Mba Semester 1 Assignment

Mba Semester 1 Assignment Words: 10651

Master of Business Administration – MBA Semester I MB0042 – Managerial Economics – 4 Credits (Book ID: B0908) Assignment Set- 1 ( 60 Marks) Note: Each question carries 10 Marks. Answer all the questions. Q. 1 Price elasticity of demand depends on various factors. Explain each factor with the help of an example. Q. 2 A company is selling a particular brand of tea and wishes to introduce a new flavor. How will the company forecast demand for it ? Q. 3The supply of a product depends on the price.

What are the other factors that will affect the supply of a product. Q. 4Show how producers equilibrium is achieved with isoquants and isocost curves. Q. 5 Discuss the full cost pricing and marginal cost pricing method. Explain how the two methods differ from each other. Q. 6 Discuss the price output determination using profit maximization under perfect competition in the short run. Q. 1 Price elasticity of demand depends on various factors. Explain each factor with the help of an example.

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Answer: Consumers in a market economy are influenced by various factors in deciding what to buy. One of these factors is price, and the law of demand that defines the typical relationship between price and quantity demanded states that consumers will demand more of a particular product at a lower price, and less at a higher price. However, the price elasticity of demand extends this and examines the extent of such changes in demand in relation to price.

How much demand contracts or expands in response to a price change is of importance to businesses and governments, and hence methods such as the total outlay method have been developed to test the price elasticity of demand at various price levels. The price elasticity of demand measures the responsiveness or sensitivity of the quantity demanded of a particular product to changes in its price. As a figure, the price elasticity of demand shows the percentage change in the quantity of a good demanded resulting from a 1% increase in its price. Demand can hence be said to be relatively elastic, relatively inelastic or unitary elastic.

As for most goods, a fall in price will cause an expansion in demand, but if that expansion in demand were proportionately greater than the fall in price, then we would say that quantity demanded is very responsive to a price change; thus demand is said to be relatively elastic. The opposite situation, relatively inelastic demand, indicates that there has been a less than proportionate change in quantity demanded – a weak response to price change. When the total amount spent remains unchanged, the proportionate change in quantity demanded is the same as the proportionate change in price, and demand is said to be unitary elastic.

There are other methods of determining the price elasticity of demand, such as the arc method and the point method, but the total outlay method is a simple way of measuring price elasticity. It looks at the effect of changes in price on the total revenue earner by the producer. Total outlay (or revenue) is found by multiplying price by the quantity that would be demanded at that price. In effect, the total outlay (or total expenditure) by consumers on a certain product is equivalent to the total revenue that sellers of the product would receive at that price.

If total outlay moves in the same direction as the price change, demand in that price range would be relatively inelastic. Consumers demand 50 units at a price of $5, so total outlay is $250. When the price rises to $6, demand falls to 45 units, but the total outlay increases to $270. Total outlay has moved in the same direction as the price change – the price increase would lead to an increase in total revenue for firms, therefore demand is said to be relatively inelastic over this price range. If total outlay moves in the opposite direction to the price change, demand in that price range would be relatively elastic.

At a price of $8, consumers demand 35 units, so the total outlay is $280. If the price rises to $9, demand falls to 30 units, and total outlay decreases to $270. Total outlay has moved in the opposite direction to the price change – the quantity demanded is highly responsive to price changes. Hence, demand is said to be relatively elastic over this price range. If total outlay remains the same following a price change, then the demand would be said to be unitary elastic. At price $7, consumers demand 40 units, so the total outlay is $280. When the price rises to $8, demand falls to 35 units, but the total outlay remains the same at $280.

Total outlay has remains the same, so demand has unitary elasticity over this price range. This shows that, even with a linear demand curve, which has a constant slope, the price elasticity of demand will vary along the curve. In the upper part of the curve (where prices are high), demand will be relatively elastic (quantity demanded is highly responsive to price changes), whereas at low levels, demand will be relatively inelastic. When using graphs, the price elasticity of demand over a particular price range can be determined by using the total outlay method with the price and quantity demanded from the graph.

Hence, by using diagrams, we can recognize two extremes of elasticity of demand –perfectly elastic demand and perfectly inelastic demand. These two extreme circumstances are the only ones where looking at the slope of the demand curve is sufficient to determine the price elasticity of demand through the entire curve. When demand is perfectly elastic, the demand curve is a horizontal straight line, and when demand is perfectly inelastic, the demand curve is a vertical straight line. With perfectly elastic demand, consumers will demand an infinite (unlimited) quantity at a certain price, but nothing at all at a price above or below this.

It would be very hard to satisfy these conditions for any market as a whole, so this situation can be regarded as being merely theoretical. However, an individual seller may face perfectly elastic demand in certain circumstances. If the seller were in a perfectly competitive market, then no individual seller would be able to charge a higher price, since he or she would lose all customers to the others selling identical products. In addition, the seller would not seller the product at a price below the other growers, because he or she can sell it at the higher market price and make more money.

Therefore, from the point of the individual seller, the demand curve for the product is perfectly elastic at the going market price. For perfectly in elastic demand, consumers are willing to pay any price in order to obtain a given quantity of a good. Again, it would be very difficult to satisfy these conditions for any market as a whole. It could however apply to some products over a given range of prices. For example, persons with a life threatening disease that can only be treated with a particular drug would be willing to pay almost any price to obtain that drug.

Thus, it is often argued that governments should regulate such markets, in order to prevent the exploitation of vulnerable consumers. The price elasticity of demand for any good can be affected by one or more of five factors. Firstly, price elasticity of demand depends on whether the good is a luxury or a necessity. Goods and services regarded as necessities for daily life, such as bread or milk, have a relatively inelastic demand – even if there is an increase in price, the quantity demanded will not contract greatly.

On the other hand, price elasticity of demand would be expected to be higher for products that may be regarded as luxuries, such as dining out in restaurants. Goods and services with close substitutes, such as different brands of breakfast cereal, tend to have highly elastic demand. If the price of one brand of cereal increases, then demand is likely to contract more than proportionately, since people would simply switch to another brand that they perceive to be equally as good.

