OOHw OH” OH OO.m a OO.w a no.9 OOH H
oSHm> can x Amv ammnma camsma msoa mo. x AHV camps: samsma mHmSmsm
xmesH msasa mmosw mmopm SH oxam> mmosm mmosu SH
Hapoe mesH Hmpoe pHup asHpmssw xmng Hmpos pHgD spHpnmsa anHm
Hmv va Amv HOV Amv Adv Amv Amv HHV
doom Shoo
mQMa>som msHpomeafimO xomsH on» so soHuspmmaoo "mamsmxm .m oHQmH

 

 

«m

 

 

28

" Q/
standard errors were determined.2”
The regression coefficients and their respective standard

errors were found to be:

~387950 t .123377

Labor bl
Inventory and Accounts Receivable b2: .163434 + .083167

.269722 1 .090065

Direct Operating Expenses b3

Nachinery and Equipment Investment bu: .187699 : .090Qh7.
All the regression coefficients were positive and less than
one. This indicates that additional increments of each input
will increase gross margin, but that additional increments
'of any one input, with the other inputs fixed at a specific
level, will increase gross margin at a decreasing rate.

The equation obtained for predicting gross income is as
follows:

Log 9 = 1.339103 + .387980 log X1 + .163434 log X2 + .269722
log X3 + .187699 log K“.

The sum of the regression coefficients is 1.006835, in-
dicating that there is slightly increasing returns to scale.
However, the sum of the regression coefficients does not differ
significantly from one. Therefore, it was not concluded that
these firms had increasing returns to scale.

The coefficient of multiple determination (32) is .87.
This means that 87 percent of the total variance in the log-
arithms of the dependent variable (gross income) is associated

with the independent variables. To test the reliability of

 

28/ See "Computational Methods for Handling Systems of Simul-
taneous Equations" by Joan Friedman and Richard J. Foote,
Agricu ture Handbock Ho. 94, USDA, ANS, Nov. 1955.

39

the coefficient of determination, the F test of variance was

emoloyed.g3/ The F value obtained from the test was “3.0619

’3
a“:

or well beyond th 8 upper .001 point, thus making R§.X 2 u

clearly significant when tested against zero.

Thirteen percent of the variance in Y is not eXplained
by the indenendent variables. It can be assumed that this
difference is caused by such factors as mane ge:nent, quality
of labor, comoetitive factors, percent utilization of capacity
and ooseibly certain ther unmeasured elements. The assumption
used regarding the influence of variation in the unmeasured
factors about their means on gross income is that they are
randomly and normally distributed.

The logarithm of gross income at the geometric me. n(G )
was estimated to be 4.92259, the antilog of which is 83, 674.0
dollars. The standard error of estimate (§) was 0+:E79.
Under conditions of random sampling and iiven the same bus siness
conditions that existed in 1955, 32 percent of the time the
logarithm of gross income would be eXpected to be greater or
smaller than 4.02259 1. Ti?“ In dollar values the gross

income in two out of three times, on the average, would be

within the range of 74,767 to 93,642 dollars. .if

&

 

_9/ Frederick qE. Croxton and Dudley J. Cowden, Applied General
Statist (New York; Prentice—H.311, Inc.) 9. 733. The
formula used in determining the F value was:

 

2
F = 31.239§-m ; (n_1) ___
(1 ‘ Rl.23u-—m) ; (N—m)

Computation of the Karginal Value Products.

A

30

Ihe next

step in evaluating the results of the regression and corre-

lation analysis is

to compute the marginal value product (EV?)

'3
for each input category for the "usual" or "typical"‘Q/firm.

The following table gives the data required in computing

 

 

 

the HVP.
Table 3. "Usual" Organization and Estimated Harginal
Value Product of 34 Elevator Farm Supply Firms
in Nichigan, 1955.
Input Quantity Log of Log of Log of *
Categories of (3) bi bi Gross KVP
Input Input Income
Labor (X1) 101.3 2.00581 .38798 9.58881-10 4.92259 $320.32
Inventory & '
Accounts 89- $76,194 4.88192 .16343 9.21333-10 .179
ceivable(X2
Direct !
Operating $13,305 b.12402 .26972 9.43091—10 1.696
Expense(X3)
Replacement
Value Of ‘58,697 b.76862 .13770 9.273u6—1o .268

Machinery &

Equipment(X4)

V

WPX; b1(E)Y antilog of log

1
‘i

The regression coefficients (b1) are used directly in

computing the marginal value products.

necessary that the coefficients be reliable.

Therefore, it is

One method of

testing the significance of these coefficients is to test them

against the null hypothesis of zero.

 

30/ The term "usual" or "typical" is used to mean the elevator
farm supply firm having the geometric mean amounts of in-
puts used in the production of gross margin.

31

The regression coefficient (b1) of labor (X1) was signifi-
cantly different from zero at the one percent level. The re-
gression coefficient (b2) of inventories and accounts receiv-
able (X2) was significantly different from zero at the 10
percent level. The regression coefficient (b3) of direct
Operating expenses (X3) was significantly different from zero
at the one percent level and b4 of total replacement value
of machinery and equipment (Xu) was significantly different
from zero at the five percent level.

An alternative method of testing the regression coefficients
and one which seems more realistic in determining the Optimum
combination of inputs, is to test the bi's determined by the
regression analysis, against a minimum bi which will yield
an I'CVPX1 equal to the NFCXi . This is computed by setting

WP

x1 equal to the 1".ch1 and fixing E(Y) and Xi at their

respective geometric mean values and solving for the minimum

b algebraically.

X1
Labor (X1) was priced by dividing the mean value of the
cost of labor by the mean amount of labor.il/ Inventory and
accounts receivable (X2) was priced at several different levels.
The reason for doing this was that the cost of carrying these
two items in an elevator varies considerably. The cost of
carrying inventories includes interest, depreciation, losses,

taxes, and risk. The elevator industry generally considers

12 percent per annum as the total cost of carrying an inventory.

 

}1/ Labor is measured in man-months, which is one man‘s labor
for a month.

The cost of accounts receivable as determined by Dunn
and Bradstreetig/ for country elevators varies from 6 to 24
percent. The major difference between the cost of inventory
and accounts receivable is bad debt loss. The cost of direct
Operating expenses (X3) is equal to actual outlays. The cost
of machinery and equipment was computed at three different
levels. Cne level was computed at a depreciation rate, a
higher level for depreciation and r pairs. A still higher
level was computed to provide for depreciation, repairs and
the normal return that it probably would take to induce business-
men to invest money in new machinery and equipment.

The following prices were used in determining minimum
b1 values.

Labor $311.50 per month
.05
.09
.12

a;

Inventory and accounts receivable

.18
Direct operating expenses a 1.00
Machinery and equipment $ .10
.15
.20
The following table indicates the minimum b1 values.
The difference between the b? and the estimated bi is then

measured in terms of the standard error of the estimated b1.

 

32/

33

 

 

 

 

3mm. ommam. omega. eHHeH. m.
a m. mmeom. omame. ommea. we.
mom. oommm.a masaa. emcee. meomo. enema. 0H. www.mm Amtmfiaoov
.mdswm e mpmsazowa
use. mmmHN.H Named. ooewfi. weeme. Nemem. oo.H mem.ma Amteeaoov .emxm
msapmsogo pompao
:Ho. mwmae.u s:aoo.a omzmfl. we.
owe. memew.. mmmmo. omaoa. NH.
one. sense. moeme. eemwe. . oe. .
new. meeH:.H mmuee. cameo. semme. memmfi. me. soa.ee Amteeaonv .eem
.mpooe e zpou9m>sH
ewe. mmmee. memoe. mmmsm. mmmmfi. wmsmm. om.HHm m.aoa Amngoe mezv Loewe
\ .fnw m5; .Caa Seapmm
®>hzo IMIIAI. Shapmm on a Hp .D.m.u Iacmmmo anommpmo
Heapom * D: Q tamnap mammueomz 9w Uopmermm eamSmpe pzmspmo>sh so psmsH
nods; seam H
t p
.nmmfiSOea
ca eeeezem mates samesm atmmatoeeseam an en» toe meea ens axes;

opmzwm 0p assumeooz 1H9 one dam HQ wmpmefipmm

flu soospmm nomapmmsoo

.2 mapme

‘JJ
4:

This in turn indicates the probe ility of the bi occurring,
if the estimated bi is the true population regression coef-
ficient.

