Cost estimation calls for knowledge of the functional relationship of costs with output rate, technology, and product mix and factor price. In the short run, some costs are fixed. Although these fixed costs should be identified and measured, the usual procedure is to estimate the total or average variable cost functions and then, if necessary, add the fixed cost component to obtain the total or average cost function.
In the long run, all costs are variable. The theory of cost estimation is a fundamental concern of managerial economics. This requires the estimation of both short run and long run cost functions, which are discussed as under:. One of the initial steps in estimating a cost function is to choose the mathematical form of relationship between output and cost. For this, managers use time-series data and relate the total cost of a firm in each time period to its output level in that period.
Regression analysis is often used to estimate this relationship. In estimating the short-run cost function on the basis of time-series data, the following problems arise:. Determination of depreciation of an asset over a period of time on the basis of tax laws rather than economic criteria.
A number of empirical studies have found that a linear function often fits the data for particular firms and plants in the short run. This technique is based on engineering estimates of the costs of production for various levels of output. The physical units of various inputs are computed for a given level of output.
This is done on the basis of the rated capacity of plant and equipment and on the basis of input-output norms, which are derived from the pooled judgements of practical operations.
Multiplying the estimated physical inputs by their respective current or expected prices yields the cost of production in money terms. By dividing this with the level of output, average cost is obtained. Similar calculations are made for different levels of output. The engineers will be doing such exercises. They will be knowing precisely the requirements of different inputs for different levels of output.
This technique for measuring the relative efficiency of difficult sizes of firms was suggested by Prof. Stigler used this method to study the steel and automobiles industry in USA. This technique is based on the fact that if there are advantages in the large scale production in a particular industry and if the industry is fairly competitive, one would expect firms in the lowest size range to increase their share of the market over time.
For the application of this technique, firms in an industry are classified into groups by size in order to estimate an implied shape of the long run cost curve.
The share of the industry output coming from each size group is then calculated over time. An increase in the share over the specified time means it is efficient if not inefficient.
Assuming that market forces work efficiently, firms in the most efficient size category take an increased share of the market and firms in less efficient size category take a small share of the market. The survivor technique fails to adequately estimate the cost curve due to a number of unrealistic assumptions:.
As a result of these conditions which are unlikely to be fulfilled, the survivor technique has not been used in the estimation of cost function.
This technique is also known as econometric approach to measure the economies of scale. Under this approach, the ex-post data on cost and output is used to estimate the cost function for the firm or industry.
In the statistical method of cost estimation, statistical techniques are used. Under this method, the historical data on cost and output are used to estimate the cost-output relationship. The alternative mathematical forms of the function are to be specified first and then fitted to the data using least-squares method. The function which explains the maximum variation of the cost with the level of output will be the best one. It may be linear or nonlinear in shape from which we can derive the conclusions about the economies of scale.
The linear total cost function would give a constant marginal cost and a monotonically falling average cost curve. The quadratic function could yield a U-shaped average cost curve and a rising marginal cost curve. The cubic cost function is consistent both with a U-shaped average cost curve and U-shaped marginal cost curve.
Thus to check the validity of the theoretical cost-output relationship one should hypothesize a cubic cost function. The statistical method is more suitable for estimating this function at the industry or national level, there has been a growing application of the statistical method at the macro level. It has the advantage of isolating fixed cost elements from the total cost.
But, in reality, firms seldom produce identical product. Economists have also used regression analysis based on cross-section data to estimate the long- run cost function. In this way, cross-section data are used to compare cost-output relationships of firms with different sizes at some specific time. As a result, their cost data are not comparable. Despite these problems, many valuable studies of long-run cost functions based on cross-section data have been carried out. In fact, management is interested in estimating the minimum efficient scale MES of plant of the firm.
The management is interested in MES of plants because plants below this size have higher costs and the firm is at a disadvantage in comparison to its rival firms. Cost Control. You must be logged in to post a comment. Leave a Reply Click here to cancel reply. We use cookies We use cookies to personalise content and ads, to provide social media features and to analyse our traffic.
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Note: All the columns on the StockCode sheet with a yellow column heading require user input. The columns with light blue column headings contain formulas that are automatically copied when you add a new stock code in the first empty cell in column A. Error Code - the formulas in this column display an error code if there is a problem with the data that has been entered in any of the user input columns. This column should therefore be blank if all user input has been entered correctly.
If any error codes are reflected in this column, the errors should be investigated and rectified in order to ensure that all template calculations remain accurate. Refer to the Error Codes section of these instructions for guidance on how to correct the appropriate user input errors. Product Type - this column indicates whether the stock code relates to a stock item that is bought-in from a supplier or to a product that is manufactured.
A product costing should be compiled for all manufactured products by linking the manufactured product and its components on the BOM sheet. The formula that has been entered in this column therefore checks whether the stock code is included in column A on the BOM sheet and if so, identifies the product as a manufactured product. Alternatively, the product is deemed to be a bought-in product. Product Cost - this column contains the product cost of each stock code.
If a product is classified as a bought-in stock item, the product cost equals the purchase price that is specified in column D. If the product is classified as a manufactured product, the product cost is calculated based on the components that have been linked to the product on the BOM sheet and the appropriate purchase prices, input quantities and yields of the linked components.
The Product Cost column therefore contains the product costs of all stock items. What-If Cost - this column contains the what-if costs of each stock code. The what-if costs are calculated on the same basis as the product costs, but the what-if costs in column E are used instead of the purchase prices in column D for all stock components.