Goods and services with few or no close substitutes, such as the local water supply, would have an inelastic demand – even if price increases, people cannot switch to another product, so demand will not fall greatly. Goods and services that take up a very small proportion of a person’s income, such as disposable lighters, cheap pens, and chewing gum, would have a lower price elasticity of demand, whereas the demand for more expensive items would tend to be more elastic. For example, most people would not refuse to buy chewing gum because its price increased by 10%, but they may well decide not to buy a new car which has had a 10% price rise.

When the price of a certain product increases, the quantity demanded may not initially respond greatly, as consumers become aware and take time to adjust to the price change. If the price has increased, with time consumers will have the opportunity to seek out alternatives, and in particular, identify substitute products making demand more responsive. Similarly, if the price of a product has fallen, with time as consumers become aware that it is relatively cheaper now compared to its substitutes, they switch towards it and demand becomes more responsive.

The responsiveness subsequent to a price change may also depend on whether the good in question is durable or not. After an initial price change, durable goods tend to have a more elastic demand than non-durable goods. For example, a rise in price of new cars would initially tend to encourage people to repair rather than replace their existing cars, so demand would be highly elastic. However, with time, the elasticity would decline, as old cars have to be replaced at some point. Goods that tend to be habit forming, like cigarettes and alcoholic beverages, tend to have a relatively inelastic demand.

People who regularly drink alcohol and smoke tend to continue with the same habits, even following price increases. Intimate knowledge of the price elasticity of demand and factors that may alter it is important to both businesses and the government. Business would like to maximize profits, and utilization of price elasticity of demand to determine the best pricing policy is thus very important. The government needs to understand price elasticity of demand to price community goods and services, and to determine levels of taxation on particular products.

Business firms needs to understand price elasticity of demand for the goods they sell in order to decide on their optimal pricing policy. If demand were relatively elastic, the firm would know that lowering the price would expand the volume of sales, thus increasing total revenue. On the other hand, if demand were relatively inelastic, the firm could increase the price, which would also lead to an increase in total revenue, since the drop in sales would be less then proportionate.

Awareness of the elasticity of demand in different price ranges is important for determining the best pricing policy for a firm and in deciding whether to change prices. To that extent, businesses often engage in statistical market research in order to determine consumer preferences, and in particular, the price elasticity of the demand for their product. The government needs to understand price elasticity of demand when pricing the goods and services that it provides for the community (such as public transport fares).

Further, it also needs to be able to predict the effects of changes in the level of any indirect taxes, such as sales taxes, excise duties and special levies that is imposes on goods such as alcohol, tobacco products and petrol. These taxes and charges raise the price of the goods affected, and the government needs to be able to gauge the responsiveness of demand in order to estimate accurately the amount of revenue they will raise. This relationship explains why governments tend to charge indirect taxes, such as excise duties, on those goods that have a relatively inelastic demand, including alcohol, petrol and tobacco products.

On the other hand, if the government were to impose an excise duty on a good for which demand is relatively price elastic, the increase in price caused by the tax would lead to a more than proportionate drop in sales. As a result, the increase in the tax may not raise revenue significantly. In conclusion, economics is a social science of human needs and wants that must be satisfied. In market economies, consumers can exercise their right to buy whatever they want. However, consumers will only purchase certain goods in certain quantities at certain prices; if there is a price change, quantity demanded will adjust correspondingly.

This is where price elasticity of demand comes in, measuring the responsiveness or sensitivity of the quantity demanded to changes in price using methods such as the total outlay method. Finally, this information is important to businesses, which need to find their optimal pricing policy in order to achieve their goal of maximizing profits, as well as to governments, which need to price their own goods and services and determine indirect taxes imposed on goods and services. Determinants of price elasticity are 1.

Nature of commodity-commodities coming under category of necessaries and essentials tend to be inelastic since people them irrespective of price. Ex Grains, Milk, Vegetables. 2. Existence of Substitutes- economically interchangeable goods are considered as substitutes by buyers. If commodity has no substitute in market, demand tends to be inelastic and buyers pay high price for such goods. Ex salt, Tooth pastes, Soaps. 3. Number of uses of commodity- Single use goods is those that can be used for only purpose and multi-use goods are those that can be used for variety of purposes. . Level of knowledge- Demand in case of enlightened customer would be elastic and in case of ignorant customers, it would be elastic. 5. Range of Prices- Goods for which a small fall or rise in prices will have insignificant effect on their demand. Eg cars, computers etc 6. Habits- when people are habituated for use of commodity, they do not care about the price eg alcohol. Q. 2 A company is selling a particular brand of tea and wishes to introduce a new flavor. How will the company forecast demand for it ?

Answer:-A demand forecast is the prediction of what will happen to the company’s existing product sales. It would be best to determine the demand forecast using a multi-functional approach. The inputs from sales and marketing, finance, and production should be considered. The final demand forecast is the consensus of all participating managers. Determination of the demand forecasts is done through the following steps: •  Determine the use of the forecast •  Select the items to be forecast •  Determine the time horizon of the forecast •  Select the forecasting model(s) •  Gather the data   Make the forecast •  Validate and implement results The time horizon of the forecast is classified as follows: Description| Forecast Horizon| Short-range| Medium-range| Long-range| | Duration| Usually less than 3 months, maximum of 1 year| 3 months to 3 years| More than 3 years| Applicability| Job scheduling, worker assignments| Sales and production planning, budgeting| New product development, facilities planning| How is demand forecast determined? There are two approaches to determine demand forecast – (1) the qualitative approach, (2) the quantitative approach.

The comparison of these two approaches is shown below: Description| Qualitative Approach| Quantitative Approach| Applicability| Used when situation is vague & little data exist (e. g. , new products and technologies)| Used when situation is stable & historical data exist(e. g. existing products, current technology)| Considerations| Involves intuition and experience| Involves mathematical techniques| Techniques| Jury of executive opinionSales force compositeDelphi methodConsumer market survey| Time series modelsCausal models|  Qualitative Forecasting Methods

Your company may wish to try any of the qualitative forecasting methods below if you do not have historical data on your products’ sales. Qualitative Method| Description| Jury of executive opinion| The opinions of a small group of high-level managers are pooled and together they estimate demand. The group uses their managerial experience, and in some cases, combines the results of statistical models. | Sales force composite| Each salesperson (for example for a territorial coverage) is asked to project their sales.