The standard error of the regression coefficients is
deternined by the range of the data, size of sample and the
inter—correlation occurring between variables. Relatively
high inter—correlation between variables reduced the reliability
of the coefficients. Such influences are reflected in the

tandard errors of the b's and, hence; in the reliability

m

f the marginal value products. Relatively high inter-

O

correlations between two variables may cause an overestimation
of one of the b's and an underestimation of the other b. In
an attenpt to reduce inter-correlation, the rules outlined in
the previous chapter for input categorization were followed.
The sample was also selected in such a manner as to give
substantial range to the pronortions of inputs used.

Even through these precautions were taken, it can be
seen from the following sample correlations that consider-
able inter-correlation was exhibited between certain sets of

the variables.

r12 = .7eie5 r2, 2 .5779e r24 = .Hgseo
/ f (“if

r12 = .72459 I?” : .030eo

rqu = .64338

Observation of the above values indicates that x1 and x2,
and x1 and x3 show the highest degree of correlation. However,

the rest of the variables exhibited a substantially smaller

35

degree of correlation. In either set of the variables in-
dicating a higher degree of correlation the estimated b's
could be higher or lower than the true regression coefficients.
If bias exists in the regression coefficients it would be re-
flected in the marginal value products.

The only regression coefficient which yielded an hVP
below the minimum return Was the accounts receivable and in-
ventory input category. This occurred when the category was
priced at a reservation price of 18 percent; however, the re-
gression coefficient was within the 68 percent confidence
interval.

On the basis of outside information and experience the
returns to labor and direct Operating expenses did not differ
too much from expectations. Generally in these businesses
an excess amount of labor is used relative u: the utilization
of machinery and equipment. Therefore, the returns to labor
are barely enough to cover the cost of labor, while the re—
turns to direct Operating expenses are relatively high. The
most logical adjustment by which to increase gross margin is
to increase the prOportion of direct operating expenses re-
lative to the amount of labor used.

It is extremely difficult to determine the returns on
inventory and accounts receivable without an empirical analysis.
The interrelated factors of composition, level and rate of
turnover make it difficult to evaluate inventory. Accounts
receivable are also difficult to evaluate because of the many

types of credit policies which prevail in the feed and grain

industry.

36

The returns to machinery and equipment are venerally con-

3
sidered low because of the excess capacity needed to handle
harvest runs and seasonal livestock feeding peaks. However,
the marginal value product calculated in the empirical portion
Of this study indicates that an increase in the proportion of
machinery and equipment investment relative to other inputs
may increase total gross margin.

From the results of the above analyses it agpears that
the usual organization of the Hichigan elevators is not in
serious maladjustment except for direct Operating eXpenses.
The regression coefficient of direct operating expenses is
significantly higher (at the 75 percent level) than the b1*
necessary to return a minimum NVP, indicating that more of
this input can be used.

An adjustment in machinery and equipment investment may
increase the returns of the typ cally organized elevator
although the case for this type of an adjustment with a reser-
vation price of 20 percent is not strong. The high returns
to direct Operating eXpenses indicates that these plants are
Operating at something less than full capacity. It would then

pear that if these firms desired to increase gross margin,

93
*0

efforts should first be made to eXpsnd output in existing

facilities.

Ratio Comparisons. An alternative method of analyzing

 

the returns of these firms is to make certain ratio comparisons

With the aggregate results Of the functional anclysis. The

mean estimated gross margin (G) as determined by the function-

\A)

al analysis was $3 ,674. The total Operating expenses includ-
ing depreciation, measured at the geometric mean is $76,823.
By subtracting total Operating expenses from gross margin, the
net Operating profit is $6,851.

When this value is compared to net fixed assets, we have
a significant measure Of the earning power of present invest-
ment in plant facilities. fhe averaqe net fixed assets of the
3H elevators studied in this survey was $69,502. Net Operat-
ing margin as a percentage Of net fixed assets is 9.857 per-
cent. Another meaningful financial measure is the return
on the replacement Value of buildings, machinery and equipment.
This measure is a useful indication Of the ability of these
firms to rebuild and modernize their physical plants. The
replacement values Of buildings, machinery and equipment used
are appraisals that hichigan fillers Futual Insurance Company
use as a basis for insuring these firms. Replacement values
for trucking equipment were taken directly from balance sheet
data on total investment in trucking equipment. It was
necessary to use this data because inadequate information on
numbers and types of trucking equipment made it impossible to
compute the cost Of new trucking equipment.

It is necessary to make certain qualifying assumptions,
when ratio comparisons are made with replacement values. These

assumptions are:

38

1. Rates Of depreciation will remain constant though the
total depreciation charge may change.
2. Property taxes will remain constant.
3. All operating expenses exclusive Of depreciation
will remain constant.

4. Dollar volume of business will remain constant.

It is necessary tO adjust total Operating expenses by
the increase in depreciation, which will result from using
replacement values. The average total replacement value of
buildings, machinery and equipment is $143,197 for the 34
elevators. This amount plus $10,746, the average investment
in trucking equipment, gives a total &V€P&$€ replacement value
Of $153,943 for all fixed assets. The depreciation rate appli—
ed tO the investment in buildings, machinery and equipment is
5.7313 percent. The rate applied tO trucking equipment in-
vestment is 20.1586 percent.32/ The adjusted total depreci-
ation is $10,373.00, hence total Operating expenses increased
from $76,823 to $79,638. When adjusted total Operating ex-
penses are subtracted from the gross margin derived from the
functional analysis, the adjusted net Operating margin is
34,036.

The average investment over a period Of years would be
approximately one-half Of the replacement value Of fixed assets,

or $76,971.50. Net profit divided by the average investment

 

33/ These rates are computed on the basis of 24 elevators, in-
adequacies in balance sheet data made it impossible tO
compute an average rate based on all Of the 34 elevators

surveyed.

over a ceriod of years gives a measure of the net return on
investment in plant facilities. This percentage is 5.24.

So :._et an indication of the total returns to investment in
fixed assets, it is necessery to add defraoietion to net re-
turns. The total return on average investment over a period
of years would be 18.72 percent, when fixed facilities are
priced at replacement values. Esperience indicates that a
return of 15—20 percent on the average investment in fixed
facilities is reasonable in the Operation of elevator-farm
supply firms. The above return of 18.72 percent is probably
enough for the average firm to replace its present facilities,
but it is unl Rely that this is a high enough return to carry

out any extensive expansion program.

Short-Run Adjustment. The ultimate purpose of this study

 

was to provide reference points to make ju gments on alter-
native economic orgenizetions of elevators and to serve as
guides in reorganizing these firms. The estimated regression
coefficients were believed reliable enough, to warrant their
use in estimating gross margin and marginal velue products
for different combinations of inyuts.

As a preliminary to e suggested reorganization, consid-
eration is first given to the effect on gross margin and the
merginsl velue products of increasing the input which has the
highest rate of return. A reorganization based on this cri—

teria will be referred to as a short-run adjustment.

 

no

The input having the highest rate of return is direct

Operating expenses. Direct operating expenses have previously

Q

.5.

been defined as those expenses which vary with the volume of
business done by the firm. Greater amounts of this input re-
sult in increased utilization of plant capacity.

EXperience indicates that one of the major economic pro-
blems in country elevators is excess capacity. Capacity is

defined as the bushels of grain or tons of feed, that a feed

and grain elevator can handle in a given period of time. Due
to the seasonal nature of grain and bean harvests and the re-
sulting necessity of handling these commodities in a short
period of time, it is necessary to maintain unused capacity
during certain parts of the year. This also is true to a
lesser degree on feed processing facilities.

The average plant studied in this survey utilized only
9.32 percent of its grain capacity and 48.95 percent of its
feed handling capacity.3&/ While these are only rough estimates,
they do give an indication of capacity used.

When direct Operating expenses are increased from $13,305
to $27,250, a better than two fold increase is obtained in the
utilization of plant facilities. These results apply only if

the commodity mix is not changed from the average values

 

.1&/ Percent utilization of grain facilities is based on rated
grain handling capacity for a 101 day period at eight hours
per day. It was believed that the normal grain handling
period is approximately four months in length.

