Theory of Demand
2.1 Introduction
Demand theory evinces the relationship between the demand for goods and
services. Demand theory is the building block of the demand curve- a curve that establishes a relationship between consumer demand and the amount of goods available. Demand is shaped by the availability of goods, as the quantity of goods increases in the market the demand and the equilibrium price for those goods decreases as a result.
Demand theory is one of the core theories of microeconomics and consumer
behaviour. It attempts at answering questions regarding the magnitude of demand for a product or service based on its importance to human wants. It also attempts to assess how demand is impacted by changes in prices and income levels and consumers preferences/utility. Based on the perceived utility of goods and services to consumers,
companies are able to adjust the supply available and the prices charged.
In economics, demand has a specific meaning distinct from its ordinary usage. In
common language we treat ‘demand’ and ‘desire’ as synonymously. This is incongruent from its use in economics. In economics, demand refers to effective demand which implies three things:
Desire for a commodity
Sufficient money to purchase the commodity, rather the ability to pay
Willingness to spend money to acquire that commodity
This substantiates that a want or a desire does not develop into a demand unless it is supported by the ability and the willingness to acquire it. For instance, a person may desire to own a scooter but unless he has the required amount of money with him and the willingness to spend that amount on the purchase of a scooter, his desire shall not become a demand. The following should also be noted about demand:
Demand always alludes to demand at price. The term ‘demand’ has no meaning
unless it is related to price. For instance, the statement, 'the weekly demand for potatoes in city X is 10,000 kilograms' has no meaning unless we specify the price at which this quantity is demanded.
Demand always implies demand per unit of time. Therefore, it is vital to specify the period for which the commodity is demanded. For instance, the statement that demand for potatoes in city X at Rs. 8 per kilogram is 10,000 kilograms again has no meaning, unless we state the period for which the quantity is being demanded. A complete statement would therefore be as follows: 'The weekly demand for potatoes in city X at Rs. 8 per kilogram is 10,000 kilograms'. It is necessary to specify the period and the price because demand for a commodity will be different at different prices of that commodity and for different periods of time. Thus, we can define demand as follows:
“The demand for a commodity at a given price is the amount of it which will be bought per unit of time at that price”.
2.2 Theory of Demand
2.2.1 ESSENTIALS OF DEMAND
1. An Effective Need: Effective need entails that there should be a need supported by the capacity and readiness to shell out. Hence, there are three basics of an effective need:
a. The individual should have a need to acquire a specific product.
b. He should have sufficient funds to pay for that product.
c. He should be willing to part with these resources for that commodity.
2. A Specific Price: A proclamation concerning the demand of a product without
mentioning its price is worthless. For example, to state that the demand of cars is 10,000 is worthless, unless expressed that the demand of cars is 10,000 at a price of Rs. 4,00,000 each.
3. A Specific Time: Demand must be assigned specific time. For example, it is an
incomplete proclamation to state that the demand of air conditioners is 4,000 at the price of Rs. 12,800 each. The statement should be altered to say that the demand of air conditioners during summer is 4,000 at the price of Rs. 12,800 each.
4. A Specific Place: The demand must relate to a specific market as well. For example, every year in the town of Dehradun, the demand for school bags is 4,000 at a price of Rs. 200.
Hence, the demand of a product is an effective need, which demonstrates the
quantity of a product that will be bought at a specific price in a specific market at some stage in a specific period. Nevertheless, the significance of a specific market or place is not as significant as the price and time period for which demand is being measured.
2.2.2 LAW OF DEMAND
We have considered various factors that fashion the demand for a commodity. As explained the first and the most important factor that determines the demand of a commodity is its price. If all other factors (noted above) remain constant, it may be said that as the price of a commodity increases, its demand decreases and as the price of a commodity decreases its demand increases. This is a general behaviour observed in a market. This gives us the law of demand:
“The demand for a commodity increases with a fall in its price and decreases with a rise in its
price, other things remaining the same”.
The law of demand thus merely states that the price and demand of a commodity are inversely related, provided all other things remain unchanged or as economists put it ceterisparibus.
Assumptions of the Law of Demand
The above statement of the law of demand, demonstrates that that this law operates only when all other things remain constant. These are then the assumptions of the law of demand. We can state the assumptions of the law of demand as follows:
1. Income level should remain constant: The law of demand operates only when the
income level of the buyer remains constant. If the income rises while the price of the commodity does not fall, it is quite likely that the demand may increase. Therefore, stability in income is an essential condition for the operation of the law of demand.
2. Tastes of the buyer should not alter: Any alteration that takes place in the taste of the consumers will in all probability thwart the working of the law of demand. It often happens that when tastes or fashions change people revise their preferences. As a consequence, the demand for the commodity which goes down the preference scale of the consumers declines even though its price does not change.
3. Prices of other goods should remain constant: Changes in the prices of other goods often impinge on the demand for a particular commodity. If prices of commodities for which demand is inelastic rise, the demand for a commodity other than these in all probability will decline even though there may not be any change in its price. Therefore, for the law of demand to operate it is imperative that prices of other goods do not change.
4. No new substitutes for the commodity: If some new substitutes for a commodity
appear in the market, its demand generally declines. This is quite natural, because with the availability of new substitutes some buyers will be attracted towards new products and the demand for the older product will fall even though price remains unchanged.
Hence, the law of demand operates only when the market for a commodity is not
threatened by new substitutes.
5. Price rise in future should not be expected: If the buyers of a commodity expect that its price will rise in future they raise its demand in response to an initial price rise. This behaviour of buyers violates the law of demand. Therefore, for the operation of the law of demand it is necessary that there must not be any expectations of price rise in the future.
6. Advertising expenditure should remain the same: If the advertising expenditure of a firm increases, the consumers may be tempted to buy more of its product. Therefore, the advertising expenditure on the good under consideration is taken to be constant.
Desire of a person to purchase a commodity is not his demand. He must possess
adequate resources and must be willing to spend his resources to buy the commodity.
Besides, the quantity demanded has always a reference to ‘a price’ and ‘a unity of time’. The quantity demanded referred to ‘per unit of time’ makes it a flow concept. There may be some problems in applying this flow concept to the demand for durable consumer goods like house, car, refrigerators, etc. However, this apparent difficulty may be resolved by considering the total service of a durable good is not consumed at one point of time and its utility is not exhausted in a single use. The service of a durable good is consumed over time.
At a time, only a part of its service is consumed. Therefore, the demand for the services of durable consumer goods may also be visualised as a demand per unit of time. However, this problem does not arise when the concept of demand is applied to total demand for a consumer durable. Thus, the demand for consumer goods also is a flow concept.
Demand Schedule
The law of demand can be illustrated through a demand schedule. A demand
schedule is a series of quantities, which consumers would like to buy per unit of time at
different prices. To illustrate the law of demand, an imaginary demand schedule for tea is
given in Table 2.1. It shows seven alternative prices and the corresponding quantities
Demand Curve
The law of demand can also be presented through a curve called demand curve.
Demand curve is a locus of points showing various alterative price-quantity combinations. It
shows the quantities of a commodity that consumers or users would buy at difference prices
per unit of time under the assumptions of the law of demand. An individual demand curve
for tea as given in Fig. 2.1 can be obtained by plotting the data give in Table 2.1.
In Fig. 2.1, the curve from point A to point G passing through points B, C, D and F is
the demand curve DD’. Each point on the demand curve DD’ shows a unique price-quantity
combination. The combinations read in alphabetical order should decreasing price of tea
and increasing number of cups of tea demanded per day. Price quantity combinations in
reverse order of alphabets illustrate increasing price of tea per cup and decreasing number
of cups of tea per day consumed by an individual. The whole demand curve shows a
functional relationship between the alternative price of a commodity and its corresponding
quantities, which a consumer would like to buy during a specific period of item—per day,
per week, per month, per season, or per year. The demand curve shows an inverse
relationship between price and quantity demanded. This inverse relationship between price
and quantity demanded results in the demand curve sloping downward to the right.
• Why does the demand curve slope downwards
As Fig. 2.1 shows, demand curve slopes downward to the right. The downward slope
of the demand curve reads the law of demand i.e. the quantity of a commodity demanded
per unit of time increases as its price falls and vice versa.
The reasons behind the law of demand i.e. inverse relationship between price and
quantity demanded are following:
Substitution Effect: When the price of a commodity falls it becomes relatively cheaper if
price of all other related goods, particularly of substitutes, remain constant. In other
words, substitute goods become relatively costlier. Since consumers substitute cheaper
goods for costlier ones, demand for the relatively cheaper commodity increases. The
increase in demand on account of this factor is known as substitution effect.
Income Effect: As a result of fall in the price of a commodity, the real income of its
consumer increase at least in terms of this commodity. In other words, his/her
purchasing power increases since he is required to pay less for the same quantity. The
increase in real income (or purchasing power) encourages demand for the commodity
with reduced price. The increase in demand on account of increase in real income is
known as income effect. It should however be noted that the income effect is negative in
case of inferior goods. In case, price of an inferior good accounting for a considerable
proportion of the total consumption expenditure falls substantially, consumers’ real
income increases: they become relatively richer. Consequently, they substitute the
superior good for the inferior ones, i.e., they reduce the consumption of inferior goods.
Thus, the income effect on the demand for inferior goods becomes negative. Diminishing Marginal Utility: Diminishing marginal utility as well is to be held
responsible for the rise in demand for a product when its price declines. When an
individual purchases a product, he swaps his money revenue with the product in order to
increase his satisfaction. He continues to purchase goods and services as long as the
marginal utility of money (MUm) is lesser than the marginal utility of the commodity
(MUC). Given the price of a commodity, he modifies his purchase so that MUC = MUm.
This plan works well under both Marshallian assumption of constant MUm as well as
Hicksian assumption of diminishing MUm. When price falls, (MUm = Pc) < MUC. Thus,
equilibrium state is upset. To get back his equilibrium state, i.e., MUm = PC, = MUC, he
buys more quantities of the commodity. For, when the supply of a commodity rises, its
MU falls and once again MUm = MUC. For this reason, demand for a product rises when
its price falls.
• Exceptions to the Law of Demand
The law of demand does not apply to the following cases:
Apprehensions about the future price: When consumers anticipate a constant rise in
the price of a long-lasting commodity, they purchase more of it despite the price rise.
They do so with the intention of avoiding the blow of still higher prices in the future.
Likewise, when consumers expect a substantial fall in the price in the future, they delay
their purchases and hold on for the price to decrease to the anticipated level instead of
purchasing the commodity as soon as its price decreases. These kinds of choices made by
the consumers are in contradiction of the law of demand.
Status goods: The law does not concern the commodities which function as a ‘status
symbol’, add to the social status or exhibit prosperity and opulence e.g. gold, precious
stones, rare paintings and antiques, etc. Rich people mostly purchase such goods as they
are very costly.
Giffen goods: An exception to this law is the typical case of Giffen goods named after Sir
Robert Giffen (1837-1910). 'Giffen goods' does not represent any particular commodity.
It could be any low-grade commodity which is cheap as compared to its superior
alternatives, consumed generally by the lower income group families as an important
consumer good. If price of such goods rises (price of its alternative remaining stable), its
demand escalates instead of falling. E.g. the minimum consumption of food grains by a
lower income group family per month is 30 kgs consisting of 20 kgs of bajra (a low-grade
good) at the rate of Rs 10 per kg and 10 kgs of wheat (a high quality good) at Rs. 20 per
kg. They have a fixed expenditure of Rs. 400 on these items. However, if the price of bajra rises to Rs. 12 per kg the family will be compelled to decrease the consumption of
wheat by 5 kgs and add to that of bajra by the same quantity so as to meet its minimum
consumption requisite within Rs. 400 per month. No doubt, the family's demand for
bajra rises from 20 to 25 kgs when its price rises.
