MODULE-I: MANAGERIAL ECONOMICS 1.1 Introduction Economics is the study about making choices in the presence of scarcity. The notions, ‘Scarcity’ and ‘Choice’ are very important in Economics. If the things were available in plenty then there would have been no choice problem, you can have anything you want. The point is that problem of choice arises because of scarcity. The study of such choice problem at the individual, social, national and international level is what Economics is about. Thus, Economics as a social science, studies the human behaviour as relationship between numerous wants and scarce means having alternative uses. Economics, as a basic discipline, is useful for certain functional areas of business management. Economics could be broadly classified into two categories: 1) Macro economics and 2) Micro economics. Macroeconomics is the study of the economic system as a whole. Microeconomics, on the other hand, focuses on the behaviour of the individual economic activity, firms and individuals and their interaction in markets. Managerial economics is an applied microeconomics. It bridges the gap between abstract theories of economics in the managerial decision-making. So, managerial economics is an application of that part of microeconomics, focusing on those topics of the greatest interest and importance to 1
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MODULE-I: MANAGERIAL ECONOMICS
1.1 Introduction
Economics is the study about making choices in the presence of scarcity. The
notions, ‘Scarcity’ and ‘Choice’ are very important in Economics. If the things were
available in plenty then there would have been no choice problem, you can have anything
you want. The point is that problem of choice arises because of scarcity. The study of
such choice problem at the individual, social, national and international level is what
Economics is about. Thus, Economics as a social science, studies the human behaviour as
relationship between numerous wants and scarce means having alternative uses.
Economics, as a basic discipline, is useful for certain functional areas of business
management. Economics could be broadly classified into two categories: 1) Macro
economics and 2) Micro economics. Macroeconomics is the study of the economic
system as a whole. Microeconomics, on the other hand, focuses on the behaviour of the
individual economic activity, firms and individuals and their interaction in markets.
Managerial economics is an applied microeconomics. It bridges the gap between
abstract theories of economics in the managerial decision-making. So, managerial
economics is an application of that part of microeconomics, focusing on those topics of
the greatest interest and importance to managers. The topics include demand, demand
forecasting, production, cost, cost function, pricing, market structure and government
regulation. A strong grasp of the principles that govern the economic behaviour of firms
and individuals is an important managerial talent.
In general, managerial economics can be used by the goal-oriented manager in
two ways. First, given an existing economic environment, the principles of managerial
economics provide a framework for evaluating whether resources are allocated being
efficient within a firm. For example, economist can help the management to determine if
reallocating labour from marketing activity to the production line could increase profit.
Second these principles help managers respond to various economic signals. For
example, given an increase in price of output or development of new lower cost
production technology, the appropriate managerial response would be to increase output.
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Alternatively, an increase in the price of one input, say labour, may be a signal to
substitute other inputs, such as capital, for labour in production process.
1.2 Meaning and Definition of Managerial Economics
Managerial Economics is the application of economic theory and methodology to
decision-making processes within the enterprise.
Hailstones and Rothwell defined managerial Economics as “Managerial
Economics is the application of economic theory and analysis to practices of
business firms and other institutions.”
According to McNair and Merian say that “managerial economics consists of
the use of economic modes of thought to analyze business situations”.
Spencer and Siegelman defined Managerial Economics as “the integration of
economic theory with business practice for the purpose of facilitating decision-
making and forward planning by the management”.
According to Prof.Evan J.Douglas “Managerial Economics is concerned with
the application of economic principles and methodologies to the decision making
process within the firm or organization under the conditions of uncertainties”
In general, Managerial Economics could be defined as the discipline which deals
with the application of economic theory to business management.
1.3. Nature of Managerial Economics
Management is the guidance, leadership and control of the efforts of a group of
people towards some common objective. It tells about the purpose or function of
management. Koontz and O’ Donell define management as the creation and maintenance
of an internal environment in an enterprise where individuals work together in groups,
can perform efficiently and effectively towards the attainment of group goals. Thus,
management is coordination, an art of getting things done by other people. On the other
hand, economics due to scarcity of resources is primarily engaged in analyzing and
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providing answers to the various basic economic problems like what to produce? How to
produce? And for whom to produce? Science of Economics has developed several
concepts and analytical tools to deal with the problem of allocation of scarce resource
among competing ends. Close interrelationship between management objectives and
economic principles has led to the development of Managerial Economics. Managerial
Economics as a link between economic theory and decision science, its purpose is to
contribute to sound decision making not only in business but also in government agencies
and Non- profit organizations. In particular, managerial economics assists in making
decisions about the optimum allocation of scarce resources among competing activities.
The following chart shows the nature of Managerial Economics.
1.4. Scope of Managerial Economics
Scope of the subject is said to be an extent of coverage of the subject concerned or
boundaries within which subject is set in and also the importance of the subject.
Managerial Economics, among others, embraces following important aspects.
Demand Analysis and Forecasting
Production and Cost Analysis
Pricing Decisions, Policies and Practices
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EconomicsTools and Techniques
Business ManagementChoosing the best alternative
Managerial EconomicsApplication of Economics to
Solve business problems
SOUND BUSINESS DECISION
Capital Management, and
Profit Management
Though the above ones are treated as subject matter of Managerial Economics, in the
recent years some of the techniques like Linear Programming, Input-output analysis, etc.
are also become the part of the subject.
1.4.1 Demand Analysis and Forecasting
Demand is a starting force for any business firm to emerge. A business firm is an
economic organism, which transforms productive resources into goods, and services that
are to be sold in a market. So, a major part of managerial decision-making depends on
accurate analysis of demand. Demand analysis helps identify the various factors
influencing the demand for firm’s product and thus provides guidelines to manipulating
demand. Hence, Demand analysis and forecasting, therefore, is necessary for business
planning and occupies a strategic place in Managerial Economics.
1.4.2 Production and Cost Analysis
In the competitive environment, business firms are forced to produce goods and
services with cost effectiveness. Production function and cost analysis enable the firms to
achieve these goals. The factors of production may be combined in a particular way to
yield maximum output. In case the prices of inputs shoot up, a firm is forced to work out
a least cost combination of inputs in producing a particular level of output. Along with
the above, a study of economic costs, combined with the data drawn from the firm’s
accounting records can yield significant cost estimates that are useful for managerial
decisions. The suitable strategy for the minimization of cost could be evolved.
1.4.3 Pricing Decisions, Policies and Practices
The success of a business firm mainly depends on the sound price policy of the
firm. The price policy of the firms determines its sales volume as well as its revenue.
Price X Sales volume = Gross Revenue of the firm
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Therefore, pricing is very important area of Managerial Economics. Important aspects
dealt with under this area are: Price and output determination in various Market forms,
pricing methods, Differential pricing, Product line pricing and so on.
1.4.4 Capital Management
Capital is one of the most important factors of production. In developing countries
like India it is a limiting factor on the economic development. It is to be managed more
efficiently for the overall development of the economy as well as for the prosperity of the
firm. A firm’s capital management is most troublesome and complex activity of business
management. This kind of capital management implies planning and control of capital
expenditure. The major areas dealt here are: Cost of capital, Rate of return and selection
of projects.
1.4.5 Profit Management
All kinds of business firms generally organized for the purpose of making profits.
In the long-run profits provide the chief measure of success. An element of risk deserves
place at this point. Profit analysis becomes an easy task in the absence of risk. However
in the business it is difficult to assume something without risk. The important aspects
covered under this are: Nature and measurement of profit, Profit policies.
The above-mentioned aspects represent the major uncertainties, which a business
firm has to reckon with. Thus, Managerial Economics is application of economic
principles and concepts towards adjusting with various uncertainties faced by a business
firm.
1.5. Managerial Economics and its Relationship with Other DisciplinesManagerial Economics is an interdisciplinary course. In fact most of the
management courses are of that sort. Managerial economics is linked with various other
fields of study. Subjects like Economics, Statistics, Mathematics, and Accounting deserve
greater emphasis in this regard. However, the relation of Managerial Economics is not
confined only to them.
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1.5.1 Managerial Economics and Economics:
Managerial Economics is widely understood as economics applied to managerial
decisions. It may be viewed as a special branch of economics, functioning as bridge
between economic theory and managerial decisions. Microeconomics, one of the main
divisions of economics, is main source of concepts and analytical tools for managerial
economists. To illustrate, concepts such as elasticity of demand, elasticity of production,
demand forecasting, marketing forms, production function etc. are of great significance to
managerial economists. Thus, it is felt that the roots of managerial economics spring from
micro-economic theory. The chief contribution of macroeconomics is in the area of
forecasting of general business conditions. The modern theory of income and
employment has direct implications for forecasting general business conditions.
1.5.2 Managerial Economics and Statistics:
Economics in general, Managerial economics in particular deals with quantifiable
variables. Quantification and estimations plays crucial role in managerial economics.
Therefore, application of statistics in Managerial Economics helps in decision-making in
several ways. It helps in the estimation of demand function, which in turn helps in
demand forecasting. Similarly statistics is also useful in the estimation of production and
cost functions. Estimation of price index relays heavily on statistical tools. In this way
Managerial Economics is heavily rely on statistical methods.
1.5.3 Managerial Economics and Mathematics:
Mathematics is another important discipline closely related to Managerial
Economics. It is again because managerial economics is quantifiable. Knowledge of
geometry, calculus and matrix-algebra is not only essential but certain mathematical
concepts and tools such as Logarithms and Exponentials, Vectors and so on are the tool
kits of managerial economists. In addition, Operations Research is also closely related to
Managerial Economics, used to find out the best of all possibilities. Linear Programming
is an important tool for decision-making in business and industry as it can help in solving
problems like determination of facilities on machine scheduling, distribution of
commodities and optimum product mix etc. Input-output analysis is also very much
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useful in managerial economics. Thus, there is close relationship between Managerial
economics and Mathematics.
1.5.4 Managerial Economics and Accounting:
Accounting mainly deals with systematic recording of the financial reports of
business firms. As a matter of fact accounting information is one of the principle source
of data required by a managerial economist for his decision making purpose. For
example, the profit and loss account of a firm tells how well the firm has done and the
information it contains can be used by a managerial economist to throw light on the
present economic performance of the firm and future course of action. It is in this context
that the growing link between management accounting and managerial economics
deserve special mention. The main task of the management accountants now seen as
being to provide the sort of data which manager needs if they are to apply the ideas of
managerial economists to solve the business problem.
1.6. Fundamental Concepts of Managerial EconomicsManagerial Economics as explained earlier, it is the application of economic
theory to management decision-making. Economic theory offers a variety of concepts
and analytical tools, which can be of considerable assistance to the manager in his/her
decision-making process. These basic concepts or principles are fundamental to the entire
gamut of managerial economics. Some important basic concepts are discussed in this
section. The basic concepts discussed in this section includes:
1. Opportunity cost principle
2. Incremental principle
3. Time perspective principle
4. Discounting principle
5. Equi-marginal principle
1.6.1 Opportunity Cost Principle
Opportunity cost is of fundamental importance in decision-making process. The
opportunity cost principle may be stated as under: The cost involved in any decision
consists of the sacrifices of alternatives required by that decision. If there are no
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sacrifices, there is no cost. Decision implies making a choice from among the various
alternatives. By the opportunity cost of a decision is meant the sacrifice of alternatives
required by that decision. A decision is cost free if it involves no sacrifice. For example,
a businessman invests his own capital in business; its opportunity cost can be measured in
terms of interest, which he could have earned by lending that money to somebody.
Another illustration, when a businessman devotes his time in organizing his business, the
opportunity cost may be measured in terms of salaries he could have earned from some
employment from elsewhere. Thus, in above cases, businessman compares expected rate
of return (prospective yields) from business with current rate of interest/salary and if he
finds that prospective yields happen to be greater than the rate of interest/salary he would
take a positive decision for further investment, otherwise not. Thus, opportunity cost is
the benefit foregone by not selecting the best alternative.
1.6.2 Incremental Principle
The concept of incremental principle is related to the marginal costs and marginal
revenues concepts of economics. The incremental concept refers to the change in total. It
involves estimating the impact of decision alternatives on cost and revenues. The two
basic components of incremental reasoning are incremental cost and incremental revenue.
Incremental cost may be defined as the change in the total cost due to particular decision.
Incremental revenue is the change in total revenue caused by particular decision. Thus,
when incremental revenue exceeds incremental cost resulting from a particular decision,
it is regarded as profitable. This certainly helps arriving at a better decision comparing
between incremental costs and revenues of alternative decisions. For example table 1
illustrates the revenue and cost of producing commodity ‘X’ by ABC Company.
Table 1: Revenue and Cost of X Commodity Pertaining to ABC Company
Sl.No.(1)
Production of X commodity
(2)
Total Revenue
(3)
Incremental Revenue
(4)
Total Cost
(5)
Incremental Cost
(6)
Total profit7=(3-6)
1 1000 20000 - 18000 - 2000
2 2000 39500 19500 37000 19000 2500
3 3000 58500 19000 58500 21500 0
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Increase in production from 1000 units to 2000 units results higher incremental revenue
(Rs.19500) compared to incremental cost (Rs.19000). Therefore, it is advisable to
increase production from 1000 units to 2000 units. Incremental cost (Rs.21500) is more
than the incremental revenue (Rs.19000) when the producer increases his production
from 2000 units to 3000 units.
1.6.3 Time Perspective Principle
The economic concepts like short-run and long-run are part of every day
language. This time perspective of short and long-run period is important in business
decision-making. Managerial economists are also concerned with long and short – run
effects of decisions on revenues as well as costs. Important problem in decision-making
is to maintain the right balance between short-run and long-run considerations.
1.6.4 Discounting Principle
The concept of discounting is applied to future costs and returns as there are
variations in the time perspective underlying different decisions. Discounting originates
from the concept of opportunity cost and time perspective. A simple example would
make this point clear. Suppose a person is offered a choice to have Rs.1000 now or after
two years. He/She would be obviously choosing the first one, as the present value of
Rs.1000 is less after two years than it is available today. In business decision-making
process, thus, the discounting principle may be stated as: “If decision affects costs and
revenues at future dates, it is necessary to discount those costs and revenues to present
values before a valid comparison of alternatives is possible”
1.6.5 Equi-Marginal Principle
Equi-marginal principle deals with the allocation of the available resources among
the alternative activities. According to this principle, an input should be so allocated that
the value added by the last unit is the same in all uses. Suppose a firm has 100 units of
labour at its disposal. The firm engages in three economic activities, which need services
of labour viz. A, B, and C. It could enhance any of these activities by adding more of
labour only at the cost of other activity. Thus, It should be clear that if the marginal value
product is higher in one activity than another, an optimum allocation has not been
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attained. It would therefore, be profitable to shift labour from low marginal value product
activity to higher marginal value product activity. The optimum allocation of labour
could be ensured when:
(VMPL)a = (VMPL) b = (VMPL)c
Here, VMPL refers to the value of marginal product of labour; a, b, c are three activities.
