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This is to certify that the

thesis entitled

A FINANCIAL EFFICIENCY MODEL

presented by

Charles Robert Carlson

has been accepted towards fulfillment
of the requirements for

Ph . D degree mm

 
  

 
 

ajor professor

4- Date Ma 12 1971 ‘

0-169

 

 

 

 

 

 

 

 

 

 

 

 

 

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ABSTRACT

A FINANCIAL EFFICIENCY MODEL
BY

Charles Robert Carlson

The major objective of this research was to develop
a model by which a firm in a given industry would be able
to obtain assistance in establishing long-range financial
guidelines. The model provides a systematic approach to
aid in providing a base for establishing policies for as—
set management and financial planning. Specifically, a
financial efficiency model was developed to assist in the
establishment of the appropriate level of current ratio,
cash, inventory, fixed assets, long—term debt and cash div—
idends.

It was assumed that there were no transaction costs,
no taxes and that the goal of the firm was the maximization
of shareholder wealth. Financial decision making was clas_
sified into three subdivisions: the investment, the fi—
nancing and the dividend decisions. Specific ratios were
the independent variables specified to measure the relative
efficiency of the three major decisions. Several independ—

ent variables were considered simultaneously in the

-|. i ,

 

 

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Charles Robert Carlson

iterative solution procedure and correlated with the de—
pendent variable—-the index of shareholder wealth appre—
ciation.

Eighteen companies in the drug industry were se-
lected for the study over the time period 1960 thru 1969.
All data were obtained from the Standard Statistics Coms
pustat Tape, which collected its data from annual finan-
cial statements, filings with the Securities Exchange
Commission and questionnaires received directly from the
firms.

In this study, the model developed an index of fi—
nancial efficiency using the Spearman Rho Rank Correlation
Test. A Specifically designed computer program was the
vehicle for determining the highest correlation between
the mean values of several financial ratios and the mean
value of the index of shareholder wealth.

The results were highly significant for the best
computer run——achieving a rho value equal to .690 which
is significant at (K = .01 confidence level. In this run
the seven financial ratios were the current ratio; the
cash turnover; the inventory turnover; the receivables
turnover; the fixed asset turnover; the debt ratio and
the dividend payout ratio. The current ratio and the re-
ceivables turnover ratio assisted in increasing the final

rho level even though on a univariate analysis they were

 

 

 

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Charles Robert Carlson

of low significance. Also, the model developed weighting
factors for the seven financial ratios, which indicated
the relative importance of each variable. This provides,
management with additional information for determining
areas on which to concentrate their efforts.

Several other practical applications of the model
were shown to be easily applicable for practical decision
making purposes——such as assisting bankers, credit manag~
ers and investors. Even if they do not have access to a
computer, manual calculations on a small selected number
of firms could be useful since the model's attributes are

its simplicity and low cost.

 

 

 

 

 

 

A FINANCIAL EFFICIENCY MODEL

BY

Charles Robert Carlson

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Accounting and
Financial Administration

1971

 

 

 

"470330

ACKNOWLEDGMENTS

The author would like to express his appreciation
to Professor Myles S. Delano for his tolerance and great
patience during the conduct of this study. His important
contributions as well as those of Professor Alan E. Grune—
wald and Professor Richard J. Lewis are also gratefully

acknowledged.

 

To Professor James Don Edwards, Chairman of the
Department of Accounting and Financial Administration, I
wish to express a special note of thanks for providing the
needed financial support. The author is also indebted to
several other faculty members and many fellow doctoral
candidates for helpful criticisms and suggestions. I es—
pecially want to thank Professors Alvin A. Arens, Hayden
R. Howard, Gardner M. Jones, Maryellen McSweeney, Roland
I. Robinson and Floyd W. Windal for important influences
on me——not just on this study—-but during my entire Ph.D.
program. I also want to thank Jim Mullin, Tim Sullivan
and Don Wort for their assistance on this thesis.

An extra Special note of appreciation goes to my
wife, Nancy Kay, for the tremendous contribution that she

has made.

 

 

TABLE OF CONTENTS

LIST OF TABLE. . . . . . . . . . . . . . . . . . .
LIST OF FIGURES. . . . . . . . . . . . . . . . . .
Chapter
I. INTRODUCTION
A. Purpose. . . . . . . . . . .
B. Rationale for need . . . . . . . . .
C . Technique l O O 0 O O 0 I O I O O O C

II.

III.

IV.

AK

§{E. Selection of independent variables

ANTECEDENTS OF THE FINANCIAL EFFICIENCY
MODEL. . . . . . . . . . . . . . . . . .

THE CONCEPTUAL FRAMEWORK

A. Overview . . . . . . . . . . . .
B. Financial objective of the firm.
C. Selection of dependent variables
D. The three major decisions. . .

MODEL DEVELOPMENT

A. Overview . . .

B. Selection of industry and companies.
C. Data . . . . . . . . . . . . . . . .
D. Time period. . . . . .
E. Dependent variables——ranking . . . .
F. Independent variables--normalizing .
G. Independent variables——rankings. . .
H. Financial policy guidelines. . . . .
RESULTS

A. Least square deletion program. . . .
B. Iterative solution runs. . . . . . .
C. Five year prediction . . . . . . . .

iii

0 o o o s

o o o - o o o o

Page

vi

(BOND-d

ll

 

Page
VI. SUMMARY AND CONCLUSIONS
A. sumary Of technique a o 0 o I I' I o 77
B . Limitations 0 I I O O O O O 0 O I O O 80
C. Contributions. . . . . . . . . . . . 82
BIBLIwRAPHY l O O O O l O O O D I l 0 O O O O D 86
GENERAL REFERENCES . . . . . . . . . . . . . . . . . 88
APPENDIX
A. Compustat classification of drug
companies I O O O 0 C I C O O I O C O 90
B. Compustat industrial definitions . . 91
C. Computer program for iterative
solution procedure . . . . . . . . . 103

iv

 

 

 

    

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10.

ll.

12.

13.

LIST OF TABLES

Rankings on Dependent9 Variables
Mean Values; 1960— 196 . . . . . .

Rankings on Dependent Variables
Mean Values; 1960—1969
Explanatory Example. . . . . . . . . .

Normalizing Procedure for Cash
Turnover Ratio Top and Low Quartile
Companies Mean Values; 1960-1969. . .

Univariate Spearman Rho Correlation
Tests Top and Low Quartile Companies
Mean Values; 1960-1969 . . . . . . . .

Mean Values, Normalized Values and
Component Scores 1960—1969. . . . .

Index of Financial Efficiency. . . . .

Rankings of Top and Low Quartile
CompanieS. . . . . . . . . . . . . . .

Financial Guidelines 18 Companies;
1960-1969. . . . . . . . . . . . . . .

Weighting Factors — 18 Companies
1960— 1969. . . . . . . . . . . . . .

Univariate Spearman Rho Correlation
Tests Mean Values; 1960—1969
18 Companies . . . . . . . . . . . . .

Simultaneous Spearman Rho Correlation
Tests 18 Companies; 1960-1969 . . . .

Simultaneous Spearman Rho Correlation
Tests 18 Companies; 1960-1964 . . . .

Simultaneous Spearman Rho Correlation
Tests 18 Companies; 1965- 1969 . . .

 

 

Page

46 n

47

51

52

54

57

6O

65

69

71

73

74

76

 

 

 

LIST OF FIGURES
Figure Page

1. Investment, Financing and Dividend
Decisions and Their Related Inde—

pendent Variables . . . . . . . . . . . .; 4
2. Investment Decision. . . . . . . . . . . . . . 28
3. Financing Decision . . . . . . . . . . . . . . 30
4. Dividend Decision. . . . . . . . . . . . . . . 31
5. Index of Financial Efficiency

 

BriStOl-Myers. o o I o a o o o I I I u o a o o 48

6. Weighting Factors and Spearman Rho
Rank Correlation Test ResultS. . . . . . . . . 53

7. Financial Guideline Computation
For Cash Turnover Ratio. . . . . . . . . . . 61

8. Financial Guideline Computation
For Inventory Turnover Ratio . . . . . . . . . 62

9. Financial Guideline Computation
For Fixed Asset Turnover Ratio . . . . . . . . 63

vi

 

 

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CHAPTER I

INTRODUCTION

A. Purpose

The objective of the research was to develop a
technique by which a firm in a given industry can obtain
assistance in establishing long range financial guide-
lines. Specifically, a financial efficiency model was
developed to assist in the establishment of the appro—
priate level of current ratio, cash, inventory, fixed
assets, long—term debt and cash dividends. The drug
industry was selected for the study and the data obtained
from the compustat tape.l

Establishing effective overall long—range finan—
cial guidelines requires knowledge of the prime objec-
tives of a firm. The literature of finance2 frequently
assumes that the principal objective of a firm is to
maximize shareholder wealth. This study assumed that
management would try to achieve this objective. In addi—

tion it was assumed that there were no income taxes nor

 

lCompustat Tape, Standard Statistics Company,
Inc., 1971.

2See James C. Van Horne, Financial Management
and Policy, Englewood Cliffs, N.J.: Prentice-Hall, Inc.,
1968’ p. 8‘90

 

 

brokerage charges. Removal of the latter two assumptions
would not significantly alter the technique used in this
research-u-it would only complicate the mathematics in—
volved.

In this study, the goal of maximization is viewed
in the same manner as it would be in a linear programming
problem. In linear programming the solution is regarded
as an optimal value, whereas in this study it was only con-
sidered to be the best value relative to other values gen-
erated by other firms in their respective industry. One
way to measure shareholder wealth is to look at the sum of
market price appreciation of a stock plus the cash dividends
paid to its shareholders between points of time. An index
of shareholder wealth appreciation is the dependent variable
used in this study. It is the percentage change in market
price over time with any cash dividends reinvested each year
in its own respective stock.

If the objective of the firm is to increase share-
holder wealth through cash dividends and/or increase in the
market price of its stock, decisions by the firm should
reflect this objective. Financial decision making in a firm
can be classified as the investment, the financing, and the
dividend decision. These decisions are interrelated and
should be considered simultaneously to insure the efficient

operation of the firm for the shareholders. Determining an

 

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appropriate level of cash, inventories, receivables, fixed
assets, current ratio, long—term debt and cash dividends
are the major components of these decisions. The financial
decisions should lead to an effective utilization of the
resources available to the firm by considering the degree
of goal fulfillment and the efforts required to achieve
this result. The focal point for the final result is divi-
dend and share appreciation.

Several independent variables were selected to
measure the efficiency of the three major decisions of a
firm. Figure 1 shows the seven independent ratios chosen
to reflect the efficiency of the three financial decisions
made within a firm. Chapter III will discuss the reasons
for the selection of these seven ratios.

Even with detailed internal data-u-generally un-
available to the researcher—-the measurement of efficiency
is extremely difficult. For those outside of the firm the
problem is even more difficult. Since the yardstick gen-
erally used to evaluate management decisions by those out—
side the firm is the annual financial statement, the fin—
ancial efficiency model developed here will incorporate
only data from these statements. Roy A. Foulke said: "Ev—
ery managerial policy, or absence of managerial policy, is
reflected somewhere in the figures in the balance sheet,

in the income statement, or in the reconciliation of sur-

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plus."3 The independent variables used in this research

are standard financial ratios——such ratios are the means
of comparing data between firms. Ratios selected were
those which reflect best the results of the investment,

the financing and the dividend decisions.

Current ratio. . . . . . X1
Cash turnover. . . . . . X2

Inventory turnover . . . X3

/ W.C.
I
\\\\\\\ Receivables turnover . . X4
C.B.-—

 

Fixed asset turnover . . X5
F ——-—-—— L.T.«—- Debt ratio . . . . . . . X6

D ________—————_—- Dividend payout. . . . . X7

where I = Investment decision
F = Financing
D = Dividend decision
W.C. = Working capital
C.B. = Capital budgeting

L.T. = Long—term

Figure 1

Investment, Financing and Dividend Decisions
and Their Related Independent Variables

 

3Roy A. Foulke, Practical Financial Statement Anal-
ysis, 6th Edition, New York: McGraw—Hill, 1968, p. 4.

 

     

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Ratios and indexes are the I'nuts and bolts“ that

 

 

make up security analysis. Ratios take two absolute num-

 

bers and allow a meaningful comparison between entities.

An index takes one absolute number and again allows a mean—
ingful comparison between entities. ”The ratios are snap-
shots of the picture at one point in time, but there may be
trends in motion that are in the process of rapidly eroding
a relatively good present position. . . . Conversely, an

analysis of the ratios over the past few years may suggest

 

that a relatively weak present position is being improved
at a rapid rate.“4 The number and form of ratios are numer—
0115, however, the model will accomodate any reasonable num—
ber of independent variables—-up to the Specific limita—
tion of the particular computer in use. Since it was desir—
able in this model to use a minimum number of independent
variables, it would be extremely unlikely that any upper
limit of independent variables would ever become a limitation.
Necessarily, any model should be parsimonious in its
use of independent variables for easy interpretation and use.
Those independent variables were selected that are relevant
to the drug industry. The relevancy of these ratios for
other industries was not investigated in this study. The

drug industry was selected because of a large number of

 

4J. Fred Weston and Eugene F. Brigham, Essentials
of Managerial Finance, New York: Holt, Rinehart and Winston,
1968, p. 49.

    

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firms with a comparatively homogeneous product line. Addi—
tional reasons are given in Chapter II-._resu1ts of other
research studies- -for restricting the use of this model to
a given industry.