• The Market Demand Curve
The quantity of a commodity which an individual is willing to buy at a particular price
of the commodity during a specific time period, given his money income, his taste and prices
of substitutes and complements, is known as individual demand for a commodity. The total
quantity which all the consumers of a commodity are willing to buy at a given price per time
unit, other things remaining the same, is known as market demand for the commodity. In
other words, the market demand for a commodity is the sum of individual demands by all
the consumers (or buyers) of the commodity, per time unit and at a given price, other
factors remaining the same. For instance, suppose there are three consumers (viz., A, B, C)
of a commodity X and their individual demand at different prices is of X as given in Table 2.2.
The last column presents the market demand i.e. the aggregate of individual demand by
three consumers at different prices.
Graphically, market demand curve is the horizontal summation of individual demand
curves. The individual demand schedules plotted graphically and summed up horizontally
gives the market demand curve as shown in Fig. 2.2. The individual demands for commodity X are given by DA, DB and Dc, respectively. The
horizontal summation of these individual demand curves results into the market demand
curve (DM) for the commodity X. The curve DM represents the market demand curve for
commodity X when there are only three consumers of the commodity.
Demand Function
The functional relationship between the demand for a commodity and its various
determinants may be expressed mathematically in terms of a demand function, thus:
Dx = f (Px, Py, M, T, A, U) where,
Dx = Quantity demanded for commodity X.
f = functional relation.
Px = The price of commodity X.
Py = The price of substitutes and complementary goods.
M = The money income of the consumer.
T = The taste of the consumer.
A = The advertisement effects.
U = Unknown variables or influences.
The above-stated demand function is a complicated one. Again, factors like tastes
and unknown influences are not quantifiable. Economists, therefore, adopt a very simple
statement of demand function, assuming all other variables, except price, to be constant.
Thus, an over-simplified and the most commonly stated demand function is: Dx = f (Px),
which connotes that the demand for commodity X is the function of its price. The traditional
demand theory deals with this demand function specifically.
It must be noted that by demand function, economists mean the entire functional
relationship i.e. the whole range of price-quantity relationship and not just the quantity
demanded at a given price per unit of time. In other words, the statement, 'the quantity
demanded is a function of price' implies that for every price there is a corresponding
quantity demanded.
To put it differently, demand for a commodity means the entire demand schedule,
which shows the varying amounts of goods purchased at alternative prices at a given time. Shift in Demand Curve
When demand curve changes its position retaining its shape (though not necessarily),
the change is known as shift in demand curve.
commodity X. As shown in the figure, at price OP2 consumer buys OQ2 units of X, other
factors remaining constant. If any of the other factors (e.g., consumer’s income) changes, it
will change the consumer’s ability and willingness to buy commodity X. For example, if
consumer’s disposable income decreases, say, due to increase in income tax, he may be able
to buy only OQ1 units of X instead of OQ2 at price OP2 (This is true for the whole range of
price of X) the consumers would be able to buy less of commodity X at all other prices. This
will cause a downward shift in demand curve from D2 to D1. Similarly, increase in disposable
income of the consumer due to reduction in taxes may cause an upward shift from D2 to D3.
Such changes in the position of the demand curve are known as shifts in demand curve.
Reasons for Shift in Demand Curve
Shifts in a price-demand curve may take place owing to the change in one or more of
other determinants of demand. Consider, for example, the decrease in demand for
commodity X by Q1Q2 in Fig 2.3. Given the price OP1, the demand for X might have fallen
from OQ2 to OQ1 (i.e., by Q1Q2) for any of the following reasons:
• Fall in the consumer’s income so that he can buy only OQ1 of X at price OP2—
it is income effect.
• Price of X’s substitute falls so that the consumers find it beneficial to substitute Q1Q2 of X with its substitute—it is substitution effect.
• Advertisement made by the producer of the substitute, changes consumer’s taste or
preference against commodity X so much that they replace Q1Q2 of X with its substitute,
again a substitution effect.
• Price of complement of X increases so much that they can now afford only OQX of X
• Also for such reasons as commodity X is going out of fashion; its quality has deteriorated;
consumer’s technology has so changed that only OQ1 of X can be used and due to
change in season if commodity X has only seasonal use. Elasticity of Demand
While the law of demand establishes a relationship between price and quantity
demanded for a product, it does not tell us exactly as how strong or weak the relationship
happens to be. This relation, as already discussed, is inverse baring some rare exceptions.
However, a manager needs an exact measure of this relationship for appropriate business
decisions. Elasticity of demand is a measure, which comes to the rescue of a manager here.
It measures the responsiveness of demand to changes in prices as well as changes in income.
A manager can determine almost exactly how the demand for his product would change
when he changes his price or when his rivals alter prices of their products. He can also
determine how the demand for his product would change if incomes of his consumers go up
or down. Elasticity of demand concept and its measurements are therefore very important
tools of managerial decision making.
From decision-making point of view, however, the knowledge of only the nature of
relationships is not sufficient. What is more important is the extent of relationship or the
degree of responsiveness of demand to changes in its determinants. The responsiveness of
demand for a good to the change in its determinants is called the elasticity of demand. The
concept of elasticity of demand was introduced into the economic theory by Alfred Marshall.
The elasticity concept plays an important role in various business decisions and government
policies. In this unit, we will discuss the following kinds of demand elasticity.
• Price Elasticity: Elasticity of demand for a commodity with respect to change in its price.
• Cross Elasticity: Elasticity of demand for a commodity with respect to change in the price
of its substitutes.
• Income Elasticity: Elasticity of demand with respect to change in consumer’s income.
• Price Expectation Elasticity of Demand: Elasticity of demand with respect to consumer’s
expectations regarding future price of the commodity.
PRICE ELASTICITY OF DEMAND
The price elasticity of demand is delineated as the degree of responsiveness or
sensitiveness of demand for a commodity to the changes in its price. More precisely,
elasticity of demand is the percentage change in the quantity demanded of a commodity as
a result of a certain percentage change in its price. A formal definition of price elasticity of
demand (e) is given below:
The measure of price elasticity (e) is called co-efficient of price elasticity. The
measure of price elasticity is converted into a more general formula for calculating
coefficient of price elasticity given as
Where QO = original quantity demanded, PO = original price, Q = change in quantity
demanded and P = change in price.
Note that a minus sign (-) is generally inserted in the formula before the fraction with
a view to making elasticity coefficient a non-negative value.
2.4.2 POINT AND ARC ELASTICITY OF DEMAND
The elasticity of demand is conventionally measured either at a finite point or
between any two finite points, on the demand curve. The elasticity measured on a finite
point of a demand curve is called point elasticity and the elasticity measured between any
two finite points is called arc elasticity. Let us now look into the methods of measuring point
and arc elasticity and their relative usefulness.
(A) POINT ELASTICITY
The point elasticity of demand is defined as the proportionate change in quantity
demanded in response to a very small proportionate change in price. The concept of point
elasticity is useful where change in price and the consequent change in quantity demanded
are very small.
The point elasticity may be symbolically expressed as
Measuring Point Elasticity on a Linear Demand Curve
To illustrate the measurement of point elasticity of a linear demand curve, let us
suppose that a linear demand curve is given by MN in Fig. 2.4 and that we want to measure
elasticity at point P.
Let us now substitute the values from Fig. 2.4 in eq. II. As it is obvious from the
figure, P = PQ and Q = OQ. What we need now is to find the values for δQ and δP. These
values can be obtained by assuming a very small decrease in the price. However, it will be
difficult to depict these changes in the figure as and hence Q –O. There is however an easier
way to find the value for δQ/δP. In derivative given the slope of the demand curve MN. The
slope of demand curve MN, at point P is geometrically given by QN/PQ. That is, may be
proved as follows. If we draw a horizontal line from P and to the vertical -.here will be three
triangles.
Since at point P, P=PQ and Q=OQ, substituting these values in eq. II, (ignoring
the minus sign), we get
Geometrically,
MON, MRP and PQN (Fig. 3.1) in which MON and PQN are right angles.
Therefore, the other corresponding angles of the triangles will always be equal and hence,
MON, MRP and PQN are similar triangles. According to geometrical properties of similar triangles, the ratio of any two sides of
similar triangle is always equal to the ratio of corresponding sides of the other sides.
Therefore, in PQN and MRP,
It follows that at mid-point of a linear demand curve, e = 1, as shown at point P in Fig.
2.6, because both lower and upper segments are equal (i.e., PN = PM) at any other point to
the left of point P, e > I and at any point to the right of point.
Price Elasticity at Terminal Points
The price elasticity at terminal point N equals 0 i.e. at point N, e = 0. At terminal
point M, however, price-elasticity is undefined, though most texts show that at terminal
point M, e = ∞. According to William J. Baumol, a Nobel Prize winner, price elasticity at
upper terminal point of the demand curve is undefined. It is undefined because measuring
elasticity at terminal point (M) involves division of zero and division by-zero is undefined. In
his own words, “Here the elasticity is not even defined because an attempt to evaluate the fraction p/x at that point forces us to commit the sign of dividing by zero. The reader who
has forgotten why division by zero is immoral may recall that division is the reverse
operation of multiplication. Hence, in seeking the quotient c = a/b we look for a number, c,
which when multiplied by b gives us the number a, i.e., for which cb = a. But if a is not zero,
say a = 5 and b is zero, there is no such number because there is no c such that c x 0 = 5”.
(B) MEASURING ARC ELASTICITY
The concept of point elasticity is pertinent where change in price and the resulting
change in quantity are infinite or small. However, where change in price and the consequent
hunger in demand is substantial, the concept of arc elasticity is the relevant concept. Arc
elasticity is a measure of the average of responsiveness of the quantity demanded to a
substantial change in the price. In other words, the measure of price elasticity of demand
between two finite points on a demand curve is known as arc activity. For example, the
measure of elasticity between points J and K (Fig. 2.7) is: the measure of arc elasticity. The
movement from point J to K along the demand curve D) shows a fall in price from Rs 25 to Rs
10 so that AP = 25 - 10 = 15. The consequent increase in demand, AQ = 30 - 50 = - 20. The arc
elasticity between point J and K and (moving from J to K) can be obtained by substituting
these values in the elasticity formula.
method does not give one measure of elasticity.
Determinants of Demand
Price elasticity of demand fluctuates from commodity to commodity. While the
demand of some commodities is highly elastic, the demand for others is highly inelastic. In
this section, we will describe the main determinants of the price elasticity of demand.
1. Availability of Substitutes
One of the most significant determinants of elasticity of demand for a commodity is
the availability of its substitutes. Closer the substitute, greater is the elasticity of demand for
the commodity. For instance, coffee and tea could be regarded as close substitutes for one
another. Thus, if price of one of these goods rises, its demand reduces more than the
proportionate rise in its price as consumers switch over to the relatively lower-priced
substitute. Moreover, broader the choice of the substitutes, greater is the elasticity. E.g.
soaps, washing powder, toothpastes, shampoos, etc. are available in several brands; each
brand is a close substitute for the other. Thus, the price-elasticity of demand for each brand
will be to a large extent greater than the general commodity. In contrast, sugar and salt do
not have their close substitute and for this reason their price-elasticity is lower.
2. Nature of Commodity
The nature of a commodity as well has an effect on the price elasticity of its demand.
Commodities can be categorised as luxuries, comforts and necessities, on the basis of their
nature. Demand for luxury goods (e.g., luxury cars, decorative items, etc.) are more elastic
than the demand for other types of goods as consumption of luxury goods can be set aside
or delayed when their prices increase. In contrast, consumption of essential goods, (e.g.,
sugar, clothes, vegetables, etc.) cannot be delayed and for this reason their demand is
inelastic. Demand for comforts is usually more elastic than that for necessities and less elastic than the demand for luxuries. Commodities may also be categorised as durable goods
and perishable or non-durable goods. Demand for durable goods is more elastic than that
for non-durable goods, as when the prices of the former rises, people either get the old one
fixed rather than substituting it or buy ‘second hand’ goods.