Thus, this principle is greatly useful in the allocation of any of the resources among
alternative uses.
1.7. Objectives of the Firm
Each and every business firm strives to achieve some predetermined objectives. In
the conventional economics emphasis was given to the profit maximization objective. In
modern society, very few experts will argue that a firm is motivated by the sole objective
of maximization of profit. In the modern days a firm invariably pursues multiple
objectives even though one or some of them may receive priority over others. The
objectives of the modern firm could be summarized under the following headings.
1. Profit maximization
2. Long run survival
3. Sales maximization with Profit constraint
4. Cost minimization
1.7.1. Profit Maximisation: The success of any business is measured by the volume of
its net income. The Net Income is the residual income, which accrues to a firm after all
other costs have been met. In other words Net Income = Total Revenue –Total Cost. It
is considered to be the acid test of the performance of the individual firm. Emphasis has
been given to this objective in conventional economics.
1.7.2. Long Run Survival: Economists, in the modern days, however, do not accept
that profit maximisation is the only objective to be attained by the firm. K. Rothdchild
expressed that the primary objective of any business enterprise is long run survival. For
the long run survival to some extent firms compromise with their profit level. In the
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modern days, firms’ aims at limited instead of maximum profit for various reasons.
Professor Joel Dean mentioned some of the reasons for limiting profits viz. 1.To
discourage the potential competitors, 2. To maintain costumers good will, 3. To keep
market control undiluted 4. To maintain pleasant working condition etc.
1.7.3. Sales Maximization with Profit Constraint: Prof. William J. Baumol,
American economist, does not agree with the traditional view that firms aims at
maximizing profit. According to him, the objective of a modern firm is sales
maximisation with a profit constraint. Sales maximisation does not mean an attempt to
get largest possible physical volume of output. Here the sales means the revenue earned
by selling the product. Hence, sales maximisation refers to the maximisation of the total
revenue that measures the quantity of product sold in Rupee terms. It could be presented
with the Support of the figure No.1.1.
Figure 1.1: Sales maximization with Profit constraint
In this figure X-axis measures the output and Y-axis measures the Total Revenue
(TR), Total Cost (TC) and Total Profit (TP). OM is the minimum profit, which the firm
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intends to earn. With the increase in the output/sales level the TR goes on increasing up
to a certain extent then start falling. Similarly TC goes on increasing with the increase in
the sales level. TP is the difference between the TR and TC; hence TP is the vertical
distance between the TR and TC. If the firm intends to get maximum profit it has to
produce/ sale OA quantity of output because TP curve is maximum at point H. On the
other hand if the firm intends to maximize the sales it has to produce and sell OC amount
of the commodity because TR curve maximum at point R2. At OC level of output profit
level (CG) is less than intended level (CP). According to Baumol the firm produce/sell
OB amount of output. It maximizes the total revenue subjected to minimum profit shown
by ML curve. BE is the profit earned by the firm at OB level of output.
1.7.4. Cost Minimization: Whether a firm is pursuing the profit maximisation goal or
total revenue maximisation subjected to profit constraint goal or even long run survival
goal the firm has to produce the goods or render the service at the least cost through the
achievement of the technical efficiency. Cost minimization through the existing technical
efficiency is within the control of the firm. Total revenue, along with quantity of the
commodity sold, depends on the market price of the commodity, which is many a time
beyond the control of the firm. The cost minimization enables the firm to achieve the
objectives discussed above.
1.8 Factors Affecting Managerial Decisions
Managerial decision-making is not just only influenced by economics but also by
various other significant factors. Undoubtedly economic analysis contributes a great deal
to the problem solving in an enterprise, at the same time it is important to remember three
other variables, which have equal impact on the choices and decisions of managers.
Therefore, the major factors affecting managerial decisions are:
1. Economic factors
2. Human and behavioral factors
3. Technological factors, and
4. Environmental factors
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1.8.1 Economic Factors
Economic factor works as backbone for every decision-making particularly, in
case of commercial organizations .In the present day situation it is even extended to not-
for-profit organizations. In business organizations for the purpose of survival and growth
more than anything economic factors like, profit maximization and/or sales revenue
maximization play vital role.
1.8.2 Human and Behavioral Factors
It is proved beyond the doubt that economic factors occupy significant place in
decision-making process. However, economic rationality may not hold well all the times.
Ultimately economics is for the well-being of people concerned. So, management of any
organization will look into their personal comfort as well employees morale and
motivation. It can be observed with small entrepreneurs, who refuse to expand or
diversify their economic activity even though economic rational provides clear signal of
the opportunities ahead that await them. Yet many of them decide to remain small since
they feel that such expansion will tend to strain their lifestyles or threaten their control
over the management.
1.8.3 Technological Factors
Technological factors also play crucial role in managerial decision-making
process. In the resource allocation process management of an organization will assess the
technological alternatives, the technological moves of competitors and emergence of new
technologies and processes. No major investment decision is made without a close
scrutiny of relevant technological alternatives. This is applicable for new establishment,
expansion of an existing concern, modernization and diversification decisions.
1.8.4 Environmental Factors
It is impossible to imagine any business organization in isolation. It functions
amidst of turbulent environment consists of socio-economic, physical, political forces etc.
Environmental pressures operating on the enterprise have a bearing on managerial
decisions even when they are primarily economic in nature. For example, economic
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rationality might suggest a strong case for a price rise and yet the organization might be
forced by political, social hostility not to do the same. In the recent times the force of
environmental considerations is growing stronger. Public awareness about the impact of
firm level decisions on society is growing. Politicians, consumer activists, community
organizations and so on are increasingly concerned about the nature and consequences of
these decisions and constantly make their presence felt which may conflict with the
economic rationality.
1.9. Self Review Questions
1. Define Managerial Economics and discuss its nature and scope.
2. “Managerial Economics is economics applied to decision-making” Explain.
3. Explain how managerial economics is related to Economics, Mathematics, Statistics
and Accounting.
4.Discuss the objectives of a modern business firm.
5. Explain the factors influencing the managerial decisions.
6. Define opportunity cost? Explain its applications in management decisions.
7. Describe the importance of equi-marginal principle in Managerial decision making
process.
8. Explain the importance of incremental principle in the management science.
1.10. References/ Suggested Readings
1. Varshney RL, and Maheshwari K.L: “Managerial Economics”, Sultan Chand & Sons,
New Delhi-110002
2. Mote, V. L., Samuel Paul, Gupta,G. S: “ Managerial Economics: Concepts and Cases”,
Tata McGraw-Hill Publishing Company Limited, New Delhi
3. D.M.Mithani : “Managerial Economics: Theory and Applications”, Himalaya
Publishing House, Mumbai-400 004
6. Gopalakrishna, D.: “ A Study in Managerial Economics” Himalaya Publishing House,
Mumbai-400 004
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MODULE-II: DEMAND ANALYSIS AND FORECASTING
2.1 Introduction
The success or failure of a business depends primarily on its ability to generate
revenues by satisfying the demand of consumers. Firms that are failed to attract the
consumers are soon forced to be out of the business. Demand analysis is a source of
many useful insights for business decision-making. It serves the following managerial
objectives;
It helps in product planning and product improvement.
It gives direction for demand manipulation through advertising and sales
promotion strategies.
It is useful technique for demand forecasting with greater reliability.
It reveals the scope of business expansion.
It is, therefore, worthwhile to understand some of the concepts related to demand
analysis. Meaning, types, determinants of demand, demand functions, elasticity of
demand and demand forecasting are discussed in this chapter.
2.2 Meaning of Demand.
Demand, ordinarily, is defined as desire. But desire of a beggar to travel by air
could not be materialized for lack of his ability to pay. Desires come and vanish. So all
such desires could not be considered as demand. A desire to be called demand should be
backed by two things; one, ability to buy and two, willingness to buy. Thus, the demand
for any commodity is the desire for that commodity backed by willingness as well as
ability to pay for it and is always defined with reference to a particular time and at given
price. Demand = Desire + Ability to pay (purchasing power) + Willingness to pay. In
another way the demand for a product could be defined as the amount of it, which
will be bought per unit of time at a particular price. It is not out of context to
introduce some of the concepts pertaining to the concept demand. The concept of
Individual demand, Market demand, the law of demand, and change in quantity demand
versus change in demand.
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2.2.1 Individual Demand and Market Demand
An individual demand refers to, other things remaining the same, the quantity of a
commodity demanded by an individual consumer at various prices. Market demand is the
summation of demand for a good by all individual buyers in the market. The distinction
between individual demand and market demand has been explained with the help of
individual and market demand schedule as well as demand curves.
Tab-2.1:Individual Demand Schedule
Price (Rs.) Quantity demanded
(units)
6 10
5 20
4 30
3 40
2 60
1 80
Fig 2.1 Individual Demand Curve
An individual demand refers to the quantity of a commodity demanded by an
individual consumer at various prices, other things remaining same. An individual’s
demand for a commodity is shown on the demand schedule (Table-2.1) and demand
curve (Fig 2.1). A demand schedule is a list of prices and quantities and its graphical
representation is demand curve. It could be seen from the demand schedule that as the
price of the commodity goes on declining the quantity demand goes on increasing. Only
10 units of commodity are demanded when the price is Rs. 6 per unit whereas the
quantity demand increased to 80 units when the price declined to Rs.1 per unit. DD1, in
figure 2.1, is the demand curve drawn on the basis of the above demand schedule. The
dotted points D, Q, R, S, T and U are the ‘demand points’. They show the various price-
quantity combinations. The demand curve shows the effect of rise or fall in the price of
one commodity on the consumer’s behaviour.
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In a market, there will be many consumers for a commodity. Therefore, Market
demand shows the sum total of various quantities demanded by all the individuals at
various prices. The market demand of a commodity is depicted on a demand schedule
and demand curve. Suppose there are three individuals A, B, and C in a market who
purchase the commodity. The demand schedule for commodity is depicted in table-2.2.
The column 5 of the table represents the market demand for the commodity at various
prices. It is obtained by adding the column 2, 3 and 4 which represent the demand of the
consumers A, B and C respectively. The relation between column 1and 5 shows the
market demand schedule.
Table 2.2 Market Demand for the X Commodity
Price (Rs./Kg)
(1)
Quantity demand in Kgs.
Consumer A
(2)
Consumer B
(3)
Consumer C
(4)
Market Demand
(5) (2+3+4)
6 10 20 40 70
5 20 40 60 120
4 30 60 80 170
3 40 80 100 220
2 60 100 120 280
1 80 120 160 360
The market demand for the commodity at the price level of Rs.6 per unit is 70 Kg. The
market demand increased to 360 Kg with the fall in the price to Rs.1 per Kg. In the figure
2.2, Dm is the market demand. It is the horizontal summation of all the individual demand
curves DA+DB+DC. The market demand for a commodity depends on all factors that
determine an individual demand.
2.2.2. The Law of Demand
The law of demand describes the general tendency of consumers’ behaviour in
demanding a commodity in relation to the change in its price. The law of demand simply
states that the quantity demand of a commodity varies inversely to change in price.
“Ceteris paribus, the higher the price of a commodity, the smaller is the quantity
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demand and lower the price, larger the quantity demand”. The law of demand
relates the change in quantity of demand to the change in the price variable only. It is
always stated with the ceteris paribus i.e other things remaining same. It assumes other
determinants of demand to be constant. Thus the law of demand based on, among others,
the following major assumptions:
No change in the price of related goods
No change in the consumers income
No change in the consumers preference
No change in the advertisement strategies of business houses
Figure 2.2: Market Demand Curve
It is almost a universal phenomenon of the law of demand that the demand curve
slopes downward from left to right. In certain cases demand curve may slopes up from
left to right. It is because consumer may buy more when the price of a commodity rises
and less when price falls. Such circumstances are termed as exceptions to law of demand.
Exceptional cases may be categorized as;
1.Giffen found that in the 19th century, Ireland people were so poor that they spent a
major part of their income on Potatoes and small part on meat. For them potatoes and
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meat are inferior and superior goods respectively. When price of potatoes rose, they had
to economise on meat even to maintain the same consumption of potatoes. Further to fill
up the resulting gap in food supply caused by a reduction in meat consumption, more
potatoes had to be purchased because potatoes were still the cheapest food. Thus the rise
in the price of potatoes increased the demand for potatoes. Such goods are popularly
known as Giffen goods.
2. Some goods are purchased mainly for their snob appeal. When the price of such goods
rises, their snob appeal increases and they are purchased in large quantity and vis-à-vis.
Such goods are called Veblen goods. It is named after an American economist, Thorstein
Veblen, who advocated that some purchases were made not for the direct satisfaction,
which they yield, but for the impression, which they made on other people.
3. In the speculative market, a fall in price is frequently followed by smaller purchase and
a rise in price by larger purchases. When price of certain goods rises, people may expect
further rise and rush to buy. When price fall, they may wait for further falls, and stop
buying.
2.2.3. Change in Quantity Demand versus Change in Demand
The movement along the demand curve measures the change in quantity demand
in relation to the change in price while change in demand is reflected through shift in
demand curve. The phrase ‘Change in quantity demand’ essentially implies variation in
demand referring to ‘extension, or ‘contraction’ of demand which are quite distinct from
the term ‘increase or decrease in demand.
A. Extension and Contraction of Demand
A movement along a demand curve takes place when there is a change in the
quantity demand due to change in the commodity’s own price. The extension of demand
refers to a situation when more of a commodity is bought with the fall in the price.
Similarly, when a lesser quantity is demanded with a rise in price, there is a contraction
of demand. In short, demand extends when the price falls and it contracts when the price
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rises. The term extension and contraction are technically used in stating the law of
demand. Figure 2.3 illustrates the extension and contraction of demand.