Since the salesperson is the one closest to the marketplace, he has the capacity to know what the customer wants. These projections are then combined at the municipal, provincial and regional levels. | Delphi method| A panel of experts is identified where an expert could be a decision maker, an ordinary employee, or an industry expert. Each of them will be asked individually for their estimate of the demand. An iterative process is conducted until the experts have reached a consensus. | Consumer market survey| The customers re asked about their purchasing plans and their projected buying behavior. A large number of respondents is needed here to be able to generalize certain results. | Quantitative Forecasting Methods There are two forecasting models here – (1) the time series model and (2) the causal model. A time series is a s et of evenly spaced numerical data and is obtained by observing responses at regular time periods. In the time series model, the forecast is based only on past values and assumes that factors that influence the past, the present and the future sales of your products will continue.

On the other hand, the causal model uses a mathematical technique known as the regression analysis that relates a dependent variable (for example, demand) to an independent variable (for example, price, advertisement, etc. ) in the form of a linear equation. The time series forecasting methods are described below: Time Series Forecasting Method| Description| Naive Approach| Assumes that demand in the next period is the same as demand in most recent period; demand pattern may not always be that stableFor example:If July sales were 50, then Augusts sales will also be 50| Time Series Forecasting Method| Description|

Moving Averages (MA)| MA is a series of arithmetic means and is used if little or no trend is present in the data; provides an overall impression of data over timeA simple moving average uses average demand for a fixed sequence of periods and is good for stable demand with no pronounced behavioral patterns. Equation:F 4 = [D 1 + D2 + D3] / 4F – forecast, D – Demand, No. – Period(see illustrative example – simple moving average)A weighted moving average adjusts the moving average method to reflect fluctuations more closely by assigning weights to the most recent data, meaning, that the older data is usually less important.

The weights are based on intuition and lie between 0 and 1 for a total of 1. 0Equation:WMA 4 = (W) (D3) + (W) (D2) + (W) (D1)WMA – Weighted moving average, W – Weight, D – Demand, No. – Period(see illustrative example – weighted moving average)| Exponential Smoothing| The exponential smoothing is an averaging method that reacts more strongly to recent changes in demand by assigning a smoothing constant to the most recent data more strongly; useful if recent changes in data are the results of actual change (e. g. seasonal pattern) instead of just random fluctuationsF t + 1 = a D t + (1 – a ) F tWhereF t + 1 = the forecast for the next periodD t = actual demand in the present periodF t = the previously determined forecast for the present period•  = a weighting factor referred to as the smoothing constant(see illustrative example – exponential smoothing)| Time Series Decomposition| The time series decomposition adjusts the seasonality by multiplying the normal forecast by a seasonal factor| NEW PRODUCT FORECASTING SYSTEM (NPFS) This study aims to solve the new product sales forecasting problem.

However, no standard procedure for new product sales forecasting currently exists. Therefore, we propose a procedure that standardizes the steps from data collection to the final subjective adjustments of the forecast results. Step 1: Collect and Analyze Data Different types of data related to new product forecasts are required and must be collected in step 1. Forecasts are usually based on past product sales patterns; however, with new products, it is difficult to observe any pattern since very little historical sales data is available.

In this first step, forecasters should focus on increasing the quantity of the input data so that at least three sales data periods are available. In addition to increasing the data quantity, in this step, the data quality should also be improved by attempting to reduce the variation and identifying the leading indicators. Step 2: Determine Parameters for Forecasting Methods and Select the Best Forecasting Method The parameters for each forecast method must be determined. Different forecasting methods require different parameters, which have a direct impact on the forecast results.

In the procedure proposed in this study, we use the Mean Absolute Percentage Error (MAPE) as the evaluation standard for selecting a method. Experienced forecasters who know the market well can later help to decide whether or not to adjust the results subjectively. Companies can also define rules or indices for altering the results. The evaluation rules for forecast accuracy are based not only on the historic sales data, but also on the weighted average heuristic. Step 3: Calculate Sales Forecast

Once the parameters and the forecasting method have been determined, the forecast is calculated according to the desired planning horizon—short-term, mid-term, and/or long-term. For instance, when managers make long-term strategic decisions, such as picking the location for a new factory site, they need a rough idea of the future sales trends and thus sales forecasts for the next year could be appreciated. On the other hand, short-term decisions are facilitated by daily and weekly sales forecasts. Step 4: Adjust Results Subjectively

Experienced managers or forecasters often adjust the forecast results manually. The survey results of Sanders et al showed that more than 80% of the respondents adjust quantitative forecast results based on their subjective judgment. Professional managers often have their own perceptions of future trends based on the events occurring on the market and their industry experience. Consequently, step 4 allows managers to make adjustments, with the final results being used for future planning for a variety of purposes at the end of forecast procedure.

The tasks in steps 1, 2 and 3 of the above procedure are facilitated by a decision-support system called New Product Forecast System (NPFS). This decision-support system comprises four modules that provide functions for the forecasting tasks so that users don’t have to be experts in business forecasting techniques. There are three major difficulties inherent to new product sales forecasts: dealing with limited data, using the forecasting methods, and selecting the best method to use.

The four modules of Decision-support system —Data Handling, Forecasting Model, Learning Platform and Forecasting—can tackle these three problems. Data Handling Module The data handling module is responsible for dealing with the limited data problem. Because new products have been recently introduced on the market, little or no sales data are available for analysis. It is thus necessary to find substitute data in order to calculate the sales forecast. There are many external factors that can affect sales, including special events and promotional events.