3. Proportion of Income Spent on a Commodity
Another aspect that has an impact on the elasticity of demand for a commodity is the
proportion of income, which consumers use up on a specific commodity. If proportion of
income spent on a commodity is extremely little, its demand will be less elastic and vice
versa. Characteristic examples of such commodities are sugar, matches, books, washing
powder etc., which use a very tiny proportion of the consumer’s income. Demand for these
goods is usually inelastic as a rise in the price of such goods does not largely have an effect
on the consumer’s consumption pattern and the overall purchasing power. Thus, people
continue to buy approximately the same quantity even at the time their price rises.
4. Time Factor
Price-elasticity of demand relies moreover on the time which consumers take to
amend to a new price: longer the time taken, greater is the elasticity. As each year passes,
consumers are capable of altering their spending pattern to price changes. For instance, if
the price of bikes falls, demand may not rise instantaneously unless people acquire surplus
buying capacity. In the end nevertheless people can alter their spending pattern so that they
can purchase a car at a (new) lower price.
5. Range of Alternative Uses of a Commodity
Broader the range of alternative uses of a commodity, higher the price elasticity of its
demand intended for the fall in price however less elastic for the increase in price. As the
price of a versatile commodity falls, people broaden their consumption to its other uses.
Thus, the demand for such a commodity usually rises more than the proportionate fall in its
price. E.g., milk can be consumed as it is, it could be transformed into curd, cheese, ghee and
buttermilk. The demand for milk will thus be extremely elastic for fall in their price. Likewise,
electricity can be utilised for lighting, cooking, heating, as well as for industrial purposes.
Thus, demand for electricity is extremely price elastic for fall in its price. For this reason,
nevertheless, demand for such goods is inelastic for the increase in their price.
6. The Proportion of Market Supplied
Price elasticity of market demand furthermore relies on the proportion of the market
supplied at the determined price. If less than half of the market is supplied at the determined price, elasticity of demand will be higher if more than half of the market is
supplied. i.e. demand curve is more elastic at the upper half than at the lower half. Demand Forecasting
Demand forecasting entails forecasting and estimating the quantity of a product or
service that consumers will purchase in future. It tries to evaluate the magnitude and
significance of forces that will affect future operating conditions in an enterprise. Demand
forecasting involves use of various formal and informal forecast techniques such as informed
guesses, use of historical sales data or current field data gathered from representative
markets. Demand forecasting may be used in making pricing decisions, in assessing future
capacity requirements, or in making decisions on whether to enter a new market. Thus,
demand forecasting is estimation of future demand. According to Cardiff and Still, “Demand
forecasting is an estimate of sales during a specified future period based on a proposed
marketing plan and a set of particular uncontrollable and competitive forces". As such,
demand forecasting is a projection of firm’s expected future demands.
2.6.1 DEMAND FORECAST AND SALES FORECAST
Due to the dynamic and complex nature of marketing phenomenon, demand
forecasting has become an important and regular business exercise. It is essential for profit
maximisation and the survival and expansion of a business. However, before selecting any
vendor a retailer should well understand the requirement and the importance of demand
forecasting. In management circles, demand forecasting and sales forecasting are used
interchangeably. Sales forecasts are first approximations in production and forward
planning. These provide a platform upon which plans could be prepared and amendments
may be made. According to American Marketing Association, “Sales forecast is an estimate
of sales in monetary or physical units for a specified future period under a proposed
business plan or programmer or under an assumed set of ‘economic and other environment
forces, planning premises, outside business/ antiquate which the forecast or-estimate is
made”. 2.6.2 COMPONENTS OF DEMAND FORECASTING SYSTEM
• Market research operations to procure relevant and reliable information about the
trends in market.
• A data processing and analysing system to estimate and evaluate the sales performance
in various markets.
• Proper co-ordination of steps (i) and (ii) above
• Placing the findings before the top management for making final decisions.
2.6.3 OBJECTIVES OF DEMAND FORECAST
1. Short Term Objectives
a. Drafting of Production Policy: Demand forecasts facilitate in drafting appropriate
production policy so that there may not be any space between future demand and
supply of a product. This can in addition ensure:
• Routine Supply of Materials: Demand forecasting assists in figuring out the
preferred volume of production. The essential prerequisite of raw materials in
future can be calculated on the basis of such forecasts. This guarantees regular
and continuous supply of the materials in addition to managing the amount of
supply at the economic level.
62 Managerial Economics
• Best Possible Use of Machines: Demand forecasting in addition expedites cutting
down inactive capacity because only the necessary amount of machines and
equipments are set up to meet future demands.
• Regular Availability of Labour: As soon as demand forecasts are made, supplies
of the necessary amount of skilled and unskilled workers can be organised well
beforehand to meet the future production plans.
b. Drafting of Price Policy: Demand forecasts facilitate the management to prepare a
few suitable pricing systems, so that the level of price does not rise and fall to a great
extent during depression or inflation.
c. Appropriate Management of Sales: Demand forecasts are made area wise and after
that the sales targets for different regions are set in view of that. This abets the
calculation of sales performances.
d. Organising Funds: On the basis of demand forecast, an individual can find out the
monetary requirements of the organisation in order to bring about the desired
output. This can make it possible to cut down on the expenditure of acquiring funds.
2. Long Term Goals: If the demand forecast period is more than a year, in that case it is
termed as long term forecast. The following are the key goals of such forecasts:
a. To settle on the production capacity: Long term decisions are entwined with
capacity variations by adding or discarding capacity in the form of capital assets -
manufacturing plants, new technology implementation etc. Size of the organisation
should such that output matches with the sales requirements. Organisations that are
extremely small or large in size might not be in the financial interest of the company.
Inadequate capability can hasten declining delivery performance, needless rise in
work-in-process and disturb sales personnel and those in the production unit.
Nevertheless, surplus capacity can be expensive and pointless. The incompetence to
appropriately deal with capacity can be an obstacle to attaining the best possible
performance. By examining the demand pattern for the product as well as the
forecasts for the future, the company can prepare for a company's output of the
desired capacity.
b. Labour Requirements: Spending on labour is one of the most vital elements of cost
of production. Dependable and correct demand forecasts can facilitate the
management to evaluate suitable labour requirements. This can ensure finest labour
supply and uninterrupted production procedures.
c. Production Planning: Long term production planning can aid the management in
organising long term finances on practical terms and conditions.
The study of long term sales is accorded greater importance as compared with shortterm
sales. Long term sales forecast facilitates the management to take a few policy
decisions of huge importance and any mistake carried out in this could be extremely
different or costly to be corrected.
Therefore, the complete success of an organisation usually is contingent upon the
quality and authenticity of sales forecasting methods.
2.6.4 IMPORTANCE OF DEMAND FORECAST
1. Management Decisions: An effective demand forecast facilitates the management to
take appropriate steps in factors that are pertinent to decision making such as plant
capacity, raw-material requisites, space and building requirements and availability of
labour and capital. Manufacturing schedules can be drafted in compliance with the
demand requisites; in this manner cutting down on the inventory, production and other
related costs.
2. Evaluation: Demand forecasting furthermore smoothes the process of evaluating the
efficiency of the sales department.
3. Quality and Quantity Controls: Demand forecasting is an essential and valuable
instrument in the control of the management of an organisation to provide finished
goods of correct quality and quantity at the correct time with the least amount of
expenditure.
4. Financial Estimates: As per the sales level as well as production functions, the financial
requirements of an organisation can be calculated using various techniques of demand
forecasting. In addition, it needs a little time to acquire revenue on practical terms. Sales
forecasts will, as a result, make it possible for arranging adequate resources on practical
terms and in advance as well.
5. Avoiding Surplus and Inadequate Production: Demand forecasting is necessary for the
old and new organisations. It is somewhat essential if an organisation is engaged in large
scale production of goods and the development period is extremely time-consuming in
the course of production. In such situations, an estimate regarding the future demand is
essential to avoid inadequate and surplus production.
6. Recommendations for the future: Demand forecast for a specific commodity
furthermore provides recommendations for demand forecast of associated industries.
E.g. the demand forecast for the vehicle industry aids the tyre industry in calculating the
demand for two wheelers, three wheelers and four wheelers.
7. Significance for the government: At the macro-level, demand forecasting is valuable to
the government as it aids in determining targets of imports as well as exports for various
products and preparing for the international business.
2.6.5 METHODS OF DEMAND FORECAST
No demand forecasting method is 100% precise. Collective forecasts develop
precision and decrease the probability of huge mistakes.
1. Methods that relay on Qualitative Assessment:
Forecasting demand based on expert opinion. Some of the types in this method are:
• Unaided judgment
• Prediction market
• Delphi technique
• Game theory
• Judgmental bootstrapping
• Simulated interaction
• Intentions and expectations surveys
• Conjoint analysis
2. Methods that rely on quantitative data:
• Discrete event simulation
• Extrapolation
• Quantitative analogies
• Rule-based forecasting
• Neural networks
• Data mining
• Causal models
• Segmentation
2.6.6 SOME DEMAND FORECASTING METHODS
A. QUALITATIVE ASSESSMENT
1. Prediction markets: These are speculative markets fashioned with the intention of
making predictions. Assets that are produced possess an ultimate cash worth bound to a
specific event (e.g. who will win the next election) or situation (e.g., total sales next
quarter). The present market prices can then be described as forecasts of the likelihood
of the event or the estimated value of the situation. Prediction markets are as a result
planned as betting exchanges, without any kind of compromise for the bookmaker.
People who buy low and sell high are rewarded for improving the market prediction,
while those who buy high and sell low are punished for degrading the market prediction.
Evidence so far suggests that prediction markets are at least as accurate as other
institutions predicting the same events with a similar pool of participants.
Many prediction markets are open to the public. Betfair is the world's biggest
prediction exchange, with around $28 billion traded in 2007. Intrade is a for-profit company
with a large variety of contracts not including sports. The Iowa Electronic Markets is an
academic market examining elections where positions are limited to $500. Trade Sports are
prediction markets for sporting events.
2. Delphi method: This is a systematic, interactive forecasting method which relies on a
panel of experts. The experts answer questionnaires in two or more rounds. After each
round, a facilitator provides an anonymous summary of the experts’ forecasts from the
previous round as well as the reasons they provided for their judgments. Thus, experts
are encouraged to revise their earlier answers in light of the replies of other members of
their panel. It is believed that during this process the range of the answers will decrease
and the group will converge towards the 'correct' answer. Finally, the process is stopped
after a pre-defined stop criterion (e.g. number of rounds, achievement of consensus,
stability of results) and the mean or median scores of the final rounds determine the
results.
3. Game theory: Game theory is a branch of applied mathematics that is used in the social
sciences, most notably in economics, as well as in biology (particularly evolutionary
biology and ecology), engineering, political science, international relations, computer
science and philosophy. Game theory attempts at mathematically capturing behaviour in
strategic situations or games in which an individual's success in making choices depends
on the choices of others. While initially developed to analyse competitions in which one
individual does better at another's expense (zero sum games), it has been expanded to
treat a wide class of interactions, which are classified according to several criteria.
Today, "game theory is a sort of umbrella or 'unified field' theory for the rational side of
social science, where 'social' is interpreted broadly, to include human as well as nonhuman
players (computers, animals, plants)" (Aumann 1987).
Traditional applications of game theory aim at finding equilibrium in these games. In
equilibrium, each player of the game has adopted a strategy that they are unlikely to
change. Many equilibrium concepts have been developed (most famously the Nash
equilibrium) in an endeavor to capture this idea. These equilibrium concepts are differently
motivated depending on the field of application, although they often overlap or coincide.
This methodology is not without criticism and debates continue over the appropriateness of
particular equilibrium concepts, the appropriateness of equilibrium altogether and the
usefulness of mathematical models more generally.