Percent utilization of feed facilities is based on rated
feed handling capacity for a 305 day period at eight hours
per day. Some feed business is done nearly every day of
the year, however, there are seasonal fluctuations.

41

included in the sample. The following table shows the effects
on the marginal value products when the above mentioned increase
in direct Operating expenses is made and other inputs are used
in the "usual" amounts.

Table 5. Changes in PVP's for the "Pypical" Organization

Resulting from Increasing Directing Operating
Expenses from $13,305 to $27,250.

 

 

Quantity Original New
Input Category of N.V.P. M.V.P.
Inpyts (Dollars) (Dollars)
Labor in Kan months (X1) 101.3 320.32 388.64
Inventory and
Accounts Receivable (X?) $76,194 .179 .217
Direct Operating “
Expenses (X3) $27,250 1.696 1.004
Investment in Machinery H
and Equipment (X4) $58,697 .267 .324

 

The estimated gross margin increased from $83,674 to
$101,517 as a result of increasing the amount of direct Operat—
ing expenses (X3) to the point where the l-FVPx3 = hFCxB. This
causes the FVP's of the three other factors of production to
increase substantially. Figure 1 illustrates the change in
the FVP of labor when the "usual" amounts of all inputs except
direct operating expenses are used in deriving gross margin.
The NVP of the marginal unit of labor increased from $320.32
to $388.64.

t would seem that the next question to be answered is
the effect on net Operating profit as a result of the short-

run adjustment. It should be reCOgnized that profit is the

1&2

0.3.38 Ho «mammsoé nu nomneumm “335.390 comps

 

on mm mm aw . . «m cm ma an ad
‘ u - J u a n d a 1
«n
can M
m
J
m
.Sn m
TI
u
a
0
Wu
.awn n
I

 

 

fig

9.3.53 3 nonfiam not nouaoaxm $93988 9398 mfiwaeuanu
song mauoaaacm noduaudnamuo .Hmogaha. «no no» magma uo.mpw on» no mucougm .n mnswfim

 

14.3

conseiuence of using all the factors of production. However,
the elevator Operator is most concerned about the absolute
magnitude of net Ope-ttlng prof end the rate of return it

ssets. Estimated net Operat-

Q)

it
represents on investment in fixed
ing profit increes d from $6,851 to $10,749 with the above
short-run adjustment. In estimating the net profit after the
short-run adjustment was made, the increase in direct Operet-

geometric mean of total Operating

ing eXpenses was added to the
expenses. Ihis total was then substraoted from the estimated
gross margin derived from making the adjustment. The rate of
return on net fixed assets increases from 9.86 to 15.46 per-

cent or an increes of 56.95 percent.

I
LJ

Long-Run Adjustment. Another sugiested reorganization

 

is a long-run adjustment when two or more variables are changed
simultaneously. Phe high rate of return on direct Operating
expenses and investment in machinery and equipment, indicates
that increase in amount expended on these two factors of pro-
duction, could enhance the gross margin of country elevators.
In determining an organization which would be nearer
optimum adjustment, several trial combinations of different
amounts of X3 and K” were made, while X1 and X2 were used in
the "usual" amounts. The amounts of X3 and X4 used in the
trial combinations were determined by an "expansion" line
(ibteined by preportionete increeses in X3 and X“. The line

is a.path which represents successive points of tengency between

.iso-vslue product curves and iso-cost curves. It is partly

 

an

determined by the nature of the production function and partly
by the relative prices of the two inputs. It should further
be remembered that the expansion line indicates the most pro—
fitable preportions in which to combine direct 03erating ex-
penses and investment in machinery and equipment, to derive
various levels of gross margin. The following fggnma shows
he expansion line (C.P) with direct operating eXpenses priced
at one dollar per unit and machinery and equipment investment
included at a reservation return of 20 percent.

£ 100,000 dollar iso-value product curve has been super-
imposed upon the eXpansion line. The iso-cost line which is
tangent to the iso-value product curve at point (A) repre-
sents an annual cost of £36,700.

The investment in machinery and the equipment is $75,000.
The annual cost of K3 is $21,700 while the annual cost of Xu
is $15,000.

As can be seen from the point of tangency between the
iso-value product curve and the iso-cost line the selected
points representing different amounts of X3 and X” are also
points of Optimum combination. The following KVP‘s of X3 and
X4 at the trial points 1, 2, 3, and a, show the effects of the

law of diminishing returns, when part of the measured inputs,

(X1 and X2) are fixed at a specific level.

.6»

“5

Table 6. Che n5 :es in the IJP of K 8nd XU as a Result of
lncrea;ing the Exgtendit res on Dire ct Cpereting
' chi nery and Equipment Inve st-

.. Y ‘
Expenses and he.
m

ent.

 

 

 

. Estimated FVP KVP
Trial Gross Direct Cperat- Hachinery &
Kara in ing-Expenses Equipment
1 90,110 1.41 .28
2 111,392 1.09 .22
3 115,722 1.03 .21
a 119,025 1.01 .20

 

After exploring the effects of increasing th e amount of
X3 and KM used, as dictated by the exoansion line a proposed
reor: anization was developed. Hie proposed organization was

to use labor (X1) and accounts receivable and inventory (X2)

in the "usual" amounts, while direct Operating expenses (X3)

U)

and machinery and equipment investment (X4) were incr ea ed
to the point where the NVP'S of X3 and Kb were approximately

equal to their respective IFS's .

a?

estimated gross Irarrin of the propcsed reorgani 8 tion
is $119,025. The resulting NVP'S are shown in the following
table,(7),

While the marginal factor cost of all the input cate-
gories are not equated with the minimum marginal value products,
it is evident that the preposed reorganization is nearer cpti-
Inum adjustment than the "typical" organization. The reorgan-
ized firm does not have the RV? of all inputs equated with

their respective 133's. No attempt is made to equate these

Figure 2. Trial Combinations of Direct Cperating Expenses (K3)
and Kachinery and Equipment Investment (K4)

 

 

XL»

120m F

u
3
100-4
2

U)
a
T:
r-i
r-i
O
n 80-
‘H
o A
U)
rd
9
5 .
3 60-1 - 1
E:

nee

20-

0 I l l r I l
10 20 30 no 50

Thousands of Dollars

Table 7. Changes in FVP's for the "Typical" Organi-
zation Resulting from Increases in Direct
Operating Expenses and Investment in
Fachinery and Equipment.

 

 

 

Input or Investment Quantity Original New
Category Used EV WVP
Labor (x1) 101.3 320.32 £55.66

Inventory and
Accounts Receivab1e(X2) 76,194 .179 .255

Direct Operating

Q

Expenses (X3) 31,750 1.696 1.011

Investment in Kachinery
and Equipment (KM) 110,000 .267 .203

 

values for all factors because increasing returns to scale
prevents attaining the high profit point. Further, on the
basis of experience and judgment it is believed that the other
two inputs should not be increased. with reference to labor
it was believed that having more qualified employees was a
more appropriate goal than increased amounts of labor. There-
fore, it was concluded that labor inputs should not be in-
creased in attempting to increase gross margin.

Due to the complications involved in eVeluating the accounts
receivable and inventory category, it was believed that this
input category should not be increased. Most of these compli-
cations arise because the three interrelated factors of level,
composition, and rate of turnover make it difficult to evaluate
inventory adequately. In order to provide the surrounding
farming community with the required items it is necessary for

elevator-farm supply firms to maintain a certain level and

47
composition of inventory. Certain items such as feed, ferti-
lizer and hardware normally turnover several times every year.
On the other hand, a wheat or been inventory may be stored
for a.considerable period of time. Due to inadequate measur-
ing devices for handling all these factors, it is impossible
to make accurate measurements.