Fig.2.3: Extension and Contraction of Demand
In the figure 2.3 D1D1 is the demand curve. When the price is OP1, the quantity
demand is OQ1. With the fall in price to OP2 the quantity demand rises to OQ2. Thus,
with the fall in price there has been a downward movement from A to B along the same
demand curve D1D1. This is known as extension in demand. On the contrary, if we take B
as the original price-demand point, then a rise in the price from OP2 to OP1 leads to a fall
in the quantity demand from OQ2 to OQ1. The consumer moves upwards from point B to
A along the same demand curve D1D1. This is known as contraction in demand.
B. Increase and Decrease in Demand
These two terms are used to indicate change in demand. A change in demand,
thus, implies an increase or decrease in demand. An increase in demand signifies either
more will be demanded at a given price or same quantity will be demanded at higher
price. It really means that more is now demanded than before at each and every price.
Similarly decrease in demand indicates either that less will be demanded at a given price
or the same quantity will be demanded at the lower price. The terms increase and
decrease in demand are graphically expressed by the movement from one demand curve
to another in figure 2.3A and B respectively.
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Fig. 2.3: Increase in Demand (A) and Decrease in Demand (B)
In the case of increase in demand, the demand curve shifted to the right. In figure
2.3 (A) the shift of demand curve from DD to D1D1 shows an increase in demand. In this
case a movement from point ‘A’ to ‘B’ indicates that the price remains same at OP, but
more quantity (OQ2) is now demanded instead of OQ1. Here, increase in demand is Q1Q2
which due to the factor other than price. Similarly the shifting of demand curve towards
its left depicts a decrease in demand. In the figure 2.3 (B) the decrease in demand is
depicted by the shift of demand curve from D1D1 to D2D2. In this case the movement
from point ‘A’ to ‘B’ indicates that the price remains same at OP but quantity demanded
decreased by Q1Q2.The decrease in demand by Q1Q2 quantity is due to the factor other
than price.
2.3 Types of Demand
The demand behaviour of the buyer or consumer is different with different types
of goods. Demand could be classified in to following types from managerial point of
view.
a. Demand for Consumer’s Goods and Producer’s Goods.
b. Demand for Perishable Goods and Durable Goods
c. Derived Demand and Autonomous Demand
d. Joint Demand and Composite Demand
e. Industry Demand and Company Demand
f. Demand by Total Market and by Market Segment.
g. Short-run Demand and Company Demand.
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a) Demand for Consumers’ Goods and Producers’ Goods.
Producer goods are those, which are used for the production of other goods.
Examples for such goods are machines, tools, raw materials, locomotives etc.
Consumers’ goods can be defined as those, which are used for final consumption.
Examples of consumers’ goods can be food items, tooth paste, ready-made cloth etc.
these goods satisfies the consumers’ wants directly. The distinction between consumers’
and producers’ goods is somewhat arbitrary. Whether a particular commodity is producer
good or consumer good depend upon who buys and what for. For example, sugar in the
case of a confectioner is a producer good, whereas in case of a household it is a consumer
good. However the distinction is useful because, among other factor, demand for
consumer goods depends on consumers’ income whereas demand for producer good
depends on demand for the products of the industries using this product as an input.
b) Demand for Perishable Goods and Durable Goods
Perishable goods are those, which can be consumed only once, while durable
goods are those, which can be consumed more than once over a period of time. Sweets,
ice cream, fruits, vegetables, edible oil, petrol etc. are perishable goods. Car, refrigerator,
machines, building are durable goods. It is important to note that perishable goods are
themselves consumed whereas only the services of durable goods are consumed. This
distinction is useful because durable products present more complicated problems in
demand analysis than the products of durable nature. Sales of perishable are made largely
to meet current demand, which depends on current conditions. Sales of durables, on the
other hand, add to the stock of existing goods whose services are consumed over a period
of time. Thus they have two kinds of demand Viz. replacement of old products and
expansion of the total stock. Their demand fluctuates with business conditions.
c. Derived Demand and Autonomous Demand
The demand for a product is said to be derived demand if demand for such
product is tied to the purchase of some parent product. For example the demand for
cement is a derived demand because it is needed not for it’s own sake but for satisfying
the demand for buildings. The demand for all producers’ good is derived. Autonomous
demand, on the other hand, is not derived. In case of autonomous demand, demand for a
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product is independent of demand for other goods. Today, it is difficult to find the
products whose demand is wholly independent of demand for other goods. However, the
degree of this dependence varies widely from product to product. For example, the
demand for petrol is fully tied up with the demand for vehicles using the petrol, while the
demand for sugar is loosely tied up with demand for drinks. Thus the distinction between
derived and autonomous demand is more of a degree than of kind.
d) Joint Demand and Composite Demand
When two goods are demanded in conjunction with one another at the same time
to satisfy a single want, they are said to be joint or complimentary demand. Examples are
pens and inks, bread and butter, sugar and milk and so on. A commodity is said to be
composite demand if it is wanted for several different uses. Electricity is needed for
lighting, cooking, ironing, boiling the water, lifting water, T.V, radio and many other
uses.
e) Industry Demand and Company Demand
At the outset let us understand the concept of industry and company. An industry
is a group of companies or firms, which produce similar goods or services. A company is
a single firm producing a particular type of goods or services. Sugar industry in India
consists of all the companies of the country, which produce the sugar. Shamanur sugars is
a company or a firm which produces the sugar. Industry demand denotes the demand for
the products of a particular industry while company demand means the demand for the
products of a particular industry. For example, demand for steel produced by TISCO is a
company (TISCO) demand while demand for steel produced by all companies in India is
industry demand for steel in India.
f) Demand by Total Market and by Market Segment.
Total market demand refers to the total demand for a product where as market
segment demand refers to a part of it. Demand for certain products has to be studied not
only in its totality but also by breaking it into different segments. Viz. different regions,
different use for the product, different customers, different distribution channels and also
its different sub products. Each of these segments may differ significantly with respect to
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delivery price, profit margin, competition and seasonal pattern. When these differences
are considerable, demand analysis should focus on the individual market segments.
Knowledge of these segments’ demand helps a unit in manipulating its total demand.
g) Short-run Demand and Company Demand.
Short-run demand refers to demand with its immediate reaction to price changes,
income fluctuations etc. Long-run demand is that which will ultimately exist as result of
change in pricing, promotion or product improvement after enough time has been
allowed to let the market adjust itself to new situation. For example, if electricity rates are
reduced, in the short run existing users of electric appliances will make greater use of
these appliances but in the long run more and more people might induced to purchase
these appliances ultimately leading to still greater demand for electricity.
2.4 Determinants of Demand
Demand for a commodity depends on various factors. Factors influencing the
demand could be classified into two groups. Factors influencing the individual demand
and market demand.
A) Factors Influencing the Individual Demand
Factors influencing the individual demand are explained as follows:
Price of the product: Normally, a large quantity is demanded at lower price and
vis-à-vis.
Income level of the consumer: Purchasing power of an individual consumer
depends on his income level. Therefore, income level is an important
determinant of demand. Consumers with higher income level demand more and
more goods compared to the consumers with lower income level.
Price of the related goods: Demand for a particular commodity depends on the
price of its related goods such as substitute and complementary goods. For
example if the price of tea increases the demand for coffee is expected increase
because tea and coffee are substitutes for many consumers. Similarly with the
increase in the price of petrol the demand for vehicles is expected to decrease
because car and petrol are complementary goods.
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Taste, Habit and Preferences of the consumers: People with different taste
and habit have different preference for different goods. Demand for several
products like beverages, ice cream, chocolates and so on are depending on the
individual’s taste. Similarly demand for tea, coffee, gutka betel, cigarette,
tobacco is a matter of habits of the consumers. A strict vegetarian will have no
demand for meat at any price whereas a non-vegetarian who has liking for
chicken may demand it even at higher price.
Expectation: Consumer’s expectations about the future change in the prices of a
given commodity influence the demand for such commodity. When he expects
its price to rise in the future, he will buy less at the prevailing price. Similarly, if
he expects its price to fall in future, he will buy less at present.
Advertisement: Nowadays advertisement plays crucial role in altering the
preferences of the consumers. Demand for products like toothpaste, toilet soaps,
cosmetics etc. are greatly influenced by the advertisements.
B) Factors Influencing the Market Demand
Market demand is the sum total of various quantities demanded by all the
individuals at various prices. Therefore, factors influencing individual demand are also
influencing the market demand. In addition to the factors explained above (in section A)
following factors influence the market demand.
Distribution of income and Wealth in the country: Market demand for goods
and services is more in countries with equal distribution of income and wealth
compared to the countries with unequal distribution.
Growth of population and number of buyers in the market: Market demand
for the products depends on the number of buyers. Number of buyers in the
market, among other factors, mainly depends on the population size and its
growth. A large number of buyers will usually constitute a large demand vis-à-
vis. Therefore, growth of population over a period of time increases the demand
for goods and services in the market.
Age and sex structure of the population: Age structure of population
influences the demand for various goods and services in the market. In the
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country with bottom heavy age structure (relatively more children), relatively
more children, the market demand for toys, school bags, chocolates etc. will be
relatively more. Similarly sex structure also influences the demand for goods and
services in the market. If sex ratio is favorable to females then the demand for
goods and services required for females will be relatively more. For example
demand for goods like saries, bangals, lipsticks etc. is more in the countries with
the sex ration favourable to females.
Climatic conditions: Demand for certain products is determined by climatic
conditions. For example, in rainy season, there will be more demand for
umbrellas, rain coats et. Similarly demand for cool drinks, ice creams, fans etc.
are more in summer season.
2.5 Demand Function
A demand function states the functional relationship between the demand for a
commodity or services and the factors or variables affecting it. The demand function for
commodity X can be symbolically stated as follows:
Dx = f(Px) 2.1
Where,
Dx = Demand for X
Px = Price of x commodity
The function 2.1 demand for commodity X depends on the price of the commodity. It
does not consider the demand influencing factors other than the price. This is a single
variable model. Multiple variable models are presented in the following function (2.2).
Dx = f (Px, I, Pr, A, U) 2.2
Where
Dx = Demand for X
Px = Price of X
I = Income of the consumer
Pr =Price of the related goods
A =Advertisement or sales promotional activities
U =Error term
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The demand function 2.2 shows that the quantity demand of X influenced by the
price of commodity X, income of the consumers, price of its related goods and
advertisement or sales promotion activities. The demand for commodity X might be
influenced by the factors other than these factors also. The influence of the variables
other than those included in the model is represented by error term (U). It is a general
form of demand function because the independent variables included in the model (RHS)
are considered to be influencing the quantity demand of commodity X but it does not
reveal in what direction and to what extent they are influencing. The empirical demand
function shows the quantitative relationship between the demand for a particular
commodity and its determinants. Empirical demand function also reveals the direction of
relationship between the dependent variables (Quantity demand of a commodity) and
independent variables (Demand determinants) through the sign (i.e + or -).
2.6 Elasticity of Demand
Demand usually varies with variation in the price. The law of demand states that
with the fall in the price of commodity, the quantity demand increases and vis-à-vis. But
it does not states by how much the quantity demand increases as a result of certain fall in
the price of the commodity. Elasticity of demand is a useful tool to understand the extent
of change in quantity demand due to change in price or other demand influencing factors
like income, price of related goods and advertisement.
2.6.1 Meaning of Elasticity of Demand.
The term elasticity of demand, very often, used as a synonymous of price
elasticity of demand. This is a loose interpretation of the term. In the strict sense of the
term the concept of elasticity of demand refers to the responsiveness of the quantity
demand to the change in demand determinants. It can be depicted as
Percentage change in quantity demand Elasticity of Demand = Percentage change in demand determinant
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The demand determinants mainly include the price of the commodity, price of related
good, income of the consumer.
2.6.2 Types of Elasticity of Demand.
There are as many types of price elasticity of demand as there are demand
determinants. However, considering its major determinants economists broadly classified
the elasticity of demand into following types.
Price elasticity of demand
Income elasticity of demand
Cross elasticity of demand
2.6.3 Price Elasticity of Demand.
In the words of Prof. Lipsey “Price elasticity of demand may be defined as the
ratio of the percentage change in quantity demand to the percentage change in price.”
Price elasticity of demand may be written as
Percentage change in quantity demand Price Elasticity of Demand = Percentage change in Price
In the algebraic form it could be presented as Ep = [ΔQ/Q] / [ΔP/P]
Where Ep = Coefficient of Price Elasticity of Demand ΔQ = Change in demand Q = Initial demand ΔP = Change in Price
Ep is the coefficient of price elasticity of demand. The coefficient of price elasticity of
demand is always negative because price and quantity demand varies inversely with the
change in the price of the commodity. It is, however, customary to disregard the negative
sign. Using the above formula, the numerical coefficient of price elasticity of demand can
be measured for any given data. Obviously, depending on the magnitudes and
proportionate changes involved in data on demand and prices, one can obtain various
numerical values ranging from zero to infinity. Price elasticity of demand depending on
the value of coefficient could classify into different types.
2.6.3.1 Types of Price Elasticity of Demand.
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A. Perfectly Elastic Demand
In case of perfectly elastic
demand, a slight or infinitely
small rise in price of a
commodity, consumers stop
buying it. The numerical
coefficient of perfectly elastic
demand is infinity (Ep=α) The
demand curve, in this
case, will be a horizontal
straight line. In figure
2.4 DD demand curve is
horizontal to OX axis.
Fig 2.4: Perfectly Elastic Demand
B. Perfectly Inelastic Demand
Perfectly inelastic demand is one
for whatever the change in price;
there is absolutely no change in
demand. In this case, the quantity
demand shows no response to a
change in price. Thus, perfectly
elastic demand has zero coefficient
(Ep=0). In figure 2.5 DD demand
curve is a vertical line. In this case,
whatever may be the price level the
quantity demand remains same at
OD.
Fig 2.5: Perfectly Inelastic Demand
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C. Relatively Elastic Demand
If a reduction in price leads to more
than proportionate change in quantity
demand, the demand is said to be
relatively elastic. For example if 5
per cent decline in price leads to 10
per cent increase in quantity demand,
the demand is said to be relatively
elastic. In this case coefficient of
elasticity of demand is greater than 1
but it is not infinite. In figure 2.6
DD1 demand curve is relatively
flatter.