Although, some developments occurred before it, the field of game theory came into
being with Émile Borel's researches in his 1938 book Applications aux Jeux des Hazard and
was followed by the 1944 book Theory of Games and Economic Behavior by John von
Neumann and Oskar Morgenstern. This theory was developed extensively in the 1950s by
many scholars. Game theory was later explicitly applied to biology in the 1970s, although
similar developments go back at least as far as the 1930s. Game theory has been widely
recognised as an important tool in many fields. Eight game theorists have won the Nobel
Memorial Prize in Economic Sciences and John Maynard Smith was awarded the Crafoord
Prize for his application of game theory to biology.
The games studied in game theory are well-defined mathematical objects. A game
consists of a set of players, a set of moves (or strategies) available to those players and a
specification of payoffs for each combination of strategies. Most cooperative games are
presented in the characteristic function form, while the extensive and the normal forms are
used to define non-cooperative games.
QUANTITATIVE DATA
1. Discrete-event simulation: The operation of a system is represented as a chronological
sequence of events. Each event occurs at an instant in time and marks a change of state
in the system. For example, if an elevator is simulated, an event could be "level 6 button
pressed", with the resulting system state of "lift moving" and eventually (unless one
chooses to simulate the failure of the lift) "lift at level 6".
A common exercise in learning how to build discrete-event simulations is to model a
queue, such as customers arriving at a bank to be served by a teller. In this example, the
system entities are CUSTOMER-QUEUE and TELLERS. The system events are CUSTOMERARRIVAL
and CUSTOMER-DEPARTURE. (The event of TELLER-BEGINS-SERVICE can be part of
the logic of the arrival and departure events.) The system states, which are changed by these
events, are NUMBER-OF-CUSTOMERS-IN-THE-QUEUE (an integer from 0 to n) and TELLERSTATUS
(busy or idle). The random variables that need to be characterised to model this
system stochastically are CUSTOMER-INTERARRIVAL-TIME and TELLER-SERVICE-TIME.
2. Rule based forecasting: Rule-based forecasting (RBF) is a proficient method that
incorporates judgment as well as statistical techniques to merge forecasts. It involves
condition-action statements (rules) where conditions are based on the aspects of the
past progress and upon knowledge of that specific area. These rules give in to the load
suitable to the forecasting condition as described by the circumstances. In fact, RBF uses
structured judgment as well as statistical analysis to modify predictive techniques to the
condition. Practical outcomes on several sets of the past progress indicate that RBF
generates forecasts that are more precise than those generated by the conventional
predictive techniques or by an equal-load amalgamation of predictions.
3. Data mining: Data mining is the process of extracting patterns from data. Data mining is
seen as an increasingly important tool by modern business to transform data into an
informational advantage. It is currently used in a wide range of profiling practices, such
as marketing, surveillance and scientific discovery.
Data mining commonly involves four classes of tasks:
• Clustering - is the task of discovering groups and structures in the data that are in some
way or another "similar", without using known structures in the data.
• Classification - is the task of generalising known structure to apply to new data. For
example, an email program might attempt to classify an email as legitimate or spam.
Common algorithms include decision tree learning, nearest neighbor, naive Bayesian
classification, neural networks and support vector machines.
• Regression - Attempts to find a function which models the data with the least error.
• Association rule learning - Searches for relationships between variables. For example a
supermarket might gather data on customer purchasing habits. Using association rule
learning, the supermarket can determine which products are frequently bought together
and use this information for marketing purposes. This is sometimes referred to as
market basket analysis.
2.6.7 METHODS OF ESTIMATION
1. Regression analysis: Regression analysis is the statistical technique that identifies the
relationship between two or more quantitative variables: a dependent variable whose
value is to be predicted and an independent or explanatory variable (or variables), about
which knowledge is available. The technique is used to find the equation that represents
the relationship between the variables. A simple regression analysis can show that the
relation between an independent variable X and a dependent variable Y is linear, using
the simple linear regression equation Y= a + bX (where a and b are constants). Multiple
regression will provide an equation that predicts one variable from two or more
independent variables, Y= a + bX1+ cX2+ dX3.
The steps in regression analysis are:
a. Construction of the causal model: The construction of an explanatory model is a
crucial step in the regression analysis. It must be defined with reference to the action
theory of the intervention. It is likely that several kinds of variable exist. In some
cases, they may be specially created, for example to take account of the fact that an
individual has benefited from support or not (a dummy variable, taking values 0 or
1). A variable may also represent an observable characteristic (having a job or not) or
an unobservable one (probability of having a job). The model may presume that a
particular variable evolves in a linear, logarithmic, exponential or other way. All the
explanatory models are constructed on the basis of a model, such as the following,
for linear regression:
Y = β0 + β1X1 + β2X2 + …. + β kXk + ε, where
Y is the change that the programme is mainly supposed to produce (e.g. employment
of trainees)
X1-k are independent variables likely to explain the change.
β0-k are constants and
ε is the error term
Phenomena of co-linearity weaken the explanatory power. For example, when
questioning women about unemployment, if they have experienced periods of previous
unemployment which are systematically longer than those of men, it will not be possible to
separate the influence of the two explanatory factors: gender and duration of previous
unemployment.
b. Construction of a sample: To apply multiple regression, a large sample is usually
required (ideally between 2,000 to 15,000 individuals). Note that for time series data,
much less is needed.
c. Data collection: Reliable data must be collected, either from a monitoring system,
from a questionnaire survey or from a combination of both.
d. Calculation of coefficients: Coefficients can be calculated relatively easily, using
statistical software that is both affordable and accessible to PC users.
e. Test of the model: The model aims to explain as much of the variability of the
observed changes as possible. To check how useful a linear regression equation is,
tests can be performed on the square of the correlation coefficient r. This tells us
what percentage of the variability in the y variable can be explained by the x variable.
A correlation coefficient of 0.9 would show that 81% of the variability in Y is captured
by the variables X1-k used in the equation. The part that remains unexplained
represents the residue (ε). Thus, the smaller the residue better is the quality of the
model and its adjustment. The analysis of residues is a very important step: it is at
this stage that one sees the degree to which the model has been adapted to the
phenomena one wants to explain. It is the residue analysis that also enables one to
tell whether the tool has made it possible to estimate the effects in a plausible way
or not. If significant anomalies are detected, the regression model should not be
used to estimate effects and the original causal model should be re-examined, to see
if further predictive variables can be introduced.
2. Time series analysis: An analysis of the relationship between variables over a period of
time. Time-series analysis is useful in assessing how an economic or other variable
changes over time. For example, one may conduct a time-series analysis on a stock, sales
volumes, interest rates and quality measurements etc.
Methods for time series analyses may be divided into two classes: frequency-domain
methods (spectral analysis and recently wavelet analysis) and time-domain methods
(auto-correlation and cross-correlation).
a. Frequency domain: Frequency domain is a term used to describe the domain for
analysis of mathematical functions or signals with respect to frequency, rather than
time. A time-domain graph shows how a signal changes over time. Whereas a
frequency-domain graph shows how much of the signal lies within each given
frequency band over a range of frequencies. A frequency-domain representation can
also include information on the phase shift that must be applied to each sinusoid in
order to be able to recombine the frequency components to recover the original
time signal.
b. Time domain: Time domain is a term used to describe the analysis of mathematical
functions, or physical signals, with respect to time. In the time domain, the signal or
function's value is known for all real numbers, for the case of continuous time, or at
various separate instants in the case of discrete time. An oscilloscope is a tool
commonly used to visualise real-world signals in the time domain.
3. Utility analysis: A subset of consumer demand theory that analysis consumer behavior
and market demand using total utility and marginal utility. The key principle of utility
analysis is the law of diminishing marginal utility, which offers an explanation for the law
of demand and the negative slope of the demand curve. The main focus of utility analysis
is on the fulfillment of wants and needs acquired by the utilization of goods. It
additionally facilitates in getting the knowledge of market demand as well as the law of
demand. The law of demand by way of utility analysis states that consumers buy goods
that fulfill their wants and needs, i.e., create utility. Those goods that create more utility
are more important to consumers and therefore buyers are prepared to pay a higher
price. The main aspect to the law of demand is that the utility created falls when the
quantity consumed rises. As such, the demand price that buyers are prepared to pay falls
when the quantity demanded rises.
The law of diminishing marginal utility asserts that marginal utility or the
extra utility acquired from consuming a good, falls as the quantity consumed rises.
Basically, each extra good consumed is less fulfilling as compared to the previous one.
This law is mostly significant for awareness into market demand as well as the law of
demand.
a. Cardinal utility: A measure of utility, or satisfaction derived from the consumption of
goods and services that can be measured using an absolute scale. Cardinal utility
exists if the utility derived from consumption is measurable in the same way that
other physical characteristics--height and weight--are measured using a scale that is
comparable between people. There is little or no evidence to suggest that such
measurement is possible and is not even needed for modern consumer demand
theory and indifference curve analysis. Cardinal utility, however, is often employed
as a convenient teaching device for discussing such concepts as marginal utility and
utility maximisation.
b. Ordinal utility: A method of analysing utility, or satisfaction derived from the
consumption of goods and services, based on a relative ranking of the goods and
services consumed. With ordinal utility, goods are only ranked only in terms of more
or less preferred, there is no attempt to determine how much more one good is
preferred to another. Ordinal utility is the underlying assumption used in the analysis
of indifference curves and should be compared with cardinal utility, which
(hypothetically) measures utility using a quantitative scale.
Summary
Demand: "The demand for a commodity at a given price is the amount of it which
will be bought per unit of time at that price”.
Law of Demand: “The demand for a commodity increases with a fall in its price and
decreases with a rise in its price, other things remaining the same”. The Law of demand thus
merely states that the price and demand of a commodity are inversely related, provided all
other things remain unchanged or as economists put it ceteris paribus.
Assumptions to the Law of Demand: We can state the assumptions of the law of
demand as follows: (1) Income level should remain constant, (2) Tastes of the buyer should
not change, (3) Prices of other goods should remain constant, (4) No new substitutes for the
commodity, (5) Price rise in future should not be expected and (6) Advertising expenditure
should remain the same.
Why Demand Curve Slopes Downwards: The reasons behind the law of demand, i.e.,
inverse relationship between price and quantity demanded are following: (i) substitution
effect, (ii) income effect, (iii) diminishing marginal utility.
Market Demand: The total quantity which all the consumers of a commodity are
willing to buy at a given price per time unit, other things remaining the same, is known as
market demand for the commodity. In other words, the market demand for a commodity is
the sum of individual demands by all the consumers (or buyers) of the commodity, per time
unit and at a given price, other factors remaining the same.
Individual demand: The individual demand means the quantity of a product that an
individual can buy given its price. It implies that the individual has the ability and willingness
to pay.
Demand Function: Demand function is a mathematical expression of the law of
demand in quantitative terms. A demand function may produce a linear or curvilinear
demand curve depending on the nature of relationship between the price and quantity
demanded. The functional relationship between the demand for a commodity and its various determinants may be expressed mathematically as:
Dx = f (Px, Py, M, T, A, U) where, Dx = Quantity demanded for commodity X, f =
functional relation, Px = The price of commodity X, Py = The price of substitutes and
complementary goods, M = The money income of the consumer, T = The taste of the
consumer, A = The advertisement effects, U = Unknown variables or influences
Elasticity of Demand: The concept of elasticity of demand can be defined as the
degree of responsiveness of demand to given change in price of the commodity.
Methods of Measurement of Elasticity of Demand: By using three different
methods, elasticity of demand is measured.
• Ratio Method
• Expenditure Method
• Point Method
Demand Forecasting: According to Cardiff and Still, “Demand forecasting is an
estimate of sales during a specified future period based on a proposed marketing plan and a
set of particular uncontrollable and competitive forces’’.
Objectives of Demand Forecast: Following are the objectives of demand forecasting:
• Formulation of production policy
• Price policy formulation
• Proper control of sales
• Arrangement of finance
• To decide about the production capacity
• Labour requirements
• Production planning
GAME THEORY
Game theory is a branch of applied mathematics that is used in the social sciences,
most notably in economics, as well as in biology (particularly evolutionary biology and
ecology), engineering, political science, international relations, computer science and
philosophy. It attempts to capture behaviour mathematically in strategic situations or games
in which an individual's success in making choices depends on the choices of others.