Consequently, the model will provide the technique
by which a firm in a given industry can develop guidelines
for several independent variables. The development of these
guidelines were attempted by an iterative solution procedure

based on a previous or past interval of time considered to

 

be the long—term. The drug industry was used to demonstrate
the soundness of the technique. Naturally the question should
be raised and answered about whether the future will be like
the past to project future target guidelines. Also, quanti-
tative methods established internally should be used in or-
der to refine the specific levels of cash, inventories, etc.
If conflict arises between the levels obtained by the de—
tailed internal analysis and the overall guidelines estab—

lished by the model, further investigation will be necessary.

B. Rationale for need

 

“Apart from the stock market, we have no objective
standard of managerial efficiency. . . . A fundamental prem—
ise underlying the market for corporate control is the exis-
tence of a high positive correlation between corporate mana-

gerial efficiency and the market price of shares of that

 

company. . . .”5 Given that the firm's objective is to
maximize shareholder wealth and that the independent vari—
ables selected in this study reflect the efficient opera—
tion of the firm; then a model achieving a high statistical
correlation between the two should be extremely useful.
Manne indicates a need for an objective standard of manage—
rial efficiency, and he also indicates that there is a high
positive correlation between managerial efficiency and the
market price appreciation of a firm's stock over a period
of time. Therefore, a model designed to provide a standard
of managerial efficiency—-an index of financial efficiency
-—should assist corporate management in establishing long—
range financial guidelines.

In reviewing the relevant literature, no research
study was found concerning ratios or measures of the deci-
sion making process within a firm as to the correlation to
the firm's objective. Alexander Wall6 in 1919 pointed out
that to get a complete picture, it is necessary to consider
relationships in financial statements other than that of
current assets to current liabilities. Many authors since
have pointed out the necessity of simultaneously relating

ratios to obtain a complete picture.

 

5Henry G. Manne, ”Mergers and the Market for Corpo—
rate Control," The Journal of Political Economy, LXXIII,
No. 2 (April, 1965), p. 112-113.

6Alexander Wall, How to Evaluate Financial Statements,
New York and London: Harper and Brothers Publishers, 1936,
p. 70-72.

 

 

     

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In this study a model was designed Specifically to
develop an index of financial efficiency. Simultaneously,
the mean values of several independent variables were the
input data to an iterative solution procedure with the task
of correlating their values-u-using nonparametric statistics
—-with the mean value of the index of shareholder wealth.

The highest correlation obtained produces the index
of financial efficiency. Then this index can be used to
assist the management of a firm in establishing long-range

financial guidelines.

C. Technique

An iterative solution procedure was used to empir—
ically investigate the relationship between several inde—
pendent variables and a dependent variable. A specifically
designed program (see Appendix C) was the vehicle for deter—
mining this relationship. The input data for all variables
came from the compustat tape; the information or data on
the tape were obtained from annual financial statements,
questionnaires from companies and information filed with
the Securities Exchange Commission.

The steps in the iterative solution procedure are

as follows:

1) Compute a mean value for the two dependent and sev—

en independent variables (as listed on page 4,

 

 

    

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Figure 1) of the companies in the drug induse
try for 1960-1969;

2) Rank all drug companies from high to low based
on the mean value of their dependent variable;

3) Normalize all values of independent variables
on a scale from one to one hundred;

4) Select various combinations of weighting fac—
tors which sum to 1.00;

5) Multiply the various sets of weighting factors
times each normalized value obtained in Step 3;

6) Compute a composite value by adding these com—
ponent scores obtained in Step 5 for each firm;

7) Rank the composite values for each company from
high to low;

8) Use each set of weighting factors as Specified
in Step 4 to run a Spearman Rho Rank Correlation
Test between the rankings in Step 7 and Step 2;

9) Select the composite value arrived at in itera-
tive solution procedure described above with the
highest Spearman Rho coefficient-u-this will be

the index of financial efficiency.

A least square deletion (multiple regression) pro-
gram was used in this study and proved to be an unreliable
predictor. For example, the program eliminated all the in—

dependent variables but one (at d{ = .05 confidence level)

 

10

in trying to explain the changes in the dependent variable.
Consequently, a nonparametric test was used.

According to Mendenhall: “Finally, one should note
that many nonparametric methods are nearly as efficient as
their parametric counterparts when the assumptions under-
lying the parametric procedures are true, and, as noted
earlier, they could be more efficient when the assumptions
are unsatisfied.”7 The data for this study were believed
to violate the assumptions of normality and independence of
variables for parametric tests.

By evaluating the index of financial efficiency a
range of values for each independent variable can be derived.
This range of values will provide assistance in establishing
broad financial guidelines for a firm. With this type of
model a sensitivity analysis can be accomplished-u-changing
the mean values of independent variables and observing the
relative changes in the ranking of the composite values or

ranking of the index of financial efficiency.

 

7William Mendenhall, Introduction to Probability
and Statistics, Belmont, California: Wadsworth Publishing
Company, Inc., Second Edition, 1968, p. 318.

 

CHAPTER II

ANTECEDENTS OF THE FINANCIAL

EFFICIENCY MODEL

Alexander Wall published an article in 1919 sug-
gesting that it is necessary to consider relationships in
financial statements other than that of the current ratio
alone. In 1936 he developed “An Index of Related Propor—
tions."1 Subjective judgment was used in weighting the

ratios as follows:

Current ratio. . . . . . . . 25 %
Net Worth-to—fixed . . . . . 15 %
Net Worth—to—debt. . . . . . 25 %
Sales-to-receivables . . . . 10 % Managerial
Sales-to—merchandise . . . . 10 % Capacity
Sales-to—fixed assets. . . . lO %

Sales—to—net worth . . . . . 5 %

 

100 %

Wall went on to explain that two years of data

were necessary to develop the index. "Those ratios having

 

lAlexander Wall, How to Evaluate Financial State-
ments, New York and London: Harper and Brothers Publishers,
1936, p. 70~72.

 

ll

 

 

 

12

to do with profit or losses cannot be worked successfully

into an index, because if we should be using a profit fig—

 

ure as a base and our subject should show a loss it is dif—

ficult to establish the relation between such plus and mi-

nus data.“2 This difficulty of negative profits could pro-

bably be handled by merely dropping the data for that spe—
cific period. Profit figures are not used in this study as
they are the result of the financial decisions made in the

firm. Adhering to the cause and effect relationship it is

 

believed that the independent variables selected in this
study are the cause or efficiency yardstick of the three
financial decisions made in the firm. The profit figures
then were considered to be the effect of these decisions.
Efficient decision making should cause greater profitabil-
ity——resulting in increased cash flows to the shareholders
through cash dividend and/or share price appreciation.

Roy A. Foulke3 looks at groups of financial ratios
in evaluating overall performance; and though relationships
are discussed, it appears that guidelines for selected ra—
tios are developed individually. As an example, his guide—

line for the current ratio is the familiar 2:1. "The ratio

 

21bid. p. 72.

3Roy A. Foulke, Practical Financial Statement Anal—
ysis, New York and London: Harper and Brothers Publishers,
1936, p. 10—72.

 

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13

would hardly have been adopted so extensively as a standard
if ordinary experience had not indicated its practical sig-

nificance."4

Foulke does look at the overall firm by making
judgments based on whether the firm deviates from his guide-
lines. The 2zl guideline is known to be good since a lower
ratio is a characteristic of many firms that have failed.
However, no experimental evidence of its relationship to
other ratios is revealed in his book. Nowhere does he re—
late these ratios simultaneously to explain the changes in
shareholder wealth appreciation. Mr. Foulkes‘ and Mr. Walls'
emphasis is primarily on a firm's credit standing or credit
worthiness.

Mr. Vance in his article, "Is your Company a Take—
over Target?”5 developed an index of vulnerability by using
four financial ratios. His take—over indicators and weight-
ing factors were as follows:

Liquidity: % of working capital
to total assets . . . . . 30 %

Long—term debt as a % of net
worth . . . . . 25 %

Annual earnings per share divided
into share price . . . . 35 %

Percentage growth in earnings
over the past three years . . . . . 10 %

100 %

 

4Ibid., p. 191.

5Mr. Vance, "Is Your Company a Takeover Target?“
Harvard Business Review, May—June 1969, p. 93—98.

 

      

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14

All four financial ratios can be calculated from data found
in the annual financial statements which is also true of the
model developed in Chapter IV. Mr. Vance indicated that his
Raiders Index was particularly applicable to industrial com-
panies, not to debt—heavy financial institutions. He empir—
ically tested his model against twenty-one companies that
were approached with tender offers during a three month per—
iod—-May, June, and July of 1968. By this test, seventeen
of the twenty—one companies could have detected their vul-
nerability to take—over.

Vance continues: “Statistical research, verified by
subsequent observation, suggests the possibility of combin-
ing these four signals to provide a sort of 'Raider's index'
or formula for the possible takesover victim. Obviously,
such an index cannot be definitive. It can, however, serve
as a useful spur to management thinking for further analysis."6
Vance uses profit figures in his index which Wall rightfully
warns against because of negative profit possibilities. A1—
so, profit figures are believed to be the effect of and not
a cause of efficient financial decisions made in the firm.
In addition, the article unfortunately does not explain how
the weighting factors are developed.

Vancds research technique is closely related to this

study--even though his objective was different-—as it uses

 

61bid., p. 94.

 

 

15

only data available on annual financial statements; uses
only a minimum number (4) of independent variables for his
predictive model; and combines independent variables into
an index. The financial efficiency model developed in Chap—
ter IV accomplishes these points and serves as a Spur or a7
helping device for management to establish financial guide—
lines.

Robert Jess Frame, in his thesis on “Corporate Fin—

ancial Policy and Growth: A Behavioral Model"7 suggests that

 

financial decision variables controlling retained earnings,

external equity, and debt sources are rarely altered.

The basic hypothesis advanced in this study is
that the firm maintains stable financial policies
which, through their influence on the source of funds
available to the firm, determine the long—run growth
rate it can achieve. . . . . . . . . . . .

much of the empirical evidence available is
based on broad aggregates, rather than the behavior
of individual firms.

Further, both the theoretical and empirical
work in the literature typically focus on one finan—
cial policy, ignoring its inter—relationships with
other policies and their combined influence on
growth. . .8

Finally, even though the basic hypothesis was sub—
stantially supported, it was pointed out that stable finan—

cial policies are not necessarily Optimal. During the most

 

7Robert Jess Frame, "Corporate Financial Policy and
Growth: A Behavioral Model,“ (unpublished Ph.D. Dissertation,
University of Colorado, 1966).

8Ibid.

16

recent three year period we have seen changes in financial
policies. For example, American Telephone and Telegraph,

a conservative company, has increased its debt ratio signi-
ficantly over the past two years.

It is the thrust of this research effort to provide
insights into previous patterns of financial guidelines
that have appeared to be related to the efficient operation
of the firm.

Ralph Michael Kraus' thesis concerned itself with
managerial performance ratios which supplemented the tradi—
tional framework of financial ratios by encompassing phys—

ical as well as financial stocks and flows.9

The managerial control ratio system he used
consisted of the following:

1) The rate of return on total investment

2) unit profits

3) selling prices

4) total unit costs

5) physical output turnover of total investment

6) the rate of capacity utilization

7) the ratio of capacity to fixed investment

8) the ratio of fixed investment to total

investment.

Empirical findings covered twenty years exper—
ience in nine industries and sixteen companies in
reSpect to each of ninety—two hypothesis. . . .
Perhaps the most interesting, however, from a
decision—making point of view is the finding that
industries seem to differ significantly in the
relative influence of adjustments in’the various
control ratios on concomitant adjustments in
their reSpective rates of return on total invest-
ment. This opens the possibility of developing

 

9Ralph Michael Kraus, “Empirical Testing of New
Managerial Control Ratios,“ (unpublished Ph.D. disserta—
tion, University of Pittsburg, 1967).

 

17

differentiated managerial strategies for various
sectors of industry——emphasizing profit margins
in some, capacity utilization in others and in—
vestment allocations in still others.10
The empirical findings of Kraus' thesis suggests that any
financial policies derived from any set of financial ra—
tios should be confined to a single industry.

Many of the items in Kraus' control ratio system
seemed to be related to efficiency measures and were con—
sidered in the selection of the independent variables in
this study. For example, the turnover ratios (cash, inven-
tory and fixed assets) were highly significant when cor—
related individually to the dependent variable.

Manak Chand Gupta's thesis analyzes corporate
financial structures with reSpect to three exogenous var-
iables——size, growth, and industrial variations——and at—
tempts to make a modest theoretical contribution to the

construction of a theory of corporate financial structures.11

The study relates to the year 1961—62 and es—
sentially indicates the following:

a) accessibility to outside capital markets
varies positively with the size of the corpora—
tion, because of various psychological, institu—
tional, and cost factors;

(b) the greater degree of integration (vertical,
forward, backward) that larger corporate size favors;

 

lOIbid.

llManak Chand Gupta, “A Synchronic Study of Cor—
porate Financial Structures 1961—1962," (unpublished Ph.D.
dissertation, University of California, Los Angeles, 1967).

 

18

(c) the volatility of earnings that varieS“
negatively with corporate size and the associa;
ted operation and cash breakeven points consid—
eration that it entails.

Profitability ratios based on sales vary
positively with size, but those based on assets
show no significant differences among various
sized corporations. . . . . . . . . . . . . .

No significant difference between the fin-
ancial ratios of the growth group and nongrowth
group of industries was observed. . . . . . . .