Fig 2.6: Relatively Elastic Demand
D. Relatively Inelastic Demand
If a decline in price leads to less than
proportionate increase in quantity
demand, the demand considered to be
relatively inelastic. For example if a 5
per cent decline in price leads to 3 per
cent increase in quantity demand then
demand considered to be relatively
inelastic. In this case the coefficient
of elasticity of demand lies between
zero and one. DD1 demand curve in
figure 2.7 is relatively steeper.
Fig 2.7: Relatively inelastic Demand
E. Unitary Elastic Demand
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Price elasticity of demand is unity when the
change in demand is exactly proportionate
to the change in price. For example if a 5
per cent increase in price leads to 5 per cent
decrease in quantity demand then demand
considered to be unitary elastic. In this case
the coefficient of elasticity of demand is
one. DD demand curve in figure 2.8 is a
rectangular hyperbola.
Fig 2.8: Unitary Elastic Demand
2.6.3.2 Factors Influencing Price Elasticity of Demand.
a) The availability of substitutes: The demand for a commodity is more elastic if
there are close substitutes for the commodity.
b) The nature of the need that the commodity satisfies: In general luxury goods
are price elastic, while necessities are price inelastic.
c) The time period: Demand is more elastic in the long run than in the short run.
d) The number of uses to which a commodity can be put: The more the possible
uses of a commodity the greater its price elasticity will be.
e) The proportion of income spends on the particular commodity: The demand
is inelastic if a very small proportion of income is spent on a particular
commodity.
2.6.4 Income Elasticity of Demand.
The income elasticity is defined as a ratio of percentage or proportionate change
in quantity demand to percentage or proportionate change in income. The coefficient of
income elasticity of demand could be measured by the following formula:
Percentage change in quantity demand Income Elasticity of Demand = Percentage change in Income
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In the algebraic form it could be presented as Ey = [ΔQ/Q] / [ΔY/Y]
Where
Ey = Coefficient of Income Elasticity of Demand ΔQ = Change in demand Q = Initial demand ΔY = Change in income Y = Initial income
The coefficient of income elasticity of demand will be positive for the normal goods.
Some economists have used income elasticity in order to classify the goods into luxuries
and necessities. A commodity is considered to be a luxury if its income elasticity is
greater than unity. A commodity is a necessity if its income elasticity is small(less than
unity).
2.6.4.1 Factors Influencing Income Elasticity of Demand.
a) The nature of the need that the commodity covers: The percentage of income
spent on food declines as income level increases while the percentage of income
spent on the luxuries increases with increase in income level.
b) The initial level of income of a country: TV is a luxury in a poor country while it
is a necessity in a country with high per capita income.
c) Time period: Time period influence the income elasticity of demand because
consumption pattern adjust with a time lag to changes in income.
2.6.4.2 Uses of Income Elasticity of Demand.
a) Business planning: In India, per capita income is low and it has been slowly
increasing. Since income elasticity of income for luxury goods is more, the
prospect for long run growth in sales for these goods is very bright. The firms can
plan out its business accordingly.
b) Marketing strategy: Income elasticity of demand is helpful in developing the
marketing strategy.
2.6.5 Cross Elasticity of Demand.
32
The cross elasticity of demand refers to the degree of responsiveness of demand
for a commodity to a given change in the price of some related commodity. The related
commodity may be substitute or complementary. The coefficient of cross elasticity of
demand could be measured by the following formula:
Percentage change in quantity demand of X Cross Elasticity of Demand = Percentage change in Price of Y
In the algebraic form it could be presented as Ey = [ΔQx/Qx/ [ΔPy/Py]
Where Ec = Coefficient of Cross Elasticity of Demand ΔQx = Change in Quantity Demand of x Qx = Initial Quantity demand of x ΔPy = Change in price of Y Py = Initial price of Y
The concept of cross elasticity of demand can be useful in determining competitive price
strategy and policy in the substitute goods or complementary goods such as coco cola or
Pepsi, tea or coffee. Coefficient of cross elasticity of demand here is taken, as a measure
of effect of a change in the price of coco cola on the demand for Pepsi. Similar is the case
with respect to tea or coffee.
2.7 Demand Forecasting
In the business production of goods or services is of no use if there is no demand for
goods or services produced by the business houses. Demand forecasting is an useful tool
in anticipating the future demand which enable the business house to take the appropriate
business decisions. In this section meaning, types, purpose and methods of demand
forecasting are discussed.
2.7.1 Meaning of Demand forecasting
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Demand forecasting means an estimation of the level of demand that might be
realized in future under given circumstances. It is not a speculative exercise into the
unknown. It is based on mathematical laws of probability. It can’t be hundred per cent
precise. But it gives a reasonable accuracy. Thus, demand forecasting involves
predicting future economic condition and assessing their effect on the operation of the
firm and its demand. The objective of demand forecasting is to predict the future demand.
2.7.2 Classification of Demand Forecasting
Demand forecasting can be classified into different types based on the different
criterion. Demand forecasting can be classified into short-run and long run demand
forecasting based on the time period. Similarly based on the role of the demand
forecasting firm demand forecast can be classified into active demand forecast and
passive demand forecast. Based on the level of demand forecasting it could be classified
into macro, industry and firm level demand forecasting.
a) Short-period and Long period demand forecast: Short-run forecasting, usually,
covers any period up to one year. Long period, on the other hand, will cover any
period more than one year. Normally it covers the period of 5, 10 or even 20
years. Short-run forecasting useful in taking decision concerning the day to day
working of the firm whereas long run forecasting facilitates major strategic
decisions.
b) Passive and active demand forecasting: Passive demand forecasting predicts the
future demand in the absence of any action by the firm. While active forecasting
estimate the future demand taking into consideration of the likely future action of
the firm. For example, Samsung electronic company takes no policy actions to
influence its future sales, what would be sales in the year 2010? Such forecasts
are passive demand forecasts. However, forecasted level of sales may not be
desirable level and so the company may be initiated some sales promotion actions
with a view to increase its future sales. The predicted sales if such planned sales
promotion activities are undertaken denote the active forecast.
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c) Macro, Industry and Firm level demand forecasting; Macro-economic forecasting
refers to the forecasting of business conditions over the entire economy.
Aggregate demand for goods and services in the entire economy can be
forecasted. Such forecast is called as macro-economic forecasting. Forecasting the
demand for the products of a particular industry is the industry level demand
forecasting. Generally, it is undertaken by the trade association and the results are
made available to the member firms. A firm can forecast the demand for its
products at its own level. It is called firm level demand forecasting. It is most
important from the point of view of managerial decisions.
2.7.3 Purpose of Demand Forecasting:
The purpose of demand forecasting could be classified into purpose of short-term
and long-term demand forecasting. They are separately explained hereunder:
A Purpose of Short-Term Demand Forecasting:
o It is useful in appropriate production Scheduling: To avoid the problem of
over production and the problem of short supply appropriate production
scheduling is essential for which demand forecasting is useful.
o It helps in purchase planning to reduce the cost of operation: Demand
forecasting enables the firms to understand the right quantity of resources
required to the firm at different points of time, which in turn, reduces the cost
of operation.
o It is useful in adopting suitable advertising and promotional programme. A
short-term demand forecasting is useful in evolving suitable sales policy in
view of the seasonal variation of demand.
o It is useful in forecasting short-term financial requirements. A firm’s need for
cash depends on its production level. Without sales forecasting a rational
financial planning is not possible.
o It is useful in determining appropriate price policy: Short-term sales
forecasting will help the firm in determination of a suitable price policy to
35
clear off the stocks during the off-season, and to take advantage in the peak
season.
B Purpose of Long-Term Demand Forecasting:
o Long-term demand forecasting is useful for planning of a new unit or
expansion of an existing unit.
o It is useful in planning long term financial requirements
o It is useful in planning the manpower requirements. Manpower development
requires long time. Manpower development process has to start well in
advance to meet the future manpower requirements.
2.7.4 Methods of Demand Forecasting
Demand forecasting mainly involves two important methodological aspects viz.
data collection and analytical methods. Demand for any goods or services could be
forecasted based on the available information or data on the related parameter. Demand
forecasting may be based on two types of data sources viz primary sources and secondary
sources. Primary data or information is original in nature which is collected for the first
time for the purpose of analysis. Secondary data, on the other hand, are those which are
obtained from someone else records. These data are already in existence in the recorded
or published form. In case of primary data, demand forecaster has to collect the data
through some sort of survey method. The collected data has to process through some
statistical technique. Method of demand forecasting, therefore, has been discussed under
two headings viz. 1 Survey Method and 2. Econometric Method
2.7.4.1. Survey Method.
In the demand forecasting survey plays vital role. The data required for the demand
forecasting could be collected through the survey method. For the purpose of demand
forecasting survey method could be classified into following types (Chart 2.1):
i) Experts Opinion Survey Method: In this method the future demand for a particular
commodity is estimated based on the opinions of experts in the marketing of that
particular commodity. Since salesmen are in close contact with customers in their
36
respective areas, they can forecast consumer behavior in the market in the future. Hence,
under this method salesmen are to estimate the expected sales in their respective area.
These estimates of individual salesmen are to be consolidated in order to obtain the total
estimated sales for the future.
Chart 2.1: Types of Survey Method of Demand Forecasting
Survey Method
The top executives of the firm are to further examine the total estimated sales in
the light of the factors like proposed change in the selling price, packaging design,
advertisement programme, change in macro variable like purchasing power of the people
etc. Through these processes a firm could come out with its final demand forecast. This
method is also known as the ‘collective opinion method’ because it takes the advantage
of the collective wisdom of the salesmen’s, corporate heads, dealers etc. This method is
cheaper and easy to handle. It is less time consuming also. The main limitation of this
method is that it tends to substitute opinion for analysis of the situation. It is purely
subjective and different experts may have significantly different forecasts.
37
Survey Meyhod
Experts’ Opinion Survey Consumers Interview
Census Method Sample Survey End Use Method
ii) Consumers Survey Method: Consumers, the potential future buyers are focal point for
the demand forecasting. Under this method, consumers are directly asked about their
future plan of purchase. This may be done in any of the following ways:
a) Complete enumeration method
b) Sample survey method
c) End use method
a) Complete Enumeration Method: Under this method forecaster has to collect
information from all consumers of the commodity for which he wishes to forecast the
demand. He asks every consumer the quantity of that commodity he would like to buy in
the forecasting period. Once this information is collected, demand could be forecasted by
simply adding the probable demand of all consumers. For example there are ‘n’ number
of consumers and their probable demand for commodity X in the forecast period are X 1,
X2, X3…Xn then the demand forecast would be
X = X1 +X2 + X3 +…Xn
In this method the forecasting agency could not introduce any bias of its own. Just it has
to collect the information and tabulate them. Report has to be prepared accordingly. But it
is an expensive and time-consuming method for the products having large number of
consumers.
b) Sample Survey Method: In sample survey method forecaster aimed to ascertain the
characteristics of parameter based on the characteristics of statistic. For example, ABC
company intended to forecast demand for its X commodity. Suppose ABC firm has
about one lakh consumers. Expected aggregate quantity demand of these one-lakh
consumers in the forecasting period (say in the year 2010) is parameter of this demand
forecasting. Demand forecaster can draw conclusion about this parameter by two
different methods. 1) Complete enumeration method and 2) Sample survey method.
In complete enumeration method forecaster collect information from all the one-
lakh consumers about their expected quantity demand for forecasting period and forecast
the demand based on this information (the details of this method discussed in the earlier
section). In case of sample survey method forecaster need not collect information from all
38
the one-lakh consumers. He has to choose some sample respondents out of one-lakh
consumers using appropriate sampling method and sample size. He may adopt simple
random sampling method or stratified random sampling method or cluster sampling
method or even snowball sampling method according to the nature of the population
distribution. Forecaster may choose 100 or 500 sample respondents or 1000 or more
sample respondents based on the available time, budget, expected level of accuracy of the
result etc. For this example let us assume that the forecaster has selected 500 respondents
using the simple random sampling method. After collecting information from the sample
respondents he can calculate the expected average demand of these selected respondents
for the forecasting period. The value calculated for the sample is known as the sample
statistics.
åXX1+X2+……….X500 = ------ = X
500Here, X is the sample statistics because it is estimated for the sample respondents. In this
example X .N = Aggregate demand for the forecasting period. In this example N refers to
the population size i.e. one lakh. Thus conclusion about the aggregate demand by the
one-lakh consumers is estimated by using the data collected from the 500 sample
respondents.
This method of demand forecasting is less expensive and requires less time when
compared to complete enumeration method. If sample is properly chosen the sample
survey method will yield good results. However it is not so simple to choose the
representative sample. If sample is not good representative of the population concerned
then the results will mislead the producers.
C) End use Method of Demand Forecasting: This method of demand forecasting is
suitable if the producer/firm desire to obtain use-wise or sector wise demand forecasts. In
this method of demand forecasting, the demand for a particular commodity is estimated
through a survey of its users of different uses. For example a commodity may be used
for:
i. Final consumption
ii. Production of some other commodity
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iii. Export
In this method demand forecaster is to obtain separate demand forecast for these different
uses. For example a steel firm wants to forecast demand for steel in the year 2010. It can
be obtained as
Sd2010 = Sc2010 + Se2010 + asi.(Xi)2010
Where
Sd2010 = Total demand for the steel in the year 2010
Sc2010 = Consumption demand for steel in the year 2010
Se2010 = Export demand for steel in the year 2010
asi. = Steel requirement of ith industry per unit of its output
(Xi)2010 = Output of ith industry using steel as an input
Consumption demand and export demand could be directly estimated by using the
appropriate method. Demand for intermediate use could be forecasted through the survey
of its user industries regarding their production plan and input-output coefficients. The
principle advantage of this method is that it provides use-wise demand forecast. If the
number of end users of a product is limited it will de convenient to use this method. The
major weakness of this method is that the individual industry will have to relay on some
other method to estimate the final demand of its products for final consumption and
export.
2.7.4.2 Econometric Method
The term Econometrics means, literally, Economic measurement. Econometric
methods integrate statistics, mathematics and economic theory in order to measure
relationship among economic variables. Econometric models provide insights into the
relationship between the variables. These insights can be very useful to the managers in
evaluating the probable effect of alternative decisions. For example, an econometric
study that estimate the impact of advertising on the demand could be used to advertising
strategies. The important steps involved in the formulation of econometric models are: 1.