While initially developed to analyse competitions in which one individual does better
at another's expense (zero sum games), it has been expanded to include a wide class of
interactions, which are classified according to several criteria.
2.1 Introduction
Demand theory evinces the relationship between the demand for goods and
services. Demand theory is the building block of the demand curve- a curve that establishes a relationship between consumer demand and the amount of goods available. Demand is shaped by the availability of goods, as the quantity of goods increases in the market the demand and the equilibrium price for those goods decreases as a result.
Demand theory is one of the core theories of microeconomics and consumer
behaviour. It attempts at answering questions regarding the magnitude of demand for a product or service based on its importance to human wants. It also attempts to assess how demand is impacted by changes in prices and income levels and consumers preferences/utility. Based on the perceived utility of goods and services to consumers,
companies are able to adjust the supply available and the prices charged.
In economics, demand has a specific meaning distinct from its ordinary usage. In
common language we treat ‘demand’ and ‘desire’ as synonymously. This is incongruent from its use in economics. In economics, demand refers to effective demand which implies three things:
Desire for a commodity
Sufficient money to purchase the commodity, rather the ability to pay
Willingness to spend money to acquire that commodity
This substantiates that a want or a desire does not develop into a demand unless it is supported by the ability and the willingness to acquire it. For instance, a person may desire to own a scooter but unless he has the required amount of money with him and the willingness to spend that amount on the purchase of a scooter, his desire shall not become a demand. The following should also be noted about demand:
Demand always alludes to demand at price. The term ‘demand’ has no meaning
unless it is related to price. For instance, the statement, 'the weekly demand for potatoes in city X is 10,000 kilograms' has no meaning unless we specify the price at which this quantity is demanded.
Demand always implies demand per unit of time. Therefore, it is vital to specify the period for which the commodity is demanded. For instance, the statement that demand for potatoes in city X at Rs. 8 per kilogram is 10,000 kilograms again has no meaning, unless we state the period for which the quantity is being demanded. A complete statement would therefore be as follows: 'The weekly demand for potatoes in city X at Rs. 8 per kilogram is 10,000 kilograms'. It is necessary to specify the period and the price because demand for a commodity will be different at different prices of that commodity and for different periods of time. Thus, we can define demand as follows:
“The demand for a commodity at a given price is the amount of it which will be bought per unit of time at that price”.
2.2 Theory of Demand
2.2.1 ESSENTIALS OF DEMAND
1. An Effective Need: Effective need entails that there should be a need supported by the capacity and readiness to shell out. Hence, there are three basics of an effective need:
a. The individual should have a need to acquire a specific product.
b. He should have sufficient funds to pay for that product.
c. He should be willing to part with these resources for that commodity.
2. A Specific Price: A proclamation concerning the demand of a product without
mentioning its price is worthless. For example, to state that the demand of cars is 10,000 is worthless, unless expressed that the demand of cars is 10,000 at a price of Rs. 4,00,000 each.
3. A Specific Time: Demand must be assigned specific time. For example, it is an
incomplete proclamation to state that the demand of air conditioners is 4,000 at the price of Rs. 12,800 each. The statement should be altered to say that the demand of air conditioners during summer is 4,000 at the price of Rs. 12,800 each.
4. A Specific Place: The demand must relate to a specific market as well. For example, every year in the town of Dehradun, the demand for school bags is 4,000 at a price of Rs. 200.
Hence, the demand of a product is an effective need, which demonstrates the
quantity of a product that will be bought at a specific price in a specific market at some stage in a specific period. Nevertheless, the significance of a specific market or place is not as significant as the price and time period for which demand is being measured.
2.2.2 LAW OF DEMAND
We have considered various factors that fashion the demand for a commodity. As explained the first and the most important factor that determines the demand of a commodity is its price. If all other factors (noted above) remain constant, it may be said that as the price of a commodity increases, its demand decreases and as the price of a commodity decreases its demand increases. This is a general behaviour observed in a market. This gives us the law of demand:
“The demand for a commodity increases with a fall in its price and decreases with a rise in its
price, other things remaining the same”.
The law of demand thus merely states that the price and demand of a commodity are inversely related, provided all other things remain unchanged or as economists put it ceterisparibus.
Assumptions of the Law of Demand
The above statement of the law of demand, demonstrates that that this law operates only when all other things remain constant. These are then the assumptions of the law of demand. We can state the assumptions of the law of demand as follows:
1. Income level should remain constant: The law of demand operates only when the
income level of the buyer remains constant. If the income rises while the price of the commodity does not fall, it is quite likely that the demand may increase. Therefore, stability in income is an essential condition for the operation of the law of demand.
2. Tastes of the buyer should not alter: Any alteration that takes place in the taste of the consumers will in all probability thwart the working of the law of demand. It often happens that when tastes or fashions change people revise their preferences. As a consequence, the demand for the commodity which goes down the preference scale of the consumers declines even though its price does not change.
3. Prices of other goods should remain constant: Changes in the prices of other goods often impinge on the demand for a particular commodity. If prices of commodities for which demand is inelastic rise, the demand for a commodity other than these in all probability will decline even though there may not be any change in its price. Therefore, for the law of demand to operate it is imperative that prices of other goods do not change.
4. No new substitutes for the commodity: If some new substitutes for a commodity
appear in the market, its demand generally declines. This is quite natural, because with the availability of new substitutes some buyers will be attracted towards new products and the demand for the older product will fall even though price remains unchanged.
Hence, the law of demand operates only when the market for a commodity is not
threatened by new substitutes.
5. Price rise in future should not be expected: If the buyers of a commodity expect that its price will rise in future they raise its demand in response to an initial price rise. This behaviour of buyers violates the law of demand. Therefore, for the operation of the law of demand it is necessary that there must not be any expectations of price rise in the future.
6. Advertising expenditure should remain the same: If the advertising expenditure of a firm increases, the consumers may be tempted to buy more of its product. Therefore, the advertising expenditure on the good under consideration is taken to be constant.
Desire of a person to purchase a commodity is not his demand. He must possess
adequate resources and must be willing to spend his resources to buy the commodity.
Besides, the quantity demanded has always a reference to ‘a price’ and ‘a unity of time’. The quantity demanded referred to ‘per unit of time’ makes it a flow concept. There may be some problems in applying this flow concept to the demand for durable consumer goods like house, car, refrigerators, etc. However, this apparent difficulty may be resolved by considering the total service of a durable good is not consumed at one point of time and its utility is not exhausted in a single use. The service of a durable good is consumed over time.
At a time, only a part of its service is consumed. Therefore, the demand for the services of durable consumer goods may also be visualised as a demand per unit of time. However, this problem does not arise when the concept of demand is applied to total demand for a consumer durable. Thus, the demand for consumer goods also is a flow concept.
Demand Schedule
The law of demand can be illustrated through a demand schedule. A demand
schedule is a series of quantities, which consumers would like to buy per unit of time at
different prices. To illustrate the law of demand, an imaginary demand schedule for tea is
given in Table 2.1. It shows seven alternative prices and the corresponding quantities
(number of cups of tea) demand per day. Each price has a unique quantity demanded,
associated with it. As the price per cup of tea decreases, daily demand for tea increases, in
accordance with the law of demand.
Demand Curve
The law of demand can also be presented through a curve called demand curve.
Demand curve is a locus of points showing various alterative price-quantity combinations. It
shows the quantities of a commodity that consumers or users would buy at difference prices
per unit of time under the assumptions of the law of demand. An individual demand curve
for tea as given in Fig. 2.1 can be obtained by plotting the data give in Table 2.1.
the demand curve DD’. Each point on the demand curve DD’ shows a unique price-quantity
combination. The combinations read in alphabetical order should decreasing price of tea
and increasing number of cups of tea demanded per day. Price quantity combinations in
reverse order of alphabets illustrate increasing price of tea per cup and decreasing number
of cups of tea per day consumed by an individual. The whole demand curve shows a
functional relationship between the alternative price of a commodity and its corresponding
quantities, which a consumer would like to buy during a specific period of item—per day,
per week, per month, per season, or per year. The demand curve shows an inverse
relationship between price and quantity demanded. This inverse relationship between price
and quantity demanded results in the demand curve sloping downward to the right.
• Why does the demand curve slope downwards
As Fig. 2.1 shows, demand curve slopes downward to the right. The downward slope
of the demand curve reads the law of demand i.e. the quantity of a commodity demanded
per unit of time increases as its price falls and vice versa.
The reasons behind the law of demand i.e. inverse relationship between price and
quantity demanded are following:
Substitution Effect: When the price of a commodity falls it becomes relatively cheaper if
price of all other related goods, particularly of substitutes, remain constant. In other
words, substitute goods become relatively costlier. Since consumers substitute cheaper
goods for costlier ones, demand for the relatively cheaper commodity increases. The
increase in demand on account of this factor is known as substitution effect.
Income Effect: As a result of fall in the price of a commodity, the real income of its
consumer increase at least in terms of this commodity. In other words, his/her
purchasing power increases since he is required to pay less for the same quantity. The
increase in real income (or purchasing power) encourages demand for the commodity
with reduced price. The increase in demand on account of increase in real income is
known as income effect. It should however be noted that the income effect is negative in
case of inferior goods. In case, price of an inferior good accounting for a considerable
proportion of the total consumption expenditure falls substantially, consumers’ real
income increases: they become relatively richer. Consequently, they substitute the
superior good for the inferior ones, i.e., they reduce the consumption of inferior goods.
Thus, the income effect on the demand for inferior goods becomes negative. Diminishing Marginal Utility: Diminishing marginal utility as well is to be held
responsible for the rise in demand for a product when its price declines. When an
individual purchases a product, he swaps his money revenue with the product in order to
increase his satisfaction. He continues to purchase goods and services as long as the
marginal utility of money (MUm) is lesser than the marginal utility of the commodity
(MUC). Given the price of a commodity, he modifies his purchase so that MUC = MUm.
This plan works well under both Marshallian assumption of constant MUm as well as
Hicksian assumption of diminishing MUm. When price falls, (MUm = Pc) < MUC. Thus,
equilibrium state is upset. To get back his equilibrium state, i.e., MUm = PC, = MUC, he
buys more quantities of the commodity. For, when the supply of a commodity rises, its
MU falls and once again MUm = MUC. For this reason, demand for a product rises when
its price falls.
• Exceptions to the Law of Demand
The law of demand does not apply to the following cases:
Apprehensions about the future price: When consumers anticipate a constant rise in
the price of a long-lasting commodity, they purchase more of it despite the price rise.
They do so with the intention of avoiding the blow of still higher prices in the future.
Likewise, when consumers expect a substantial fall in the price in the future, they delay
their purchases and hold on for the price to decrease to the anticipated level instead of
purchasing the commodity as soon as its price decreases. These kinds of choices made by
the consumers are in contradiction of the law of demand.
Status goods: The law does not concern the commodities which function as a ‘status
symbol’, add to the social status or exhibit prosperity and opulence e.g. gold, precious
stones, rare paintings and antiques, etc. Rich people mostly purchase such goods as they
are very costly.
Giffen goods: An exception to this law is the typical case of Giffen goods named after Sir
Robert Giffen (1837-1910). 'Giffen goods' does not represent any particular commodity.
It could be any low-grade commodity which is cheap as compared to its superior
alternatives, consumed generally by the lower income group families as an important
consumer good. If price of such goods rises (price of its alternative remaining stable), its
demand escalates instead of falling. E.g. the minimum consumption of food grains by a
lower income group family per month is 30 kgs consisting of 20 kgs of bajra (a low-grade
good) at the rate of Rs 10 per kg and 10 kgs of wheat (a high quality good) at Rs. 20 per
kg. They have a fixed expenditure of Rs. 400 on these items. However, if the price of bajra rises to Rs. 12 per kg the family will be compelled to decrease the consumption of
wheat by 5 kgs and add to that of bajra by the same quantity so as to meet its minimum
consumption requisite within Rs. 400 per month. No doubt, the family's demand for
bajra rises from 20 to 25 kgs when its price rises.