For this reason, in addition to finding substitute data, this module focuses on improving the quality of input data by identifying these external factors and prepares the input data for processing by the forecasting model module. The data handling module produces at least three periods of sales data, either from its own historic data or from the historic data of items in the same class. This data, together with all the parameters needed for each forecast method, are send on to the forecasting model module. Forecasting Model Module

Unlike sales forecasts for mature products with a stable demand, the most difficult problem with new product sales forecasting is the lack of historical data. Because newly introduced products have no historic behavior to be traced, Regression is not appropriate for new product forecasting and thus was not included in the NPFS decision-support system. N-period Moving Average, Exponential Smoothing, and Exponential Smoothing With Trends (an extension of Exponential Smoothing), though predicting the future sales based on a product’s historic patterns, require only a few data points and thus were included in our system.

In addition, the NPFS decision-support system includes all three of the new product forecasting methods presented in our literature review: Sales Index, Diffusion Model, and truncated Taylor Series. Each of these methods have their own limitations, and thus we have modified them for use in our NPFS system. By the end of processing in the forecasting module, for each new product, there is a choice of at least six methods, each with multiple parameter selections. Learning Platform The learning platform module provides an automatic learning platform that uses input from data handling module and forecasting model module.

It determines the best parameters for each method and then chooses the most appropriate method for future sales forecasting according to most current available data. When sales occur and new historical data are input into NPFS, the learning platform module is activated again and selects the most appropriate method for the current situation. The final method selected, together with its best parameters, is used for future forecasts The Architecture of New Product Forecast System (NPFS) Forecasting

Once the learning platform module has selected the best forecasting method and the best parameters for each new product, the forecasting module then computes the future sales forecast. The resulting forecast will become the basis for future planning, which can be long-term, mid-term and short-term. Future sales forecasts may focus on different geographical levels (e. g. , country, region, city, and store) or different time dimensions (e. g. , yearly, quarterly, monthly, weekly, and daily). In order to meet different planning objectives, the forecasting module predicts future sales for different combinations of these two dimensions.

TESTING NPFS ON REAL-WORLD CASES This section demonstrates the applicability of NPFS using two real-world problems, involving two retail company selling different kinds of products: tea and cosmetics. The first case deals with new tea products. The data used was provided by a leading tea company in Taiwan, whose business encompasses the planting, producing, and retailing of tea. In addition, this leading tea company has started serving “tea meals” in their shops in recent years. As of April of 2007, the company had 133 chain stores all over Taiwan.

The date for introducing new tea products depends on the tea leaf picking season—winter or spring. A successful tea product can be sold for years. Three successful new tea products that had good initial sales periods in 2006 were used to compare the NPFS forecast results with the results of the commonly-used Moving Average method. The information about these three new products from different classes is given in Table 1. Two of the new products have an appropriate number of actual data points, while one has data points for only 2 periods. Table 1 shows the NPFS result and Moving Average (MA) result.

Judging by the future MAPE, the NPFS forecast is better than the MA forecast. NPFS chose the ES method for two of the new products and the SI method for the last new product because the sales of the item 450XX followed a pattern similar to other products in the same class. The result for the new tea products also agrees with the scenario analysis conclusion that the number of actual data points affects the forecast accuracy. Table 1: Forecast Results using NPFS and MA for the New Tea Products The second case deals with new cosmetic products. The data used was provided by a leading chain drugstore with more than 100 stores across Taiwan.

Five successful new cosmetic products from different classes were selected to test the applicability of NPFS (Table 2). These products had been sold in the leading chain drugstore in 2006. Cosmetics are such a competitive business that hundreds of new products are launched every year to satisfy customer needs. The lifecycle of a cosmetic product is short, and the demand is usually unstable. As shown in Table 2, most of the new products used in this test had only a few actual data points. Table 2 reports the NPFS results and the MA results. Because the demand was unstable, ES was selected for three of the products and SI for the other two.

The forecast produced by NPFS is obviously better than the one produced by the MA method based on the future MAPE. The results for these two real-world cases show that NPFS forecasts are better than those of the commonly used MA method. CONCLUSION New product sales forecast usually depends on the decisions of experienced managers, such as decisions about the selection of the forecasting model when only limited data is available. Instead of relying on human judgments, this study introduces a standard forecast procedure offering a general work flow to perform forecast.

In addition, New Product Forecast System (NPFS) is proposed to help executing the standard forecast procedure for new product sales forecast. A prototype of NPFS is constructed to evaluate the performance. NPFS is applied to a real-world case of cosmetics. In this case, several successful products in different classes were tested and the forecast result showed that NPFS had better performance than the commonly used methods. It can be concluded that the commonly used methods that widely adopted in practice is not suitable one to be used in new product forecast.

More real-world cases—such as consumer electronics and fashion products—should be tried because they introduce different types of new products every seasons. Furthermore, this study only include quantitative models in NPFS. The qualitative model which considers consumer behavior should also be included in NPFS in the future to boost the forecast accuracy. Some product characteristics—color, style, or special design—affect the sales of products significantly and thus should be identified and quantified in NPFS in the future to help product classification or future sales forecast. Q. The supply of a product depends on the price. What are the other factors that will affect the supply of a product? Answer: A supply schedule and supply curve show that the supply of a product is function of its price. However the supply depends not only on the price of the product but on several factors, will the change in other factors the entire supply curve shifts upward and downward shift of a demand curve are detailed below. (1) Change the cost of production: Supply depends on the cost of production, a rise in the cost production will shift the supply curve upward showing the decrease in the supply.

On the other hand a fall in the cost leads to an increase in the supply. In such a case the supply curve shifts tumid. (2) Production technology A change in technology leads to a fall in the cost of production. If the technologies followed by the firms are improved, the cost of production will decline so that the firms would supply more than before. Thus the improvement in technology leads to an increase in the supply of a commodity. (3) New Source of raw materials. Discovery and exploitations of new sources of raw materials enable the produce to supply more at the same price.

As against this, the supply of the commodity decrease was with the constant depletion of sources of basic raw materials. (4) Composite relationship: There are certain commodities the productions of which bring about the production of another commodity as in the case of paddy and straw. This happens in case of joint goods. Any increase in the product of paddy will result in the increase in the production of straw. (5) Natural Factors: The supply of agricultural commodities depends on the natural factors. The supplies of agricultural products rise with the handsome rainfall and good weather.