Development of a theoretical model, 2 Data collection, 3 Choice of functional form, and
4 Estimation and interpretation of results. Econometric method could be further classified
into:
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i) Regression method
ii) Trend method
iii) Leading indicator method
i). Regression Method: Regression is a statistical devise with the help of which it is
possible to estimate the unknown value of one variable from the known value of another
variable. The variables which is/are used to predict the value of other variable is/are
called independent/explanatory variable/variables. The variable we tried to predict is
called dependent variable. Estimated regression equation reveals the cause and effect
relationship between the dependent and independent variables. It shows the extent to
which the value of dependent variable changes with the change in the value/s of
independent variable/s. In economic theory it is well-established fact that the quantity
demand of a commodity depends on various factors. In simple algebraic form it could be
shown as:
Dx = f (Px, I, Ps, Pc, A, U) 2.3
Where
Dx = Demand for X
Px = Price of X
I = Income of the consumer
Ps =Price of the substitute goods
Pc =Price of the complimentary goods
A =Advertisement or sales promotional activities
U =Error term/influence of other unexplainable/uncontrollable variables
Equation 2.3 reveals that the quantity demand of commodity depends on its own price,
income level of the consumers, price of its substitutes, price of complements, expenditure
on advertising X commodity, and uncontrollable or unexplainable variables. In this
equation U indicates the random error or the influence of other unexplainable or
uncontrollable variables. It is a general form of demand function because the independent
variables included in the model (RHS) are considered to be influencing the quantity
demand of commodity X but it does not reveal in what direction and to what extent they
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are influencing. The above general form of function could be presented in any of the
following specific form of functions.
Dx = a - b1Px + b2I + b3Ps - b4Pc +b5A + U 2.4
Or
Dx = a - Px b1 + I b2+ Ps b3
- Pc b4 +A b5 + U 2.5
The equation number 2.4 and 2.5 are the linear and power function forms respectively for
the variables given in the equation number 2.3. They are nothing but different functional
forms of regression equations. In 2.4 and 2.5 equations Dx, Px, I, Ps, Pc, A and U refer to
the same meaning as in the equation 2.3. In the equation 2.4 b i’s are the coefficients of
the respective variables and ‘a’ is the value of intercept.
The estimated coefficient values show the extent to which quantity demand
changes with the change in the values of the respective variables by one unit. In this
equation some coefficients are having the + sign while others having the – sign. The
coefficient of the variables which are having the + sign are influencing the quantity
demand positively while the coefficient of the variables which are having the - sign are
influencing the quantity demand negatively. In the equation 2.5 all the symbols and
letters are used to indicate the same thing as in the equation 2.4. But the only difference is
that the estimated coefficient values show the extent to which quantity demand changes
with the change in the values of the respective variables by one percent.
In the regression equations estimated coefficients are of vital importance. They
show the extent of responsiveness of quantity demand to the change in the value of the
variables. In order to understand the regression method of demand forecasting let us take
the following numerical example. Table 2.3 provides the data on electric power
consumption (in billion K W)(Y) and GNP (in million Rupees)(X) for the period 1995 to
2004.
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Table 2.3. Electric Power Consumption and GNP Year Electric consumption (Y)
In this equation ln2.151 is the value of the intercept. 0.573 is the regression
coefficient of X (GNP) variable. It shows that with the increase in the GNP by one
percent the consumption or demand for electricity increases by the 0.573 per cent.
For this example the same results could be obtained by the most widely used soft wear
Microsoft Excel. The summary output of the Microsoft excel is given in the table 2.7.
Table 2.7:SUMMARY OUTPUT OBTAINED BY MICROSOFT EXCELRegression Statistics
Multiple R 0.9816R Square 0.9635Adjusted R Square 0.9590Standard Error 0.0334Observations 10ANOVA
df SS MS FRegression 1 0.2362 0.2362 211.3931Residual 8 0.0089 0.0011Total 9 0.2451
Coefficients Standard Error t Stat P-valueIntercept (lna) 2.1518 0.2851 7.5465 0.0000663Coefficient of GNP (b) 0.5728 0.0394 14.5394 0.0000005
In the above example we consider only one independent variable model. In
practice, quantity demand of any commodity will not be influenced by only one variable.
It may be influenced by several variables. In the regression model we could use two or
more than two independent variables. If we use two or more independent variables in the
regression models such regression model is termed as multiple regression model. In case
of the multiple regression manual estimation of the coefficients is tedious job. Nowadays
various computer softwares are available to estimate the coefficients in case of multiple
regression models. The above example has been extended to two independent variable
model by incorporating one more independent variable i.e. price of the electricity. Table
2.8 provides the data on electric power consumption (in billion K W)(Y) and GNP (in
million Rupees)(X1) and price of the electricity (in Rs. Per unit) (X2) for the period 1995
to 2004. For this numerical illustration income elasticity and price elasticity of demand
for electricity could be estimated through the following form of equation.
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Y = a X1 b1 X2 b2
2.10
In this equation a represent the intercept value, b1 and b2 shows the regression coefficients
of income and price on electric consumption, which are same as income and price
elasticity of demand for electricity. The value of these constants has been estimated by
using the Microsoft excel. The summary of output is given in table 2.9.
Table 2.8: Consumption, GNP and Price of Electric Power.Year Electric
consumption (Y)(In billion K W)
G N P (X1)(In Million Rs.)
Price of Electricity (X2)
(Rs./Unit)
1995 407 944 2.09
1996 447 992 2.10
1997 479 1077 2.19
1998 511 1185 2.29
1999 554 1326 2.38
2000 555 1434 2.83
2001 586 1594 3.21
2002 613 1718 3.45
2003 652 1918 3.78
2004 679 2163 4.03
Table 2.9: SUMMARY OUTPUT OBTAINED BY MICROSOFT EXCELRegression Statistics
Multiple R 0.9924R Square 0.9849Adjusted R Square 0.9806Standard Error 0.0230Observations 10ANOVA
Df SS MS FRegression 2 0.2414 0.1207 228.6488Residual 7 0.0037 0.0005Total 9 0.2451
Coefficients Standard Error t Stat P-valueIntercept -0.496 0.8628 -0.5748 0.5834Coefficient of G N P (X1) 1.008 0.1408 7.1603 0.0002Coefficient of Price of Electricity (X2) -0.495 0.1572 -3.1512 0.0161
Y = -0.496 X1 1.008 X2 –0.495
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In the summery of the regression output the income elasticity of demand for
electricity was worked out to be 1.008, which means for every one per cent increase in
GNP there will be 1.008 per cent increase in the demand for electric power. Similarly
price elasticity of demand for electricity was worked out to be -0.495 which means for
every one percent increase in the price of electric power there will be fall in the electric
power consumption or demand by 0.495 per cent.
The principle advantage of this method is that the variation in demand is
explained through the variation in its casual variables. Demand has varied by a certain
amount or percentage because its determining variables have varied by certain amount or
percentage. This is indicated by the regression equation itself. Any social scientist
possessing sufficient knowledge of economic theory and econometric methods can use
this method for forecasting purpose. The major limitation of this method is that it requires
the use of some other forecasting method to estimate the value of the explanatory
variables in the prediction period. The extent of reliability of the results depends on the
extent of the reliability of the estimated future values of explanatory variables.
ii. Leading Indicator Method: The previous section dealt with the relationship between
the two or more coincident series, which enables us to forecast the demand. Coincident
variables are those the values of which vary along with some other variables. For
example if X and Y are close substitutes, increase in the price of X leads to increase in
the demand for Y on the day itself. There are some variables the values of which move up
or down ahead of some other variable and such variables are called leading variables or
series. Agricultural income (harvest) in the year influences the demand for agricultural
inputs in the subsequent year. Here agricultural income is a leading indicator because it
indicates the fact that there will be more demand for agricultural input in the subsequent
year. Demand for agricultural input, in this example, is lagging variable because its value
moves up or down behind the value of agricultural income. This relationship could be
expressed in the following way:
Yt = a + bXt-1 2.11Where,Yt = Quantity demand of forecasting variable in time t
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Xt-1 = Value of explanatory variable in time t-1
a & b represent the intercept and coefficient of independent variables
respectively
The value of intercept and coefficient value could be estimated by using the
method discussed in the previous section. But only difference is that the value of
explanatory variable pertains to time period t-1. If the calculated value of ‘b’ is 0.75 it
implies that every one-unit increase in the value of independent variable in this year leads
to increase in the quantity demand by 0.75 unit. The main advantage of this method is
that present period value of explanatory variable could be used to predict the demand for
(lagging variable) commodity in the next period, may be next month or year or decade.
The major limitation of this method is that it is not possible to find leading indicator for
variable under forecast.
iii. Trend Method: Time series analysis or the trend method is one of the most frequently
used methods of demand forecasting. Time series data refers to the values of a variable
arranged chronologically by days, weeks, months or years. Time series analysis attempts
to forecast future values of time series by examining the past observation of the data only.
This method is mainly based on the assumption that the time series will continue to move
as in the past. For this reason this method is also called naïve forecasting. Time series
data can be presented either in the tabular form or graphical form. The following table,
for example, shows the sales of the television sets of X company (in thousand units).
Table2.10 Sales of T V sets Pertains to X CompanyYear 1998 1999 2000 2001 2002 2003 2004
Sales of T. V. (in thousand) 80 90 92 83 94 99 92
The data shown in the table 2.10 presented through the graph 2.9. It is evident from the
graph that the sale of the T V sets of the above firm has been fluctuating over the years.
In spite of such fluctuation there is a general increasing trend . Time series fluctuation
can be explained through the different components.
Components of time series
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Seasonal Variation: Changes that have taken place during a period of one
year as a result of changes in season i.e. change in the climate, weather
condition, festival etc.
Cyclical Variation: It refers to recurrent up and down movements of
business activities around some sort of statistical trend level or normal
business conditions.
Irregular variation: Changes that have taken place as a result of such
forces that could not be predicted like floods, earthquake etc. they are also
called erratic variations
Secular trend: Changes that have occurred as a result of general tendency
of data to increase or decrease is known as secular trend.
Changes that have taken place during a period of one year as a result of changes in season
i.e. change in the climate, weather condition, festival etc.
The most important aspect of time series analysis is the projection of trend of the
time series. A trend line can be fitted through series either visually i.e. freehand method
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based on the personal judgment or by means of statistical technique. The most popular
statistical method that is used in the time series analysis is least square method. The
straight line could be represented by the following equation
Yt = a + bt 2.12
Here, Yt and t are the variables represent the value of the time series to be forecasted
for period t, and the time period respectively. , a is the intercept and b is the coefficient of
the trend equation which shows the absolute amount of growth per period. Trend
equation could be estimated as follows for the example given in the table 2.10.
The trend equation of the form 2.12 could be estimated to the example given in
the table 2.10 by solving the following normal equation.
åYt = Na + b åt 2.13
å tYt = a åt + b åt2
For fitting the straight-line trend by the least square method we must specify the year,
which is taken as the origin. We can measure t by taking either first year or the mid point
in the time period as the origin. Here the trend equation has been estimated by taking the
first year as the origin.
Table 2.11 Sum of Variables, their Products and Squares
The firm will be earning Economic Profits only if it is making revenue in excess of the
total of accounting and implicit costs. Thus, when the firm is in no profit and no loss
position, it means that the firm is making revenue equal to the total of accounting and
implicit costs and no more. Therefore;
Economic Profit = Total Revenue – Economic Costs.
Economic profits are relevant from the managerial point of view, as they truly reflect the
profitability of a business concern. A business firm may be making profits in the
accounting sense; but it may be actually incurring losses in the economic sense. Such a
firm will not survive in the long run. Hence, economic profits are more useful than the
accounting profits, for managerial purposes.
Functional Role of Business Profits: According to Prof. Peter Ducker, business profits
play a functional role in three different ways.
They indicate the effectiveness of business efforts: The success or effectiveness of
the business is indicated through the profit it earns. Higher the profit of concern,
we generally consider that the business is more successful. Even though it may be
argued that profit is not a perfect measure of business efficiency, it is an easy and
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quick basis on which business performance can be compare among the various
firms.
They provide the premium to cover costs of staying in business: Profit is a source
of funds from which a business firm will be able to defray certain expenses like
replacement, obsolescence, marketing, etc. Business firms must generate profits
sufficient to provide for these costs.
They ensure supply of future capital: Profits are the principal source for a firm’s
future capital requirements for innovation and expansion. Business concerns help
themselves by generating profits in meeting part of their capital requirement apart
from raising funds through extraneous sources.
5.2 Theories of Profit
There are several theories of profit propounded by economists. None of these deal
with all aspects of profit. Each theory focuses on the different aspects of profit. We shall
study some of the theories of profit.
5.2.1. Hawley’s Risk Theory
An American economist Hawley advocated this theory. According to him, profits
arise because the entrepreneur undertakes the risk of the business and he has to be
rewarded for that. As per this theory, higher the risk, greater is the possibility of profit.
But this theory is criticized on the following grounds:
There is no relationship between risk and profit.
Insurable risks are no risk at all. Only uninsurable risks are real risks.
Profit is the result of not only risk bearing, but also due to other factors.
5.2.2 Knight’s Uncertainty-bearing Theory
This theory, advocated by Prof. Knight, agrees with Hawley’s theory that profit is
a reward for risk-taking. However, the term risk is clarified and there are two types of
risks: a) Foreseeable risks; and b) Unforeseeably risks. The latter risk is called
uncertainty bearing. If risk can be insured against, it is not risk at all. For instance, fire,
flood, theft, etc., are risks in business, which can be insured, and the loss arising out of
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these will be made good by the insurance company. The premium paid for insurance is
included in the cost of production. Insurable risk, thus, does not give rise to profit. So,
according to Prof. Knight, profit is due to non-insurable risk or unforeseen risk. Some of
the non-insurable risks:
Competitive risk;
Technical risk;
Risk of government’s intervention; and
Risk arising out of business cycle.
Since, these risks cannot be foreseen and measured, they become non-insurable
and uncertainties have to be borne by the entrepreneur. According to this theory, there is
a direct relationship between profit and uncertainty bearing.
Knight’s theory is criticized on the following grounds:
If profits are due to uncertainty bearing, what explanation could be given in cases
where profits do not accrue in spite of uncertainty bearing.
Uncertainty bearing is one of the determinants of profit, and that is not the only
determinant.
