Applications of the Price Elasticity of Demand

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					Applications of the Price Elasticity of Demand

The concept of elasticity of demand plays a crucial role in the pricing
decisions of the business firms and the Government when it regulates prices.
The concept of price elasticity is also important in judging the effect of
devaluation of a currency on its export earnings. If has also a great use in
fiscal policy because the Finance Minister has to keep in view the elasticity of
demand when it considers to impose taxes on various commodities. We shall
explain below the various uses, applications and importance of the elasticity
of demand.

Elasticity of demand is mainly useful in Pricing Decisions by Business Firms.
The business firms take into account the price elasticity of demand when
they take decisions regarding pricing of the goods. This is because change in
the price of a product will bring about a change in the quantity demanded
depending upon the coefficient of price elasticity. This change in quantity
demanded as a result of, say a rise in price by a firm, will affect the total
consumer’s expenditure and will therefore, and affect the revenue of the
firm. If the demand for a product of the firm happens to be elastic, then any
attempt on the part of the firm to raise the price of its product will bring
about a fall in its total revenue. Thus, instead of gaining from the increase in
price, it will lose if the demand for its product happens to be elastic. On the
other hand, if the demand for the product of a firm happens to be inelastic,
then the increase in price by it will raise total revenue. Therefore, for fixing a
profit maximizing price, the firm cannot ignore the price elasticity of demand
for its product.

Price elasticity of demand can be used to answer the following types of
questions:

   1. What will be the effect on sales if a firm decides to raise the price of its
      product, say by 5 percent?
   2. How large a reduction in price of a product is required to increase
      sales, say by 25 percent.

It has been found by some empirical studies that business firms often fail to
take elasticity into account while taking decisions regarding prices, or they
give insufficient attention to the coefficient of price elasticity. No doubt, the
main reason for this is that they don’t have means to calculate price
elasticity for their product, since sufficient data regarding past prices and
quantity demanded at those prices are not available. Even if such data are
available, there are difficulties of interpretation of it because it is not clear
whether the changes in quantity demanded were the result of changes in
price alone or changes in some other factors determining the demand.
However, recently big corporate business firms have established their
research departments which estimate the coefficient of price elasticity from
the data concerning past prices and quantities demanded. Further, they are
also using statistical techniques to isolate the price effect of the quantity
demanded from the effects of other factors.
Applications of Cross Elasticity of Demand for
Business Decision Making


The concept of cross elasticity of demand is of great importance in
managerial decision making for formulating proper price strategy.
Multiproduct firms often use this concept to measure the effect of change in
price of one product on the demand for other products. For example, Maruti
Udyog decides to lower the price of Maruti-800; it will significantly affect the
demand for Maruti Vans and Maruti Esteem. So it will formulate a proper
price strategy fixing appropriate price for its various products. Further,
Gillete Company produces both razors and razor blades which are
complements with high cross elasticity of demand. If it decides to lower the
price of razor, it will greatly increase the demand for razor blades. Thus
there is need for adopting a proper price strategy when it produces products
with high positive or negative cross price elasticity of demand.

Second, the concept of cross elasticity of demand is frequently used in
defining the boundaries of an industry and in measuring interrelationship
between industries. An industry is defined as a group of firms producing
similar products (that is, products with a high positive cross elasticity of
demand. For example cross elasticity of demand between Maruti Esteem,
Dawoo Ceilo, and Opel Astra is positive and quite high. They therefore
belong to the same industry (i.e., automobiles). It should be noted that
because of interrelationship of firms and industries between which cross
price-elasticity of demand is positive and high, any one cannot raise the
price of its product without losing sales to other firms in related industries.

Further, the concept of cross elasticity of demand is extremely used in the
United States in deciding cases relating to antitrust laws and monopolistic
practices used by firms. If so happens that in order to reduce competition
that one dominant firm try to merge with each other to form a cartel to
enjoy monopolistic profits. These actions are held illegal by Antitrust or anti-
monopoly laws. An interesting attempt was made in India by Casa-Cola and
it further made efforts to take over ‘Pure Drinks’, venture it could have
significantly reduced competition. With this its competition would have been
with other multinational rival firm Pepsi-Cola.
Applications of Income Elasticity for Business Firms


The concept of income elasticity is important for decision making both by
business firms and industries. First, the firms producing products which have
high income elasticity have great potential for growth in an expanding
economy. For example, if for a firm’s product income elasticity of demand is
greater than one; it means that it will gain more than proportionately to the
increase in national income. Thus firms which are producing products having
high income elasticity are more interested in forecasting the level of
aggregate economic activity (i.e., level of national income) because the
demand for their products will greatly depend on the level of overall
economic activity. Further, as seen above, the demand for luxuries is highly
income elastic. Therefore, the demands for luxuries increase very much, and
decline sharply during recessionary periods.