The profitability ratios show no significant
relation to corporate growth. This,is because
(1) the sales concept of growth is used in this
study and sales expansion need not always be as—
sociated with Operational efficiency or technol—
ogical progressiveness; (2) sales expansion may
be in response to 'trade position motivation'
rather than extra—profit opportunities, and (3)
the existence of a 'speed premium function' as
well as greater possibilities of production——
sales mischeduling

Even though Gupta's study covers only two years and
treats only financial structure, some of his results indi-
cate that the model should only cover one industry. Part
(a) and (b) could possibly explain why companies in the
drug industry with mean values of total assets and/or to—
tal sales have substantially lower debt ratios than the
mean value of debt ratios for the industry. Gupta's com-
ments on profitability——particu1ar1y in the last para—
graph in the quote—~infers that sales expansion is usually
associated with operational efficiency or technological
progressiveness. Thus, it lends support for the use of

turnover ratios as an efficiency measure and supports the

 

lzIbid.

 

l9

interpretation that profitability ratios are the end re—
sult of efficient decision making. Technology, research
and development expenditures probably should be used; how—
ever, the data are not available for all of the companies
in this study.

Edward Ira Altman investigated empirically the

characteristics of bankrupt corporations and attempted to

develop an accurate bankruptcy predictive model.13

The model contained five independent ratios
which served as the predictive variables. These
ratios were also investigated on an univariate
basis. . . . From an original list of twenty—two
ratios, the suggested model contained five vari—
ables. They represent measures of corporate li-
quidity, profitability, solvency and capital
turnover. . . . . . . . . . . . . . . . . . . .

Results of the study indicate that it is pos—
sible to classify successfully corporations into
either bankrupt or non—bankrupt groups. . . prior
to bankruptcy with the effectiveness of the model
substantially deminishing after the second year.

The bankruptcy predictive model was shown to
be easily applicable for practical decision—mak—
ing purposes with two of its attributes being
simplicity and low cost. Important utilities of
the model were suggested pertaining to business
credit evaluation, internal and external manage—
ment considerations and investment guidelines.14

The utilities of business credit evaluation, in-
ternal management considerations and investment guidelines

are also applicable to the financial efficiency model in

 

l3Edward Ira Altman, “Financial Ratios, Discrimin—
ant Analysis and the Prediction of Corporate Bankruptcy,"
Journal of Finance, Vol. XXIII, No. 4 (Sept. 1968) p. 589—609.

 

14Ib1d.

 

20

this study. The technique and the objectives are dif-
ferent in this study as multiple discriminant analysis
and profitability ratios were not used. Success of the
firm as measured by a relative ranking of a ten year
mean value of shareholder wealth appreciation was the
dependent variable used in the model develOped in Chap-
ter IV.

Beaver found that the ratio of cash-flow to total—

debt was the best predictor of failure.15 This ratio had

 

a 13% error rate using data for the year prior to failure
and a 22% error rate using data five years before failure.l6
Altman did not consider this ratio because of a lack of
consistent appearance of precise depreciation data.17
Cash—flow involves net income which is a profitability
measure that was not used in this research.

Altman pointed out that it is essential to analyze
the entire variable profile simultaneously rather than se—
quentially examining its individual characteristics. His

X5, Sales/Total Assets or Capital turnover ratio was the

least significant ratio on a univariate or individual basis.

 

15W.H. Beaver, "Financial Ratios as Predictors of
Failure,“ Empirical Research in Accounting: Selected Studigg
1966, Institute of Professional Accounting, University of
Chicago, January, 1967, p. 71—111.

 

16Ibid.

l7Altman, op. cit., p. 594.

 

21

However, because of its unique relationship to other var-
iables in the model, the capital—turnover ratio ranked
second in its contribution to the overall discriminating
ability of his model.18 Being able to justify the indi—
vidual ratio's contribution is subject to the assumption
of independence between the variables. Since Altman seems
to indicate that there is a unique relationship of this
ratio to other ratios, one would suSpect that this assump—
tion is violated. It appears that Altman clearly enhances
the credibility of using financial ratios in predictive
models, successfully uses a turnover ratio, and adds addi-
tional support for simultaneously combining ratios.

James S. Stone's thesis investigates the effect of
conglomerate mergers on the performance of the economy in
terms of capital allocation and suggests that the exist—
ence of the conglomerate merger movement is inconsistent
with the belief in profit maximization as the primary moti—
vation of firm managers.lg His thesis is relevant to this
study as he uses an efficiency measure which is a rate of
return on assets or net earnings after taxes per dollar of
asset value. Yet, no justification for using this effi—

ciency measure is given in his thesis. Stone indicates in

 

18Ibid., p. 596.

19James S. Stone, "Conglomerate Mergers: Their Impli—
cations for the Efficiency of Capital and the Theory of the
Firm," (unpublished Master's Thesis, Harvard University,
March, 1969).

          

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22

his conclusions that the questions which prompted his the-
sis are without definitive answers.20 Perhaps his criteria
for efficiency is not a relevant one to use for his study.
The Annual Statement Studies of 1969 says the fol—
lowing: “The Robert Morris Associates is the national as—
sociation of bank loan and credit officers. It is actively
engaged in promoting improvement in principles and practices
of commercial lending, loan administration, and asset manage—
ment in commercial banks,”21 Their treatment of ratios is
to develop medians and quartiles by industry groupings.
“For any given ratio, in any size class, these figures were
calculated by, first, arranging all the numerical values
of that ratio in the order of the strongest to the weakest
ratio. The figure which falls in the middle of the list
of ratio values is the median. The figure halfway between
the median and the best of the ratio values is the upper
quartile. The ratio halfway between the median and the

22 The emphasis in this

weakest is the third quartile.“
study is clearly on credit worthiness and each individual
ratio is treated separately. Obviously, a subjective over—

all evaluation of the firm is made by whichever institution

 

201bid., p. 48, 88.

21The Robert Morris Associates Annual Statement
Studies, The Robert Morris Associates, Philadelphia National
Bank Building, 1969.

22

 

Ibid., p. iii.

 

23

is doing the evaluation. This naturally can vary by who—
ever is making the overall subjective judgment as to the
credit worthiness of the firm.

The purpose of this chapter was to look at earlier
works and to show how they were related to the model devel—
oped in this thesis. Selection of a single industry for
review, use of data from annual financial statements, the
credibility of ratios, the use of a minimum number of in—
dependent variables, the combination of ratios into an

index and background information on the use of certain ra-

 

tios were some of the relevant items that earlier research
substantiated. The work of Wall and Altman was extremely

beneficial in the development of the financial efficiency

model presented in this thesis.

The main purpose of the model is to develop a
technique for assisting management in the establishment
of long—term financial guidelines. Inputs for the model
were mean values of financial ratios which were chosen to
best represent the efficient financial decision making
within the firm. In searching the literature no study
was found that simultaneously combined financial ratios——
designed to measure financial decision making—-to corre-

late with performance in shareholder wealth appreciation.

 

CHAPTER III

THE CCNCEPTUAL FRAMEWORK

A. Overview

In this chapter the conceptual framework will be
discussed since it is the foundation which was used to
build the model as explained in the next chapter. The
major objective of a firm, the three major financial deci~
sions, and the selection of the dependent and independent

variables are the topical areas of this framework.

B. Financial objective of a firm

 

In this study it was assumed that the objective
of a firm is to maximize its value to its shareholders——
the appreciation of the market value of stock and cash
dividends. It would seem that the firm utilizing its
assets most efficiently (making the most efficient deci-
sions) would also be the one to achieve the greatest in—
crease in shareholder wealth. It is possible for a firm
that is efficiently using its resources to fail. In a
given industry——for instance, in a dying industry such as
the railroad industry——it would appear that the most effi-
cient firm would be the last one to fail, ceteris paribus.

However, a firm in any industry should be able to generate

24

 

25

profitable investment opportunities by finding the best
uses for scarce resources. Consequently, it should con—
tinue as a successful “going concern” and concomitantly
be recognized as such in the market place.

According to Van Horne: "Because the principle
of maximization of shareholder wealth provides the most
rational guide for running a business and for the effi—
cient allocation of resources in society, we shall use
it as our assumed objective in considering how financial
decisions should be made.“1

The model in this study provides a systematic ap—
proach to aid in providing a base for establishing guide—
lines for asset management and financial planning. All
resources are not included in the model, and as such sub—
optimal results will undoubtedly occur. On a relative
basis within a given industry it will, perhaps, provide
assistance or a technique to assist in increasing the pre-
sent level of efficient operation.

Because there are day to day fluctuations in mar—
ket price, this study is concerned with the long—term View,
and except in rare cases management should be concerned
with this view in the stewardship of an organization.
Short—term decision making with no consideration for the
impact on the long—term goals of the firm will certainly

not enhance the success of a firm.

 

1Van Horne, Op. cit., p. 8—9.

 

 

 

26

How long is the long—term view? There are many
factors that must be considered in answering this question.
The financial efficiency model which is developed in Chap—
ter IV will be flexible enough for any time period to be
chosen to fit the particular circumstances. Crucial to the
selection of this time period is the removal of day-to-day
fluctuations in share price so that an average market
price can be obtained. Generally, a three to five year
period would seem to be a reasonable range to use in the

model.

C. Selection of dependent variables

This financial efficiency model was designed to
incorporate two dependent variables. The first dependent
variable was an index of shareholder wealth appreciation.
As explained in Chapter I, shareholder wealth consists of
cash dividends and market price appreciation. Latane’and
Tuttle use these two components in computing holding peri—
od returns.2 An index was used as this method takes ab—
solute values and makes them comparable among firms. For
this study the base year for the index calculation was
1959. The index of shareholder wealth was the preferred
dependent variable as it considered the total return to

the shareholder. Each year the cash dividends were

 

2Henry A. Latane’ and Donald L. Tuttle, Security
Analysis and Portfolio Management, New York: The Ronald
Press Company, 1970.

 

 

 

27

assumed to be reinvested in the same dividend paying stock
in order to allow comparison between both dividend and non-
dividend paying firms. One of the original assumptions
stated in the introduction was that there would be no
transaction costs.

The second dependent variable was an index of mar-
ket price appreciation. Ranking stocks using mean values
of both dependent variables gave almost identical rankings
in the drug industry. Therefore, the index of shareholder
wealth appreciation was the only dependent variable used

in the model development as explained in Chapter IV.

D. The three major decisions

 

The broad classification of decision making into
the investment, the financing and the dividend decisions
includes almost every financial management decision within
a firm. Together they help determine the efficient Opera—
tion of a firm.

The investment decision's impact is felt on the
entire left—hand side of the balance sheet. Working capi-
tal management, for example, includes determining cash,
inventory and receivables level. Managing these existing
assets efficiently is essential to the success of the firm.
In addition to working capital management, allocating capi—
tal to long—term investment proposals is a major part of

the investment decision. These long—term investments,

 

 

 

28

merger considerations, failures and reorganizations, re~
search and development expenditures are referred to as
long-term capital budgeting decisions. Included also
under these decisions are the reallocation of capital
when an asset no longer justifies economically the capi—
tal committed to it—-an abandonment decision. Again, the
resultant impact is observed on the left hand—side of the
balance sheet usually as fixed assets. Therefore, the in-
vestment decision determines the total asset mix of a firm.

Figure 2 shows the breakdown of the investment
decision within a firm.

Cash and Marketable Securities
Management of

Accounts Receivables
Working Capital

Inventories
I
Mergers
Capital Failures and Reorganizations
Budgeting Research and Development

Plant and Equipment

Where I = Investment decision

Figure 2

Investment Decision

 

 

29

The investments of a firm should be financed to‘
maintain an optimal capital structure for a firm. Though
this issue has not been solved with empirical results,
firms tend to behave as if there is an optimal capital
structure. In addition, when raising capital in the fi—
nancial markets, they seem to act as though they believed
that changing their financial mix (capital structure) may
change their common stock price. The model will hopefully
assist in providing guidelines or some insights for this
Optimal structure. Also, consideration should be given to
the firm's desired asset mix; hence the financing decision
cannot be made in isolation. The concern of this study is
the long-term funds portion of a firm's debt and equity
and not the short and intermediate term funds. Again, the
attempt is to assist in the development of long—range fi—
nancial guidelines and, by definition, not consider the
intermediate and short—term market since it will generally
fluctuate within any given years time. The impact of the
financing decision makes its appearance under long-term
debt and equity sections on the right hand side of the
balance sheet. Figure 3 shows the breakdown of the fi—

nancing decision.

30

Common and Preferred Stock
Long—Term Convertibles, Rights and Warrants

Debt

Term Loans
F.——————Intermediate Conditional Sales Contracts

Leases

Trade Credit
Short—Term Commercial Paper
Receivables and Inventories

Where F = Financing decision

Figure 3

Financing Decision

The dividend decision could have been included with
the financing decision but because its impact on the index
of shareholder wealth of a firm seemed so great it was
treated separately. The dividend payout ratio (dividend
policy) determines the allocation of earnings between pay—
ments to common shareholders and retained earnings. Re-
tained earnings are one Of the most significant sources of
funds in the drug industry for financing the firm's invest-
ments. Cash—flows to shareholders in the form Of cash divi—
dends constitute an increment in their wealth. In the lit-

erature of finance, this variable has sometimes been divided

 

31

into two parts-—either an active or a passive decision
variable. Figure 4 shows the breakdown of the dividend
decision. Hopefully, the model will assist in providing
guidelines for what the dividend payout ratio should be

for an efficiently operated firm.