Effe ts on Net Profit and Cperstinprefital of Increasing,

0

Direct Operating Expenses and Investment in Fachinery and

Eduipment. It should a ain be emphasized that profit is a

L;
'_J

 

residual value derived from using all the factors of production.
is a result of increasing the amount of direct Operating ex-
penses and machinery and equipment investment, net Operating
profit was increased substantially over the net operating
profit derived from the typically organized elevator-farm

'reat as it was when

S

93
(750

supply firm. However, profit was not
the short-run adjustment was made. This was due to the in-
crease in depreciation, which resulted from the increased
investment that was incurred in the long-run adjustment. The
procedure in estimating the net operating profit was the same
as was used in estimating net Operating profit for the short-
run adjustment. The same rates of depreciation35/ were
applied to the estimated investment in building machinery

and equipment and trucking equipment, as was used in the

 

35/ 5.7313 percent on investment in building, machinery and
equipment. 20.1586 percent on investment in trucking
equipment.

us

. . i ' z
snort-run adJustment on the returns to replECenent v lues.2£/

The increase in depreciation plus the increese in direct

operating eXpenses was added to total Operating expenses cal-

culated a the geometric mean. This total was then subtracted

 

35/ with investment in machinery and equipment being only a

part of the total investment in the physical facilities,
it is necessary to estimate what the total investment in
all plant facilities will be if the in'estment in machinery
and equipment is expanded. To estimate what the total in-
vestment will be, a correlation and regression analysis
was computed to determine the degree of relationship that
existed between machinery and equipment investment, and
total investment in all facilities. Total investment in
all facilities priced at replacement value represented the
dependent variable and investment in machinery and equip-
ment priced at rep acement.

5 = o919008 The predicting equation Was:
52: .8445757 log 2 = - .588544 + 1.208Qu7
s = .105659 a 105 X4-

O'r= .OE-OLVZLL .3 = estimated total in-
lb: .097757 vestment.

Pb: 12.361752 X4: investment in nschinery

end equipment priced at
replacement velue.

D

The results indicated u significant relationship exist-
ed betveen total investment in all plant facilities and
investment in machinery and equipment. Therefore, the
predicting eguation was believed reliable enough to be
employed in determining what total investment in all
physical facilities would be, if machinery end equipment
was set at a specific level.

The specific level at which investment in mechinery
ind equipment should be set, is theoretically determined
by increasing the amount of this input used, to the
point where the PVBU- RFCX . The theoretical term-
ination point for increases in direct Operating eXpenses
would also be where the EJ} = hFC .

X1: X1

‘.

from the estimated gross mer;in derived from the long-run
adjustment. The estimated gross margin from increasing direct
operating expenses to 331,750 and mechinery and equipment to
$110,000, was f119,025. The estimated total operating ex-
penses are $109,201 which when subtrected from estimated

gross margin leaves an estimated net operating profit of
$9,82u.

f

4- 3.9
T] “'0" O

m

Net operating profit es a pore average invest-
ment in fixed assets, priced at replacement values, over a
period of years is 6.1303 percent. Estimated total invest-
ment priced at replacement velue was $318,943, which would
make the average in estment over a period of years equal to
approximately one-half of this, or fil59,h71.50. To get an

indication of the total returns to the investment in fixed

plus depreciation were taken as

.L ‘4.

assets, net Operating profit
a percentage of the average investment in fixed assets. This

)

was 19.6Q percent.

\

The net Cferating profit is not as great with the long-
run adjustment as with the short-run adjustment where in the
latter case total depreciation is based on the present in-
vestment in facilities. However, when replacements values are
used in pricing facilities in all situations a comparison of
the accumulation of liquid capital can be me e. The importance
of the concept of liquid capital accumulation lies in the fact
that the rate of accumulation relative to total investment

determines the firm's ability to maintain and modernize its

50

3

physical plant and grovide e return on investment.
The following table shows the absolute amount and rate

of liquid capital accumulation, when facilities are priced

ecement velues.

m
Cf
*1
<1)
9

Eeble 8. Accumulation of Liquid Capital when
Facilities are Priced at Replacement Values.

 

 

 

Geometric Short— Long—
Feen Run Run
Net Profit 2 4.036 3 7.934 : 9.824
£1-
, Depreciation 10,373 10,373 21,492
Total Returns 14,409 18,307 31,316
Total Replac,ment Value 153,943 153,943 318,943
Averege Investment over
Period of Years 76,971 76,971 159,471
Accumulation rate on In-
vestment over 3 Period of 18.72 23.78 19.54
Years
% Rates of depreciation: 5.73 on buildings, machinery and

equipment
20.16 on trucking equipment
It is seen from the above table that the greatest abso-
lute emount of accumulation occurs in the long-run situation.
However, the rate of accumulation is highest in the short-
Pun situation. This further substantiates the case for in-
creasing the utilization of existing facilities rather than

Constructing new facilities.

51

LEALYSIS OF EESID";LS

Several of the firms analyzed had an index of marketing
services which deviated a considerable amount from the value
estimated by the function fitted to the data. Explanation of
these deviations requires an individual analysis of each firm.
To determine which firms should be analyzed the standard
deviation of the logarithm residuals was computed. The standard
deviation was determined to be t .0786. There were five firms
which had a positive residual greater than this value and five
firms which had a negative value larger than - .0786. It was
believed that an empirical analysis could be based on averages

f the grougs and that further exglanation of the individual
firms which deviated radically from the average of the groups
would be given.

Product mix, utilization of cegacity, comgetition,
volume handled, and quality of inputs are the five major
factors assumed to be affecting the degree to which a given
firm deviates from the function fitted to the data from the
3M elevators studied.

The quality of inputs used is related to the caliber of
management operating an elevator. It is impossible to measure
these factors related to management directly, but it is
possible to develOp indirect measures of their efiects on
gross margins. The two prime examples are the quality of

personnel and the quality of machinery and equipment emgloyed.

Kn
to

Probdbly more of the personnel emgloyed in a country

"~ 1! .3 .~ 0 I ,-.- ,. ..r- ‘5‘ - r .~.' - ‘r- (‘3‘ - r. '1. A. ‘ ~<~ ' -‘ _.""-‘ ‘ ”a
elevator .eriorm nsnaaement tuoKS than in most other businesses,

.L

because mucn of the work to o done is of a non-routine nature.

(D

t is desirable for key eugloyees in the feed grinding and
mixing department to have considerable knowledge of feed con-
centrates and subplements so that they can aid farmers in the
development of balance feed rations. fhe key employee in the
are n egartment should be able to determine the grade of a
sgecific lot of a grain so that the menarer of the elevator
and farmers are able to conclude a nutually satis actory
transaction.

The productivity of labor is closely related to the
quality of mechinery and equipment in an elevator. A firm
that has relatively modern machinery and equipment which is
synchronized will probably obtain more business reldtive to
its competitors. Plant layout will enhance the groductivity
of labor in two ways: (1) it enables the emyloyees to handle

riven time

\_‘

a ”reater physical volume of production in a

S—J

period, and (2) decreases the chsn e over time required for

each customer.
fhe first factor examined was the product mix or the
[I

sources of gross margin for the iirms in the positive and

negative residual roups. These figures were compared to each

g
other and to tie average for the 34 elevators studied (Iable 9).

v

Substantial differences existed in four sources of iros

margin.

\J'K
b)

. f“ r ~ ‘ IF. ‘ r. ‘ ," ,A I“ . ‘ ,-
Teole Q. uOngricOfl CI tL? ooLrCes of gross herein.

 

 

.- ~_.—._.. .- -—.

 

Yerchendised Processed Farm Service
Grain Grain Supply Income

 

Ave. 34 firms 18.07 20°09 17°24 22°25
i 5 p idiel 20.22 19. 8 12.35 28.00
Ave. 5 neietive residue 1u.48 32.63 17.05 21.45

 

The five firms with lsrse gositive residuals, obtained

V

rcent:

(I)

e greeter y ross margin from merchandised

grain and service income relative to the average for the Be
firms and to the average of the five firms with negative re-
siduals. The five firms with the large negative residuals

:reeter percentere of total gross margin from

obtained a be
processed grein and farm supply relative to the group with
large positive residuals. The L€?&tiV€ group also obtaine

reeter percentese of total gross Terrin from trocessed

J

{D

U

n
1

rr in end farm supply relative to the group with large positive

C
C

residuals. The negative group also obteined a larger percent-

age of total margin from processed grain tten the everaee for

all firms and obtained about the seme percentege from farm

\

s pply. In themselves these figures do not mean too much,
but when they are related to the percent utilization of grain
capacity and feed capacity they give an indication of the

reasons for the direction of the residuals (Table 10).