• The Market Demand Curve
The quantity of a commodity which an individual is willing to buy at a particular price
of the commodity during a specific time period, given his money income, his taste and prices
of substitutes and complements, is known as individual demand for a commodity. The total
quantity which all the consumers of a commodity are willing to buy at a given price per time
unit, other things remaining the same, is known as market demand for the commodity. In
other words, the market demand for a commodity is the sum of individual demands by all
the consumers (or buyers) of the commodity, per time unit and at a given price, other
factors remaining the same. For instance, suppose there are three consumers (viz., A, B, C)
of a commodity X and their individual demand at different prices is of X as given in Table 2.2.
The last column presents the market demand i.e. the aggregate of individual demand by
three consumers at different prices.
curves. The individual demand schedules plotted graphically and summed up horizontally
gives the market demand curve as shown in Fig. 2.2. The individual demands for commodity X are given by DA, DB and Dc, respectively. The
horizontal summation of these individual demand curves results into the market demand
curve (DM) for the commodity X. The curve DM represents the market demand curve for
commodity X when there are only three consumers of the commodity.
The functional relationship between the demand for a commodity and its various
determinants may be expressed mathematically in terms of a demand function, thus:
Dx = f (Px, Py, M, T, A, U) where,
Dx = Quantity demanded for commodity X.
f = functional relation.
Px = The price of commodity X.
Py = The price of substitutes and complementary goods.
M = The money income of the consumer.
T = The taste of the consumer.
A = The advertisement effects.
U = Unknown variables or influences.
The above-stated demand function is a complicated one. Again, factors like tastes
and unknown influences are not quantifiable. Economists, therefore, adopt a very simple
statement of demand function, assuming all other variables, except price, to be constant.
Thus, an over-simplified and the most commonly stated demand function is: Dx = f (Px),
which connotes that the demand for commodity X is the function of its price. The traditional
demand theory deals with this demand function specifically.
It must be noted that by demand function, economists mean the entire functional
relationship i.e. the whole range of price-quantity relationship and not just the quantity
demanded at a given price per unit of time. In other words, the statement, 'the quantity
demanded is a function of price' implies that for every price there is a corresponding
quantity demanded.
To put it differently, demand for a commodity means the entire demand schedule,
which shows the varying amounts of goods purchased at alternative prices at a given time. Shift in Demand Curve
When demand curve changes its position retaining its shape (though not necessarily),
the change is known as shift in demand curve.
Let’s suppose that the demand curve D2 in Fig. 2.3 is the original demand curve for
commodity X. As shown in the figure, at price OP2 consumer buys OQ2 units of X, other
factors remaining constant. If any of the other factors (e.g., consumer’s income) changes, it
will change the consumer’s ability and willingness to buy commodity X. For example, if
consumer’s disposable income decreases, say, due to increase in income tax, he may be able
to buy only OQ1 units of X instead of OQ2 at price OP2 (This is true for the whole range of
price of X) the consumers would be able to buy less of commodity X at all other prices. This
will cause a downward shift in demand curve from D2 to D1. Similarly, increase in disposable
income of the consumer due to reduction in taxes may cause an upward shift from D2 to D3.
Such changes in the position of the demand curve are known as shifts in demand curve.
Reasons for Shift in Demand Curve
Shifts in a price-demand curve may take place owing to the change in one or more of
other determinants of demand. Consider, for example, the decrease in demand for
commodity X by Q1Q2 in Fig 2.3. Given the price OP1, the demand for X might have fallen
from OQ2 to OQ1 (i.e., by Q1Q2) for any of the following reasons:
• Fall in the consumer’s income so that he can buy only OQ1 of X at price OP2—
it is income effect.
• Price of X’s substitute falls so that the consumers find it beneficial to substitute Q1Q2 of X with its substitute—it is substitution effect.
• Advertisement made by the producer of the substitute, changes consumer’s taste or
preference against commodity X so much that they replace Q1Q2 of X with its substitute,
again a substitution effect.
• Price of complement of X increases so much that they can now afford only OQX of X
• Also for such reasons as commodity X is going out of fashion; its quality has deteriorated;
consumer’s technology has so changed that only OQ1 of X can be used and due to
change in season if commodity X has only seasonal use. Elasticity of Demand
While the law of demand establishes a relationship between price and quantity
demanded for a product, it does not tell us exactly as how strong or weak the relationship
happens to be. This relation, as already discussed, is inverse baring some rare exceptions.
However, a manager needs an exact measure of this relationship for appropriate business
decisions. Elasticity of demand is a measure, which comes to the rescue of a manager here.
It measures the responsiveness of demand to changes in prices as well as changes in income.
A manager can determine almost exactly how the demand for his product would change
when he changes his price or when his rivals alter prices of their products. He can also
determine how the demand for his product would change if incomes of his consumers go up
or down. Elasticity of demand concept and its measurements are therefore very important
tools of managerial decision making.
From decision-making point of view, however, the knowledge of only the nature of
relationships is not sufficient. What is more important is the extent of relationship or the
degree of responsiveness of demand to changes in its determinants. The responsiveness of
demand for a good to the change in its determinants is called the elasticity of demand. The
concept of elasticity of demand was introduced into the economic theory by Alfred Marshall.
The elasticity concept plays an important role in various business decisions and government
policies. In this unit, we will discuss the following kinds of demand elasticity.
• Price Elasticity: Elasticity of demand for a commodity with respect to change in its price.
• Cross Elasticity: Elasticity of demand for a commodity with respect to change in the price
of its substitutes.
• Income Elasticity: Elasticity of demand with respect to change in consumer’s income.
• Price Expectation Elasticity of Demand: Elasticity of demand with respect to consumer’s
expectations regarding future price of the commodity.
PRICE ELASTICITY OF DEMAND
The price elasticity of demand is delineated as the degree of responsiveness or
sensitiveness of demand for a commodity to the changes in its price. More precisely,
elasticity of demand is the percentage change in the quantity demanded of a commodity as
a result of a certain percentage change in its price. A formal definition of price elasticity of
demand (e) is given below:
The measure of price elasticity (e) is called co-efficient of price elasticity. The
measure of price elasticity is converted into a more general formula for calculating
coefficient of price elasticity given as
demanded and P = change in price.
Note that a minus sign (-) is generally inserted in the formula before the fraction with
a view to making elasticity coefficient a non-negative value.
2.4.2 POINT AND ARC ELASTICITY OF DEMAND
The elasticity of demand is conventionally measured either at a finite point or
between any two finite points, on the demand curve. The elasticity measured on a finite
point of a demand curve is called point elasticity and the elasticity measured between any
two finite points is called arc elasticity. Let us now look into the methods of measuring point
and arc elasticity and their relative usefulness.
(A) POINT ELASTICITY
The point elasticity of demand is defined as the proportionate change in quantity
demanded in response to a very small proportionate change in price. The concept of point
elasticity is useful where change in price and the consequent change in quantity demanded
are very small.
The point elasticity may be symbolically expressed as
suppose that a linear demand curve is given by MN in Fig. 2.4 and that we want to measure
elasticity at point P.
figure, P = PQ and Q = OQ. What we need now is to find the values for δQ and δP. These
values can be obtained by assuming a very small decrease in the price. However, it will be
difficult to depict these changes in the figure as and hence Q –O. There is however an easier
way to find the value for δQ/δP. In derivative given the slope of the demand curve MN. The
slope of demand curve MN, at point P is geometrically given by QN/PQ. That is, may be
proved as follows. If we draw a horizontal line from P and to the vertical -.here will be three
triangles.
the minus sign), we get
Therefore, the other corresponding angles of the triangles will always be equal and hence,
MON, MRP and PQN are similar triangles. According to geometrical properties of similar triangles, the ratio of any two sides of
similar triangle is always equal to the ratio of corresponding sides of the other sides.
Therefore, in PQN and MRP,
2.6, because both lower and upper segments are equal (i.e., PN = PM) at any other point to
the left of point P, e > I and at any point to the right of point.
Price Elasticity at Terminal Points
The price elasticity at terminal point N equals 0 i.e. at point N, e = 0. At terminal
point M, however, price-elasticity is undefined, though most texts show that at terminal
point M, e = ∞. According to William J. Baumol, a Nobel Prize winner, price elasticity at
upper terminal point of the demand curve is undefined. It is undefined because measuring
elasticity at terminal point (M) involves division of zero and division by-zero is undefined. In
his own words, “Here the elasticity is not even defined because an attempt to evaluate the fraction p/x at that point forces us to commit the sign of dividing by zero. The reader who
has forgotten why division by zero is immoral may recall that division is the reverse
operation of multiplication. Hence, in seeking the quotient c = a/b we look for a number, c,
which when multiplied by b gives us the number a, i.e., for which cb = a. But if a is not zero,
say a = 5 and b is zero, there is no such number because there is no c such that c x 0 = 5”.
(B) MEASURING ARC ELASTICITY
The concept of point elasticity is pertinent where change in price and the resulting
change in quantity are infinite or small. However, where change in price and the consequent
hunger in demand is substantial, the concept of arc elasticity is the relevant concept. Arc
elasticity is a measure of the average of responsiveness of the quantity demanded to a
substantial change in the price. In other words, the measure of price elasticity of demand
between two finite points on a demand curve is known as arc activity. For example, the
measure of elasticity between points J and K (Fig. 2.7) is: the measure of arc elasticity. The
movement from point J to K along the demand curve D) shows a fall in price from Rs 25 to Rs
10 so that AP = 25 - 10 = 15. The consequent increase in demand, AQ = 30 - 50 = - 20. The arc
elasticity between point J and K and (moving from J to K) can be obtained by substituting
these values in the elasticity formula.
Price elasticity of demand fluctuates from commodity to commodity. While the
demand of some commodities is highly elastic, the demand for others is highly inelastic. In
this section, we will describe the main determinants of the price elasticity of demand.
1. Availability of Substitutes
One of the most significant determinants of elasticity of demand for a commodity is
the availability of its substitutes. Closer the substitute, greater is the elasticity of demand for
the commodity. For instance, coffee and tea could be regarded as close substitutes for one
another. Thus, if price of one of these goods rises, its demand reduces more than the
proportionate rise in its price as consumers switch over to the relatively lower-priced
substitute. Moreover, broader the choice of the substitutes, greater is the elasticity. E.g.
soaps, washing powder, toothpastes, shampoos, etc. are available in several brands; each
brand is a close substitute for the other. Thus, the price-elasticity of demand for each brand
will be to a large extent greater than the general commodity. In contrast, sugar and salt do
not have their close substitute and for this reason their price-elasticity is lower.
2. Nature of Commodity
The nature of a commodity as well has an effect on the price elasticity of its demand.
Commodities can be categorised as luxuries, comforts and necessities, on the basis of their
nature. Demand for luxury goods (e.g., luxury cars, decorative items, etc.) are more elastic
than the demand for other types of goods as consumption of luxury goods can be set aside
or delayed when their prices increase. In contrast, consumption of essential goods, (e.g.,
sugar, clothes, vegetables, etc.) cannot be delayed and for this reason their demand is
inelastic. Demand for comforts is usually more elastic than that for necessities and less elastic than the demand for luxuries. Commodities may also be categorised as durable goods
and perishable or non-durable goods. Demand for durable goods is more elastic than that
for non-durable goods, as when the prices of the former rises, people either get the old one
fixed rather than substituting it or buy ‘second hand’ goods.
3. Proportion of Income Spent on a Commodity
Another aspect that has an impact on the elasticity of demand for a commodity is the
proportion of income, which consumers use up on a specific commodity. If proportion of
income spent on a commodity is extremely little, its demand will be less elastic and vice
versa. Characteristic examples of such commodities are sugar, matches, books, washing
powder etc., which use a very tiny proportion of the consumer’s income. Demand for these
goods is usually inelastic as a rise in the price of such goods does not largely have an effect
on the consumer’s consumption pattern and the overall purchasing power. Thus, people
continue to buy approximately the same quantity even at the time their price rises.