Stability
Informational Content
Preference for Current Income

Tax, Ordinary vs. Capital Gains

 

Active
Clientele Theory
D Control — Restrictions
Bond Ratings
Liquidity
Anything left over after all in—
Passive or vestment opportunities have been
Residual satisfied is distributed to share—
holders
Where D : Dividend decision
Figure 4

Dividend Decision

 

32

E. Selection of independent variables

V The end result of almost every financial decision
makes an impact on a firm's annual financial statements.
Consequently, the model was designed to incorporate data
available from annual financial statements. This data
are available on compustat tape.

As indicated before, the investment decision was
divided into working capital management and capital bud-
geting. The initial variables selected for these compo-
nents were the current ratio, cash turnover, inventory
turnover, accounts receivable turnover and fixed asset
turnover.

When reviewing the literature it is apparent that
the current ratio was used early in this century and con—
tinues to be widely used today. The current ratio is cal-
culated by dividing total current assets by the total cur-
rent liabilities. It is one measure of the firm's ability

to meet its current debt.3
In tracing the history of the current ratio
Foulke says:
By 1908 one author had written, ‘. . . many
good judges feel that the ratio of quick (current)

assets to (current) liabilities should be about
2% to 1.‘ Gradually, 2 and not 2% dollars of

 

3See Appendix B for definitions Of Total Current
Assets and Total Current Liabilities.

 

33

current assets for each dollar of current lia-
bilities came to be expected as a reasonable mar—
gin of protection. . . . In case of bankruptcy,
falling prices, or inflated figures, the book
value of the current assets could shrink 50 per
cent in liquidation and current creditors, pro-
vided there were no long-term creditors, would
still receive payment of their obligations in
full. For many years this 'two for one' current
ratio was the alpha and omega of balance sheet
analysis; even today the businessmen are legion
who believe this single ratio to be one infalli—
ble guide to balance sheet interpretation.

Thus, a current ratio that might be suitable for

A.T.& T. might not be suitable for a relatively new golf

 

driving range. Moreover, depending on the product line,
different current ratio guidelines will be different for
different industries. Because this ratio is predominantly
used in the market place and the data are readily avail—
able, it was used as a component of the financial effi—
ciency model.

A cash turnover ratio should tell how efficiently
a firm uses its cash to generate sales--at least relative
to other firms in the industry. The cash turnover ratio
was a highly significant independent variable used in the
model. It is calculated by dividing net sales by cash.5

Foulke refers to inventories as the “graveyard of

American business“ because they have so frequently been

 

4Foulke, op. cit., p. 178.

5See Appendix B for definitions of net sales and
cash.

 

34

the prime cause of business falures.6 Inventories require
large investments of money and represent a significant per-
centage of a firm's total assets in the drug industry. For
example, it represents about 30% of Baxter Laboratories
total assets as of December 31, 1969. Quantitative tools
are available to provide efficient levels of inventory.
Because inventory levels are generally related to net sales,
inventory turnover was selected as the independent variable
to be used for this guideline. The inventory turnover ra-
tio is calculated by dividing cost of goods sold by the
average inventory——an average Of beginning and ending in—
ventories for the period.7 Classification of inventories
by product line would certainly enhance the use of this ra—
tio, but existing data availability on annual financial
statements precludes this possibility.

Sales of inventories replenish the level of re—
ceivables. Again, receivables represent a sizable portion
Of a firm's total assets. Management Of receivables, i.e.
credit and collection policies, can be crucial to the suc—
cess of a firm. ". . . credit policy involves a tradeoff
between the profit on sales that give rise to receivables

on one hand and the cost of carrying these receivables

 

6Foulke, op. cit., p. 310.

7See Appendix B for definitions of cost of goods
sold and inventories.

 

35

plus bad-debt losses on the other."8 The receivable turn-
over ratio is calculated by dividing annual credit sales
by receivables. Annual credit sales are calculated by
dividing net sales by three hundred and sixty-five.9 WhiCh
is a usual procedure in the financial community. If the
credit terms granted to customers were known, the effi—
ciency of the level of receivables could be appraised.

The receivables turnover ratio is actually the re—
ciprocal of the collection period and should be helpful in
evaluating the collectibility of receivables. Dunn & Brad—

street say the collection period should not exceed the net

maturity of selling terms by more than ten to fifteen days.10

When trying to compare collection periods between firms the
variations in selling terms should be stated, but selling
terms were not available on the compustat tape.

Turnover ratios allow the comparison Of companies
within an industry and then allow judgments to be made as
to the efficiency of utilizing assets to produce sales.
Wide recognition has been given in American industry to

the du Pont system of financial control, and total asset

 

8Van Horne, op. cit., p. 362.

9See Appendix B for definitions of net sales and
receivables.

loKey Business Ratios in 125 Lines 1968; Retailing,
Wholesaling, Mfg., Construction, Dunn & Bradstreet, Inc:
New York.

 

36
turnover is one of its key variables.11 This study uses
the fixed asset turnover ratio, which relates the effi-
ciency with which the firm utilizes its fixed assets to
generate sales. It is computed by dividing net sales by
fixed assets.12 A danger exists in using a fixed asset
turnover ratio; it could stimulate the use of Old equip—
ment. When equipment is almost fully depreciated and
highly inefficient, it may show a high turnover but actu—
ally be unprofitable. The profitability ratios ignore

the efficient utilization of assets--at least in the short

 

run. A firm sacrificing the profitable purchase of new
equipment for the sake of higher turnover ratios would ex—
perience a relative decline in profits and share price.
The current ratio, cash turnover, receivables turn—
over and inventory turnover were the independent variables
selected to assist in measuring the efficiency of working
capital management. These are the variables for which the
model will establish guidelines. The fixed asset turnover
ratio was the independent variable used to measure the ef—
ficiency of capital budgeting decisions. Since the drug
industry was selected for research, a valid question would

be the following: why not use research and development as

 

llT.C. Davis, "How the du Pont Organization Appraises
Its Performance,“ Financial Management Series, No. 94, New
York: American Management Association Treasurer's Dept" 1950.

12See Appendix B for definitions of net sales and
fixed assets.

 

37

a variable? One reason was that the data were only avail-
able for thirteen of the desired eighteen companies on the
compustat tape. Another reason was that the rankings be-
tween the percent R & D of net sales and the index of share-
holder wealth produced a Spearman Rho = —.39. The t cal—
culated value was — 1.405 and the tabled value of

tioC = .20; df = 11 = 1.363. Therefore, with a negative
correlation and significance at the confidence level of
CE, = .20 there was little reason to use this variable,
particularly when the data were only available for thir—
teen Of the desired companies.

A debt ratio was used to assist in the measure—
ment of the efficiency Of the financing decision. It is
calculated by dividing long—term debt by total assets.13
There are many debt ratios used in the market today, but
preference was given to long-term debt divided by total
assets. The purpose of the ratio is to appraise a firm's
ability to meet its obligations as well as to help achieve
greater efficiency Of operation for the firm. Since this
measure excludes the short-term accounts in the current
liability section, it was felt to be a better measure of

the long—term financial policy of a firm.

 

13See Appendix B for definitions.

 

 

38

Finally, the dividend payout ratio was used as the
measure or proxy for efficiency of the dividend decision.
It is calculated by dividing earnings available to common
shareholders into cash dividends paid to common sharehold—
ers.l4 One of the most important financial decisions made
annually by the firm is to determine the allocation of pro—
fits after taxes between dividends and retained earnings;
it may have a critical influence on the value of the firm.
To illustrate the importance of the dividend payout policy,
retained earnings financed 43 percent and new capital 57
percent of a group of firms' investments during a 12—year
period.15 The twelve year period was between 1955 and 1966
and the total uses of funds by these corporations was $705
billion.16

The efficient firm should be able to generate a
large number of attractive investment opportunities, there-
by needing a large amount of capital. This appears to be
the situation for the more successful firms in the drug in—

dustry, a fact which helps to explain their lower cash div-

idend payout ratios. Thus, for purposes of the model in

 

14See Appendix B for definitions.

l5J. Fred Weston and Eugene F. Brigham, Essentials
of Managerial Finance, New York: Holt, Rinehart and Winston,
1968, p. 359—360.

 

16Ibid., p. 359—361.

 

39

this study, the lower the dividend payout ratio the more
efficient the dividend decision. In this sense, the
dividend payout ratio is a proxy for the generation of

attractive investment opportunities.

 

CHAPTER IV

MODEL DEVELOPMENT

A. Overview

The financial efficiency model will be devel-
oped in this chapter and accompanied by an explanatory
example. Initially, the selection of industry, inde-
pendent and dependent variables, data source, and time
period will be discussed. The explanatory example will
consider the top five and the low five of the eighteen
companies chosen for the study. Finally, sensitivity
analysis will be used to develop range of values as an

assistance in establishing financial guidelines.

B. Selection of industry and companies

Compustat provides a reliable source of financial
information covering a wide range of companies and indus—
tries. After reviewing the companies listed by industry
in the Compustat Information Manual, the drug industry
was selected because it comprises a large number of com—
panies with a fairly homogeneous product line.

Under the classification of drug industry twenty—

nine companies were listed (see Appendix A). Five

40

 

41

companies were eliminated from the study because of in—
complete data for the independent variables. Several of
the listed firms were small and exhibited quite different
data from the larger firms, so firms having a mean value
of less than $100 million in sales and/or total assets
were also eliminated.1

It may be useful for officers of any given firm
to compare their firm‘s policies and financial data with
those of other carefully selected firms in the industry.
Detailed information such as future product line direction,
depreciation policies, accounting differences and differ-
ing collection periods with their associated selling terms
may be available about their competition. With this addi—
tional information available as input data to the model,
the output data used in establishing financial guidelines

should be more meaningful and useful.

cpaj

The data base compiled on the Compustat tape cov—
ers the most widely used balance sheet and profit and loss
information. It includes all the data necessary for the

independent and dependent variables used in the model.

 

1It is customary in ratio analysis to segregate
firms by size, i.e., Robert Morris Associates segregate by
total assets. Their lowest category is $250 M and less in
total assets, however, their time period is two years.

 

42

As explained in Chapter III, the independent variables

are as follows:

X1
X2
X3
X4
x5
X6

x7

Current ratio

Cash turnover
Inventory turnover
Receivables turnover
Fixed asset turnover
Debt ratio

Dividend payout ratio

and the dependent variables are:

Y1

Y2

Index of shareholder wealth appreciation

Index of market price appreciation

To verify the reliability of the data all of the

variables were calculated for several randomly selected

firms. The raw data were reviewed for reasonableness and

much of it was verified with specific annual reports.

Standard Statistics states:

Extreme care has been used to investigate
each item of the data for correctness and accur—
acy checking against many primary sources of
information. Highly developed computer tech—
niques are applied to further refine and verify
all of the items which are translated to machine
readable magnetic tapes.

A high degree of comparability has been
achieved through the use of Specifically defined
accounting terms which have been reviewed by

 

 

43

leading accounting firms. Necessarily, some cf
the information has been altered from that con—
tained in the annual reports of various compan—
ies, since all reporting methods are not similar.
For this purpose additional public and confiden-
tial sources of information are used so as to ‘
insure reliability. . . .2 1
Based on manual computations done for this research the

data were believed to be highly reliable.

D. Time period

The time period selected for this research was
1960—1969. The objective of the research was to develop
long—term financial guidelines for the financial variables,
and ”long—term“ was defined as five years or more. Work—
ing with mean values of market price seems to dictate at
least a three to five year time interval so that year-to—
year fluctuations can be ironed out. The time period se-
lected was long enough to satisfy this condition, was long
enough to contain two recessionary periods and was the
most recent interval of time possible for the study. Nev—
ertheless, the model could be used with different inter—

vals of time.

E. Dependent variables—-ranking

A mean value for the selected firms was calculated

for both dependent variables-—index of market price

 

2Compustat Information Manual, April 1970, p. 1-1.

 

44

appreciation and index of shareholder wealth appreciation--
over the time period 1960 thru 1969. Next, each firm was
comparatively ranked against other firms on both dependent
variables. For the twenty-four companies chosen, Table I
shows a marked correlation between two dependent variables.
Running a Spearman Rho Rank Correlation Test on these pair-
ed observations yielded a coefficient of rho = .9939,
which is highly significant. A calculated t test value
was 42.4 whereas the tabled value of t CC = .01; df = 22
= 2.819. With this high correlation the index of share—
holder wealth appreciation was used as the sole dependent
variable.

Table 2 also shows a marked correlation between
the two dependent variables for the eighteen companies.
A Spearman Rho equal to .9918 is also highly significant.
A calculated t test value was 30.5 whereas the tabled

value of toC = .01, (if = 16 = 2.921.

F. Independent variables——normalizing

 

A mean value was calculated for each independent
variable for all firms for the ten year time period and
each variable was normalized. The firm with the lowest
mean value of cash turnover was equated to one. The firm
with the highest mean value was equated to one hundred.

Then, the remaining firm‘s mean values were interpolated

 

45

to their relative position between one and one hundred.
Similarly, normalized values were calculated for the re-
maining mean values of the independent variables—-with
the exception of the dividend payout. The lowest mean
value of the dividend payout ratio was equated to one
hundred and the highest equated to one.

The logic for equating the highest mean value for
the independent variables (and the lowest for dividend
payout) was assumed to be the most efficient level ob-

tained for that given listing of companies. Certainly

 

it is possible that these ratios could be too high (too
low for dividend payout) and in reality be inefficient.
For example, an inventory turnover ratio may be so high
that it causes a loss in sales due to frequent stock
shortages. Detailed knowledge of the factors involved

in each of the chosen independent variables would be nec—
essary to be precise in setting the most efficient levels.
The top performing companies exhibited the lowest divi-
dend payout ratios; the highest debt ratios; and the high—
est cash, inventory and fixed asset turnover ratios. Con-
sequently, it followed then that the higher the level of
the independent variables (lowest in dividend payout), the

more efficient the financial decision making in the firm.