Table 10. Comgerison of Capacity Utilization.

 

 

Percent Grain Percent Feed
Capacity Used Capacity Used

 

Ave. 34 firms 25-81 52-85
Ave. 5 positive residuals 41.31 67.53
Ave. 5 negative residuals 19.00 52.97

 

Fhis table shows that the five firms with positive re-

siduals utilizei 22.31 peroentere roints more of their grain

m
I

’ :1
._>
m
m
(D
H)
LJ-
<;
o

irms with negative residual-
firms on the average also utilized a higher gercentgge cl grain
bid feed capacity then the average of all firms. Cne firm
in this group utilisei sn exceptionally low percentage of its
groin capacity; the reason for the large gesitive res'dusl

is tertially due to the high gercentage of gross margin
derived from yetroleum yroflucts, which is a high Kerk-up
product. In general, the basis for psrtiel explanation of

a percent

ioeitive residual is indicated by the hi

U]

the large

n

of total gross margin from merohendised grain in coordination
with greeter utilization of grain facilities. The inverse

relationship is also a yertiel explanation of the large

(D
U)

iiuel. The group with negative r idusls, aerived

0)

w .J— .-
negatiVe re

(D

a larger percentage of :ross margin from proc ssed grain but

V

iei loner utilization of feed process‘n capacity then the

hp
U '4

J.

group with positive resifiuels. This implies thst these firms

K“

Le product which was

Q

were not doing a laree enough volume in t

H
:5
L34
g.»-
0
LI
Cr
(1)
C‘!‘
s
(y
(.1-
(‘f’
3
(D
H)
J0
3
J
{J
pl
('f'
sJ
’55
(D
2
0-
(‘1'
H.
<:
(D
*‘5
(T‘
(f)
H.
L J
C
L‘i
H
U)
s
*3
(D
a
(.1-
Q:
C;
Ho
'5‘5
09

enough total business relative to those firms with ycsitive
resiluals or to the average of all firms.

In an attempt to -oc if those firms with negative rssiiual

('1

were not doing enough total business, actual cross msrgin

(Ya), index of marketin services (YO), sni estimeted index

q

of marketing services (?) are compsrec in Table 11. These
comparisons indicate the relationship between the price of
market services and the total volume of business done by these
firms. Price competition and volume handled are highly inter-
related because both grestly effect the msinitude of total
gross margin. Ihis means that the mazsgement of a country
elevator must have some idea of the elesticity of demand for
its services. If demand is relatively inelastic, total gross
,
msrgin will be decreased if price is reduced.22? If demand
is relatively elastic a decrease in price will increese total
gross margin. While the exact dessnd schedules for the ser-
vices sold ere not Know, it still is possible to use the con—
cepts involved to develop a better urderstending of the
direction and magnitude of the deviations for the productivity
function.

The everegeԤ.for the group with negative residuals was
$1,450 under the everage‘? for those firms with positive
residuals. This indicates thfit the amount of inputs used by
these firms wss not radically different from the group with
positive residuals. fherefore, it appeers t.st partial ex-
planation of the residual is related to the price—volume re-
lationships confronting these elevators.

The index of marketing services (YO) was computed to
eliminate differences in unit gross margin and for all practi-

cal purposes eliminate the effects of price competition

 

32/ Actually unit gross margin is reduced and the selling
price is out by the amount of this reduction.

kn
0\

end’?

Table 11. C nr'rison of I , Y

 

 

 

a c'
y Y I -y ‘?’ r J?
a C a. C C ‘
”v .3u firms 96, 956 96,5u3 + u13* 9M,959 + 1,5eu**
Ave. 5 positive Res. 99 9,5d3 103,937 — 4,39h 75,312 +28,625
3V8. 5 negative Res. “56 58,202 +11,398 73,312 -15,660

 

* This difference is due to the 14,056 dollar aggregate
positive error between Ed and

** This difference is due to a :ositive tia.s crest ad by con-
verting the logarithm estimates into natural num oer s.

between these firms. Stiff price competition, relative to

the average firm studied, is indicated when Yo is subtracted

from Y and the M3 ”ultin -Hif er nce is Den?“

(1)

is true when the difference is positive. The inverse relation-
ship between Ya-YC and Ice? is an important indication of the
elasticity of demand for the services offered by a country
elevator. The difference between Ya and Ye shows what change
will occur in total gross margin when price differences occur
between firms, while the difference between Yo and ? is an
indication of the volume differences on total gross margin.

1

Based on the functional relationship develOped for the 34

firms analyzed a neg; tive difference Yo and I would indicate
a deficiency in the physical volume hand led by the firm in
question for the amount of inputs used.

s comparison of the difference between Ya and Ye for each
of the groups points out very conclusively th t this is the
situation, because Yo eliminates price differences (in the

sense of unit gross margins), thus a true picture of the

physical volume differences is shown. qutirioO es of the

average Ye for t? e t 0 groups shows that the firms with

positive residuals have an average of f45,000 more gross mer-

‘in, than the firms with n retive residuals. kurisors of

the Ya tetween the two groups shows that the difference is
only $30,000. Roughly fll,OOO of this £15,000 chengc occurred

in the group with negetive residuals, which indicates that

E‘-

‘

1e se firms are ettemgtin3 to maintain total gross m:r ii oy

s e
increasin3 unit 3ross m r3ins, rather than striving to i: crease
physicel volume. This further indicates that demand for a
given elevetor's services is relatively elastic, hence the

total gross margin will increese when unit gross margins are

decreased.

(T)

On firm in the group with positive residue ls had a

positive differ:nce o: tTeen Ye and EC, however, this same firm
had a le r3e positive difference between Y0 and X, which in turn
offset all the positive difference between Ia and yo and leaves
a substantial positive difference between En EDd‘?. This firm
is in an extremely advent 3eous com; etiti‘e tosition, heeuuse
it is simultaneously able to take a wider mar
sold end heve e lerge physical volume of business. This seme
firm utilized (2.21 percent of its grain capacity and 97.11
percent of its feed cap scity.

All firms in the 3roup with n<3;~tive res duals had
negetive differences as ween Ya and Ye. This indicates that

these firms have a lesser degree of comgetition then the

evera3e for all firms studied. This could result from localized

kn
(D

gentleme '3 es

.J
O

reements or the actual lack of effective oom—
petition in the area. In light of the lerg positive residuals
for those firms which cferete with lower margins it would ep-
peer that these firms are in error by not cuttin3 unit gross

n er3ins. Greater volume rather than high wer3ins appeensto

be the more apprOpriete objective if me egement desires to

increase the profitability of the or3enizetion.

A Further Zoraent on the Crereting ?remework of the
Tic hi3:;n Country Elevator. lhere ere many factors, other than
those empirically anelvzed in this study, which effect the
profitability of a country elevator. While there was no
epperent relationship with the resilue ls comru uted in the pre-
vious section, it was believed that a des CPlf tion of these
factors could help to eXplein the business Operating framework
of the country elevator. Credit sveilebility,pricin3 policies,
competitive practices of competitors, how these practices ere
met, edvertising end tromotion nel schemes are ell factors which
affect the gross margin of these firms.

When the mene3ers of these firms were asked under whet
conditions they needed operating ca; tel in the lest two or
three years, 20 of the 34 manegers indicated e need for capital
to meet seasonel demand. Six me;n qers said thet there was
no need for seasonal Operating ce11tel and eight did not reply
to the question or said that there was 3 need for long-term

investment cepitel. Ien managers seid that short-term capital

for meeting seasonal demand would have increased gross margin.

59

The reason 3iven no t often for the need of short«term capital
was to take advantage of pre-season discounts on fertilizer
and other farm supplies. Cnly one manager indicated short-
term Capital would be used for financin3 grain purchases.

when check a3iinst a question which asked if the mana3ers

held 3rain for hi3her prices only five indicated that they

had followe this practice.