On the other hand, the demand for products with low income elasticity will
not be greatly affected by the fluctuations in aggregate economic activity.
During booms the demand for their products will not increase much and
during recessions it will not decrease sharply. Therefore, the firms with low
income elasticity for their products would not be much interested in
forecasting future business activity. Remember it is generally necessities for
which demand is not much income elastic. However, there is one good thing
for the firms which face low income elasticity. They are to a good extent
recession-proof. In the periods of recession, their incomes do not fall to the
extent of decline in aggregate income. Of course, to share the benefits of
increasing national income firms currently producing products with low
income elasticity would try to enter the industries demand for whose
products is highly income elastic as this would ensure better growth
opportunities.

The knowledge of income elasticity of demand also plays a significant role in
designing marketing strategies of the firms. If income of people is an
important determinant of demand for a product, the firms producing product
with high income elasticity of demand will be located in those areas or set up
their sales outlets in those cities or regions where incomes are increasing
rapidly. Besides, the firms will direct their advertising campaigns and other
sales production activities to those segments of people whose income is high
and also increasing rapidly. This is to ensure higher growth of sales of their
products.

The concept of income elasticity of demand shows clearly why farmers
income do not rise equal to that of urban people engaged in manufacturing
industries. Income elasticity of demand for agriculture products such as food
grains is less than one. This implies that it is difficult for the farmers’ income
from agriculture to increase in production to the expanding national income.
Thus farmers cannot keep up with the urban people who derive their
incomes from industries producing goods with high income elasticity of
demand.



Demand Forecasting
‘Forecasting is like trying to drive a car blind-folded and following direction
given by a person who is looking out of the back-window.’ –Philip Kotler

Introduction

The area of production planning and control is one in which the firm
concerns itself with means for the attainment of two objectives: the
production of required quantities of a given product and the production of
these quantities at appropriate times. This means that the producer must
anticipate the future demand for his product and, on this basis, provide the
production capacity which will be required. This call for forecasting the future
demand of a given product, translating this forecast into the demand it
generates for various production facilities and arranging for the procurement
of these facilities.

The discussion of demand forecasting is divided into seven sections. The first
describes the meaning, nature and the vital role played by demand forecasts
in the operations of business. The second deals with the types of forecasting
which arise out of the planning needs of business firms. The third explores
the various approaches to demand forecasting. The fourth explains the
major determinants of demand. The fifth deals with the major methods
adopted in estimating future demand. The sixth explains the forecasting
methods for new products. The last discusses how forecasts and forecasting
methods can be evaluated in terms of their accuracy and costs.
1. Meaning, Nature and the Role Played by Demand Forecasts in the
   Operations of Business

Estimates of expected future conditions are called forecasts and estimates of
expected future demand conditions are called demand forecasts.

Precise forecasts of future developments are clearly impossible. Expectations
depend on the assumptions made. The reliability of the forecasts, hence,
depends on the reliability of the assumptions.

The assumptions and methods employed in forecasting depend upon the
nature of the planning required. There are two major types of planning
which require the use of forecasts. They are short term planning and long
term planning. In industrially well developed countries, these grow out of the
need to predict short-term and long-term changes in demand conditions
facing industries. This has been so because demand conditions were always
more uncertain than supply in industrially advanced countries.

In recent times forecasting has come to play an important role in business
decision-making. A company is in business to serve its customers’ needs in
some way or the other. Its survival and prosperity depend on its ability and
willingness to adapt its operations to customers’ needs, to create or
stimulate the need, and serve it adequately and efficiently when the need
arises. Demand forecast serves as the link between the evaluation of
external factors in the economy which influence the business and the
management of the company’s internal affairs. The very term ‘planning’ is
intimately connected with forecasting because it is concerned with the
future.