  

46

TABLE 1

Rankings on Dependent Variables
Mean Values;

1960 - 1969

 

Index of Shareholder

Index of Market Price

 

Wealth Appreciation
*l. Syntex *l. Syntex
*2. Baxter *2. Baxter
3. Bristol Myers 3. Bristol Myers
4. American Hospital 4. American HOSpital
*5. Plough 5. Johnson/Johnson
6. Johnson/Johnson *6. Plough
*7. Searle *7. Searle
8. Gillette 8. Gillette
9. Kendall 9. Merck
10. Sterling 10. Sterling
11. Merck 11. Kendall
12. Warner Lambert 12. Warner Lambert
13. Eli Lilly 13. Eli Lilly
l4. Abbott Laboratories 14. Miles
15. Miles 15. Abbott Laboratories
16. American Home Prod. 16. American Home Prod.
17. Pfizer l7. Pfizer
18. Richardson-Merrell 18. Richardson—Merrell
l9. Schering *19. Cutter
*20. Cutter 20. Schering
21. Smith Kline 21. Smith Kline
22. Upjohn 22. Upjohn
*23. Carter Wallace *23. Carter Wallace
24. Parke Davis 24. Parke Davis

Companies with less than $100 Million Total

Assets and/or Total Sales.

 

47

TABLE 2

Rankings on Dependent Variables
Mean Values;'l960 — 1969
Explanatory Example

Index of Shareholder

Wealth

Index of Market Price
Appreciation

 

\OCOQONUIAWNH

than $100 million for 1960—1969.

Bristol Myers
American Hospital
Johnson/Johnson
Gillette

Kendall

Sterling

Merck

Warner Lambert

Eli Lilly

Abbott Laboratories
Miles

American Home Prod.
Pfizer
Richardson—Merrell
Schering

Smith Kline

Upjohn

Parke Davis

Lomxlmmpwmw

18.

Bristol Myers
American HOSpital
Johnson/Johnson
Gillette

Merck

Sterling

Kendall

Warner Lambert

Eli Lilly

Abbott Laboratories
Miles

American Home Prod.
Pfizer
Richardson-Merrell
Schering

Smith Kline

Upjohn

Parke Davis

This table excludes companies from Table l with
mean values of total assets and/or total sales of less

 

48

G. Independent variables—-rankings

Weights were developed for each independent vari-
able which summed to one. Combinations could have been
derived through an iterative or step-by—step procedure.
For this study various combinations of weighting factors
were read directly into the computer.

For each independent variable the weighting fac-
tors were multiplied by each normalized value. It re—
sulted in component scores for each company which were
then summed to obtain a composite value. An example of

this is illustrated in Figure 5.

 

Independent Weighting Normalized Component

variable factor value score
WF X NV = CS
Cash turnover .25 x 21.80 = 5.45
Inventory turnover .15 x 67.20 = 10.05
Fixed asset turnover .20 x 6.92 = 13.84
Debt ratio .30 x 38.80 = 11.64
Dividend payout .10 x 55.60 = _§;§§
Composite Value (CV) = 46.54
Figure 5

Index of Financial Efficiency
Bristol—Myers

 

49

The composite value is called the index of finan-
cial efficiency. The weighting factors which gave the
best fit to the data explain the relative importance of
each independent variable. They are significant in that
they allow management to determine in which areas to con-
centrate their efforts.

The next step was to rank all the firms from high-
est to lowest in composite value. This ranking was then
correlated by running a Spearman Rho Rank Correlation Test
with the dependent variable. This ranking was continued
with all combinations of weighting factors read into the
computer. Each final ranking was then correlated with the
ranking of the index of shareholder wealth—-the dependent
variable.

As an explanatory example, the top five and the
low five companies of those listed in Table 2 were chosen.
As indicated before, six companies were eliminated from
the list of twenty—four in Table 1 because the mean value
of total assets and/or total sales was less than $100 mil—
lion for 1960 thru 1969.

For comparative purposes normalized values were
computed for the top quartile (5) and low quartile (5) of
the eighteen companies previously listed. Table 3 lists
the mean values for cash turnover and shows the calcula—
tion of their reSpective normalized values of cash turn-

over ratios.

 

 

 

50

Similarly, the mean values were normalized for the
remaining independent variables. The results shown in
Table 4 were provided by ranking the mean value of each
independent variable and running a Spearman Rho Rank Cor-
relation Test on the shareholder wealth dependent variable.
For the five top and low quartile companies the cash turn-
over and debt ratio correlations were significant at a
confidence level OC = .01. The inventory turnover and
fixed asset turnover correlations to the dependent vari—
able were significant at CC = .05. Simultaneously, all
independent variables were combined and their resultant
rankings correlated using the Spearman Rho on the depen—

dent variable.

 

51

TABLE 3

Normalizing Procedure for Cash Turnover Ratio
Top and Low Quartile Companies
Mean Values; 1960-1969

Mean Value Rearranging Normalized
Cash Turnover High to Low Value (NV)

 

l. Bristol—Myers 13.32 -—-50.36 100.0 -—
2. American Hosp. 50.36 32.40 —~ —— 62.1 0*
3. Johnson/Johnson 10.08 13.32 21.8
4. Gillette 7.25 10.08 15.0
5. Kendall 32.40 8.08 10.8
Z Y
6 Richardson—Mer. 8.08 7.25 W X 9.2
7. Schering 3.82 6.68 7.7
8. Smith Kline 4.22 4.22 2.7
9. Upjohn 6.68 3.82 L—- 1.7
10. Parke Davis 2.96 —— 2.96-— 1.0 —_

 

 

 

 

32.4 — 2.96

0* = m X 99.0 + 1.0 = 62.].

Z _ y _ WY
_W_ _ -Y— where x _ _37—

Q* = X + 1.0

 

52

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53

Experimenting with five independent variables and
various combinations of weighting factors, the following
in Figure 6 gave the best fit (eliminated, for illustra-
tive purposes, the current ratio and receivables turnover
ratio). As might be expected, the weighted factors were
related to the Spearman Rho coefficients. Continuing the
computation, multiplying the normalized value times its
associated weighting factors yields all the component
scores as shown in Table 5. Finally, the component scores

for each independent variable were summed to obtain the

 

composite values. These values are compiled in Table 6.

 

Rho Significant
at
Cash turnover WF = .25 .851 CK = .01
Inventory turnover WF = .15 .750 CC = .05
Fixed Asset turnover WF = .20 .758 Cf = .05
Debt ratio WF = .30 .833 0C: .01
Dividend payout WF =_;19 1229 CC:= .10
1.00

Where WF = Weighting factor

Figure 6

Weighting Factors and Spearman Rho Rank
Correlation Test Results

 

54

TABLE 5

Mean Values, Normalized Values
and Component Scores

 

 

 

1960—1969

*Component

Mean Cash Normalized Score (C5;

Turnover Values (NV) (WF;7=.25
Bristol-Myers 13.32 21.8 5.45
American Hospital 50.36 100.0 25.00
Johnson/Johnson 10.08 15.0 3.75
Gillette 7.25 9.2 2.30
Kendall 32.40 62.1 15.53
Richardson—Merrell 8.08 10.8 2.70
Schering 3.82 1.7 .43
Smith Kline 4.22 2.7 .68
Upjohn 6.68 7.7 1.93
Parke Davis 2.96 1.0 .25

Mean *Component

Inventory Normalized Score (CS)

Turnover Values(NV) (WF2 =.15)
Bristol—Myers 2.90 67.20 10.05
American Hospital 3.65 100.00 15.00
Johnson/Johnson 3.56 96.07 14.41
Gillette 2.00 27.90 4.19
Kendall 3.44 90.83 13.61
Richardson—Merrell 2.74 60.30 9.04
Schering 1.36 1.00 .15
Smith Kline 2.58 53.30 8.01
Upjohn 1.41 2.20 .33
Parke Davis 1.61 10.80 1.50

* Component Score (C8) = Normalized Value (NV) x
Weighting Factor (WF)

 

55

TABLE 5——Continued

 

 

 

 

Fixed *Component

Asset Normalized Score (CS)

Turnover Value (WF3 =.20)
Bristol—Myers 6.84 69.2 13.84
American HOSpital 8.92 100.0 20.00
Johnson/Johnson 4.42 33.3 6.66
Gillette 4.98 41.6 8.32
Kendall 3.71 22.8 4.56
Richardson—Merrell 6.48 63.8 12.76
Schering 3.79 23.9 4.78
Smith Kline 4.47 34.1 6.82
Upjohn 2.17 1.0 .20
Parke Davis 2.45 4.1 .82

*Component

Debt Normalized Score (CS)

Ratio Value (WF4 =.30)
Bristol—Myers .07 38.8 11.64
American HOSpital .07 38.8 11.64
Johnson/Johnson .02 11.1 3.33
Gillette .04 22.2 6.66
Kendall .18 100.0 30.00
Richardson—Merrell .01 5.6 1.68
Schering .00 1.0 .30
Smith Kline .00 1.0 .30
Upjohn .00 1.0 .30
Parke Davis .00 1.0 .30

*Component Score (CS) = Normalized Value (NV) x
Weighting Factor (WF)

 

56

TABLE 5-—Continued

 

 

*Component

Dividend Normalized Score (CS)

Payout Value (WF5 =.10)
Bristol—Myers .50 55.6 5.56
American Hospital .34 91.1 9.11
Johnson/Johnson .30 100.0 10.00
Gillette .72 6.6 .66
Kendall .40 77.8 7.78
Richardson—Merrell .31 97.8 9.78
Schering .51 53.4 5.34
Smith Kline .67 17.7 1.77
Upjohn .54 46.7 4.67
Parke Davis .75 1.0 .10

* Component Score

(CS) = Normalized Value (NV) x
Weighting Factor (WF)

 

 

57

 

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58

The composite value or index of financial effi-
ciency for American Hospital Supply is 80.75, foriBristol-
Myers is 46.54, and for Kendall is 71.48. Thus, the rank—
ing from high to low on the index of financial efficiency
was not perfectly correlated to the ranking of the index
of shareholder wealth appreciation. The rankings of the
two indexes are listed in Table 7. The correlation be—
tween the two rankings was highly significant with a rho
= .867; t computed = 4.90 and a tabled value t CC = .01;

df = 8 = 3.355.

H. Financial policy guidelines

 

Individual variables can be analyzed for possible
strategies by which assistance in establishing financial
guidelines can be obtained. For example, assume that we
want to look at the relative ranking of Johnson/Johnson
with that of Bristol—Myers. Through sensitivity analysis
we could vary any of several ratios simultaneously and
observe the relative change in rankings. The index of
financial efficiency or composite value for Johnson/John-
son is 38.15, whereas for Bristol—Myers it is 46.54.
Therefore, the total number of index points that Johnson/
Johnson would have had to gain to overtake Bristol-Myers
is 8.39.

Johnson/Johnson has fewer financial efficiency

index points than Kendall but Johnson/Johnson is ranked

 

 

 

 

 

 

59

higher on the dependent variable. Any number of factors
could account for this: better advertising programs;
greater future earnings expectations; an imperfect market
with an overvalued issue; omission of crucial variables;
etc. Whatever the reason, a rho value of .867 is highly
significant at CC: .01.

Finally, how could Johnson/Johnson have achieved
a higher ranking (over the past decade) on the dependent
variable than Bristol—Myers? By subtracting Johnson/
Johnson's index of efficiency from Bristol—Myers' index of
efficiency a difference of 8.39 index points is obtained.
This is the amount they needed to overtake Bristol—Myers,
ceteris paribus. For example, assume that the management
of Johnson/Johnson feels that they can improve the cash
turnover ratio substantially. The 8.39 index points add—
ed to the existing component score for cash turnover of
3.75 yields 12.14 index points. After computing a normal—
ized value of 48.56, a new cash turnover value of 25.98
can be obtained by interpolation. Consequently, Johnson/
Johnson would have had to increase their cash turnover to

25.98 or more to overtake Bristol—Myers, see Figure 7.

 

 

60

TABLE 7

Rankings of Top and Low Quartile Companies

 

Index of Shareholder

Wealth

Index of Financial
Efficiency

 

(AN

LO(D\IO\UI¢

lO.

Bristol-Myers
American HOSpital
Johnson/Johnson
Gillette

Kendall
Richardson—Merrell
Schering

Smith Kline/French
Upjohn

Parke Davis

U'l

(DQO‘

10.

American HOSpital
Kendall
Bristol-Myers
Johnson/Johnson
Richardson—Merrell
Gillette

Smith Kline/French
Schering

Upjohn

Parke Davis

 

 

61

 

Index of,,

Efficigpcy
Bristol-Myers 46.54
Johnson/Johnson 38.15

8.39 Additional points needed
3.75 Existing points

12.14 Total new component score

 

 

(cs)
Mean Cash TUrnover NV x WF = CS

50.36 100.00

51.44{:
48.56 x .25 = 12.14
47.40

10.08 15.00 x .25 = 3.75

2 96 1.00

NVXWF1=CS

NV x .25 = 12.14

NV 48.56 New normalized value needed

2 _ 51.44
47.40 100

50.36 — 24.38 = 25.98

 

Z = 24.38

Figure 7

Financial Guideline Computation
For Cash Turnover Ratio

 

 

62

Obviously, firms must forecast what will happen

in the future. If Bristol-Myers improves their cash turn—

over ratio, Johnson/Johnson will have to capture this
amount in addition to that calculated in the preceding
example.