Coven nana3ers said that capital for investment in

3,

er had also

{0
0)

facilities was needed, five of these same man
indicated a nee for short- term ce apitts l. The answers to this
question were r'ot consis tent with a later qu stion which asked
what new products and services should be added. Ihirty of
the thirty-four mana3ers indicated that new lines could
profita oly oe added to the firm's present lines. The follow-
in3 are the types of new lines that the mane3ers said were
needed: (1) bulk feed and fertilizer delivery equipment (2)
feed and molasses mixing equipment, (3) grain handlin3 and
stora3in3 facilities. It is apparent from the above list
that the new lines would reo uire intermediate or long-term
capital. Kany mana3ers indicated that havin3 the above
facilities would put them on a more equal basis with their
competitors.

Practices employed by competitors which were most trouble-
some to the managers intervkmednry be summarized into four
major classifications: (1) price cuttin3, (2) not discounting

sufficiently on dama3ed or wet 3rain, (3) cuttin3 truckin3

charges, and (h) liberal credit terms.

The menosers said they met these greetices b< providing

(0

tter ervice *h quality products end the exdvc- nte es of

‘5‘

(D
(0

b , hi
3 cooPerative in some cases. A somewhat wore complacent
answer was that they "tried to do the best possible under the
circumstances".

Pricing policies also de1:end ujon the comfctitive structure

facing the individual firm, however, products which can be

differentiated will be priced by different nethods the n those

*(3

roduc ts “hic:1 cannot be differentiated in the farmers' mind.
fhe following table shows a summary of pricing methods for
certain items sold by country elevators. The sum of each
column does not equal 3M because more the one method of
pricing a given commodity was emgloyed by p: rt of the firms

studied.

 

 

Table 12. Iethod of Pricing, lumber of Firms and
Per rc~ntege Using Each Fethod.
Kethod Per Per Other Per Ser- Per
of Grain cent- Feed ce ent- Farm cent- vices cent-
Pricing age 3g Surplies age age

 

Buyers or

suppliers sug- 8 l9 4 10 13 26 2 6
gested mark—ups

Feet competition 25 58 11 27 20 41 27 75
3ase on

estimated cost 8 19 2h 60 15 31 6 16

Try to beat
competitors 2 u 1 3 1 2 1 3

43 no 49 36

The methods of pricing grain end services indicates that
there is a high degree of competition in these two items.
This is expected in a homogeneous commodity such as grain.
Services, generally Speaking, are very much the same egerd-

less of the firm, therefore, it is to be exp cted that a sub-

(D

stantial degree of competition exists in this item.

The above table indicates that feed is a product which
can differentiated to a considerable extent. This is pri—
marily due to "complete" feed mixes and brand name protein
supplements which can be differentiated on a quality basis.

The methods employed in pricing other farm supplies
exhibit considerable variability. Items such as fertilizer
have experienced considerable price competition in the last
few years, almost to the extent of price wars in certain areas
of the State. Seed corn and legume seeds on the other hand,
may be differentiated on a quality basis, hence suppliers
suggested mark-up or margins based on estimated cost may be
used es the predominant pricing methods.

Advertising and other promotiondl schemes are not used
to any great extent in the elevator business. Probably the
major reason for this is that the country elevator primarily
merchandises farm production items and these do not lend
themselves to the emotional appeal which can be created for
such products as new automobiles, clothes and other consumer

items.

Thirty-two of the 3b firms studied anvertised, however,
the total amount spent was only ju2,303. about 41 percent of
this amount was spent on newspaper advertising, 15 percent
was used for direct mail advertising and 5 percent was spent
on radio and T.V. advertising. About 10 percent of the
total amount sgent on advertising was for calls on farmers
and 29 percent was spent for all other promotion. Kearly
all of this 29 percent was donations to community organi-

zations such as F.F.é., Junior Farm Bureau, 4-H and churches.

mfiPflmif
SUREAEY LED CCNCLUSICNS

In this study a Cobb-Douglas type production function was
euployed to determine the productivity of the different re-
sources used in 34 selected Nichigan elevator-farm supply
firms in 1955. The primary objectives were to measure the
returns to various resources used in country elevators and to
estimate the effects of varying resource combinations on gross
margin as measured by an index of marketing services. The
secondary objective was to obtain estimates of the returns to
fixed assets based on present valuations and on replacement
costs. It was hoped that these estimates would offer useful
tools to the management of country elevators concerned with
prOposed reorganization and expansion programs.

A discussion on the operating structure of the Michigan
country elevator and the nature of its production function
showed that the real product of the country elevator is ser-
vice and that the measure of this service is gross margin.

When measured at the geometric mean of inputs, it was
found that the productivity of direct Operating expenses and
machinery and equipment was considerably greater than labor
or accounts receivable and inventory. It was then concluded
that an increase in the amounts of direct Operating expezses
and fixed assets would lead to a more nearly economic Optimum.

Slight increasinr returns to scale were evidenced in the

L3

function fitted, therefore it was not possible to reach an
econ mic optimum in the se nse tzat the mar3inal value product
of each input mas equal to ts res;e ctive meQ inal factor
cost.

A proposed reorganization based on increasing direct
Operating expenses, the input wlich yield ed the h ghest re—
turn, was investigated. This is primarily an increase in the
use Of the firm's capacity, because direct Operating expenses
are these expenses which vary with the physical volume of
products handled by the elevator. It appears to be a very
reasonable1mrowo al in li3ht Of the fact the t only about 50
percent of the feed grinding and mixing capacity of these
firms was used and only about 26 percent Of the grain capa—
city was utilized.

By increasing direct Operating expenses to the point at
which the marginal value proluct we s e1u l to the mar1ine al
factor cost, gross margin was increased by 117,3u3. as a re-
sult of the incresse in gross margin, net profit was increased
from 36,851 to $10,749.

a lon —run adjustment, in which direct operating expenses
and investment in nachinery and equipment were increased in
least cost combinations was 1313 O investigated. This adjust-
ment increised the estimated gross returns from 183,67u at the
geometric mean of inputs to $119,025, however, increased de—
preciation as a result of ex; an iing tide physical plant cause

the net Operating profit to be only $9,82Q.

The net Operetinr profit is not as great with the lon

0

run 21.1:1justr'nent as with t-Lf‘} s}-ort—run 51:..jus met 1111

in facilities. 53:2 reolocenent vzlues ere used in gricing
facilities in ell situations the net {refit decreases in both
the "usuel" organization end the short—run si ultion, however,
the rete of liquid cejital eccumulttion is highest in the

short-run situation. This meens that the immediate echoern

rcre

01

f .sin: the utilization of

M

of these lirms should b: one

D‘
C)

I

rresent facilities rether than investing in new facilities.

It nust be enembered that elevator farm supply firms
are merchendising es well as producing firms. Pherefore, an
instigation of the proposed reorgsnizetions will not necessarily
increase returns unless renegement taxes action which will in—
crease the qu ntity demanded Of the firm's services.
Tirms which deviated substantially from he function

fitted to the data were analyzed to determine the cause of

U

the deviation. In 1

)

=enersl, those firms with large positive

(

higher percentewe of total gross margin

0

C“,

residuals Obtained
from merohendised grain and utilized 3 greater yercentege of
their rated capacity relative to the everege for all firms
or those with negative residuals.

A comparison of actual gross mar3in indicated in the
Operating statement (Ya), index of marketing services (YO),

A
and estimate Of the index of marketing services (1) indicated

that the demand for a given firm's services is relatively

O\
O\

’D

elastic. fherefore, i major objective of mane;

ement should

be to increase volume by decreasing the frice of its services

in order to obtain a greater totel gross margin.