More often than not, one finds forecasting decisions which have an important
influence on production planning operations being made by store-keepers or
stockroom clerks with little or no procedural or policy guidance.
Determination of the types of forecast required and establishment of
procedures governing generation of these forecasts are fundamental steps in
the organization of a well-conceived production control system.

For production planning purposes it is particularly important to distinguish
between forecasts of demand and forecasts of sales. While forecasts of sales
may be important for estimating revenue, cash requirements and expenses,
a production planning system is designed primarily to react to customer
demand. Demand may differ from sales for a variety of reasons. For
example, there may be substantial lag between customer orders and billings.
Or sales may understate demand to the extent that the manufacturing and
distribution system is unable to cope up with the volume of customer
demand. The particular characteristics of demand forecasts which are
pertinent to production and inventory control are the timing; detail and
reliability of forecasts, and the assignment within the organization of the
responsibility for making forecasts and controlling or improving the quality of
forecasts.



2. Types of Demand Forecasting

From the point of the view of the time span and from the planning
requirements of business firms, demand forecasting can be classified under
two headings: short-term demand forecasting and long-term demand
forecasting.

Short-term Forecasting
Short-term forecasting is limited to short periods, usually not exceeding an
year. It relates to policies regarding sales, purchasing pricing and finances.
Here the reference is only to the existing production capacity of the firm.

In most companies, knowledge of conditions in the immediate future is
essential for formulating a suitable sales policy. Production schedules have
to be geared to expected rather than actual sales. Often, by assuming that
prevailing conditions will continue, a firm may find itself faced with a
problem of over production or short supply. An understanding of near future
prospects would make it possible to avoid some of the violent fluctuations
which occur in production scheduling and sales planning.

Knowledge of immediate future conditions is important in pricing. If prices of
materials are expected to go up or shortages are expected, businessmen
may take advantage of the rise by earlier buying. Proper price forecasting
may, thus, help the firm in reducing the costs of operation.

Demand forecasting is also useful to the businessman in determining his
price policy. An increase of prices is avoided when future market conditions
are not expected to be good and the lowering of prices is avoided when
costs or sales levels are likely to rise considerably.
Many companies use forecasting for setting sales targets and for establishing
controls and incentives. Sales targets will not accomplish their objectives if
not geared meaningfully to the sales levels likely to be achieved. If set too
high, the targets will be discouraging to those who have to meet them. If the
targets are very low, they will be met very easily and incentives will prove
meaningless.

Above all, demand forecasting of the type mentioned above will be of
considerable assistance in short-term financial forecasting also. Cash
requirements will depend upon the levels of sales and production scale.
Some prior information is usually needed to procure additional funds on
reasonable terms. Neglect of demand forecasting will complicate financial
planning through its repercussions on production scheduling and inventory
accumulation. In the preparation of budgets, therefore, short-term forecasts
have come to play an important part.

Long-term Forecasting
In short-term forecasting a company is concerned only about the use of its
existing production capacity. But when questions of long-term planning are
involved the businessman must know something about the long-term
demand for his products. Thus the planning of a new production unit or the
expansion of an existing unit must start with an analysis of the long-term
demand potential of the products in question. A multi-product firm must
ascertain not only the total demand situation, but also the demand for
different items. This will involve the study of consumer preferences and
trends, the economy, and technological developments and trends. Once the
demand potential is assessed, it will be easier for the company to engage in
long-term financial planning. Again, manpower planning for existing as well
as new firms must be based on long-term forecasts of the company’s
growth.

When forecasts covering long periods are made, the probability of error is
high. Competent forecasts predict the conditions that are likely to prevail in
the near future with comparative confidence, and with a relatively high
degree of accuracy; the results are much less reliable when they attempt to
forecast conditions over longer periods. This is because; as the period
becomes longer certain factors that forecasters take into account in making
their estimates become more volatile. It is very difficult to predict over
extended periods such items as the probable costs of production, the trend
of prices and the changing nature of competition. Moreover, the longer the
term covered by the prediction, the more likely it is that unanticipated
events such as international conflicts including wars, periods of major
depression and prosperity and inventions and technological advances will
upset the calculations.

It is a function of the top management in each firm to make its own decision
regarding the span of time to be covered by demand forecast. It is safer to
forecast for longer periods, when the volume of demand has held fairly
constant from year to year. If demand has been erratic for reasons that are
largely unexplainable, the forecasting period should be shorter.