Suppose the management of Johnson/Johnson feels
that they can improve the inventory turnover ratio sub—
stantially. Again, by looking at Bristol-Myers, they
would need a total of 8.39 additional index points add—
ed to their existing 14.41 component score, giving a

new component score of 22.80, see Figure 8.

 

Index of

Efficiency
Bristol—Myers 46.54
Johnson/Johnson 38.15

 

8.39 Additional points needed

14.41 Existing component score

22.80 New component score

Figure 8

Financial Guideline Computation for
Inventory Turnover Ratio

 

63
If Johnson/Johnson increases their inventory turn-
over to 3.65 or above, they will only obtain the maximum
component score of 15.00. Thus, they will have to pick up
an additional 7.80 points elsewhere (22.80 — 15.00). For
example, assume they try to pick up these 7.80 additional
points by increasing their fixed asset turnover ratio.

They could do that in a manner shown in Figure 9.

 

NV X WF = CS
8.92 100.0
w 27.70
6.75 72.30 X .20 = 14.46
4.42 33.30 x .20 = 6.66
2.17 1.00

6.66 Existing points

7.80 Additional points
14.46 New component score

 

NV X .20 = 14.46
NV = 72.30

w _ 100.00-72.30
6.75 ‘ 100.00

New Fixed Asset Turnover = 8.92—1.81 = 7.11

w = 1.81

Figure 9

Financial Guideline Computation for
Fixed Asset Turnover Ratio

 

64

Consequently, Johnson/Johnson would have to in—
crease their inventory turnover ratio at least to 3.65
and their fixed asset turnover ratio to 7.11. Again, the
future must be forecast; these guidelines should form
the base on which to make intelligent forecasts. Knowing
the management of competitors and their patterns of deci-
sion making in the past is a good basis for looking into
the future. Johnson/Johnson, for example, may decide to
maximize all of the component scores and achieve an even

greater increase in financial efficiency. Naturally,

 

they have restraints as their competitors do, and by apply-
ing sensitivity analysis they can more confidently plan
their future rather than merely let it happen. Further
research is warranted when conflict arises between the
guidelines determined by the model and detailed internal
analysis of the same independent variable.

Another way of developing additional information
for establishing financial guidelines is to compute mean
and range of values for each independent variable for the
top and low quartile companies used in the preceding ex—

ample. See Table 8 for this compilation.

 

65

TABLE 8
Financial Guidelines
18 Companies;
1960—1969

Top Quartile

 

 

 

.Range
Mean High Value Low Value
Cash turnover 22.70 50.36 7.25
Inventory turnover 3.11 3.65 2.00
Fixed Asset turn. 5.77 8.92 3.71
Debt ratio .08 .18 .02
Dividend Payout .45 .30 .72

Low Quartile

 

 

Range
Mean High Value Low Value
Cash turnover 5.20 8.08 2.96
Inventory turnover 1.94 2.74 1.36
Fixed Asset turn. 3.87 6.48 2.17
Debt ratio .002 .01 .00
Dividend Payout .56 .31 .75

 

 

CHAPTER V

RESULTS

A. Least Square deletion program

 

Initially, it was decided to use parametric sta—
tistics to determine the relationships between the several
independent variables and a dependent variable. Using the
data from all twenty-four companies, as listed in Appendix
A, the stepwise deletion of independent variables from a
least square equation was run on the computer with 0C =.05
confidence level. The Michigan State University Agricul—
tural Experimental Station, Stat Series Description No. 8
LSDEL program was used on the CDC 3600 computer. As ex—
plained in previous chapters the time period was 1960 thru
1969, and in this particular run all five independent var—
iables were dropped out in the final iteration. The five
independent variables used in this run were inventory
turnover, dividend payout ratio, debt ratio, receivables
turnover and fixed asset turnover ratios. The dependent
variable was the index of shareholder wealth appreciation.
It was believed that the six small companies——with total
sales and/or total assets less than $100 million—~produced

the “noise" causing the elimination of all the independent

66

 

 

67

variables. As would be expected, a similar run on the in—_
dex of market price appreciation produced the same results.
Changing only the time period--using 1960 thru 1964——and
running the same program again on the two independent var—
iables also eliminated all five independent variables in
the final iteration.

It was decided to use eighteen companies as listed
in Appendix A and seven independent variables (dividend
payout ratio, debt ratio, current ratio, inventory turn—

over) for 1960 thru 1969. Running these seven independent

 

variables on the index of shareholder wealth appreciation
as the inputs to the LSDEL program at CC = .05 confidence
level eliminated all of the independent variables except
the fixed asset turnover ratio. The R2 = .5441 was for
all seven independent variables, which means they were
associated with approximately fifty—four percent of the
variation in the dependent variable. The F statistic was
1.7047, which is only significant at C( = .214. In the
last iteration the R2 was equal to .4284 and a F statistic
was equal to 11.911, which is significant at cC_= .003.
Making a run on the other dependent variable—-the index

of market price appreciation——with everything else the
same produced similar results. Also, changing the time
period to 1960 thru 1964 and making runs on both dependent
variables caused the identical elimination of independent

variables.

 

68

Since the sample size was small (n = 18), it was
believed that the data violated the normality assumption
of parametric statistics. Consequently, nonparametric
statistics was chosen as the technique to use in the de-

velopment of the model.

B. Iterative solution runs

A computer program (see Appendix C) was designed“
to incorporate the nine step procedure as listed in Chap—
ter I and described in Chapter IV. Data for seven inde—
pendent variables and the index of shareholder wealth
appreciation were used for the eighteen companies for 1960
thru 1969. Twelve sets of weighting factors were used for
individual runs of seven, six, five and four independent
variables. Table 9, which follows, shows the weighting
factors used in this study.

The mean value for each independent variable was
ranked from high to low. Each independent variable rank-
ing was correlated separately, on a univariate basis, to
the ranking of the dependent variable by using a Spearman
Rho Rank Correlation Test. The higher the rho the more
weight its associated independent variable was given.

For example, the rho equal to —.051 for receivables turn—
over was assigned values from .00 to .30 with predomi—
nantly more values nearer to .00 in the various sets of

weighting factors. Table 10 shows the rho's for each

 

   

69

 

 

 

TABLE 9
Weighting Factors - 18 Companies
1960 — 1969
Inven— Receiv— Fixed Divi—
Current tory ables Assets dend Debt Cash
Ratio Turn. Turn. Turn. Payout Ratio Turn.
.00 .25 .00 .25 .00 .25 .25
.00 .25 .00 .20 .30 .10 .15
.00 .20 .00 .20 .00 .30 .30
.00 .15 .00 .15 .00 .35 .35
.00 .15 .00 .15 .00 .30 .40
.00 .15 .00 .15 .00 .40 .30
.00 .20 .00 .30 .00 .30 .20
.00 .10 .00 .20 .00 .50 .20
.00 .20 .00 .30 .00 .20 .30
.00 .15 .00 .20 .00 .45 .20
.00 .30 .00 .25 .00 .20 .25
.00 .20 .00 .30 .00 .25 .25
.00 .20 .00 .25 .00 .30 .25
.00 .20 .05 .15 .10 .25 .25
.00 .15 .05 .20 .10 .25 .25
.00 .15 .10 .20 .10 .20 .25
.OO .15 .10 .10 .10 .25 .30
.00 .15 .10 .20 .15 .20 .20
.00 .20 .05 .30 .05 .10 .30
.00 .15 .30 .20 .25 .05 .05
.00 .15 .25 .20 .20 .10 .10
.00 .20 .15 .20 .15 .15 .15
.00 .20 .05 .20 .20 .15 .20
.00 .10 .05 .25 .10 .25 .25
.00 .15 .05 .10 .05 .30 .35
.15 .15 .10 .15 .15 .15 .15
.10 .15 .15 .15 .15 .15 .15
.05 .20 .05 .20 .10 .20 .20
.05 .20 .05 .20 .05 .25 .20
.05 .20 .05 .20 .05 .20 .25
.05 .15 .05 .20 .05 .25 .25
.05 .20 .05 .25 .10 .15 .20
.05 .10 .05 .10 .10 .30 .30
.05 .15 .05 .25 .05 .20 .25
.20 .10 .20 .10 .20 .10 .10
.10 .15 .05 .15 .10 .15 .30

.05 .20 .10 .20 .15 .15 .15

 

 

70

TABLE 9——Continued

 

 

 

Inven-_ Receiv— Fixed Divi—

Current tory ables Assets dend Debt Cash
Ratio Turn. Turn. Turn. Payout Ratio Turn.
.00 .15 .00 .20 .10 .30 .25
.00 .20 .00 .20 .20 .20 .20
.00 .20 .00 .20 .10 .25 .25
.00 .10 .00 .25 .10 .25 .30
.00 .15 .00 .20 .10 .20 .35
.OO .20 .00 .15 .10 .25 .30
.00 .15 .00 .20 .10 .25 .30
.00 .15 .00 .15 .25 .30 .15
.00 .20 .00 .20 .20 .30 .20
.00 .20 .00 .20 .10 .30 .20
.00 .20 .00 .10 .20 .30 .20

.00 .20 .00 .10 .10 .40 .20

 

 

71

 

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72

independent variable correlated to the dependent variable,
on a univariate basis. Increments of five were determined
to be an accurate gauge for developing the best rho value
for the purposes of this study.

Table 11 shows the highest rho value for the seven,
six, five and four independent variables. The highest rho
value was .690 and is significant at at = .01 confidence
level; the best rho for the six, five and four independent
variable runs are also significant at CC = .01 confidence
level. The current ratio and the receivables turnover ra—
tio assisted in increasing the final rho level even though

on a univariate analysis they were of low significance.

C. Five year prediction

 

It was decided to run the model for 1960 thru 1964
and develop the best rho value for each of the seven, six,
five and four independent variables. Then, assuming that
firms did not appreciably change their financial policy
over a five year interval, the predicted results were com—
pared with those that were actually achieved for 1965 thru
1969. Table 12 shows the best rho and weighting factors
for each of the seven, six, five and four independent var-
iables. The best rho value was achieved by the four inde—
pendent variable run. The next best rho was achieved with
the seven independent variable run. It would be desirable

to use the seven independent variable run (also significant

 

73

 

 

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75

at o( = .01 confidence level) since it would provide assist—
ance in setting policy for a larger number of variables.

Using all these weighting factors, as listed in
Table 12, and using the actual data for the same eighteen
companies for 1965 thru 1969 produced the best rho values
with their corresponding set of weighting factors, as
shown in Table 13.

The prediction of the results for the succeeding
five years produced results that were significant at
QC = .01 confidence level. By running all combinations
of weighting factors shown in Table 9 for 1965 thru 1969
the best rho value was the same as that shown in Table 13,
with the exception of the seven independent variable run.
The best rho for this seven independent variable run was
equal to .664, which is the highest rho value for all of

the runs for this time period.

 

 

 

 

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CHAPTER VI

SUMMARY AND CONCLUSIONS

A. Summary of techniqge

The major objective of this research was to de—
velop a technique by which a firm in a given industry
would be able to obtain assistance in establishing long

range financial guidelines. It was assumed that there

 

were no transaction costs, no taxes and that the goal
of the firm was the maximization of shareholder wealth.
Financial decision making was classified into three sub—
divisions: the investment. the financing and the divi—
dend decisions. Specific ratios were the independent
variables specified to measure the relative efficiency
of the three major decisions. The several independent
variables were considered simultaneously in the itera—
tive solution procedure and correlated with the dependent
variable-—the index of shareholder wealth appreciation.
The drug industry was selected for the study over
the time period 1960 thru 1969. All data were obtained
from the compustat tape. The steps used in the technique

were as follows:

77

 

1)

2)

3)

4)

5)

6)

7)

8)

9)

78

Compute a mean value for each dependent and
each independent variable of the companies in
the drug industry for 1960—1969;

Rank all drug companies from high to low based
on the mean value of their dependent variable;
Normalize all values of independent variables
on a scale from one to one hundred;

Select various combinations of weighting fac-
tors which sum to 1.00;

Multiply the various sets of weighting factors
times each normalized value obtained in Step 3;
Compute a composite value by adding these com—
ponent scores obtained in Step 5 for each firm;
Rank the composite values for each company
from high to low;

Use each set of weighting factors as specified
in Step 4 to run a Spearman Rho Rank Correlation
Test between the rankings in Step 7 and step 2;
Select the composite value arrived at in itera—
tive solution procedure described above with
the highest Spearman Rho coefficient-—this will

be the index of financial efficiency.

 

 

   

79

In this study the model developed an index of fi—
nancial efficiency, using the Spearman Rho Rank Correla—
tion Test. The results were significant at a confidence
level of 0C = .01. Next, it was shown how to apply sen—
sitivity analysis in assisting the management of a firm
to establish long range financial guidelines. Specifi—
cally, the model attempted to determine the levels of cash,
inventories, receivables, fixed assets, long—term debt,
cash dividend and current ratio that were correlated to
performance of the firms in the drug industry on share—
holder wealth appreciation. As explained in a previous
chapter, the model was developed to assist management and
not to be the splg determinant in establishing future fi—
nancial guidelines.