4. Time Factor
Price-elasticity of demand relies moreover on the time which consumers take to
amend to a new price: longer the time taken, greater is the elasticity. As each year passes,
consumers are capable of altering their spending pattern to price changes. For instance, if
the price of bikes falls, demand may not rise instantaneously unless people acquire surplus
buying capacity. In the end nevertheless people can alter their spending pattern so that they
can purchase a car at a (new) lower price.
5. Range of Alternative Uses of a Commodity
Broader the range of alternative uses of a commodity, higher the price elasticity of its
demand intended for the fall in price however less elastic for the increase in price. As the
price of a versatile commodity falls, people broaden their consumption to its other uses.
Thus, the demand for such a commodity usually rises more than the proportionate fall in its
price. E.g., milk can be consumed as it is, it could be transformed into curd, cheese, ghee and
buttermilk. The demand for milk will thus be extremely elastic for fall in their price. Likewise,
electricity can be utilised for lighting, cooking, heating, as well as for industrial purposes.
Thus, demand for electricity is extremely price elastic for fall in its price. For this reason,
nevertheless, demand for such goods is inelastic for the increase in their price.
6. The Proportion of Market Supplied
Price elasticity of market demand furthermore relies on the proportion of the market
supplied at the determined price. If less than half of the market is supplied at the determined price, elasticity of demand will be higher if more than half of the market is
supplied. i.e. demand curve is more elastic at the upper half than at the lower half. Demand Forecasting
Demand forecasting entails forecasting and estimating the quantity of a product or
service that consumers will purchase in future. It tries to evaluate the magnitude and
significance of forces that will affect future operating conditions in an enterprise. Demand
forecasting involves use of various formal and informal forecast techniques such as informed
guesses, use of historical sales data or current field data gathered from representative
markets. Demand forecasting may be used in making pricing decisions, in assessing future
capacity requirements, or in making decisions on whether to enter a new market. Thus,
demand forecasting is estimation of future demand. According to Cardiff and Still, “Demand
forecasting is an estimate of sales during a specified future period based on a proposed
marketing plan and a set of particular uncontrollable and competitive forces". As such,
demand forecasting is a projection of firm’s expected future demands.
2.6.1 DEMAND FORECAST AND SALES FORECAST
Due to the dynamic and complex nature of marketing phenomenon, demand
forecasting has become an important and regular business exercise. It is essential for profit
maximisation and the survival and expansion of a business. However, before selecting any
vendor a retailer should well understand the requirement and the importance of demand
forecasting. In management circles, demand forecasting and sales forecasting are used
interchangeably. Sales forecasts are first approximations in production and forward
planning. These provide a platform upon which plans could be prepared and amendments
may be made. According to American Marketing Association, “Sales forecast is an estimate
of sales in monetary or physical units for a specified future period under a proposed
business plan or programmer or under an assumed set of ‘economic and other environment
forces, planning premises, outside business/ antiquate which the forecast or-estimate is
made”. 2.6.2 COMPONENTS OF DEMAND FORECASTING SYSTEM
• Market research operations to procure relevant and reliable information about the
trends in market.
• A data processing and analysing system to estimate and evaluate the sales performance
in various markets.
• Proper co-ordination of steps (i) and (ii) above
• Placing the findings before the top management for making final decisions.
2.6.3 OBJECTIVES OF DEMAND FORECAST
1. Short Term Objectives
a. Drafting of Production Policy: Demand forecasts facilitate in drafting appropriate
production policy so that there may not be any space between future demand and
supply of a product. This can in addition ensure:
• Routine Supply of Materials: Demand forecasting assists in figuring out the
preferred volume of production. The essential prerequisite of raw materials in
future can be calculated on the basis of such forecasts. This guarantees regular
and continuous supply of the materials in addition to managing the amount of
supply at the economic level.
62 Managerial Economics
• Best Possible Use of Machines: Demand forecasting in addition expedites cutting
down inactive capacity because only the necessary amount of machines and
equipments are set up to meet future demands.
• Regular Availability of Labour: As soon as demand forecasts are made, supplies
of the necessary amount of skilled and unskilled workers can be organised well
beforehand to meet the future production plans.
b. Drafting of Price Policy: Demand forecasts facilitate the management to prepare a
few suitable pricing systems, so that the level of price does not rise and fall to a great
extent during depression or inflation.
c. Appropriate Management of Sales: Demand forecasts are made area wise and after
that the sales targets for different regions are set in view of that. This abets the
calculation of sales performances.
d. Organising Funds: On the basis of demand forecast, an individual can find out the
monetary requirements of the organisation in order to bring about the desired
output. This can make it possible to cut down on the expenditure of acquiring funds.
2. Long Term Goals: If the demand forecast period is more than a year, in that case it is
termed as long term forecast. The following are the key goals of such forecasts:
a. To settle on the production capacity: Long term decisions are entwined with
capacity variations by adding or discarding capacity in the form of capital assets -
manufacturing plants, new technology implementation etc. Size of the organisation
should such that output matches with the sales requirements. Organisations that are
extremely small or large in size might not be in the financial interest of the company.
Inadequate capability can hasten declining delivery performance, needless rise in
work-in-process and disturb sales personnel and those in the production unit.
Nevertheless, surplus capacity can be expensive and pointless. The incompetence to
appropriately deal with capacity can be an obstacle to attaining the best possible
performance. By examining the demand pattern for the product as well as the
forecasts for the future, the company can prepare for a company's output of the
desired capacity.
b. Labour Requirements: Spending on labour is one of the most vital elements of cost
of production. Dependable and correct demand forecasts can facilitate the
management to evaluate suitable labour requirements. This can ensure finest labour
supply and uninterrupted production procedures.
c. Production Planning: Long term production planning can aid the management in
organising long term finances on practical terms and conditions.
The study of long term sales is accorded greater importance as compared with shortterm
sales. Long term sales forecast facilitates the management to take a few policy
decisions of huge importance and any mistake carried out in this could be extremely
different or costly to be corrected.
Therefore, the complete success of an organisation usually is contingent upon the
quality and authenticity of sales forecasting methods.
2.6.4 IMPORTANCE OF DEMAND FORECAST
1. Management Decisions: An effective demand forecast facilitates the management to
take appropriate steps in factors that are pertinent to decision making such as plant
capacity, raw-material requisites, space and building requirements and availability of
labour and capital. Manufacturing schedules can be drafted in compliance with the
demand requisites; in this manner cutting down on the inventory, production and other
related costs.
2. Evaluation: Demand forecasting furthermore smoothes the process of evaluating the
efficiency of the sales department.
3. Quality and Quantity Controls: Demand forecasting is an essential and valuable
instrument in the control of the management of an organisation to provide finished
goods of correct quality and quantity at the correct time with the least amount of
expenditure.
4. Financial Estimates: As per the sales level as well as production functions, the financial
requirements of an organisation can be calculated using various techniques of demand
forecasting. In addition, it needs a little time to acquire revenue on practical terms. Sales
forecasts will, as a result, make it possible for arranging adequate resources on practical
terms and in advance as well.
5. Avoiding Surplus and Inadequate Production: Demand forecasting is necessary for the
old and new organisations. It is somewhat essential if an organisation is engaged in large
scale production of goods and the development period is extremely time-consuming in
the course of production. In such situations, an estimate regarding the future demand is
essential to avoid inadequate and surplus production.
6. Recommendations for the future: Demand forecast for a specific commodity
furthermore provides recommendations for demand forecast of associated industries.
E.g. the demand forecast for the vehicle industry aids the tyre industry in calculating the
demand for two wheelers, three wheelers and four wheelers.
7. Significance for the government: At the macro-level, demand forecasting is valuable to
the government as it aids in determining targets of imports as well as exports for various
products and preparing for the international business.
2.6.5 METHODS OF DEMAND FORECAST
No demand forecasting method is 100% precise. Collective forecasts develop
precision and decrease the probability of huge mistakes.
1. Methods that relay on Qualitative Assessment:
Forecasting demand based on expert opinion. Some of the types in this method are:
• Unaided judgment
• Prediction market
• Delphi technique
• Game theory
• Judgmental bootstrapping
• Simulated interaction
• Intentions and expectations surveys
• Conjoint analysis
2. Methods that rely on quantitative data:
• Discrete event simulation
• Extrapolation
• Quantitative analogies
• Rule-based forecasting
• Neural networks
• Data mining
• Causal models
• Segmentation
2.6.6 SOME DEMAND FORECASTING METHODS
A. QUALITATIVE ASSESSMENT
1. Prediction markets: These are speculative markets fashioned with the intention of
making predictions. Assets that are produced possess an ultimate cash worth bound to a
specific event (e.g. who will win the next election) or situation (e.g., total sales next
quarter). The present market prices can then be described as forecasts of the likelihood
of the event or the estimated value of the situation. Prediction markets are as a result
planned as betting exchanges, without any kind of compromise for the bookmaker.
People who buy low and sell high are rewarded for improving the market prediction,
while those who buy high and sell low are punished for degrading the market prediction.
Evidence so far suggests that prediction markets are at least as accurate as other
institutions predicting the same events with a similar pool of participants.
Many prediction markets are open to the public. Betfair is the world's biggest
prediction exchange, with around $28 billion traded in 2007. Intrade is a for-profit company
with a large variety of contracts not including sports. The Iowa Electronic Markets is an
academic market examining elections where positions are limited to $500. Trade Sports are
prediction markets for sporting events.
2. Delphi method: This is a systematic, interactive forecasting method which relies on a
panel of experts. The experts answer questionnaires in two or more rounds. After each
round, a facilitator provides an anonymous summary of the experts’ forecasts from the
previous round as well as the reasons they provided for their judgments. Thus, experts
are encouraged to revise their earlier answers in light of the replies of other members of
their panel. It is believed that during this process the range of the answers will decrease
and the group will converge towards the 'correct' answer. Finally, the process is stopped
after a pre-defined stop criterion (e.g. number of rounds, achievement of consensus,
stability of results) and the mean or median scores of the final rounds determine the
results.
3. Game theory: Game theory is a branch of applied mathematics that is used in the social
sciences, most notably in economics, as well as in biology (particularly evolutionary
biology and ecology), engineering, political science, international relations, computer
science and philosophy. Game theory attempts at mathematically capturing behaviour in
strategic situations or games in which an individual's success in making choices depends
on the choices of others. While initially developed to analyse competitions in which one
individual does better at another's expense (zero sum games), it has been expanded to
treat a wide class of interactions, which are classified according to several criteria.
Today, "game theory is a sort of umbrella or 'unified field' theory for the rational side of
social science, where 'social' is interpreted broadly, to include human as well as nonhuman
players (computers, animals, plants)" (Aumann 1987).
Traditional applications of game theory aim at finding equilibrium in these games. In
equilibrium, each player of the game has adopted a strategy that they are unlikely to
change. Many equilibrium concepts have been developed (most famously the Nash
equilibrium) in an endeavor to capture this idea. These equilibrium concepts are differently
motivated depending on the field of application, although they often overlap or coincide.
This methodology is not without criticism and debates continue over the appropriateness of
particular equilibrium concepts, the appropriateness of equilibrium altogether and the
usefulness of mathematical models more generally.
Although, some developments occurred before it, the field of game theory came into
being with Émile Borel's researches in his 1938 book Applications aux Jeux des Hazard and
was followed by the 1944 book Theory of Games and Economic Behavior by John von
Neumann and Oskar Morgenstern. This theory was developed extensively in the 1950s by
many scholars. Game theory was later explicitly applied to biology in the 1970s, although
similar developments go back at least as far as the 1930s. Game theory has been widely
recognised as an important tool in many fields. Eight game theorists have won the Nobel
Memorial Prize in Economic Sciences and John Maynard Smith was awarded the Crafoord
Prize for his application of game theory to biology.