The input quantities and yields of all the components that have been linked to the manufactured stock items on the BOM sheet are exactly the same. Refer to the What-If Costs section of the instructions for more information on the calculation of what-if costs. Quantity Forecast - the formulas in this column calculate the stock quantities that are required in order to produce the finished goods quantities that are entered on the Forecast sheet. Refer to the Quantity Forecast section of these instructions for guidance on how the forecast quantities are calculated.
Value Forecast - the value forecast is calculated by multiplying the quantity forecast by the stock purchase prices of the appropriate bought-in stock items in column D. What-if Value Forecast - the what-if value forecast is calculated by multiplying the quantity forecast by the what-if stock purchase prices of the appropriate bought-in stock items in column E. Note: Purchase prices in column D and what-if prices in column E should not be entered for manufactured products because the product costings of these stock items are determined based on the purchase prices and what-if prices of the components that have been linked to the manufactured products.
If you enter a purchase price or what-if price for a manufactured stock item, the input will have no effect on the costs that are calculated. Note: We recommend that you review all bought-in stock items on the StockCode sheet in order to ensure that no manufactured products are classified as bought-in stock items. If a manufactured product is incorrectly classified as a bought-in product, it means that no components have been linked to the appropriate product on the BOM sheet.
Once you add the appropriate components to the BOM sheet, the stock code will be automatically be classified as a manufactured product. The purpose of the BOM sheet is to create a link between stock components and manufactured products. This is accomplished by entering the appropriate stock code of the manufactured product in column A and entering the stock code of the appropriate component in column B. Multiple stock components can be added to a single manufactured product in order to create a product costing which consists of multiple stock components.
Note: Columns A and B both contain list boxes that include all the stock codes that have been created on the StockCode sheet. You therefore need to create a stock code for each manufactured or component product before you will be able to select the appropriate stock code from the list boxes in these columns. You can add a new stock component to the sheet by simply selecting the appropriate product code from the list box in the first empty cell in column A - the table will be extended automatically to include the new product code.
All the columns on the BOM sheet with a yellow column heading require user input. The columns with light blue column headings contain formulas that are automatically copied for all new stock components that are added to the Excel table. Product Stock Code - the stock code of the manufactured product to which the stock component should be added needs to be selected from the list box in this column.
The list box includes all the stock codes that have been created on the StockCode sheet. The product stock code should be repeated for all the components that are used in the manufacturing process. For example, if 10 components are required in order to produce a particular manufactured product, you need to add 10 different component stock codes in column B in 10 separate rows and repeat the product stock code in column A in each of these rows.
All 10 component stock codes will then be linked to the same manufactured product and will be included in the same product costing. Note: Components are listed on the product costing in the same order in which they appear on the BOM sheet. This means that even though all components do not need to be grouped together on the BOM sheet by the product stock code , the order in which they are entered or sorted will determine the order in which they appear in the costing.
We therefore recommend that you always sort the data on the BOM sheet by the product code in column A and the component code in column B after making changes to the BOM sheet. By sorting the data, the components will always be listed on the product costings in a consistent order.
Component Stock Code - a component stock code needs to be selected from the list box in column B for each component that is used in manufacturing the product which has been selected in column A. The product costings that are produced by this template accommodate a maximum number of 30 components per manufactured product.
The cost of a manufactured product is calculated based on the costs of all the components that have been linked to the product on the BOM sheet. Note: A very efficient method of adding components to a manufactured product is by copying the components from a similar product, selecting the appropriate new product code from the list box in column A and editing the input quantities and yields of all the components.
This method will however only be efficient if components have previously been added to a similar manufactured product on the BOM sheet. Input Quantity - the input quantity of the stock component that is used in the manufacturing process should be entered in column C. This quantity should be entered in the same unit of measure that is specified for the particular stock code on the StockCode sheet the component UOM is listed in column I.
If the unit of measure of the manufactured product is "Units", the input quantity of the component should be sufficient in order to produce 1 unit of the manufactured product but if the unit of measure of the manufactured product is for example "Dozen", the input quantity that is entered should be sufficient in order to produce 12 units of the manufactured product. Note: The yield basis should also be taken into account when determining the appropriate component input quantity.
If the yield that is entered in column D is based on an Input basis, the component quantity that is added at the beginning of the manufacturing process should be entered in column C.
If however the yield is based on an Output basis, the component quantity that remains at the end of the manufacturing process should be entered in column C. This is because the input quantity is divided by the yield as part of the component cost calculation. Note: You may also want to consider entering a calculation in the input quantity column because this approach may make it easier to determine how the input quantity has been calculated if a calculation has been necessary.
For example: if the component unit of measure is dozen and only one unit is used in the manufactured product, the component quantity is calculated by dividing 1 dozen by twelve. You therefore have the option of entering 0. Yield - the component yield should be entered in column D as a percentage. The input quantity that is entered in column C is divided by the yield in column D in order to determine the component quantity that is required in order to produce the manufactured product.
Yields can be determined on an Input or an Output basis - the difference between the two bases is best explained by a definition and a few examples. Definition: The inherent nature of a manufacturing process may result in the component quantity at the end of the manufacturing process being less than the component quantity that is introduced at the start of the manufacturing process.
The quantity difference can be described as a yield loss. The Input basis refers to the component quantity that is introduced at the start of the manufacturing process, while the Output basis refers to the component quantity which remains after the manufacturing process has been completed.
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