3. Approach to Forecasting

The following four distinct steps must be kept in view in dealing with any
demand forecasting problems:

  i)    Identify and clearly state the objectives of the forecasting problem.
        In certain cases the required forecasts may be of a short term
        nature. The approach needed here may be of quite different from
        what long-term forecasts will call for. In certain other cases
        forecasts of market shares may be required which calls for an
        approach different from that needed for a general industry forecast.

  ii)   Ascertain the determinants of demand for the particular product or
        product group. The factors influencing demand differ widely
        depending on the product/s or industry or industries involved.
        Economists have a tendency to categorize goods and services into
        three broad categories for facilitating demand analysis. These three
        categories are:
        - Consumers’ non-durable goods.
        - Consumers’ durable goods
        - Capital goods.

        We follow here the same kind of categorization for purposes of
        demand analysis. The determinants of demand pertaining to these
        categories are different. They are discussed in detail in the next
        section.
     iii)     Select appropriate methods of forecasting. The method selected will
              depend upon the purpose or objective of the demand forecasts, the
              nature of the product/s involved, the types of data available, etc.
     iv)      Present the findings in a readable form. This is important because
              the management will be interested only in the actual forecast, its
              meaning and implications for policy.

Once a product forecast for the whole industry is available, it is easy for the
company to estimate its share of the market. Analysis of past data can
indicate the trends in market share among the competitors.

In preparing company forecasts the management may rely of two varying
assumptions:

     a) The ratio of company sales to total industry sales will continue as in
        the past, or
     b) The ratio of company sales to total industry sales will change.

Demand forecasts for the company may be made based on either of these
assumptions. And often companies prepare alternative forecasts based on
them.

Forecasting must be a continuing activity. Every forecast is based on a given
set of data and assumptions hold good. As improved information becomes
available, forecasts must be reviewed and revised so that the management
is provided with a better basis for decision making.



4. Determinants of Demand

i)          Non-durable consumer goods
            There are at least three basic factors influencing the demand for non-
            durable consumer goods. They are: purchasing power (income), price
            and demography.

            a) Purchasing Power
               One of the major determinants of demand is the purchasing power
               of the consumer and this is determined by the income or rather
               disposable personal income (Personal income minus direct taxes
               and other deductions, if any) of the consumer. In Nepal, data on
   disposable income is not directly available. The Central Statistical
   Organization has not yet started the publication of data on
   disposable income. Indirect estimates can, however, be obtained
   from the published data.

   Use of disposable income for estimating demand has been criticized
   by some writers on the plea that it does not constitute ‘free’
   purchasing power.       Hence, they prefer to use the concept
   ‘discretionary income’ in place of disposable income. Discretionary
   income can be estimated by deducting three items from disposable
   income, viz. imputed income and income in kind, major fixed outlay
   payments such as mortgage debt payment, insurance premium
   payments and rent and essential expenditures such as food and
   clothing and transport expenses based upon consumption in a
   normal year. But here it may be pointed out that the disposable
   income concept is considered to be equally satisfactory by many
   experts.

b) Price
   The importance of price of a particular product and its substitutes in
   determining the demand has always been emphasized by
   economists. A measure of the price-demand relationship for a
   product is given by the concept ‘elasticity of demand’. Concepts
   such as price elasticity, income elasticity, cross elasticity, etc. of
   demand are used in economic analysis.

c) Demography
   Experience shows that demand for a product is determined by
   certain population characteristics also. For example, a study of the
   demand for lipsticks must take into account the number of women
   by age. Again, in a study of the demand of tyers, the population
   consists of the number of cars, buses, trucks and other motor
   vehicles in use. This shows that demography does not necessarily
   relate exclusively to human population. In fact, its use is in
   differentiating between total market demands on the one hand and
   ‘market segments’ on the other. The segments represent divisions
   of the total market into homogenous groups. The idea is to
   construct one or more segments that are considered to be
           important elements affecting the demand for the product.
           Demographic or population groups can be defined in terms of
           educational background, sex, age, income, social status, geographic
           location, etc. The segment, if quantified, can be used as an
           independent variable affecting the demand for the product in
           question.