Supply of adequate inputs, improved seeds and improvement in irrigation and better fertilizers enable an agriculturist to increase the supply. On the other hand, inadequate irrigation, failure of rains floods and pestilence will decrease the supply. (6) Objective of the firm: The objective of a firm also determines the supply of a product. If the objective of a firm is maximizations of sale and revenue rather than profit, the supply of the product produce by it would be larger. (7) Prices of other products:

Any change in the prices of other products would influence the supply of a product by substituting one product for another. If the market price of coffee rises, it causes a reduction of the production and supply of tea as the producers withdraw some resource from the production of tea and devote them for the production of wheat. (8) Means of transport The cost of transport also affects the supply. Improvement in means of transport results in the extension of market for the commodity. This boosts up supply of the commodity under consideration. (9) Expectations of future price:

The supply of a commodity in the market at any time is determined by sellers expectations of future prices. During inflation tellers expect the prices to rise in future. They would hoard the essential goods thereby creating artificial reduction in the supply of the goods in question. (10) Taxes and subsidies: Taxes and subsidies also influence the supply of a product. Imposition of sales tax on product will put the producer in a mate whether to supply the same quantity at higher price or less quantity at the same price. The opposite happens in case of subsidies.

Incorporation of subsidies helps the producers to increase supply. Q. 4 Show how producers equilibrium is achieved with isoquants and isocost curves. Answer: The production function and economic efficiency The ways in which resources can be combined to produce output are summarized by a firm’s Production function. The production function identifies the maximum quantities of a particular good (or service) that can be produced per time period with various combinations of resources and with a given state of technology. The production function can be presented as an equation, a graph or a table.

The production function summarized in Table 8A. 1 reflects, for a hypothetical firm, the output resulting from particular combinations of resources. This firm uses only two resources: capital and labour. The amount of capital used is listed in the left-hand column of the table, and the amount of labour employed is listed across the top. For example, if 1 unit of capital is combined with 7 units of labour, the firm can produce 290 units of output per period. We assume that the firm produces the maximum possible output given the combination of resources employed, and that the same output could not be roduced with fewer resources. Since we assume that the production function combines resources efficiently, 290 units is the most that can be produced with 7 units of labour and 1 unit of capital. Thus, we say that the firm’s production is technologically (or productively) efficient. We can examine the effects of adding additional labour to an existing amount of capital by starting with some level of capital and reading across the table. For example, when 1 unit of capital and 1 unit of labour are employed, the firm produces 40 units of output per period.

If the amount of labour is increased by 1 unit and the amount of capital employed is held constant, output increases to 90 units, so the marginal product of labour is 50 units. If the amount of labour employed increases from 2 to 3 units, other things constant, output goes to 150 units, yielding a marginal product of 60 units. By reading across the table, you will discover that the marginal product of labour first rises, showing increasing marginal returns from the variable resource (labour), and then declines, showing diminishing marginal returns.

Similarly, by holding the amount of labour employed to 1 unit and following down the column, you will find that the marginal product of capital also reflects first increasing marginal returns and then diminishing marginal returns. Isoquants Notice from the tabular presentation of the production function in Table 8A. 1 that different combinations of resources may yield the same level of output. For example, several combinations of labour and capital yield 290 units of output. Some of the information provided in Table 8A. 1 can be presented more clearly in graphical form.

In Figure 8A. 1, the quantity of labour employed is measured along the horizontal axis and the quantity of capital is measured along the vertical axis. The combinations that yield 290 units of output are presented in the figure as points a, b, c and d. These points can be connected to form an isoquant, Q1, which shows the possible combinations of the two resources that produce 290 units of output. Likewise, Q2 shows combinations of inputs that yield 415 units of output, and Q3 shows combinations that yield 475 units of output. (The colours of the isoquants atch those of the corresponding entries in the production function table in Table 8A. 1. ) An isoquant, such as Q1 in Figure 8A. 1, is a curve that shows all the technologically efficient combinations of two resources, such as labour and capital, that produce a certain amount of output. Iso is from the Greek word meaning ‘equal’, and quant is short for ‘quantity’; so isoquant means ‘equal quantity’. Along a particular isoquant, such as Q1, the amount of output produced remains constant, in this case 290 units, but the combination of resources varies.

To produce a particular level of output, the firm can employ resource combinations ranging from capital intensive combinations (much capital and little labour) to labour-intensive combinations (much labour and little capital). For example, a paving contractor can put in a new driveway with ten workers using shovels and hand-rollers; the same job can also be done with only two workers, a road grader and a paving machine. A Saturday-afternoon charity car wash to raise money to send the school band on a Gold Coast holiday at Nara Sea World is labour-intensive, involving perhaps a dozen workers per car.

In contrast, a professional car wash is fully automated, requiring only Fig 8A. 1 one worker to turn the machine on and off and collect the money. An isoquant shows such alternative combinations of resources that produce the same level of output. Let us consider some of the main properties of isoquants. Isoquants further from the origin represent greater output levels Although we have included only three isoquants in Figure 8A. 1, there is a different isoquant for every quantity of output depicted in Table 8A. 1.

Indeed, there is a different isoquant for every output level the firm could possibly produce, with isoquants further from the origin indicating higher levels of output. Isoquants slope down to the right. Along a given isoquant, the quantity of labour employed is inversely related to the quantity of capital employed, so isoquants have negative slopes. Isoquants do not intersect Since each isoquant refers to a specific level of output, no two isoquants intersect, for such an intersection would indicate that the same combination of resources could, with equal efficiency, produce two different amounts of output.

Isoquants are usually convex to the origin Finally, isoquants are usually convex to the origin, meaning that the slope of the isoquant gets flatter down along the curve. To understand why, keep in mind that the slope of the isoquant measures the ability of additional units of one resource — in this case, labour (L) — to substitute in production for another — in this case, capital (K). As we said, the isoquant has a negative slope. The slope of the isoquant is the marginal rate of technical substitution (or MRTS), defined between any two resources as: KMRTSLK = ————???????????????????