The independent variables may not be at the opti-
mum level but will be efficient relative to other firms in
the drug industry. When considering the financial deci-
sion—makers within an enterprise——from the inside looking
out—-it is crucial to have some insight as to the effi—
cient levels of cash, inventory, etc. to increase the rel—
ative efficiency of a firm's operations in their reSpective
industry. The existing levels of cash, inventory, receiv—
ables, etc. are probably determined independently in prac—
tice with little consideration given to their combined in—

fluence on the major goal of the firm. Therefore, the

 

 

80

model considered several independent variables simultane—
ously and should provide the technique to assist in in-
creasing the present level of efficient operation. If it”
accomplishes this purpose, it should be a valuable tool
for internal management. On an ongoing basis, the first
years data could be dropped and the most current years

data could be added.

B. Limitations

The results of the study are pertinent to a Spec-
ific industry for a given historical period of time. The
technique can be applied, however, to any time period and
to any industry. Since it covered a past interval of time.
the crucial question is whether the future will be like
the past. However, the study does give patterns of finan—
cial policy correlated to their success in shareholder
wealth appreciation. There is evidence in the literature
that long—range financial policy does not change drastical—
ly over time.1

The assumption that the goal of the firm is to max—
imize shareholder wealth could be a limitation; however,
this goal is commonly recognized and agreed upon in the fi—
nancial literature. "There is general agreement among econ-

omists and financial analysts that share price (stock—holder

 

1Frame, op. cit.

 

 

 

81

wealth) maximization is the appropriate normative model
for corporate behavior.“2

Solomon says: “Even the centrally planned econ-
omies, which had earlier abolished 'profitability' and
'interest' as inventions of the capitalist devil, have
begun to reintroduce these concepts in disguised form as
guides to the more efficient utilization of scarce funds
among competing uses. In doing so they too have wrestled
with a basic issue of financial management: how should
capital costs be measured and used in making optimal in-
vestment decisions?"3

It is believed that this assumption——maximization
of shareholder wealth—-is a valid objective for a busi—
ness firm. The question then is: How is this achieved?
Surely the efficient financial decision making of any firm
should enhance this objective. To the extent that inde—
pendent variables measure——at least in a relative sense
within a given industry-~the efficiency of these decisions
the model should be an effective aid in long—range finan—

cial planning.

 

2See Eugene M. Lerner and Willard T. Carleton,
“Financing Decisions of the Firm,“ Journal of Finance,
(May 1966), Vol. XXI, p. 202.

3Ezra Solomon, The Theory of Financial Management,
New York: Columbia University Press, 1963, p. 7—8.

 

 

 

 

82

Since the compustat tape was used for the data in
this study, the results are dependent upon the accuracy
accomplished by Standard Statistics. By accuracy is meant
the handling of accounting differences, industry classifi-
cations, and the placement of data on the tape.

The application of the statistical method in this
study cannot offer proof of the existence of a causal re-
lationship between selected variables. Statistical anal—

ysis with these methods can, however, provide valuable

 

information concerning the possibility of a cause—and—ef—
fect relationship between the variables selected for anal-

ysis.

C. Contributions

It is hoped that this model will provide assist—
ance to management in establishing long—range financial
guidelines. The weighting factors arrived at should focus
or re—focus attention to the more significant areas need—
ing further detailed study and attention. Perhaps this
study will stimulate further research and result in in—
creased application of quantitative tools. The results
of this study were encouraging.

Since this study was limited to large firms in
the drug industry for which comprehensive financial data

were obtainable, an area for future research would be to

 

83

extend the model to relatively smaller asset—sized firms
in several different industries. It may even be desir—
able to extend the research across industry lines to at-
tempt to uncover significant patterns of financial policy.

Several practical applications of the model could
be extended to assist bankers, credit managers, and in—
vestors. Even if they do not have access to a computer,
manual calculations on a small selected number of firms
could be useful. The evaluation of business loans is an
important function in our society——eSpecia11y by commer—
cial banks and other lending institutions. Obviously,
the analysis of the loan applicant's financial statements
is but one aSpect of the entire evaluation process—-but
it is a very important aSpect. Many of the variables
used in the model are also common to business loan evalu—
ation. Therefore, the model would seem to be useful in
this business sector.

Important variables such as the purpose of the
loan, its maturity, the security involved, the deposit
status of the applicant, and the particular characteris—
tics of the bank are not explicitly considered in the
model; hence, the model should probably not be used as
the only means of credit evaluation. The composite val—
ue or the index of financial efficiency score, however,

can be used as a guide to lower the costs of investigation

 

 

 

84

of loan applicants. Less time would be Spent on compa—
nies whose score is very high, i.e., above 50, while those
with lower scores would Signal a very thorough investiga-
tion. This points out the important advantage of the sim—
plicity and low cost of the financial efficiency model.

An extremely important task of higher level man—
agement is to periodically assess inventory management,
cash management, etc.,without spending the time necessary
for a detailed analysis. In addition it is somewhat awk—
ward to ask for a detailed analysis of a Specific opera-
tion in a firm without some justifiable reason. The sug—
gestion here is that the financial efficiency model is
able to predict corporate weaknesses, and thus could indi—
cate to management the need for a thorough analysis which
would possibly provide the means for a more efficient op—
eration. Again, the simplicity and low cost of using this
model makes it a valuable control device for higher level
management.

The potentially useful applications of the model
are not limited to credit evaluation purposes and internal
control considerations only. An accurate predictor of
successful firms—~specifically market price appreciation——
appears to be a valuable technique for screening out de-
sirable investment opportunities. Admittedly, the anal-

ysis in this Study was from only one industry, but the

 

 

 

 

85

potential implications for selection of firms to be held
for long—term capital gains are of interest. If an indi-
vidual already owns Stock in a firm that has a low index
of financial efficiency, a sale should prevent further
loss and provide capital for alternative investments with
higher index points. At least the use of this model could
proVide the rough screen to initiate a thorough detailed
"value analysis“ of fewer numbers of potentially desirable
investment opportunities. Further investigation, however,

is required on this subject.

 

 

BIBLIOGRAPHY

 

 

BIBLIOGRAPHY

Altman, Edward Ira. “Financial Ratios, Discriminant
Analysis and the Prediction of Corporate Bank—
ruptcy.“ Journal of Finance, Vol. XXIII, No. 4
(September, 1968), 589—609.

 

Beaver, W. H. ”Financial Ratios as Predictors of Failure.“
Empirical Research in Accounting: Selected Studies
1966. Institute of Professional Accounting, Uni—
versity of Chicago, (January, 1967), 71-111.

 

Compustat Information Manual. April 1970.
Compustat Tape. Standard Statistics Company Inc., 1971.

Davis, T. C. "How the du Pont Organization Appraises Its
Performance." Financial Management Series. No. 94.
New York: American Management Association Trea-
surer's Department, 1950.

Foulke, Roy A. Practical Financial Statement Analysis.
6th ed. New York: McGraw—Hill Book Company,

 

1968.
Frame, Robert Jess. “Corporate Financial Policy and Growth:
A Behavioral Model." Unpublished Ph.D. dissertation,

University of Colorado, 1966.

Gupta, Manak Chand. ”A Synchronic Study of Corporate Fi—
nancial Structures, 1961-1962." Unpublished Ph.D.
dissertation, University of California, Los
Angelos, 1967.

Key Business Ratios in 125 Lines 1968: Retailing, Whole-
saling, Mfg., Construction. Dunn and Bradstreet
Inc., New York.

Kraus, Ralph Michael. "Empirical Testing of New Managerial

Control Ratios.“ Unpublished Ph.D. dissertation,
University of Pittsburg, 1967.

86

 

 

   

87

Latané , Henry A. and Tuttle,,Dona1d_L. Security Anal-
ysis and Portfolio Management. New York: The

Ronald Press Company, 1970.

Lerner, Eugene M. and Carleton, Willard T. “Financing
Decisions of the Firm,“ Journal of Finance, Vol.
XXI (May 1966), 202.

Manne, Henry G. "Mergers and the Market for Corporate
Control,“ The Journal of Political Economy,
LXXIII, No. 2 (April, 1965), 112—113.

Mendenhall, William. Introduction to Probability and
Statistics. Belmont, California: Wadsworth Pub—
lishing Company, Inc., 2nd ed. 1968.

Solomon, Ezra. The Theory of Financial Management. New
York: Columbia University Press, 1963.

Stone, James S. "Conglomerate Mergers: Their Implica—
tions for the Efficiency of Capital and the Theory
of the Firm." Unpublished Master's Thesis, Har—
vard University, 1969.

The Robert Morris Associates Annual Statement Studies.
Philadelphia: Robert Morris Associates, 1958 —
1966.

Vance, Mr. "Is Your Company a Takeover Target?“ Harvard
Business Review, (May—June 1969), 93—98.

Van Horne, James C. Financial Management and Policy.
Englewood Cliffs, New Jersey: Prentice—Hall, Inc.,
1968.

Wall, Alexander. How to Evaluate Financial Statements.

New York and London: Harper and Brothers Publish—
ers, 1936.

Weston, J. Fred and Brigham, Eugene F. Essentials of Man—

agerial Finance. New York: Holt, Rinehart and
Winston, 1968.

 

GENERAL REFERENCES

 

 

Bock, Betty. “Mergers and Markets,“ The Conference Board
Studies in Business Economics. No. 105, 1969,
112—114.

"Emerging Questions on Efficiency, Competition,
and Antitrust." The Conference Board Record,
(November 1968), 37.

 

Bodenhorn, Diran. "A Cash Flow Concept of Profit.“ Jour—
nal of Finance, XIX (March, 1964).

Bogen, Jules I. Financial Handbook. 4th ed. New York:
The Ronald Press Company, 1965.

 

Conover, W. J. Practical Nonparametric Statistics. New
York: John Wiley & Sons, Inc., 1971.

 

Dean, Joel. Capital Budgeting. New York: Columbia Univer—
sity Press, 1951.

 

Donaldson, Gordon. “Financial Goals; Management vs. Stock—
holders." Harvard Business Review, (May-June, 1963).
Findaly III, M. Chapman and Williams, Edward E. An Inte—

grated Analysis for Managerial Finance. Englewood
Cliffs, New Jersey: Prentice—Hall, Inc., 1970.

 

Friedman, Milton. "The Methodology of Positive Economics."
Essays in Positive Economics. Chicago: University
of Chicago Press, 1953.

 

Gordon, Myron J. “Dividends, Earnings and Stock Prices.“
Review of Economics and Statistics, XLI (May, 1959).

. The Investment, Financing and Valuation of the

 

Corporation. Homewood, 111.: Richard D. Irwin,
Inc., 1962.

"Optimal Investment and Financing Policy." and
“The Savings Investment and Valuation of a Corpora—
tion. Review of Economics and Statistics. XLIV,

 

(February, 1962).

88

 

 

   

89

Grunewald, Adolph.E., and Nemmers, Erwin EsSer. Basic
Managerial Finance. New York: Holt, Rinehart and
Winston, Inc., 1970. _

Helfert, Erich A. Technigges of Financial Apalysis. Home-
wood, Illinois: Richard D. Irwin, Inc., Rev. ed.

1

 

Mason, Robert D. StatiStical Techniques in Business and
Economics. Homewood, Illinois: Richard D. Irwin,

 

Inc., 1967.
Miller, Merton H., and Modigliani, Franco. "Dividend Policy,
Growth, and the Valuation of Shares.” Journal of

Business, XXXIV (October, 1961).

Moody's Industrial Manual. New York: Moody's Investors
Service, Inc., 1959 through 1969.

-Myers, John N. Financial Statement Analysis, 3rd ed.
Englewood Cliffs, New Jersey: Prentice—Hall, Inc.,
1969.

 

Siegel, Sidney. Nonparametric Statistics for the Behavior-
ial Sciences. New York: McGraw—Hill Book Company,
1956.

 

U.S. Department of Agriculture, “Diversification and Pro-
fitability among Large Food Processing Firms,”
Economic Research Service Apriculture Economic
Report No. 171, Washington, D.C. (January, 1970).»

 

Walter, James E. Dividend Policy and Enterprise Valuation.
Belmont, California: Wadsworth Publishing Co., 1967.

 

, ”Dividend Policy: Its Influence on the Value
of the Enterprise.“ Journal of Finance. XVIII
(May, 1963).

Various corporate annual reports.

 

 

 

APPENDICES

 

 

 

 

 

APP ENDIX A

 

 

 

kOCDQO‘U'IanNH

APPENDIX A

 

Compustat classification of drug companies

Abbott Laboratories

American Home Products Corporation
American Hospital Supply Corporation
American Sterilizer Company*

Ansul Company*

Baxter Laboratories**

Becton Dickinson Company*
Bristol—Myers Company

Carter Wallace Incorporated**
Cutter Laboratories**

Forest Laboratories*

Gillette Company

Johnson/Johnson

Kendall Company

Lily Eli Company

Merck & Company

Miles Laboratories Incorporated
Parke Davis and Company

Pfizer Uchasco and Company

Plough Incorporated**
Richardson—Merrell Incorporated
Robins (A.H.) Company*

Schering Corporation

Searle G.D. Company**

Smith Kline/French Laboratories Inc.
Sterling Drug Incorporated

Syntex Corporation**

Upjohn Company

Warner—Lambert Pharmaceutical Co.

Eliminated because of insufficient data.

Eliminated because mean value total assets
and/or total sales less than $100 million.

90

 

 

 

APPENDIX B

 

 

 

APPENDIX B

Compustat indgstrial ggfinitiops

 

1. CASH AND EQUIVALENT

AL

"Cash and Equivalent'I includes all cash, government
marketable and other securities listed in the cur-
rent asset section.

Letters of credit are included.

Margin deposits on commodity futures contracts are
included.