APPEI‘CDIX

CL.
2;

 

 

oasss smmmcfi meow :msmsfi mu :m
nmqssfi mssma mosmfi :Hflssm mmfi mm
mmsmfim m smwfi amass mfizwmfi cam mm
mesmm mmmzm m m Hosmw :m Hm
:_wmwfi smash @mmm smoqfim mad om
Hsmmm mwmfiw mmmm mmmwofl :HH m
swans mmcm Hmsfi msmm: up mm
mmwzm mwwm_ dams smom: em mm
cams: Hoamm imam ssqmm mm mm
HmHTm :mmmw wmos nowwcm mm mm
mmqmm Hmmms mmwm ommmm om m
mmmema soowm mzmfi mmomm omfi mm
mmmwflfi OOHOHH mmflm mmmcm mmfi mm
mosmfifi mmzoofi mmmfi mwmmm mofi Hm
umqowm saomm was: mmcomfi wmm om
mmfifim comm: ammm omwws omfi ma
usmfimfi oqmfia Hausa mwxflofi :wH ma
mommm mmmo: moan oomcm on pH
when: ooomm m OH mmwwm mm wfi
summm mzewfi mszmfi mmssm mm ma
mssmm msfism mmmcfi mmsss 00H 3H
momma mamam Hmfiw sommm Hm ma
moosofi m on mfimsfi Husmm smfi NH
Hmmfimfi mmmfio osflsm smmfimfi «mm Ha
Hfiwmofi mmw)mfi mama mmmvm mofi OH
mmflmw :mwww mmzzfi comma mmfi m
:mmomH mmmsm :Hmam mommmfi mmm m
Humom nmwmu wweoa mmmom N: s
ommmm Nomflw omflofi NHUfis om w
smmmm Hmmfia HNHH mmmmm mm m
swamp mamms mesa Hmowo mm :
:msms muons cons mmmmmfi mmfl m
mmwam smmmm omu_ owm\m o: m
Hsmsw mwmm: msmm manna sfifi H
Awe Asxv Army onv Afixv
unmemaswm was .
mood>pmm hpmcfisowa mmemgxm thme>QH mom pondq
MQapmxps: mo m3as> mQHpMngo maos>fimcom mpssooom m>ap05doph .MH mapma
mo KodCH pnmeoomamem pompao magpcox mm$p®>q mxpcoulfiwu

psozm so Lm>o Swat

xwp moasw

mammmso mcfiam>mpm

mmsomxo noduomfiaoo

mmamappm>wm
momssgoxo

was mpssoomaa
zmmpmmamp

USE msogmmaon

moaHQQSm omsozmsmx
meaLOpQ®>mfi hog

mzmoa no pmmpmpSH

mmfiammsm moaggo

mcfiAOSLp dopam

mmsmmxm unwaopm

 

unashasmm mmmmpm .Hao .mmw mapw>dmooh monsooom
use aposflzoma mo mpmcasosa mazpaos owmsm>m moan mgpsoa new
mods» psmsoomammm madcappomfim hpousm>zfi kHSone omeho>a m>aposvopm
Arflv pflmfi \ z
Imazwm e aposagowu onv momsmgxm Amxv manm>aoomm
ma psmspmo>sH msHpmswuo pomsao monsoooa one spousm>mH AHNV Lopmq
mmHLOMmpmo pomQH
oaoosH mammzm Sampw mampw
mofi>pmm spmm ESmHospmm comm powaaaphom mowmmoopm womfiwmwgosmz

 

NH% QflWLmb mmOLU

 

NLOTGDSO DSQSH Eomfi MO 69% Sdfihfifi mmOLU %O wwfimflomfioo .dfi QHDEH

7L

Table 15.

D

Computation Cl

Farginel Value Products

70

 

 

 

tza- - v: r .2
nput Category “L ntity Of v l'rp}n*%

Inyut value rrccuct
Kl Labor 161.3 months 320.32

Inventory &
Locounts Receivable

Direct Operating

376,194

 

J EXpenSe 13,305 1.696
X“ Reflecement Value of
iachinery & Equipment 58,597 .268
YVP f b1 (“) Y == antilog of log bi + 10” (T) Y - 10% Xi
J'xi
Adtilog
yup- = 9.53881-10 + u.,2:59 - 2.c0581 = :.50559 - .320. 2
Jul
rva = 9.:1333-10 + b.92259 - b.88192 = 9.2 boo-10 = .179
.n\2
FVPX = 9.u3091—1o + n.92259 — u.12u02 = .229u8 = 1.696
‘3
DJP. = 9.273b6-1o + u.92:59 - n.76802 = 9.u27u3—1C + .268

TO

\(3

10.

ll.

EITLICGRRPHY

Beringer, ChristOph, A ie t1ioi of Sstimetin=
Froiuctivities of Insut NJn Invest :e “~
Fultiple incernrice Ffmr

 

S .
Elohlgan QCote 30118.5 , 1955.

q.
1

Bradford, Lawrence 3. and Johnson, Glenn L., Fe
ment AnalysiS, New Ior 1:: John alley anfl Sons, Inc., 1953.

 

 

Carter, K. 0., Iodific ation of tne Co fo- -Dougles unction
to Destroy Const3nt Elasticity find symmetry", Resource
Productivitv E.turns to Joele crd “wrm 5 7e. Eli ed oy
Eerl C. Keely, Glenn L. Johnson and Lowell 3. Berlin, 1955.

Cobb, Charles 3. and Douglgs Feul H., "A Theory of Pro-
"'7

(j ’
duction", Americsn Eccncwic Beviev., Supplement A1111.

 

Croxton, Jericx E. and Cowden, Dudley J., Acplied

stics, Lew York: Erentice-Hell, Inc. Second'

 

re
’1 1's .-, "‘ -.
Jenerul it t

r

Edition, .0

19:: Hri_l Eccncoics, Rew York: Prentice -H211,

Dean, JCel,
M1 ird Irintiin”,1954.

1nc.,
DUPL nd David "‘ome Thoughts (n Ker rgin nel Proluctivity
with S: ecie .1 Eeference to Pro fe :ws r Dc mu “1 s' -r'lys s",

J.

 

Journe 1 of Politics ECOLm mics, XLV, Decemo er 1953.
Friedman, Joan and Foote., Hichurd J., "Computational
Fethods for Handling -ystems of ciiultaneous Equations",
Agriculture Handbook 1C. Oh, L331, shs, Lovember 1955.

 

Johnson, Glenn L., "Classification s.d nccounting Pro-

blems in Fitting Production Function to Perm Record and

burvey Data". 36 ource Pr0‘1 Htiv ity1_ee urns to Scale

gnfi Farm Size, Elited bl Eerl O. heedy, Glenn L. Johnson
P

uni Lowell S. Hardin, 1e Iowa State College Press, lmes,
IOV‘IQL , I: o S o .751; 0

 

Johnson, Glenn L., Sour2es of Income on Utlend KcCrecgeg
County Farms", PrOgress Report Lo. 2., Kentucky gari-
cultural 2X1eriment Station, 10 51

 

 

 

Kelly, P. L., Tucker, E. and Te nuel, K. L., Rescurce Ee-
tur-ns and Productivity Coefficients in Henses Cooreretive
Grzin Elevator Iniustry. Technical Eulletin 8%, 3Fri-

 

cultural EXperiment Station, Kansas State College,
October 1956.

130

14.

 

 

State College,

Rlly, P. L., KcCoy, J. U., Ihc”er, E., sltsn, V. _.,
a~.)wr fieturns uni Fro Zuctivitx Coefiicients i1 cen-
trel ”L1 e tern K-nses Jountry55lev-:to1s of ioflern
’fi 1‘1" tC-ti on, lLE-CIJS AS

ulturel ulterirent s
1‘

Phillips, Richard, Tgnigin2 for Greater Returns in

COUUtEE Elevator 2rd heteil Eerm S‘Lrly Businesses,
Farmers Grain Deniers gssccietion of Ian (Cooperative)
Des Toinos, Ions, 1957.

Eintner, Gerhsrit, "A Note on the Derivation Cf Pro—

tion Function from Term Records", Eucn01etr1o25kni ,
Sutplement to. l, Junusry lQHM.

 

Iintner, 3., sni Brownlee, C. K., "Production Functions
Derived from Fsrm Records", Journal of Term Eccncmics,
Vol. 29, 19h5.

Te21ey, R bert V., erzinel oiu ctives of Invest"ents

 

and E":en€itures, J—-le cte i In:k;3m County Eaiwsi5135 ,
Un publisled K.S. thesis, Iichigen state College, 1953.

-ni

CONFIDENTIAL CONFIDENTIAL
Questionnaire on Elevator-Farm Supply Businesses
The information asked for on this questionnaire is for research purposes only.
It will never be divulged in such a manner that the information can be identified with

your busine ss .