L DELTA Here, the MRTSLK indicates the rate at which additional units of labour (L) can be substituted for fewer units of capital (K) while keeping output (TP) constant. When much capital and little labour are used, the marginal productivity of labour is relatively great and the marginal productivity of capital is relatively small, so one unit of labour will substitute for a relatively large amount of capital. Consider the case of moving from point a to b along isoquant Q1 in Figure 8A. 1. One unit of labour substitutes for 2 units of capital, so the MRTSLK between points a and b equals 2.

But as more units of labour and fewer units of capital are employed, the marginal product of labour declines and the marginal product of capital increases, so it takes more labour to make up for a reduction in capital. For example, in moving from point c to point d in Figure 8A. 1, 2 units of labour substitute for 1 unit of capital; hence, the MRTSLK between points c and d equals 1/2. The extent to which one input substitutes for another, as measured by the marginal rate of technical substitution, is directly linked to the marginal productivity of each input.

For example, between points a and b, 1 unit of labour replaces 2 units of capital, yet output remains constant. Thus, labour’s marginal product, MPL — that is, the additional output resulting from an additional unit of labour — must be twice as large as capital’s marginal product, MPK. In fact: All along the isoquant, the marginal rate of technical substitution of labour for capital equals the marginal product of labour divided by the marginal product of capital, which also equals the absolute value of the slope of the isoquant. Thus, we can say that: MPL Slope of isoquant = MRTSLK = ———— MPK here the vertical lines on either side of ‘Slope of isoquant’ mean the absolute value. For example, between points a and b the slope equals –2, which has an absolute value of 2, which equals the marginal rate of substitution of labour for capital and the ratio of marginal productivities. If labour and capital were perfect substitutes in production, the rate at which labour substituted for capital would remain fixed along the isoquant, so the isoquant would be a downward-sloping straight line. Since most resources are not perfect substitutes, however, the rate at which one substitutes for another changes along an isoquant.

As we move down along an isoquant, more labour is required to offset each 1-unit decline in capital, so the slope of the isoquant gets flatter, yielding an isoquant that is convex to the origin. The main properties of isoquants: 1. Isoquants further from the origin represent greater levels of output. 2. Isoquants slope downward. 3. Isoquants never intersect. 4. Isoquants tend to be convex — that is, bowed towards the origin. Isocost lines Isoquants graphically illustrate a firm’s production function for all quantities of output the firm could possibly produce.

Given these isoquants, how much should the firm produce? More specifically, what is the firm’s profit-maximising level of output? The answer depends on the cost of resources and on the amount of money the firm plans to spend. Assume a unit of labour costs the firm $15 000 per year, and the cost for each unit of capital is $25 000 per year. The total cost (TC) of production is: TC = (w x L) + (r x K) = $15 000 L + $25 000 K where w is the annual wage rate, L is the quantity of labour employed, r is the annual cost of capital, and K is the quantity of capital employed.

An isocost line identifies all combinations of capital and labour the firm can hire for a given total cost. Again, iso is from the Greek word meaning ‘equal’, so an isocost line is a line representing equal total cost to the firm. In Figure 8A. 2, for example, the line TC = $150 000 identifies all combinations of labour and capital that cost the firm a total of $150 000. The entire $150 000 could pay for 6 units of capital per year; if the entire budget is spent only on labour, 10 workers per year could be hired; or the firm can employ any combination of resources along the isocost line.

Recall that the slope of any line is the vertical change between two points on the line divided by the corresponding horizontal change (the rise over the run). At the point where the isocost line meets the vertical axis, the quantity of capital that can be purchased equals the total cost divided by the annual cost of capital, or TC/r. At the point where the isocost line meets the horizontal axis, the quantity of labour that can be hired equals the firm’s total cost divided by the annual wage, or TC/w. The slope of any isocost line in Figure 8A. can be calculated by considering a movement from the vertical intercept to the horizontal intercept. That is, we divide the vertical change (–TC/r) by the horizontal change (TC/w), as follows: –TC/r w Slope of isocost line = – ————— = – —– TC/w r The slope of the isocost line equals minus the price of labour divided by the price of capital, or –w/r, which indicates the relative prices of the inputs. In our example, the absolute value of the slope of the isocost line equals w/r, or: Slope of isocost line = w/r = 15 000/25 000 0. 6 The wage rate of labour is 0. 6 of the annual cost of capital, so hiring one more unit of labour, without incurring any additional cost, implies that the firm must employ 0. 6 units less capital. A firm is not confined to a particular isocost line. Thus, a firm’s total cost depends on how much the firm plans to spend. This is why in Figure 8A. 2 we include three isocost lines, not just one, each corresponding to a different total budget. In fact, there is a different isocost line for every possible budget. These isocost lines are parallel because each reflects the same relative resource price.

Resource prices are assumed to be constant regardless of the amount employed. Fig. 8A. 2 The firm’s isocost lines The optimal choice of input combinations Suppose the firm has decided to produce 415 units of output and wants to minimise its total cost. The firm could select point f, where 6 units of capital are combined with 4 units of labour. This combination, however, would cost $210 000 at prevailing prices. Since the profit-maximising firm wants to produce its chosen output at the minimum cost, it tries to find the isocost line closest to the origin that still touches the isoquant.

Only at a point of tangency does a movement in either direction along an isoquant shift the firm to a higher cost level. Hence, it follows that: The point of tangency between the isocost line and the isoquant shows the minimum cost required to produce a given output. Consider what is going on at the point of tangency. At point e in Figure 8A. 3, the isoquant and the isocost line have the same slope. As mentioned already, the absolute value of the slope of an isoquant equals the marginal rate of technical substitution between labour and capital, and the absolute value of the slope of the isocost line equals the ratio of the input prices.

So, when a firm produces output in the least costly way, the marginal rate of technical substitutionmust equal the ratio of the resource prices, or: MRTSLK = MPL/MPK = w/r = $15 000/$25 000 = 0. 6 This equality shows that the firm adjusts resource use so that the rate at which one input can be substituted for another in production — that is, the marginal rate of technical substitution — equals the rate at which one resource can be traded for another in resource markets, that is the resource price ratio w/r. If this equality does not hold, it means that the firm could adjust its input mix to produce the same output for a lower cost.