The theory emphasizes too much about uncertainty-bearing as to elevate it into a
separate factor of production
This theory does not separate the two functions in modern business, namely
ownership and control
The theory does not explain monopoly profit. How do profits arise, when there is
no question of uncertainty bearing in monopoly?
It is not possible to measure uncertainty in quantitative terms to ascribe profit.
5.2.3. Dynamic Theory of Profit
This theory advocated by J.B. Clark assumes that profits arise as a ‘Dynamic
Surplus’. According to this theory, in a static state, there is no change in demand and
supply and profits do not arise. This is because; under static conditions payments made to
the factors of production on the basis of marginal productivity exhaust the total output. In
this condition, in equilibrium, price of each commodity exactly equals its money cost of
production, including normal profits and there is no surplus of any kind. Profits result
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only when selling prices of goods exceed their cost of production. Therefore, in a static
state, there are no possibilities of getting profit and it arises only in dynamic condition. It
is a dynamic surplus. Profits arise due to disequilibria caused by the changes in demand
and supply conditions. Now, the question arises what Clark mentions about five changes,
which may occur in a dynamic economy to give rise to profits.
Changes in the quantity and quality of human wants
Changes in the methods and techniques of production
Changes in the amount of capital
Changes in the form of business organization
Changes in population
Such changes give some entrepreneurs advantages over other entrepreneurs and
they manage to earn surplus. This theory is criticized as follows:
This theory does not fully appreciate the nature of entrepreneurial functions. If
there are no profits in a static state, it means there is no entrepreneur. But without
an entrepreneur, it is not possible to imagine the coordination of factors of
production. Hence, Marshall solved this difficulty by his concept of normal
profit, which is earned in a static state also.
Mere change in an economy would not give rise to profits, if these changes were
predictable.
This theory has created an artificial distinction between ‘Profit’ and ‘Wages of
Management’.
5.2.4. Schumpeter’s Innovation Theory
This theory propounded by Schumpeter is more or less similar to Clark’s theory;
but this theory gives importance to innovations in the productive process. According to
this theory, profit is the reward for innovation. Innovations refer to all these changes in
the production process with an objective of reducing the cost of the commodity, so as to
create a gap between the existing price of the commodity and its new cost. Schumpeter’s
innovation may take any shape. It may be the result of introduction of a new technique or
a new plant, a change in the internal structure or organizational set up of the firm. It may
be a change in the quality of the raw material, a new form of energy, better method of
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salesmanship, etc. “Innovation is much more than invention. Invention is not innovation,
if it is stillborn, that is, if it is not used. An invention becomes an innovation only when it
is applied to industrial progress.” Innovation is brought about mainly for reducing the
cost of production and it is a cost reducing agent. Innovations are not possible by all
entrepreneurs. Only exceptional entrepreneurs with extraordinary abilities can innovate
and create opportunities through their imagination and bold action. Profit is the reward
for this strategic role. Further, according to Schumpeter, profits are of temporary nature.
The pioneer, who innovates, gets abnormal profits for a short period. Soon other
entrepreneurs swarm in clusters and compete for profit in the same manner. So, the
pioneer will make another innovation. Thus profit will appear and disappear and again
reappear. Profits are caused by innovation and disappear by imitation. The theory is
criticized on the following grounds:
Innovation is only one of the many functions of the entrepreneur and not the only
function.
It does not recognize the risk-taking functions of the entrepreneur. Now
innovations bear the element of uncertainty and risks.
Monopoly profits are permanent in nature while Schumpeter attributes the quality
of temporaries to profits.
5.2.5. Marginal Productivity Theory of Profit
The theory of marginal productivity is also applied in the case of profit.
According to Prof. Chapman, profits are equal to the marginal worth of the entrepreneur
and are determined by the marginal productivity of the entrepreneur. When the marginal
productivity is high, profits will also be high. But, the fundamental difficulty in this
theory is in measuring increasing or decreasing the units of factors can assess the
marginal productivity. In entrepreneurial function, it is not possible, as a firm will have
only one entrepreneur. To assume that all entrepreneurs are alike is highly unrealistic.
Thus theories of profits have become highly controversial and least satisfactory.
Managerial economics, though it makes use of the assumptions of profit
maximization, makes little direct use of the theories of profits. There is no single theory
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giving satisfactory explanation regarding profit. According to Briggs and Jordan, “It is
difficult to frame a simple theory of profits which would include the small independent
trader, the large employer, the small holder, and the shareholder, of a Joint-Stock
Company, whilst excluding responsible managers.” However, though none of these
theories is a correct explanation of profits, they are in sense complementary theories. It is
possible that monopoly, uncertainty and innovations are factors of vital importance, as
they affect profit-earning capacity of the firm. Hence, knowledge of these theories helps
businessmen in formulation of their profit policies.
5.3. Measurement of Profit
The measurement of the amount of profit earned by a business firm during a given
period, is not so simple as it may appear. Even in the accounting sense, measurement of
profit is not an easy task. Several practical difficulties are involved here. Some of them
arise out of conceptual differences with reference to costs, income, valuation of assets;
some differences arise due to the definition of profits by accountants and economists and
also due to financial accounting conventions, and legal requirements. In particular, the
problem arises in the question ‘what is included in the costs to be subtracted from
revenues to obtain profits, remains the crux of the problem’. There is wide variety of
generally accepted accounting principles, which provide for different methods of
treatment for certain items of revenuer of expenditure. The following methods are
generally considered while measuring profits; they are:
Depreciation Valuation of Stock Treatment of deferred expenses Capital gains and losses
5.3.1. Depreciation
We know that in every business, equipment, machines and building are used and
they wear out over a period due to frequent use. In course of time, these assets become
useless from the point of view of business and they have only scrap value. The use-value
of the assets of the firm goes on diminishing due to wear and tear. In due course their
value from the viewpoint of business declines. Therefore, to measure true income of the
business, accountants make periodic charges to income to recover the cost of equipment
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before its usefulness is exhausted. This charge is known as depreciation which represents
the decrease in the value of the assets due to use during a particular period, say a year.
This provision for depreciation charges will not be uniform in all firms. It varies in
importance from company to company. In the case of heavy industries like iron and steel,
railways, transport, etc., very heavy depreciation charges are provided. In the case of
firms like insurance companies, banks, financial institutions, wholesale business and
retail business, etc., the depreciation charges will be relatively lower.
Methods of measuring depreciation: There are a number of methods of measuring
depreciation for the purpose of reporting business profits to the shareholders and taxable
profit to the income-tax authorities. Depreciation is an important internal source of funds
and hence the method of depreciation becomes very significant as a tool of capital
formation. There are three commonly accepted methods of depreciation; they are:
Straight Line Method
Declining Balance Method
Sum of the years digits method
We shall discuss these methods of measuring depreciation in a greater detail.
5.3.1.1. Straight Line Method:
According to this method, an asset is supposed to wear out evenly during its
normal life. Hence depreciation is provided on a uniform basis regardless of the fact that
the asset depreciates more rapidly at some stages. This is calculated by using this
formula:
Initial cost of the assetDepreciation =
Estimated life span of the asset in years
The amount of annual depreciation is obtained by dividing the initial cost of the
asset by the estimated life in years, assuming that there is no scrap value. If the asset has
an estimated scrap value its amount will have to be deducted from the initial cost before
dividing it by the estimated life in years.
Illustration: suppose that an asset has an original value of Rs.10000 with a scrap value of Rs.1000 and its life span is estimated to be 10yrs. The annual depreciation charge on the asset will be:
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Rs.10, 000 – Rs.1000 = Rs.900 10
Under the working hours method, the life span of the asset is expressed in terms of
working hours, rather than in years. In those cases, depreciation is calculated by dividing
the initial cost less scrap value by the number of working hours. Suppose that an asset has
a working life of 10000 hours and its original cost is Rs.22000 and its scrap value is Rs
2000. The depreciation per working hour will be calculated as follows:
Rs. 22000 – Rs. 2000
= Rs. 2 Per working hour1000
The straight-line method is very simple in adoption. When there are no possibilities of
premature retirement of assets due to accidents, obsolescence or inadequate capacity.
This method does not take into account the increasing cost of repairs in the later years of
the life of the asset and as a result, the total cost of operation is likely to be
disproportionate in the later years.
5.3.1.2. Declining Balance Method
Under this method, depreciation is provided on a uniform rate on the written
down value of the asset at the beginning of the year. If the cost of the asset is Rs.5000
and the rate of depreciation is 10%, the depreciation for the first year would be Rs.500. in
this case the written-down value of the asset for the next year would be Rs5000- Rs.500 =
4500 and the depreciation for the second year would be calculated at 10% for Rs.4500
which would be Rs.4500 – Rs.450 = 4050. During the third year the depreciation would
be 10% of Rs.4050, i.e., Rs.405. Thus, the depreciation amount will show a declining
trend; Rs.500 in the first year; Rs.450 in the second year; and Rs.405 in the third year.
Under this method, the written down value however small, will never be zero. Hence, the
asset is assumed to have some scrap value. The formula for determining the fixed rate of
depreciation under ‘Declining Balance Method’ is as follows:
D =100 {1-n√s/c}
Where,
D = % of depreciation
s = Scrap or residual value of the asset
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c = Initial cost of the asset
n = Estimated life of the asset in the years.
The method of computing the fixed rate of depreciation as described above is
rather complicated. A similar and more widely used method is to use a uniform %, which
is double the reciprocal of the estimated life:
Uniform rate or d = 2 (1/n)
The basic idea behind this method is to provide for a more or less uniform total cost of
operation of the asset over different years of its life. On the other hand, under this
method, depreciation is higher in earlier part of the asset’s life, but it declines
progressively in the later years. The combined effect is that the total charge in the profit
and loss account so far as the asset is concerned, is equated over different years.
5.3.1.3. The Sum of the Year’s Digits Method:
The basic idea of this method is similar to that of the Declining Balance Method,
i.e., to provide for a uniform total cost of operation of the asset. The amount of
depreciation in the beginning of the life of the asset is higher and it progressively declines
with the passage of time. This method differs from the declining balance method in that
the base or book value remains constant while the annual rate of depreciation changes.
The variable rate of depreciation is calculated as follows:
Each digit of the years of the useful life of the asset is added up and the resulting
figure is the denominator of the fraction to find out the depreciation rate.
The numerator of the fraction for each year is the expected life of the asset in that
particular year and this declines by one each year. Thus the depreciation rate is
composed of a varying numerator and an unvarying denominator. And this rate is
applied each year to the asset’s original cost.
Illustration: The sum of the Year’s digit method can be explained with the following
illustration: Suppose the original cost of the asset is Rs.12000 and its scrap value is
Rs.2000 and its expected life is 4 years. In the beginning, the asset has an expected life of
4 years; one year later it has an expected life of 3 years and so on. Thus the expected life
periods of the asset are 4,3,2 and 1 years. The sum of these expected life periods is 10,
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which will be the common denominator of the annual rates. The numerators are
respectively 4,3,2 and 1. Thus the annual rates are 4/10, 3/10, 2/10 and 1/10 respectively.
The original value of the asset is Rs. 12000 and the scrap value is assumed to be Rs.2000;
the annual depreciation charge should be made for Rs. 10000. In the first year, the rate of
depreciation is 4/10 which is 40% and the depreciation amount is Rs.4000. in the second
year the rate of depreciation is 3/10 or 30% or Rs.3000. in the third year, the rate of
depreciation is 2/10 or 20% or Rs2000 and in the fourth year, the rate of depreciation is
1/10 or 10% which is equal to Rs.1000. These data can be tabulated as shown in the table.
TABLE –5.1 The Annual Depreciation
Age of the asset in years
Rate of depreciation
Annual depreciation
Accumulated depreciation
Book value of the asset
1234
4/10 or 40%3/10 or 30%2/10 or 20%1/10 or 10%
Rs4000300020001000
Rs.40007000900010000
Rs.8000500030002000
The Declining Balance Method and the Sum of the Year’s Digit method are useful, as
well as equitable in calculating depreciation, where the cost of repairs increase as
depreciation charges decrease.
Depreciation and Profit: We studied three methods of calculating depreciation of an
asset. Under the Straight Line Method, the charge of depreciation is the same throughout
the life of the asset. As a result, the profits are affected equally throughout. Under the
Declining Balance Method, and the Sum of the Year’s Digits Method, the charge for
depreciation is higher towards the end. In view of the fact that depreciation is higher in
the initial years, both these methods are called Accelerated Depreciation Methods. As
between the two methods, the charge is higher in the firs year in the case of Declining
Balance Method than under the Sum of the Year’s Digits Method. But in other years, the
depreciation is higher under the Sum of the Year’s digits method. From this, we can
understand that the amount of profit of a firm depends on the method of depreciation
adopted. With the same machine, equipment, plant, building, etc., different firms can
show different amounts of depreciation and consequently, different amounts of profit.
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For the young and growing firm, the ‘Accelerated Depreciation method’ offers
advantages as the new companies will have limited capital and they may need funds for
expansion. Even for well-established companies with excellent credit facilities, this
method is better suited than the ‘Straight-Line Method’ if the companies are engaged in
the programme of capital expansion and replacement of assets. The advantages are as
follows:
Taxable income and income-tax liability would be substantially larger towards
later years only under the declining balance method and the sum of year’s digit
method.
Under the accelerated depreciation method, the tax liability being lower in the
earlier years of the life of the asset, the company has the benefit of retaining a part
of the funds which would have been payable as tax under the straight-line method.
These funds, in effect, amount to an interest-free loan from the Government to the
company, since the accelerated methods result only in postponement of tax rather
than its permanent avoidance.
In the case of assets subject to rapid obsolescence, it is desirable to write-off the
asset as soon as possible in this respect, accelerated methods of depreciation are
more effective than the straight-line method.
The capacity of a firm to earn profits from the use of an asset is lower in the
earlier part of the life of the asset. Consequently, the capacity to pay tax is also
lower, under the accelerated depreciation methods; the tax liability is lower in the
beginning and higher towards the end. Thus, there is an adjustment in the capacity
to pay taxes and the tax liability is adjusted with the capacity to pay.
However, there are certain restrictions about the adoption of depreciation methods
by the tax rules of different countries, and these tax rules impose constraints on the
managerial choice about depreciation method. In the U.S.A. a company can choose any
one of the three methods we studied above and the Internal Revenue Act permits this.