Name of Business Date

 

Address Michigan
Post Office County

GENERAL INFORIJTATION

Kind of Omership
Individual prOprietor
Regular Corporation
Cooperative Corporation

 

 

 

How large a trade territory do you cover (miles in each direction)

 

 

 

 

East
South
West
North
EMPIDYI-IE NT RECORD
How many full time employees do you have exclusive of the manager ?

 

How much seasonal hiring did you do last year?

 

 

Can you give a job classification for each individual you employ as asked for in the
table below? If one individual works at two jobs, for exanple, if an office employee
waits on customers, or if a mill man drives truck part time, please estimate the time
spent on each job as closely as possible.

Classification of jobs by individuals

 

 

Employee and Time employed Duties Salary
Department in Imnths
Feed

 

 

 

 

 

 

 

 

 

 

 

 

NOU'Ilr'b-JNH

 

 

Employee and
department

Time employed
in months

Duties Salary

 

Grain

O\\J'lLT'UJl\)I-‘

Truck drivers

Bookkeeping

O‘sUIJT-‘WNl-Jg' \T'LJZ‘LONI-J
‘1

Managers Nana

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. Do you operate on a straight salary

 

 

What is the basis for payment of commissions or bonuses if any

or on a salary plus

commis sions or a bonus .

 

 

How much of the salary item in the operating statement of your audit represents a payment
to you for management

Do any other employees re oeive commissions or bonuses. If yes, explain

 

 

 

 

What percent of managers time is spent:

1. Waiting on customers
2. Btwing grain or beans
3. Doing clerical work
h. Studying markets, attending meetings, learning about feeding or fertilization
practices, studying past operating records otherwise acquiring information

needed for management decisions

?

 

?

 

?

 

5. Other activities

?
?

 

In.

FARM PRODUCTS MARKETED

Product Quantity Cars Cost of Average mark
bought shipped sales up taken

Beans (navy)

Corn

Oats
Wheat
Barley

Soybeans

Other

 

FARM SUPPLIES SOLD

Supplies Units Sales Cost of Mark up Average
sold sales taken price rec'd

 

Gasoline
Tractor fuel

Kerosene & fuel
oil

Lubrication oil
Feed
Seed

Fertilizer - high
low

Coal.

Other famn
supplies

 

 

5:4 h a ' 1‘
\n ”1‘ x ‘ N I‘lu \AWb
.\ \ 5 .4 .‘|\ or q i

 

Receipts Charge
Receipts from.services rendered:
Grain and seed treating and cleaning . . . . . . . . . o o
Grindfingandnfiflng.o..............u..
Warehousing(Storage)..............o.....
Tkaingooocooocoooooooo0000000coco

MONTHLY STATEMENT OF INVENTORIES AND ACCOUNTS RECEIVABIE

Month Accounts Inventories
receivable

January

 

 

Fe bur-nary

 

 

March

 

 

April

 

 

May

 

 

June

July
August

 

 

 

 

 

 

September

 

 

October

 

 

November

 

 

December

 

 

Marketing inventories include wheat and other grains, poultry, eggs, etc. Farm supply
inventories include feed, seed, fertilizer, farm machinery, miscellaneous farm supplies,

etCo
BORROWING DURING LAST FISCAL YEAR
(List each loan separately)

Loan No. 2

Term of loan in months
Source (type of lender)
Purpose (Open, cap., etc.)
Se curity (mort., etc.)
Method of repayment

I-IaxiJmm amount outstanding
during fiscal year

Amount outstanding at close
of year

Interest rate

{-5

-5-

How much did you owe on trade accounts payable during seasonal peak operations?

Spring Fall

 

 

What is the maxinnm.amount which you can borrow on a seasonal basis from banks, patrons,
relatives, etc.?

 

KIND OF ADVERTISING OR FARMLR RELATIONS USED
Method Frequency Expenditure

 

Newspaper advertising

 

 

Direct Mail

 

 

Radio or To V0

 

 

Call on farmers

 

Other

 

 

 

 

 

 

 

 

Under what conditions in the past 2 or 3 years have you been hard pressed for capital?

 

 

Could you have increased your volume if‘you had had additional Operating capital this
past year? Yes no How much .

 

Explain

 

 

 

Do you feel that at the present time you should add new lines or services which you do
not have? Yes No . What

 

 

 

 

How much capital would be needed? . How much additional would this bring
in?

Which phase of’your operation do you consider most profitable? .
Have you aggressively attempted to push it in anyway? How?

 

 

 

Have you held grain for higher prices or bought future contracts throughout the year?

 

Do you.pick'up_or deliver many_commodities whichgyou handle?

 

Item % picked up % delivered Charge
From.suppliers or farmers to buyers to farmers

 

Feed

 

Fertilizer

 

Grain

 

Petroleum

 

Other

 

 

 

 

 

What percent of your feed volume is from your mixing Operation?

 

‘What percent is from.merchandised feeds?

 

‘What percent of your feed volume is for: Average price for each.kind of
feed

1. Poultry

2. Dairy cattle
30 Beef cattle
h. Hogs

S c Other

 

 

 

 

 

 

 

 

 

 

What kind of a pricing policy do you have?

 

Grain Feed Other Other services
supplies mixing, clean-
ing, trucking,

etCo

 

Take supplies or buyers suggested
mark-up

Try to meet competitors price

Base markdup on est. cost
irrespective of competitors

Try to beat competitors

What community projects does your business sponsor or support?

 

 

Who has the authority in practice for the following types of problems?
Owner Manager Directors Others

 

a. Setting prices

b. Pricing feed and supplies
c. Selecting sales outlet
(1. Buying major equipment

e. Hiring employees

f. Complaints

 

 

 

 

How many competitors do you have?

 

Location Kind of ownership Estimated total volume
of sales

Grain Other

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Which of the plants previously mentioned give you the strongest competition? (Name
in order)

1.

 

2.

 

30
h.
S.

i What do these businesses do that cause you trouble?

 

 

 

 

 

How do you meet this competition?

 

 

How much government grain did you handle last year?

 

 

 

Did you suffer any unusual losses on commodities handled last year?

 

 

 

 

Considering now the amount of business available and your competetive situation
what maximum volume of business do you think you ought to have in the trade terri-

tory you operate in?

Feed Grain Other

 

 

About right
Should increase

(How much 4- in percent)

 

 

If you feel you should increase -- what has prevented it?

 

BUILDING AND FIXTURES RECORD

Elevator

Grain storage capacity Bu.

 

Bag storage capacity

 

Cost value of bldg.

 

Present book value

 

Age of building

 

Mill

 

Bulk storage capacity

 

Bag storage capacity

 

Cost value

 

Present book value

 

Age of tuilding

 

Office and retail

 

ft.

Size of building x

Cost value

 

Present book value

 

.Age of building

 

warehouse No. l

 

Use

 

C apac ity

 

Cost value

 

Present book value

 

Age of building

 

warehouse No. 2

 

Use

 

Capacity

 

Cost value

 

Present book value

Age of building

 

Iarehouse No. 3

 

Use

 

Capacity

 

Cost value

 

Present book value

Age of building

 

Other buildingg

 

 

 

 

 

 

 

 

 

Other buildings

 

 

 

 

 

 

 

 

 

 

Elevator or Grain
Handling

Cost value

-10...

EQUIPMENT RECORDS

 

Make Kind and Purchase Present
& year capacity gprice book value

 

 

Present book value

 

 

Average age

 

 

Daily grain capacity

 

 

Mill

Cost value

 

 

 

Present book value

 

 

Average age

 

 

Grinding and mixing

 

 

capacity

 

Office and retail

Cost value

 

 

 

 

Present book value

 

 

Average age

 

 

 

 

 

Warehouse equipment
(Include loading-
unloading equipment,
such as coal loader,
petroleum handling
equipment, etch

 

Cost value

Other equipment

 

Use

 

Cost value

 

Present book value

 

 

Present book value

Average age

 

 

Average age

 

3‘; xi”: ('1; ' "' I: :5 r
.4 .‘ . . ._ 'f - ' , F
Tabs”: U3 3mi-

LE.

5“,”7’.‘ " ,... ”"3325. ‘1
DateDue, | . -

ids

 

' 1:9 3:“;

Demco-293

 

HICHIGRN STRTE UNIV. LIBRRRIES

 

II II llll
8

312930084 9357