Finally, to demonstrate the consistency between the golden rule for consumer equilibrium (compare Chapter 7) and the producer’s equivalent least-cost input combination rule, consider again the firm’s input equilibrium condition above: MPL w MRTSLK = ———— = —– MPK r Now, simply cross-multiply the wage rate w to the denominator and the MPK to the numerator of their respective opposite sides to yield: MPL MPK ———— = ———— w r

This is the least-cost input rule for firms operating in competitive resource markets — that is, employ a combination of resources such that the marginal product per dollar spent is equated across all resources used. Here only two resources, capital and labour, are employed. If this least-cost input condition is not met, then, assuming the eventual onset of diminishing returns to variable resources, it is possible to reallocate the amount of resource use between capital and labour until this equilibrium condition does hold. Fig. 8A. 3 Optimal combinations of inputs

The expansion path Imagine a set of isoquants representing each possible level of output. Given the relative cost of resources, we could then draw isocost lines to determine the optimal combination of resources for producing each level of output. The points of tangency in Figure 8A. 4 show the least-cost input combinations for producing several output levels. For example, the output level Q2 can be produced at its least-cost combination by employing K units of capital and L units of labour. The line formed by connecting these tangency points is the firm’s expansion path.

If the resources are capital and labour, we often refer to this path as the long-run expansion path. The expansion path need not be a straight line, though it will generally slope upwards, implying that firms will expand the use of both resources in the long run as output increases. Note that we have assumed that the prices of inputs remain constant as the firm varies output along the expansion path, so the isocost lines at the points of tangency are parallel — that is, they have the same slope. The firm’s expansion path indicates the lowest long-run total cost for each level of output.

For example, the firm can produce output level Q2 for TC2, output level Q3 for TC3, and so on. Similarly, the firm’s long-run average cost curve conveys, at each level of output, the total cost divided by the level of output. The firm’s expansion path and its long-run average cost curve represent alternative ways of portraying costs in the long run, given resource prices and technology. We can use Figure 8A. 4 to distinguish between short-run adjustments in output and long-run adjustments. Let’s begin with the firm producing Q2 at point b, which requires K units of capital and L units of labour.

Now, suppose that in the short run, the firm wants to expand output to Q3. Fig. 8A. 4 The long-run expansion path Since capital is fixed in the short run, the only way to expand output to Q3 is by expanding the quantity of labour employed to L’, which requires moving to point e in Figure 8A. 4. Point e is not the cheapest way to produce Q3 in the long run, for it is not a tangency point. In the long run, capital usage is variable, and if the firm wishes to produce Q3, it should adjust capital and shift from point e to point c, thereby minimising the total cost of producing Q3.

One final point: if the relative prices of resources change, the least-cost combination of those resources will also change, so the firm’s expansion path will change. For example, if the price of labour increases, capital becomes cheaper relative to labour. The efficient production of any given level of output will therefore call for less labour and more capital. With the cost of labour higher, the firm’s total cost for each level of output rises. Such a cost increase would also be reflected by an upward shift in the average total cost curve. SUMMARY

A firm’s production function specifies the relationship between resource use and output, given prevailing technology. An isoquant is a curve that illustrates the possible combinations of resources that will produce a particular level of output. An isocost line presents the combinations of resources the firm can employ, given resource prices and the amount of money the firm plans to spend. For a given level of output – that is, for a given isoquant – the firm minimises its total cost by choosing the lowest isocost line that just touches, or is tangential to, the isoquant.

The leastcost combination of resources will depend on the productivity of resources and the relative cost of resources. Q. 5 Discuss the full cost pricing and marginal cost pricing method. Explain how the two methods differ from each other. Answer: Pricing Objective * To keep, increase or defend market share * Compare prices with the competition * Eliminate the competition * Achieve target profits or maximise profits * To use excess production capacity * To project a high quality image * To survive All of the above give rise to setting the right price for the company. Elements of pricing: The relationship between price and quantity = the price decreases as the quantities sold increases * This is known as the law of demand However price in only one of several factors influencing demand and therefore sales. Take into consideration: Quantity, quality, time and cost Prevailing price levels in the target market. In some instances the price is set by the existence of similar products in the target market Market supply ; demand. This is dependant on the intensity of demand for the product. Example: Seasonal variations imported vegetables vs. locally grown Competition. Intensive competition puts pressures on prices.

In some instances you have to align your prices with those of your competitors. Foreign Exchange. Prices often fluctuate because of exchange rates. It is wise to consult the foreign exchange division of your bank for assistance when quoting in a foreign currency. Pricing Method: There are two main pricing policies: Cost-oriented pricing: is the simplest. The cost is calculated for each unit of production. A percentage or mark-up is added to this base cost to determine price. The most common methods of applying the cost plus approach: * Full cost pricing * Direct cost pricing * Marginal cost pricing * Break-even pricing

Full cost pricing: This takes into account all the variable costs ; fixed overheads that are directly attributable to production, ; a pre-determined profit margin. Weaknesses: No account is taken of the demand side this could result in the firm producing products they cannot sell Direct cost pricing: Direct cost pricing is represented by a formula: Direct cost = raw materials + direct labour + variable factory overhead A mark-up is added to the direct cost to cover estimated overheads and leave a profit, so identifying the costs directly attributed to each specific output ; using those costs to set prices.

Marginal Cost Pricing: Marginal costing is an accounting technique whereby a marginal cost is determined on the basis of additional variable costs only. It is the amount by which the total cost is changed if the volume of output of a product is increased by one unit. For example: If spare manufacturing capability is available, export prices at marginal costs may be quoted as the fixed costs are already being covered by domestic sales revenue. Break Even Pricing Break-even pricing allows a firm to compare the profit outcome of alternative sets of prices.

Firms can set prices to achieve maximum profit by concluding the price for given volumes. Verifying the volume that will deliver the most profit. MARKET ORIENTED PRICING * Demand-oriented pricing * Competition-oriented pricing Demand oriented pricing : This implies that a high price is charge where customer interest is high and a low price is charged where customer interest is low, despite that fact that the cost may be the same in both cases. Based on the customer’s perceived value. Competition oriented prcing: This is based on the actual or anticipated behaviour of competitors.