Other countries such as Denmark, France, Holland and Sweden have introduced
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‘Accelerated Depreciation Method’ with the object of stimulating investment. In
Australia, the Straight-Line or the Declining Balance Method may be used. In India, there
are prescribed rates of depreciation to be applied to the written down value of the asset
under the declining balance method. For general machinery and plant, the depreciation is
10%. In the case of furniture and fittings, the depreciation is 15% when used in hotels,
restaurants, cinema theaters, etc. In the case of building it is 2.5%.
5.3.2. Valuation of StockIn business, the valuation of stock will influence the profit and the method
adopted in arriving at the valuation of the stock would have decisive impact on the profit.
There are three methods viz;
LIFO (Last In First Out) Method: According to this method, it is assumed that
the units acquired last are the units to be issued first. As a result, the inventory is
supposed to consist of materials purchased earliest.
FIFO Method (First In First Out): According to this method, it is assumed that
the units of stock acquired first should be issued first, i.e., First in stock should go
out first, and stock acquired very recently will be issued only later. Under this
method, the inventory is supposed to consist of goods purchased most recently.
The significance behind this is that the company may not have acquired the stock
at the uniform price throughout. With rising prices, at the beginning, the purchase
cost would have been lesser and later it would have been larger.
Weighted Average Method: This method assumes that it is not possible to
identify separately the materials purchased at different times at different prices.
Consequently the cost of one unit cannot be distinguished from the cost of
another. Units are issued at a cost of which is an average of the cost of each
purchase, weighted by the quantity purchase at that accost. The closing stock is
valued at the average cost.
Illustration: Let us take a hypothetical case to illustrate the three methods mentioned
above in the valuation of stock. Suppose a firm purchases for its factory production 500
Kgs, of a particular chemical at different times and at different prices as stated below:
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Purchased on February 18th : 100Kgs. At Rs. 3.25 per Kg
Purchased on March 20th : 250Kgs. At Rs. 3.50 per Kg
Purchased on March 31st : 150Kgs. At Rs. 3.75 per Kg
Suppose that on April 10, the materials department issued a quantity of 250kgs, of the
chemical to the production department. How will the stock on hand be valued under
different methods?
Under FIFO method, the quantity issued to the production department will be
valued at Rs.850/- and the stock on hand with the materials department will be valued at
Rs.912.50. According to this method, the first acquired should go out first. Hence the first
100kgs, are valued at Rs.3.25 and the subsequent 150kgs, are valued at Rs.3.50, which is
the purchase price. The total value of 250kgs comes to Rs.850. the total value of the stock
before issue comes to Rs.1762.50 on the basis of above purchase price and quantity.
Hence, the value of the stock on hand after issue to the Production Department will be
Rs.912.50. Under LIFO Method, the materials issued will be valued at Rs.912.50 and the
stock will be valued at Rs.850 after issue. Under this method, recently procured materials
should be issued first (Last In First Out). Hence, the first 150kgs should be valued at
Rs.3.50 per kg. This will work out to Rs.912.50. We know that the total procurement cost
under LIFO method is Rs.912.50. so; the stock on hand comes to Rs.850.
Thus, we can see that the stock on hand after issue is valued at Rs.912.0 under
FIFO method, and the stock on hand after issue is valued at Rs.850 under LIFO method.
In other words, the valuation of stock is higher under FIFO method and lesser under
LIFO method in this particular case. Under weighted average method, the materials
issued will be valued at Rs.881.25 and the stock will also be valued at Rs.881.25. Thus, it
will be seen tat the value of the stock is different under different methods.
Valuation of Stock and Profit: The impact of the method used in determining the value
of the stock depends on the movement of prices of the commodity in question. Generally,
in an inflationary period, the LIFO method or Average method. The reason is that during
the period of inflation, the costs are high and since most recent costs are taken into
consideration under LIFO method, the profits are determined accordingly. The stock is
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values at the earlier cost, i.e., under lower cost. Under FIFO method, these lower costs
would be debited to the Profit and Loss Account; the resultant profit will, therefore, be
higher. The inventory will be valued at the higher costs, i.e., later costs. This also will
lead to higher profits. The Average method lies somewhere in between LIFO and FIFO
methods. In period of deflation. LIFO method will tend to produce higher income than
FIFO method or Average method.
Our experience after the Second World War shows that in out economy, rising
prices due to inflation have become the general trend and deflation is a remote
possibility, or almost nil. So, the businessmen find it expedient to adopt LIFO method in
the valuation of stock. As LIFO method tends to show lower profits in an inflationary
period, it tends to reduce income-tax liability. It is stated that an American manufacturer
saved nearly 19,500,000 dollars in income tax, over a period of 19 years by adoption of
the LIFO method. In times of deflation the FIFO method is more beneficial. But, the
income-tax authorities would insist on using only one particular method and it should be
adhered to consistently and a departure from the method will not be allowed.
The Income Tax Act does not lay down any specific method about the valuation
of stock. But, Section 145 provides that profits shall be computed in accordance with the
method of accounting regularly employed by the assessed. A method regularly employed
will include the method of valuation of stock also and it cannot be changed to suit the
convenience of the assessee. Prof. Joel Dean has recommended the adoption of LIFO
method and the accounting bodies of UK have also recommended the same.
5.3.3. Treatment of Deferred Expenses – Allocation of expenses over Time Periods
The firm will have intangible fixed assets and the problems come in writing off
these intangible assets during their lifetime. Intangible fixed assets can be classified into
two categories.
Those having a limited life, e.g., Copyright, Leasehold, permits, etc., and
Those having no such limited life, e.g., Trade Marks, Good-Will of the
business, Preliminary Expenses, etc.
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Businessmen prefer to write off the intangible assets having limited life before their
useful life expires. This is based on conservatism, i.e. to eliminate these intangible assets
as soon as possible. The example of this type is provided in the case of ‘Copyrights’.
Legally, copyrights have life equal to author’s life plus 50 years thereafter. But
publications may not have an active market for such a long period. It is, therefore,
considered advisable to write off the cost of copyright against the income from the first
edition. Intangible assets with no limited life pose more complicated problems for two
reasons:
There is a difference of opinion whether the assets should be written off at
all or not
If they have to be written off, what should be the period for their
amortization?
This amortization can be done either gradually or by an immediate write off. To
illustrate this point, “Good-Will” can be taken for discussion. The conservative view is
that the good will is only a fancy asset having no place in the balance sheet. But this view
cannot be fully endorsed, as in some cases; good will may ensure certain decisive
advantages to the firm. Hence, a rational view would be to write off the good will over an
appropriate period of time.
5.3.4. Capital Gains and Losses
Capital gains and losses, or “Windfalls” may be defined as “unanticipated
changes in the value of property relative to other real goods. That is, windfall reflects a
change in someone’s anticipation of the property’s earning power. Fluctuations in stock
market prices are all almost of this nature”. Conservative companies may decide not to
include capital gains in the current profit. At the same time, they would like to write off
capital losses from the current profits of the year in which the loss occurs. On the other
hand, a company may decide to include the capital gains in the profits of the year.
Regarding capital losses, the company may decide to write it off out of retained earnings.
Thus the amount of profit would be affected by the treatment of capital gains and losses.
In the case of unrealized capital gains, there is unanimity that they should not be included
in the profits. If there is a revaluation of property, the gain resulting out of it is usually
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transferred to capital reserve. All these show that there can be discrepancies in the profit
reported by different companies because of the different approaches that they adhere to
the treatment of capital gains and losses.
5.4. Profit Planning
A firm has to face many uncertainties and risks. These uncertainties may arise due
to the dynamic nature of the consumer needs, the nature of competitions, continuous
change in technological developments and uncontrollable nature of cost of production.
The symptoms of a healthy business include making a reasonable profit consistent with
the risks it has to face. The profits cannot be left to chances and it has to be planned.
A firm faces unpredictable demand for its products. Barring the basic
requirements of life and other essential commodities, consumer preferences of
commodities are highly subjective and the firm may not be able to predict the demand
precisely and firm faces this uncertainty, viz.,
The pattern and quantum of demand is uncertain. This is a risk and the firm has
to take steps to forecast the demand for its products.
The firm has to face competition from the rival producers. The competition may
be price-competition or product competition or it may be both. Product
competition is more important till it reaches the stage of maturity.
In a period of continuous rising prices, no firm can be certain of its own cost
structure, as it cannot have control over the price of raw materials and wages
and transport cost, as well as taxes to be paid. This is another uncertainty.
Improvements and change in technological developments may make a firm’s
product obsolete and push the firm out of business, unless, the firm adopts the
new technology.
All these create a condition of risk and uncertainties for the firm to survive in the
business and to make profit in the enterprise. Unless the firm takes an extra ordinary care
to study all the above factors prone to risks, the profits would be left to chance. The firm
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has to plan for the profits by having a thorough knowledge of the relationship of cost,
price and volume in the enterprise .The knowledge of manipulation of these, viz., cost
price and volume will have a definite bearing on the profit making ability of the firm. If a
firm does this exercise elegantly and efficiently, the targeted profit can be ensured. If a
firm makes thorough study and exercise of COST- VOLUME PROFIT ANALYSIS and
takes decisions accordingly to decide the quantum of profit, then the firm is said to have
adopted ‘Profit Planning’ effectively. The most important method of determining the
cost-volume-profit relationship is that of Break- even- analysis.
5.5. Break Even Analysis A business unit breaks even with its total sales value if it is equal to its total
cost. The Break-even analysis helps in understanding the relationship between the
revenues and costs in relation to its volume of sales. It helps in determining the volume in
which the firm’s cost and revenue are equal. Break–even point (BEP), refers to that level
of sales volume at which there is neither profit nor loss, costs being equal to its sales
value and the contribution is equal to fixed expenses.
5.5.1 Differing Views on Break-Even Point
Accountants and Economists differ on break-even point. Economists assume that
revenue and cost vary over increasing volume of output. Accountants, on the other hand,
assume that variable cost varies in direct proportion to output and the break-even point is
constructed assuming linear cost and revenue functions. The comparison of the two views
is given in the figure by depicting the structure of the break-even chart according to
Economist and Accountants.
The figure 5.1 indicates the Economist’s viewpoint of break-even and the figure 5.2
shows the Accountants view point. In the Economists figure the firm should produce
OQ1 to maximize profits. Expansion of output beyond OQ1 results in decline in profits
due to diminishing returns and diminishing marginal revenue .The Total Revenue Curve
eventually drops down, as greater quantities can be sold only by lowering the prices .The
Total Cost Curve simultaneously continues to increase since extra output does not have a
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zero cost .The figure shows the level of output where profits are the maximum. This
situation corresponds to the distance between TR and TC.
Figure 5.1: The Break-even Chart According to Economist
Figure 5.2: The Break-even Chart According to Accountants
In the figure 5.2, the BEP is constructed assuming linear cost and revenue
functions. This view suggests that higher the output, higher is the profits. Break even
point is at B where TC=TR .In the Accountants figure, TR will be always at a higher
level beyond BEP showing increasing profits with the increase of output .TC in this
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figure will never drop down, as these are assumed to be linear .The Economist figure is
realistic and the Accountants figure is practical
5.5.2. Calculations of Break-even PointThe following formula could be used to find out the Break-even point
Total Fixed Cost BEP = Selling price- AVC
= Total fixed expenses Selling price per unit - Variable cost per unit
(a) Illustration: Find out the BEP from the following data: Variable cost per unit =Rs 30/-
Selling price per unit =Rs 40/-
Fixed expenses = Rs.1 lakh.
Answer:
Rs.1, 00,000 BEP =
Rs.40-Rs.30
1,00,000 = = 10,000 Units
10 For this illustration, calculate the selling price per unit if BEP is brought down to 8,000
Total fixed cost Fixed cost per unit =
Number of units
1,00.000= = 12.50
8,000
Selling price = Variable cost + Fixed Cost per unit = Rs.30 + Rs.12.50 = Rs.42.50
Break-even point in terms of sales value
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(b) Illustration:Find out the BEP in terms of sales value on the basis of following data:
In this case, we have to calculate the contribution ratio and then we have to calculate the BEP:
Total revenue minus Total variable costContribution ratio =
Total revenue
Sales minus variable cost =
Sales
= 10.000-6,000 = 210,000 5
Total fixed cost BEP=
Contribution Ratio
3,000
2/5
3,000 x 5 = = Rs. 7500
2
Break- even analysis helps the business firm in focusing on some important
economic leverage, which could be operated suitably to enhance its profitability. It helps
the business firm in
Calculating output or sales to earn a desired profit;
Margin of safety
Change in price
Make decisions; and
Change in cost and price etc.
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5.5.3. Calculation in Terms of Target Profit
(c) Illustration:Find out the target sales volume, if the desired profit is Rs.12.000 with the following data: fixed cost Rs.20, 000,Variable cost Rs.4 per unit; and selling price Rs. 8 per unit.
According to Break even Analysis the formula for
Fixed cost + Target profitTarget Sales volume =
Contribution margin per unit
Substituting the values to the formula, we get:
20,000+12,000Target sales volume=
8-4
32,000=
4
Target sales volume = 8,000 unites
5.5.4. Calculation in Terms of Safety Margin
(d) Illustration: If the present sales of a firm is Rs.40 lakhs and Break-even sales are Rs.30lakhs, find out percentage of margin of safety?
The formula for Safety margin is as follow:
(Sales-BEP)Safety margin= *100
Sales
40,00,000 - 30,00,000Safety margin = * 100
40,00,000
= 25%of present sales.
5.5.5. Calculation in Terms of Change in Price and New Sales Volume:Very frequently, the firm will be faced with problems of taking decisions for
reducing the price or not. A reduction of price will result in the reduction of contribution
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margin. Reduction in price need not necessarily result in the increased sales, as it depends
on the elasticity of demand of the commodity produced by the firm. Assuming that it
remains constant, the management has to take decision regarding the increase of volume
of output in order to maintain the same profit level in the context of reduction in price.
The formula for determining the new volume of sales with given reduction in price will
be as follows:
Total Fixed cost + Total profit
New sales volume = New selling price- Average variable cost
(e) Illustration: A firm sells 4,000 unites per month at a price of Rs.40per unit. Fixed cost works
out to Rs.10,000 per month and variable cost comes to Rs.24 per unit there is a proposal
to reduce the price of the commodity by 20 per cent. How many units should the firm sell
to maintain the present level of profit?