           Purchasing power(Y), Price(P) and demography(D) can be combined
           in an additive relationship in order to get a formula which can be
           used for predicting demand(d) for a consumer good. The formula
           may take the form
                                         d=Y+P+D


Durable Consumer Goods

Three different purchase characteristics can be distinguished in the case of
durable consumer goods. They are:

   i.   Time-use characteristics;
  ii.   Use-facilities characteristics; and
 iii.   Demographic characteristics.

i.      Time-use characteristics
        Consumer durables have got extended use and as such they are never
        used up in a single act as are match-sticks or ice-cream. This feature
        enables the consumers to go on using them by repairing if necessary,
        or to scrap them and get new ones. Experience shows that
        emergencies such as war or scarcity force people to postpone
        replacement of durable goods and thereby to lower the effective
        scrapping rate. The decisions to replace goods are influenced also by
        considerations such as social prestige and status, income and product
        obsolescence.
ii.     Use-Facilities characteristics
        Generally durable goods require special facilities for their use. For
        example, to use a car, or truck, one needs to have roads and petrol or
        diesel stations. Again, to use a refrigerator or a radio, one needs
        electricity. The existence and growth of such facilities is an important
        variable in determining the volume of sales or quantity demanded of
       the products in question. Hence, due consideration must be given in
       choosing the variables influencing the demand for durable consumer
       goods.

iii.   Demographic characteristics
       The decision to purchase consumer durables is influenced also by
       factors such as size of families, age distribution of adults and children,
       population groups in different income strata, price and other
       considerations. Demography here includes a study of populations other
       than human also. A study of the demand for commercial airliners has
       used the number of commercial airports as both a use facilities
       characteristics and as demographic characteristics in deriving the
       forecasting    equation.   Hence,     the    three   different   purchase
       characteristics may be considered independently, or in combination,
       depending on the product and the economic judgment of the analyst.

       The total demand for durable goods, in fact, is the sum of two
       demands: a new owner demand and a replacement demand. The new
       owner demand will increase the stock of the goods. Replacement
       demand tends to grow with the growth in the total stock with
       consumers and at times it may even exceed the new stock with
       consumers and at times it may even exceed the new demand. For
       certain well established products, life expectancy tables are made
       available in advanced countries in order to estimate the average or
       near average replacement rates.

       The basic demand equation for durables may be stated as follows:
                                     d=N+R
       Where, (d) represents total demand, (N) new-order demand and (R)
       replacement demand.

       Each of these independent variables may be forecast separately. It
       must be borne in mind that in the case of most durable goods there is
       an upper limit beyond which demand cannot grow. This upper limit
       refers to the ‘saturation point’. For example, even if income goes up,
       there is limit to the number of radios that people will buy. It is to this
       level towards which the actual volume of consumer stocks tends to
       gravitate. The difference between the ‘saturation point’ or the
      ‘maximum ownership level’ and the actual stock shows the growth
      potential of the demand for durable goods.



Capital goods

Capital goods are ‘produced means of further production’. They are used to
facilitate the production of other goods. Examples are machinery of all kinds,
factor buildings etc. The demand for capital goods is a case of ‘derived
demand’. Hence, the demand for capital goods depends upon the
profitability of the industries using the capital goods, the ratio of production
to capacity in user industries, the level of wage rates, the policy of the
Government, business prospects, etc. Where the wage rates go exceptionally
high, the management will have an added tendency to go for labor-saving
equipment.

In the case of particular capital goods, demand will depend on the specific
markets they serve and the end uses for which they are bought. The
demand for textile machinery, for instance, will be determined by the
expansion of textile industry in terms of new units and replacement of
existing machinery. Therefore, demand forecasts for capital goods will have
to take into account new demand as well as replacement demand.

Two types of data are required for forecasting the demand for capital goods,
intermediate or industrial goods. They are

      i)    The growth prospects of the user industries, and
      ii)   The criteria or norm of consumption of the capital goods per unit
            of each end use.



The critical assumptions underlying the ‘end-use approach’ are:

   a) The demand estimates for the ‘end-use approach’ are available
   b) The norms of consumption (the technology of the industry) will remain
      unchanged during the period under consideration.
   c) Norms based on present consumption patterns in industry may, in
      part, reflect existing shortages and import restrictions in the economy.
In building bridges, for example, mild steel might be in use at present
instead of constructional steel (which is more suitable for the purpose.
This might be due to the non-availability or high cost of constructional
steel. But as the pattern of availability changes, the consumption
pattern in the industry may also vary, changing the norms of
consumption in the process.

				
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