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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