U.S. Government securities are included, regardless
of whether stated by the company as a current asset
or netted against tax liability in the current sec—
tion on the liability side of the balance sheet.

Excluded from cash and equivalent are the following:

1. Money due from sale of debentures (treated
as receivable);

2. Commercial paper issued by unconsolidated
subsidiaries to parent company (treated as
receivable);

3. Cash surrender value of life insurance
(treated as non—current asset);

4. Bullion, bullion in transit, uranium in tran—
sit, etc. (treated as an inventory item);

2. RECEIVABLES

AI

“Receivables“ represent claims against others (after

applicable reserves) collectible in money generally

within 12 months. This includes,but is not limited to:
1. Trade, miscellaneous and other receivables;

2. Amounts due from unconsolidated subsidiaries;

91

 

 

   

92

3. Income tax refunds;
4. Money due from sales of securities;
5. Unbilled shipments;

6. Amounts due from officers and employees
when listed as current asset;

7. Property to be sold under lease-back ar—
rangement;

8. Commercial paper issued by unconsolidated
subsidiaries to parent company;

B. Excluded from receivables are the following items:

1. Advances on material purchases (treated as
inventory item);

 

2. Work in process and advances to subcontrac—
tors (treated as inventory item);

3. U.S. Government contract billings and ex—
pensed contracts (treated as inventory items);

4. Reserves for unearned charges on commercial
installment and equipment lease receivables
and reserves for losses for finance compa—
nies (receivables are stated after deduc—
ting these items).

3. INVENTORIES
A. "Inventories” represent merchandise bought for re—
sale and materials and supplies purchased for use
in production of revenue. Inventories include

among other items:

1. Deposits and/or advances on material pur—
chases;

2. U.S. Government contract billings and ex-
pensed contracts;

3. Work in process and advances to subcon-
tractors (net of progress payments);

4. Advance manufacturing costs;

 

 

   

Ba

93

5. Bullion in transit, bullion, uranium in
transit, etc.:

6. Revenue stamps;
7. Unbilled costs on U.S. Government contracts;

8. For motion picture companies advances to
other producers;

9. Advances to planters (when classified as a
current asset);

10. Merchandise in transit;

11. For real estate companies, land purchase
option deposits;

12. For distillers, Storage charges.

 

13. For motion picture companies film costs
and distribution rights.

Excluded from inventories are the following items:

1. Tools that are listed in current asset sec—
tion (treated as other current assets);

2. Supplies and prepaid expenses for companies
that lump these items together (treated as
other current assets);

3. Unbilled Shipments (treated as receivable);

4. Growing crops (treated as non-current asset);

5. Bottles cases and kegs (treated as property
item);

4. TOTAL CURRENT ASSETS

 

A.

“Total Current Assets“ represent cash and other as—
sets which in the next 12 months are expected to be
realized in cash or used up in the production of
revenue.

Prepayments when listed separately and not as pre—
payments, etc., prepayments and deferred charges

 

   

94

or deferred charges are included in total current
assets. The latter categories are considered non—
current assets unless listed in the company's
public reports as current assets. Prepayments for
American Telephone & Telegraph are treated as non-
current assets at the company's request.

U.S. Government securities, whether listed as cur-
rent assets by the company or netted against tax
liability in the current section on the liability
side of the balance sheet are treated as current
assets.

For finance companies, repossessions are included.

Growing crops are excluded (treated as non—current
assets .

Cash surrender value of life insurance is excluded
(treated as non—current asset).

TOTAL CURRENT LIABILITIES

 

A.

''Total Current Liabilities" represent liabilities
due within one year, including the current portion
of long term debt.

U.S. Government securities are not deducted from
tax liability in current liabilities (treated as
current asset).

Customers' deposits on bottles, cases, kegs, etc.,
are excluded from current liabilities (treated as
long—term liability).

For finance companies, reserves for unearned in—
surance premiums are excluded from current liabili-
ties (treated as other non-current liabilities).

For retail companies, deferred income taxes due to
installment sales are included.

TOTAL ASSETS

A.

“Total Assets" represent current assets plus net
plant plus other non—current assets (including in—
tangible assets and deferred items).

 

 

95

B. Treasury stock carried by the company on the asset
side of the balance sheet in its public reports is
netted against preferred or common stock respec-
tively on the liability side. Shares held Specif—
ically for officers and employees funds (incentive
compensation, pension and profit sharing) are not
considered treasury Stock. However, shares held
for officer and employees Stock option plans are
considered treasury stock and netted against pre-
ferred or common Stock respectively on the liabil-
ity side.

C. U.S. Government securities that have been netted
by the company in its public reports against tax
liability Side of the balance sheet are considered
as current assets.

LONG TERM DEBT

A. “Long-Term Debt“ represents debt obligations due
after one year.

B. Purchase obligations and payments to officers (when
listed as long term liabilities) are included as
long-term debt.

C. Notes payable, due within one year and to be re—
funded by long—term debt, when carried as a non-cur-
rent liability are included in long—term debt.

D. Subsidiary preferred stock is excluded (treated as
other liability).

E. The current portion of long-term debt is excluded
(treated as current liability).
COMMON EQUITY

A. “Common Equity“ represents common stock plus the
following items:

1. Surplus;
2. Surplus reserves (contingencies, insurance, etc.);
3. Unamortized debt premium;

4. Capital stock premium;

 

 

 

 

96

Excess value of net assets over cost (negative
intangible) less the following items:

1. Common treasury stock;
2. Intangibles (see Item # 33);
3. Unamortized debt discount and expense;

Capital Stock expense;

Accumulated unpaid preferred dividends;

G‘UIA

Excess of involuntary liquidating value of
outstanding preferred stock over carrying
value;

7. For finance companies, deferred develop—
ment costs.

B. Deferred taxes and investment credit (Balance Sheet)
are not included in this figure.

C. Negative equity figures are shown where applicable.

NET SALES

Annual

1.

Data

"Net sales” represent gross sales and other
operating revenue less discounts, returns and
allowances.

Royalty income is included.

For retail companies, sales of leased depart—
ments are included, when available.

For Shipping companies, operating differential
subsidies are included.

For shipping companies, income on reserve fund
securities is included when Shown separately.

For finance companies, earned insurance pre—
miums are included.

For airline companies, net mutual aid assist-
ance is included.

 

 

   

97

8. For cigar, cigarette, oil, rubber and liquor
companies, net sales are after deducting ex-
cise taxes.

9. For finance companies, sales are after de—
ducting net losses on factored receivables
purchased.
10. Income derived from equipment rental is con- .
sidered part of operating revenues.

10. AVAILABLE FOR COMMON

 

Annual Data

1. "Available for Common" represents net income
less preferred dividend requirements.

2. Normally, the preferred dividend requirements
used in this calculation will be the same as
the preferred dividends declared.

 

a. If more or less than four quarterly pre—
ferred dividends are declared in one year
(where dividends are declared quarterly),
then preferred dividend requirements will
be used in calculating available for com-
mon;

b. If all convertible preferred stock is con—
verted into common during the year, no pre-
ferred dividends are deducted in calcula-
ting available for common;

c. If common Stock is issued by the company
in exchange for preferred stock of another
company, the dividends on the old preferred
Stock are disregarded in calculating avail—
able for common.

11. COMMON DIVIDENDS
A. "Common Dividends“ represent the dividends (other
than Stock dividends) declared on the common stock

of the company during the year.

B. Dividends declared by a company which is merged on
a cooling of interests basis are included for the

 

 

 

 

98

year of the merger, including dividends on pre-
ferred stock of a merged company which was ex—
changed for common stock.

C. Dividends declared in Stock of other corporations,
excluding spin-offs, are included.

D. Dividends declared in preferred stock are included.
E. Subsidiary dividends (other than preferred, which

are treated as a fixed charge) are excluded (treat—
ed as a minority interest).

PRICE - HIGH, LOW, AND CLOSE

 

Annual Data

 

1. “Price — High, Low and Close” represents the
absolute high, low and close transactions dur-
ing the year for companies on national stock
exchanges and bid prices for Over—the—Counter
issues.

2. Prices are reported on a calendar—year basis,
regardless of the company's fiscal year—end.

3. Prices in COMPUSTAT are adjusted for all stock
splits and stock dividends that occurred in the
calendar year, except for fiscal year companies
which have declared Stock Splits and dividends
between the end of the fiscal year and the end
of the calendar year. In those instances, the
stated prices are not adjusted. This enables
the user to adjust prices, shares traded and
per Share statistics with a single adjustment
factor, as with calendar year companies.

4. Prices are indicated in eights, with the digit
after the decimal designating eighths. The fol—
lowing table illustrates the method used:

 

99

Stock Price Figure on Tape

20 20.0
20 1/8 20.1
20 1/4 20.2
20 3/8 20.3
20 1/2 20.4
20 5/8 20.5
20 3/4 20.6
20 7/8 20.7

The primary source for back price data was Bank
& Quotations Record, with these figures adjusted
by Standard Statistics for Stock Splits and
Stock dividends which occurred during the re-
porting year, except as indicated in paragraph

3 above. Beginning in 1964 prices were derived
from the S & P Stock Guide, data for which is
obtained directly from the Associated Press
which compiles the information electronically.

The method of adjusting data for Stock splits
and stock dividends that occurred subsequent to
the reporting year is explained in the adjust-
ment factor section of these definitions.

13. NUMBER OF COMMON SHARES OUTSTANDING

Annual Data

1.

”Number of Common Shares Outstanding“ represents
the net number of common Shares outstanding at
year—end, excluding treasury Shares and scrip.
Shares held Specifically for officers and em—
ployees' funds (incentive compensation, pension
and profit Sharing) are not considered treasury
stock. However, shares held for officer and
employee stock option plans are considered trea-
sury stock and netted against preferred or com-
mon stock reSpectively on the liability side.

 

 

 

 

 

2.

100

Shares paid in stock dividends are included,
where the stock of record date falls within the
year and the payment date the next year.

14. DIVIDENDS PER SHARE

Annual Data

1.

“Dividends Per Share” represents the cash divi-
dend per share paid during the reporting year,
adjusted for all stock Splits and stock dividends
that occurred during the year. This field, un—
like the common dividends field, excludes pay—
ments in preferred stock in lieu of cash, spin—
offs, and stock of other corporations.

The method of adjusting dividends per share for
stock Splits and stock dividends that occurred
subsequent to the reporting year is explained in
the adjustment factor section which follows.

15. ADJUSTMENT FACTOR

Annual Data

1.

The "Adjustment Factor" is an annual number
which enables the user to correct reported per
share data, such as price, earnings per share,
dividends per share, etc., for all Stock splits
and stock dividends that occurred subsequent to
the end of the year in which the original data
was reported. These factors, applied to per
share data for earlier years, in effect, convert
such data into terms of the current Share units.

The adjustment factors for all years will be
changed whenever a Stock split or stock dividend
occurs. The factors are carried to six decimal
places in order that rounding errors will be
minimized.

When no changes in capitalization have occurred
because of splits and dividends, the adjustment
factors are indicated as 1.000000. If for ex—
ample, a 2—for—1 split occurred in 1962, the ad-
justment factor for 1961 would be indicated as
2.000000. If, in addition, a 2% stock dividend
occurred in 1961, the adjustment factor for 1960
would be indicated by 2.040000.

 

 

 

 

 

16.

101

To adjust price to a current units basis, divide
the indicated price for each year by the corre-
Sponding adjustment factor. To convert shares
traded to an equivalent current basis, the re—
ported shares traded are multiplied by the cor—
responding adjustment factor.

To compute adjusted per share statistics, except
dividends per share, (e.g. earnings per share,
sales per share, etc.) multiply the number of
shares outstanding by the corresponding adjust—
ment factor and use this adjusted total number
of shares adjustment factor.

Since dividends per share are indicated separ_
ately on the tape, adjustments to this figure
are obtained directly by dividing the indicated
dividends per share by the correSponding adjust-
ment factor.

To enable the user to adjust per share statistics,
price and shares traded with a single adjustment
factor as with calendar year companies, the prices
and the shares traded for fiscal year companies
are not adjusted on the tape for stock splits and
dividends that took place between the end of the
fiscal year and the end of the calendar year.

On calendar year companies, the stock of record
date is used as a guide in determining adjustment
of per share data in any year.

COST OF GOODS SOLD

 

A.

”Cost of Goods Sold" includes all costs directly
allocated by the company to production such as
material, labor and overhead, etc.

Total operating costs are considered cost of goods
sold for non-manufacturing companies.

Included in this caption are:

1.

Taxes other than income charged to cost of
sales. When no breakdown is available, the
total amount will be included.

Pension retirement and other employee benefits
when listed separately will be included.

 

 

 

   

 

17.

18.

102

D. Excluded from cost of goods sold are the follow-
ing items:

1. Depreciation and amortization charged to cost
of sales. When no breakdown is available, the
total amount will be deducted.

2. Director's fee and remunerations.

RESEARCH & DEVELOPMENT EXPENSES

 

“Research & Development Expenses“ include all costs
incurred, such as salaries, departmental expenses,
etc., which are charged to operations as research ex-
pense. For mining, gas and oil companies, explora-
tion expenses are included.

EARNINGS PER SHARE AS REPORTED (Before extraordinary
items net of tax)

 

Annual Data

”Earnings Per Share as Reported" represents the per
share earnings figure as reported by the company.
Figure reported may be different from earnings per
share calculated from information on the tape due to
company's presentation of primary earnings per share
or the weighted average number of common shares used
to compute earnings per share.

 

 

 

 

 

APPENDIX C '

 

   

 

103

 

 

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