Sales value of 4,000 units at Rs.40 =1,60,000 Less
variable cost of 4,000 units at Rs. 24 = 96,000Contribution = 64,000 Less
fixed expenses = 10,000Present Profit Rs. 54,000
Old price is Rs.40 Reduction of price is 20 per cent, i.e., Rs.8. hence, the new sales price
is Rs.32. Sales needed to maintain the present profit of Rs.54, 000 at new price of Rs.32
The firm has to increase the sales from 400 units to 8000 units. Price reduction of 20% is
justified if the management is confident of raising the sales to 8000 units.
Break-even analysis also helps to decide whether components, which are part of their
finished products, should be manufactured by them or brought from out side firms.
Illustration: A manufacturer of bicycles buys a certain part at Rs.40 each. If he decides to
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manufacture it himself, his cost would be as follows: Fixed costs Rs 48000; Variable cost
Rs.16 per unit. Find out if it is profitable for him to manufacture the parts instead of
buying.
F.CBreak-Even Point =
Purchase price- Variable cost
48000 = 48000/24 = 2000 40- 16
This shows that the manufacturer can produce the parts profitably, if he needs more
than 2000 components per year. If his requirement is less than 2000 units, it is better to
buy from outside firms. Thus the Break-Even analysis is useful to the management in
determining profit policies and profit planning.
5.6. Linear Programming There are many varieties of analytical techniques to solve constrained
optimization problem. We have linear programming, Integer Programming, Quadratic
Programming, and Non-Linear Programming. However, linear programming technique
has been developed more and used frequently. The origin of linear programming dates
back to 1920s when W. Leontief developed this for input-output analysis. The present
version is the work of mathematician George B. Dentzig in 1947. Originally, this
technique was used in planning the diversified operation of US Air-Force. Economists
like Koopmans, Cooper, Dorfman and Samuelson have made significant contributions.
5.6.1 Meaning of Linear ProgrammingLinear programming is a mathematical technique by which rational decisions are
taken in production to optimize output with the constraints of limited input, i.e.,
resources. To put it in a simpler way, it is useful in allocating the limited resources in an
optimal manner in production. We know that resources are very limited and there are
constraints in getting adequate resources and also in the process of production. A
producer has to take decisions to make use of the little resources in order to get maximum
output, or to make a unit output with minimum cost. The problem before the management
is the allocation of firm’s resources, viz, money, material, space, time, labour etc., so as
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to get maximum profit. The linear programming technique helps in realizing the objective
of optimal utilization of resources for getting maximum returns or profits. Hence, this is
an important tool in decision-making and it is comparatively a new tool in decision-
making.
Linear Programming is defined as “a mathematical technique of study where in
we consider the maximization (or minimization) of a linear expression (called the
objective function) subject to a number of a linear equalities and inequalities (called
linear restraints)”. The term ‘linear’ denotes that it is mathematically involving linear
function, and the word ‘programming’ denotes mathematical procedures to get the best
solution to a problem utilizing limited resources.
5.6.2 Need for Linear Programming TechniqueIn economics, we have studied about Marginal Analysis and Least Cost
Combination Techniques, etc. in the production analysis. When we have these methods,
where is the need for the linear programming technique? Marginal analysis and calculus
and other usual methods cannot be used in a situation, where the problem is to obtain an
optimum solution with constraints. The usual methods are useful only in the context of
resource allocation to achieve a particular goal, rather than with the efficiency with which
the resources are to be employed. Realizing a particular objective in production is
different from utilizing the resources most efficiently subject to certain constraints. For
example, if it is a problem of suitable choice of combination of outputs so as to maximize
National income, with the constraints that no more than a given amount of resources
should be used, then, it is a problem of not only optimization. This means that we can use
only a given amount of resources and that the output level of each product has to be non-
negative. This, connotes, that we are required to choose amongst a host of possible
combinations of different outputs, that combination which does not violet the given
constraint conditions, and at the same time, it should maximize National Income.
Moreover, the constraints may be precise or specific; instead they may impose
only upper or lower limits on the decision-maker. For instance, the given limitations may
state only the maximum amounts of the inputs that are available or it may be only certain
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minimum requirements that must be met. Such constraints can be expressed only as
inequality relationships. These problems cannot be solved by means of marginal analysis.
We have to necessarily depend on a new technique of analysis, which has been provided
by linear programming.
5.6.3 Assumptions of Linear Programming Technique The linear programming technique is based on certain assumptions in the process
of obtaining the optimal solution. Some of the important assumptions are discussed
below:
Assumption of Linearity: The main assumption in the technique is the linear
relationship of the variable used in it. The various relationships should be expressed
in the form of equations or inequalities and they must be linear. This means a
proportional relationship, i.e., the exponents of all variable must be one. For
example, the raw materials used, the number of hours of work and the units of
products are proportional. By assuming linearity, we mean that a 20% change in the
productivity hours of work will lead to 20% change in raw materials and 20%
change in output. Similarly, the basic relationship between cost functions, revenue
function and their composite, i.e., profit function are directly proportional, i.e.,
linear. This assumption of linearity implies the constancy of product prices. If costs,
output and prices have to rise linearly, necessarily there must be constant returns to
scale, i.e., the production function must be linear, i.e., homogeneous production
function of first degree. This further leads to the assumption of constancy of factor
prices remain constant, such a situation can be obtained only under perfect
competition. So, the entire analysis rests on a condition of perfect competition. Thus
the technique assumes linearity relationships, which leads to the assumption of
Constancy of product prices Constant returns to Scale Constancy of factor prices Perfect competition
5.6.4. Characteristic Features of Linear Programming Problems
All problems where linear programming is applicable have the following
characteristic features;
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The Objective Function: This clearly defines the objective of the programme in
quantitative terms. This tells about the determinants of the quantity optimized.
Generally, in business, the objective will be maximization of profit or
minimization of cost. If it is planning at the national level, the objective may be
maximization of national income as the sum of outputs of different products. The
objective sought after is known as the ‘objective function’. For example, suppose
a manufacturer produces three commodities, R, S, and T. The quantities produced
are QR, QS, QT respectively. Let the profit per unit in case of these commodities be
PR, PS, PT respectively. The producer wants to maximize profit ‘P’ for them. The
objective function would then be stated as follows:
QRPR + QSPS + QTPT = Maximum
Constraints: This is an algebraic statement of the limits of a resource or input.
This expression is usually in the form of inequalities, which state the things that
are possible or not possible to be done. If a firm is trying to maximize profits, then
it has to take account of the fact that they are limited by number of machines it
has, the warehousing capacity and the amount of raw material available, etc.
suppose the commodities R, S, and T, each require per unit of product X,Y and Z
hours of machine time and only ‘H’ hours of machine time is available. The
constraints on the production of R, S and T, then will be as follows:
XQR + YQS + ZQT ≤ h
The constraints like and objective function must be capable of arithmetical or
algebraic expression. For example, a requirement that any solution shall not lower
the quality of the product is not a constraint in the linear programming sense, as
this cannot be expressed numerically.
Non-Negativity condition: Linear Programming technique is a mathematical tool
for solving constrained optimization problems. Hence we would get any answer
with any algebraic sign attached with it. Some answers may be even negative and
as such absurd. When we get such a negative solution, like negative quantity, it
will be a practical impossibility. For example, in distribution problems, the
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optimal solution arrived at by the technique may be ‘negative shipments’ from
one place to another. Of course, this is an impossible solution. In order to
eliminate such impossible and non-sensual results, it is necessary to include the
non-negativity conditions. Thus in any production problem, we would be required
to include conditions that any factor-input or the quantity produced cannot be
negative. Thus, the non-negativity condition merely states the fact that all variable
in the problems must be equal to, or greater than zero. In our example, if the firm
makes three products, R, S and T, the quantity of production should be either zero
or positive. There would be no negative production, which means that the
commodity is ‘reproduced’ or ‘dismantled’ which is absurd. So, in the illustration,
the non-negativity conditions would be:
QR ≥ 0 QS ≥ 0 QT ≥ 0
Linear relationship: As has been indicated already, the various relationships to
be expressed in the form of equations or inequalities must be linear, i.e.,
proportional relationship.
5.6.5. Methods of Linear ProgrammingA problem related to linear programming can be solved by two methods. The first
one is called the ‘graphical method’ and the second one is known as ‘simplex method’.
The latter requires advanced mathematical techniques involving extensive use of
algebraic equations and manipulations. Further, the computational procedure is very
wearisome, and without electronic computer, it will be difficult to cope with the volume
of data and calculations to find solutions to actual business problems. But the Graphical
Method is a simpler one having a close resemblance to indifference curve analysis. This
method can be used very elegantly where there are a few decision variables.
5.6.6. Graphical methodProblem: Suppose the objective of a firm is to maximize profit in the production of
product ‘R’ and/or product ‘S’. Both these products require two machines, namely,
machine ‘a’ and machine ‘b’ for purposes of processing. Product ‘R’ requires 4 hours on
both the machines ‘a’ and ‘b’, while product ‘S’ requires 6 hours on machine ‘a’, but only
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2 hours on machine ‘b’. There are only 24 and 16 hours available on machine ‘a’ and ‘b’
respectively. The profit per unit is estimated at Rs.12/- and Rs.14/- in the case of ‘R’ and
‘S’ respectively.
Now, we have dependent variable, viz, profit which is to be maximized and this is
the function of two independent variables ‘R’ and ‘S’ the production of which is
restricted by the time available in the machines.
First Step: (Formulation of problem)The above stated information has to be formulated in mathematical form. We
have the objective function. This is an equation showing relationship between output and
profit.
P = Rs. 12R + Rs.14S
If P = Profit; Rs.12R = Total profit from sale of product ‘R’
Rs.14S = Total profit from sale of product ‘S’
The time taken in processing the products in the machines must not exceed the
total time available on each. It may be less or equal to the time available on the machine.
These are the constraints and the constraints can be expressed mathematically as follows:
A: 4R + 6S ≤ 24
B: 4R + 2S ≤ 16
This means, the first inequality states that the hours required to produce one unit
of ‘R’ (4 hours) multiplied by the number of units of ‘R’ produced plus the hours
required to produce one unit of ‘S’ (6 hours) multiplied by the number of units of ‘S’
produced must be equal to or less than 24hours available on machine ‘a’. A similar
explanation holds good for the second inequality. Both these inequalities represent
capacity restrictions on output and hence on profit.
Finally, to get meaningful answers, the values of R and S must be positive i.e.,
producing negative quantities of R and S may not convey any meaning. Thus solutions
for R and S must be either zero or greater than zero, i.e., R ≥ 0; S ≥ 0.
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To sum up we get: Maximize subjects to constraintsP = 12R + 14S4R + 6S ≤ 244R + 2S ≤ 16R ≥ 0; S ≥ 0.
Second Step :(Plot the constraints on Graph)The next step is to plot the restraints of the linear programming problem on a
graph paper; products ‘R’ to be shown on ‘X’ axis and product ‘S’ on ‘Y’ axis (Figure
5.3). The inequality 4R + 6S ≤ 24 may be drawn on the graph first locating its two
terminal points, and then joining these two points by a straight line. This is done in the
following manner. If we assume that all the time available on machine ‘a’ is used for
making product ‘R’, then it would mean that the production of product ‘S’ is zero. Then 6
units of product ‘R’ would be made. Thus, if S = 0, then R ≤ 6. If we produce the
maximum number of product ‘R’, then R = 6. so the first point is (6,0) to be plotted in the
graph, i.e., zero product of S and 6 units of R.
In order to find the second point, we assume that all the time available on machine
‘a’ is used in making ‘S’; i.e.., production of ‘R’ is zero. Under this assumption, we get 4
units of ‘S’. Thus, if ‘R’ is zero, then S = 14. The maximum number of ‘S’ would be 4.
So, the second point is (0,4). This denotes 4 units of ‘S’ and zero unit of ‘R’.
Locating these points, viz., (0,4) and joining them, we get a straight line AB as shown in
figure –5.1. This line shows the maximum quantities of product R and S that can be
produced on machine ‘a’. The area AOB is the graphic representation of inequality 4R +
6S ≤ 24 It can be drawn graphically as shown in the figure.
Similarly if the output of ‘S’ is zero, the maximum output of ‘R’ on machine ‘b’
will be 4, i.e., (4,0). If the output of ‘R’ is zero, the maximum output of ‘S’ on the
machine ‘b’ will be 8. i.e., (0,8). Locating these two points and joining them, we get
straight line CD, as shown in the figure. This line again represents the maximum
quantities of products R and S that can be produced on machine ‘b’. The area COD the
graphic representation of inequality 4R + 2S≤ 16
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Figure 5.3 Graphical Representation of Linear programming Problem
Third Step: Finding out Feasibility Region and Co-ordinates of its Corner Points.The third step is to identify the cross-shaded portion are OAED in the figure. This
is generally known as feasibility region. This is formed with the following boundaries; X
axis; Y-axis; AED boundary is formed by the intersection of lines AB and CD at point
‘E’. If a point is to satisfy both the constraints and the non-negativity conditions, it must
fall inside the cross-shaded area or on its boundaries. All points outside the feasibility
region are inadmissible. For example, if we begin at the origin O, we cannot travel
beyond point ‘D’. If we were to proceed further, the capacity restriction of machine ‘b’
will be violated. Similarly on the Y-axis, we cannot proceed beyond ‘A’. Moving beyond
‘O’ leftward or downward would not satisfy non-negativity conditions
In this feasibility region, we have to study the corner points, as the optimum
solution invariably must lie in one of the corner points. We know the co-ordinates of
three corner points, viz.,
Corner point R S
O (0, 0)A (0, 4)D (4, 0)
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The co-ordinates of point ‘E’ however, are yet to be ascertained. One method is to
read the co-ordinates in the figure itself, if it is drawn accurately and to the scale in the
graph sheet. Another method is to solve simultaneously the equations of the two lines,
which intersects to form point ‘E’. The equations to be solved are:
4R + 6S = 244R + 2S = 16
Solving these two equations we get the value of R or S
4R + 6S = 244R + 2S = 16
- - -4S = 8 S = 2
Now, substitute the value of S in the equation 4R + 6S = 24. We get value of R =
3. So, the co-ordinates of point ‘E’ are (R=3: S=2)
Fourth Step: Find Most Profitable Corner Point
The final step is to test the four corner-points, viz., O, A, D; E. Of the feasible region
OAED and to see which corner- point yields the maximum profit.