The games studied in game theory are well-defined mathematical objects. A game
consists of a set of players, a set of moves (or strategies) available to those players and a
specification of payoffs for each combination of strategies. Most cooperative games are
presented in the characteristic function form, while the extensive and the normal forms are
used to define non-cooperative games.
QUANTITATIVE DATA
1. Discrete-event simulation: The operation of a system is represented as a chronological
sequence of events. Each event occurs at an instant in time and marks a change of state
in the system. For example, if an elevator is simulated, an event could be "level 6 button
pressed", with the resulting system state of "lift moving" and eventually (unless one
chooses to simulate the failure of the lift) "lift at level 6".
A common exercise in learning how to build discrete-event simulations is to model a
queue, such as customers arriving at a bank to be served by a teller. In this example, the
system entities are CUSTOMER-QUEUE and TELLERS. The system events are CUSTOMERARRIVAL
and CUSTOMER-DEPARTURE. (The event of TELLER-BEGINS-SERVICE can be part of
the logic of the arrival and departure events.) The system states, which are changed by these
events, are NUMBER-OF-CUSTOMERS-IN-THE-QUEUE (an integer from 0 to n) and TELLERSTATUS
(busy or idle). The random variables that need to be characterised to model this
system stochastically are CUSTOMER-INTERARRIVAL-TIME and TELLER-SERVICE-TIME.
2. Rule based forecasting: Rule-based forecasting (RBF) is a proficient method that
incorporates judgment as well as statistical techniques to merge forecasts. It involves
condition-action statements (rules) where conditions are based on the aspects of the
past progress and upon knowledge of that specific area. These rules give in to the load
suitable to the forecasting condition as described by the circumstances. In fact, RBF uses
structured judgment as well as statistical analysis to modify predictive techniques to the
condition. Practical outcomes on several sets of the past progress indicate that RBF
generates forecasts that are more precise than those generated by the conventional
predictive techniques or by an equal-load amalgamation of predictions.
3. Data mining: Data mining is the process of extracting patterns from data. Data mining is
seen as an increasingly important tool by modern business to transform data into an
informational advantage. It is currently used in a wide range of profiling practices, such
as marketing, surveillance and scientific discovery.
Data mining commonly involves four classes of tasks:
• Clustering - is the task of discovering groups and structures in the data that are in some
way or another "similar", without using known structures in the data.
• Classification - is the task of generalising known structure to apply to new data. For
example, an email program might attempt to classify an email as legitimate or spam.
Common algorithms include decision tree learning, nearest neighbor, naive Bayesian
classification, neural networks and support vector machines.
• Regression - Attempts to find a function which models the data with the least error.
• Association rule learning - Searches for relationships between variables. For example a
supermarket might gather data on customer purchasing habits. Using association rule
learning, the supermarket can determine which products are frequently bought together
and use this information for marketing purposes. This is sometimes referred to as
market basket analysis.
2.6.7 METHODS OF ESTIMATION
1. Regression analysis: Regression analysis is the statistical technique that identifies the
relationship between two or more quantitative variables: a dependent variable whose
value is to be predicted and an independent or explanatory variable (or variables), about
which knowledge is available. The technique is used to find the equation that represents
the relationship between the variables. A simple regression analysis can show that the
relation between an independent variable X and a dependent variable Y is linear, using
the simple linear regression equation Y= a + bX (where a and b are constants). Multiple
regression will provide an equation that predicts one variable from two or more
independent variables, Y= a + bX1+ cX2+ dX3.
The steps in regression analysis are:
a. Construction of the causal model: The construction of an explanatory model is a
crucial step in the regression analysis. It must be defined with reference to the action
theory of the intervention. It is likely that several kinds of variable exist. In some
cases, they may be specially created, for example to take account of the fact that an
individual has benefited from support or not (a dummy variable, taking values 0 or
1). A variable may also represent an observable characteristic (having a job or not) or
an unobservable one (probability of having a job). The model may presume that a
particular variable evolves in a linear, logarithmic, exponential or other way. All the
explanatory models are constructed on the basis of a model, such as the following,
for linear regression:
Y = β0 + β1X1 + β2X2 + …. + β kXk + ε, where
Y is the change that the programme is mainly supposed to produce (e.g. employment
of trainees)
X1-k are independent variables likely to explain the change.
β0-k are constants and
ε is the error term
Phenomena of co-linearity weaken the explanatory power. For example, when
questioning women about unemployment, if they have experienced periods of previous
unemployment which are systematically longer than those of men, it will not be possible to
separate the influence of the two explanatory factors: gender and duration of previous
unemployment.
b. Construction of a sample: To apply multiple regression, a large sample is usually
required (ideally between 2,000 to 15,000 individuals). Note that for time series data,
much less is needed.
c. Data collection: Reliable data must be collected, either from a monitoring system,
from a questionnaire survey or from a combination of both.
d. Calculation of coefficients: Coefficients can be calculated relatively easily, using
statistical software that is both affordable and accessible to PC users.
e. Test of the model: The model aims to explain as much of the variability of the
observed changes as possible. To check how useful a linear regression equation is,
tests can be performed on the square of the correlation coefficient r. This tells us
what percentage of the variability in the y variable can be explained by the x variable.
A correlation coefficient of 0.9 would show that 81% of the variability in Y is captured
by the variables X1-k used in the equation. The part that remains unexplained
represents the residue (ε). Thus, the smaller the residue better is the quality of the
model and its adjustment. The analysis of residues is a very important step: it is at
this stage that one sees the degree to which the model has been adapted to the
phenomena one wants to explain. It is the residue analysis that also enables one to
tell whether the tool has made it possible to estimate the effects in a plausible way
or not. If significant anomalies are detected, the regression model should not be
used to estimate effects and the original causal model should be re-examined, to see
if further predictive variables can be introduced.
2. Time series analysis: An analysis of the relationship between variables over a period of
time. Time-series analysis is useful in assessing how an economic or other variable
changes over time. For example, one may conduct a time-series analysis on a stock, sales
volumes, interest rates and quality measurements etc.
Methods for time series analyses may be divided into two classes: frequency-domain
methods (spectral analysis and recently wavelet analysis) and time-domain methods
(auto-correlation and cross-correlation).
a. Frequency domain: Frequency domain is a term used to describe the domain for
analysis of mathematical functions or signals with respect to frequency, rather than
time. A time-domain graph shows how a signal changes over time. Whereas a
frequency-domain graph shows how much of the signal lies within each given
frequency band over a range of frequencies. A frequency-domain representation can
also include information on the phase shift that must be applied to each sinusoid in
order to be able to recombine the frequency components to recover the original
time signal.
b. Time domain: Time domain is a term used to describe the analysis of mathematical
functions, or physical signals, with respect to time. In the time domain, the signal or
function's value is known for all real numbers, for the case of continuous time, or at
various separate instants in the case of discrete time. An oscilloscope is a tool
commonly used to visualise real-world signals in the time domain.
3. Utility analysis: A subset of consumer demand theory that analysis consumer behavior
and market demand using total utility and marginal utility. The key principle of utility
analysis is the law of diminishing marginal utility, which offers an explanation for the law
of demand and the negative slope of the demand curve. The main focus of utility analysis
is on the fulfillment of wants and needs acquired by the utilization of goods. It
additionally facilitates in getting the knowledge of market demand as well as the law of
demand. The law of demand by way of utility analysis states that consumers buy goods
that fulfill their wants and needs, i.e., create utility. Those goods that create more utility
are more important to consumers and therefore buyers are prepared to pay a higher
price. The main aspect to the law of demand is that the utility created falls when the
quantity consumed rises. As such, the demand price that buyers are prepared to pay falls
when the quantity demanded rises.
The law of diminishing marginal utility asserts that marginal utility or the
extra utility acquired from consuming a good, falls as the quantity consumed rises.
Basically, each extra good consumed is less fulfilling as compared to the previous one.
This law is mostly significant for awareness into market demand as well as the law of
demand.
a. Cardinal utility: A measure of utility, or satisfaction derived from the consumption of
goods and services that can be measured using an absolute scale. Cardinal utility
exists if the utility derived from consumption is measurable in the same way that
other physical characteristics--height and weight--are measured using a scale that is
comparable between people. There is little or no evidence to suggest that such
measurement is possible and is not even needed for modern consumer demand
theory and indifference curve analysis. Cardinal utility, however, is often employed
as a convenient teaching device for discussing such concepts as marginal utility and
utility maximisation.
b. Ordinal utility: A method of analysing utility, or satisfaction derived from the
consumption of goods and services, based on a relative ranking of the goods and
services consumed. With ordinal utility, goods are only ranked only in terms of more
or less preferred, there is no attempt to determine how much more one good is
preferred to another. Ordinal utility is the underlying assumption used in the analysis
of indifference curves and should be compared with cardinal utility, which
(hypothetically) measures utility using a quantitative scale.
Summary
Demand: "The demand for a commodity at a given price is the amount of it which
will be bought per unit of time at that price”.
Law of Demand: “The demand for a commodity increases with a fall in its price and
decreases with a rise in its price, other things remaining the same”. The Law of demand thus
merely states that the price and demand of a commodity are inversely related, provided all
other things remain unchanged or as economists put it ceteris paribus.
Assumptions to the Law of Demand: We can state the assumptions of the law of
demand as follows: (1) Income level should remain constant, (2) Tastes of the buyer should
not change, (3) Prices of other goods should remain constant, (4) No new substitutes for the
commodity, (5) Price rise in future should not be expected and (6) Advertising expenditure
should remain the same.
Why Demand Curve Slopes Downwards: The reasons behind the law of demand, i.e.,
inverse relationship between price and quantity demanded are following: (i) substitution
effect, (ii) income effect, (iii) diminishing marginal utility.
Market Demand: The total quantity which all the consumers of a commodity are
willing to buy at a given price per time unit, other things remaining the same, is known as
market demand for the commodity. In other words, the market demand for a commodity is
the sum of individual demands by all the consumers (or buyers) of the commodity, per time
unit and at a given price, other factors remaining the same.
Individual demand: The individual demand means the quantity of a product that an
individual can buy given its price. It implies that the individual has the ability and willingness
to pay.
Demand Function: Demand function is a mathematical expression of the law of
demand in quantitative terms. A demand function may produce a linear or curvilinear
demand curve depending on the nature of relationship between the price and quantity
demanded. The functional relationship between the demand for a commodity and its various determinants may be expressed mathematically as:
Dx = f (Px, Py, M, T, A, U) where, Dx = Quantity demanded for commodity X, f =
functional relation, Px = The price of commodity X, Py = The price of substitutes and
complementary goods, M = The money income of the consumer, T = The taste of the
consumer, A = The advertisement effects, U = Unknown variables or influences
Elasticity of Demand: The concept of elasticity of demand can be defined as the
degree of responsiveness of demand to given change in price of the commodity.
Methods of Measurement of Elasticity of Demand: By using three different
methods, elasticity of demand is measured.
• Ratio Method
• Expenditure Method
• Point Method
Demand Forecasting: According to Cardiff and Still, “Demand forecasting is an
estimate of sales during a specified future period based on a proposed marketing plan and a
set of particular uncontrollable and competitive forces’’.
Objectives of Demand Forecast: Following are the objectives of demand forecasting:
• Formulation of production policy
• Price policy formulation
• Proper control of sales
• Arrangement of finance
• To decide about the production capacity
• Labour requirements
• Production planning
GAME THEORY
Game theory is a branch of applied mathematics that is used in the social sciences,
most notably in economics, as well as in biology (particularly evolutionary biology and
ecology), engineering, political science, international relations, computer science and
philosophy. It attempts to capture behaviour mathematically in strategic situations or games
in which an individual's success in making choices depends on the choices of others.
While initially developed to analyse competitions in which one individual does better
at another's expense (zero sum games), it has been expanded to include a wide class of
interactions, which are classified according to several criteria.