Exporters would peg their price to that of their competitors. The main forms are: going rate pricing and sealed bid pricing. Going rate pricing = The price is determined by market leaders who know what price the market will bear Sealed bid pricing = Used when firms have to compete for contracts on the basis of tenders. article uses specific examples to define and explain the economic concepts of marginal and full costs and their importance to consumers. An important concept to understand when running or analyzing a business is the difference between Marginal and Full Costs.

It is impossible to make good decisions on setting prices for goods and services without taking into account what it costs to make them. Defining Full Costs All products and services are made up of many components. In order to calculate the full cost of an item, all the inputs must be included: * Raw materials * Cost of employees creating the product or performing the service * Employee benefits if applicable * Building costs, including rent, mortgage interest, depreciation, and property taxes, etc. * Income and sales taxes Overhead costs, including legal fees, personnel costs, management and accounting. All costs are then divided by the number of units produced to obtain an average full cost. The company needs to generate enough from sales to cover the full cost; therefore the average price should be set high enough to accomplish this. If, for competitive reasons, the average price cannot be set high enough, then some costs must be reduced, or the company should discontinue the product or service. Defining Marginal Costs Marginal cost is identified as the additional cost to create one more unit of a product or service.

The term comes from the fact that these costs are on the margin, or after direct costs are covered. From the above list, raw materials and the cost of employees are usually included in both marginal and full cost. The other items are generally considered fixed, and are not included in marginal cost. An extra hour of overtime to build one more car adds salary expense, but would not create additional benefits. It rarely requires additional space to make one more pizza in a pizzeria, so rent is usually not figured into marginal cost. The equation for cost is as follows:

Marginal Cost + Overhead Costs = Full or Total Cost. Why Is Marginal Cost Important? Though all companies have to generate enough revenue to cover full costs and a profit margin, once this level is achieved, marginal costing is important to assist in the ability to supply additional profit. A common example is in the airline industry. Once a plane is in the air, the additional cost to fill one more seat is fairly small. It is advantageous to sell any remaining unfilled seats at any price above marginal cost. Hotels rooms and cruises work in a similar fashion.

It is one reason hotels can offer deals to websites like Priceline or Hotwire. Selling rooms at a discount is only viable after overhead costs are covered, and only at rates higher than marginal cost. Knowing how companies work gives the consumer an advantage in negotiating lower prices, whether it is for a berth on a cruise ship or the last seat on an airplane. Q. 6 Discuss the price output determination using profit maximization under perfect competition in the short run. Answer: Perfectly Competitive Markets Perfect Competition

The behavior of firms and the determination of price and output depend on the market structures. We now consider a market structure called perfect competition. A market is in perfect competition if it satisfies the following conditions: (1) Firms in the market all produce the same product. (2) Each market participant is small enough so that the market price will not be affected by his or her actions. (3) Perfect information. (4) Free entry and exit. Although perhaps no market will completely satisfy these conditions, perfect competition serves as a useful benchmark in economic analysis.

Price Determination in the Short-run First, we need to know how an individual firm determines its output. The firm’s profit is ?(x) = TR(X) – TC(X) Since the firm takes market price as given, its marginal revenue is equal to p. The profit-maximizing output is the one at which marginal cost is equal to marginal revenue, which is in turn equal to p. What happens if at the profit-maximizing output, the firm is actually having a loss? Should the firm stop production? The answer is that it depends on whether the price is higher than the average variable cost.

If price is higher than average variable cost, the firm should produce the output at which marginal cost equals price, and if price is lower than the average variable cost, the firm should shut down. Note that the marginal cost curve passes through the minimum point of the average variable cost curve. This allows us to derive the output supplied by a firm in a market with perfect competition as a function of the market price, that is, the short-run supply function (curve) of an individual firm. When price is lower than the average variable cost, the firm produces zero output.

When price is higher than the average variable cost, the firm’s supply curve coincides with its marginal cost curve. Example. If a firm has VC = x2 and MC = 2x, what will be the function of its supply curve? Next, we can derive the short-run supply curve of an industry. It is the horizontal summation of all firms’ supply curves in the industry. Example. If each firm’s supply function is q = p/2, and there are 100 identical firms in the industry, what will the industry supply curve? Finally, we can determine the shore-run equilibrium price and quantity in the market.

This occurs when quantity demanded is equal to the quantity supplied. Example. Suppose market demand is Q = 600 – 10p, and market supply is Q = 50p. What will be equilibrium price and output on the market? If each firm VC = x2, what will be the output of each firm? What will be the profit of each firm if FC = 20? Example. Suppose the government decides to charge or to increase license fees for restaurants (or the local government imposes a property tax on restaurants). A restaurant previously making money may now lose money, but it might continue to operate in the short-run.

Price Determination in the Long-run In the long-run, firms will still produce the output at which long-run marginal cost equates price. However, now if price is higher than average cost, so that an incumbent firm makes positive profit, more firms will enter the industry. As more firms enter, the industry supply curve will shift to the right, which will lower the market price. Therefore, in the long-run, firms in a perfectly competitive market earn zero economic profit. It follows that all firms must produce at the point where average cost is minimized, and price is equal to the average cost.

Example. In a competitive industry, suppose each firm has identical cost functions as follows: LTC(q) = 200 + 10X + 2X2 and MC(q) = 10 + 4X The industry demand is: Q = 800 – 8p Suppose the industry is in long-run competitive equilibrium: (a) Find the level of output produced by each firm. (b) Find the industry price. (c) Find industry output. (d) Determine the number of single-plant firms in the industry. The shape of the long-run industry supply curve depends on how the entry of new firms will affect the cost function of a typical firm in the industry.

If the cost function of a typical firm of the industry will not be affected by the entry of new firms, then the industry is called a constant-cost industry. For a constant-cost industry, its long-run industry supply curve is horizontal. If the cost of a typical firm of the industry increases as more firms enter the industry, as a result of, say, higher input prices as more inp

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