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Determining How Costs Behave
Chapter 10
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Explain the two assumptions cost-behavior estimation.
Learning Objective 1 Explain the two assumptions frequently used in cost-behavior estimation.
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Assumptions in Cost-Behavior Estimation
Changes in total costs can be explained by changes in the level of a single activity. Cost behavior can adequately be approximated by a linear function of the activity level within the relevant range.
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Describe linear cost functions and three common ways in
Learning Objective 2 Describe linear cost functions and three common ways in which they behave.
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Cost Function What is a cost function? It is a mathematical expression
describing how costs change with changes in the level of an activity.
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Cost Function La Playa Hotel offers an airline
three alternative cost structures to accommodate its crew overnight: 1. $60 per night per room usage y = $60x The slope of the cost function is $60.
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Cost Function
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Cost Function 2. $8,000 per month y = $8,000
$8,000 is called a constant or intercept. The slope of the cost function is zero.
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Cost Function
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Cost Function 3. $3,000 per month plus $24 per room
This is an example of a mixed cost. y = $3,000 + $24x y = a + bx
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Cost Function
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Cost Classification and Estimation Function
Choice of cost object Time span Relevant range
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Choice of Cost Object Example
If the number of taxis owned by a taxi company is the cost object, annual taxi registration and license fees would be variable costs. If miles driven during a year on a particular taxi is the cost object, registration and license fees for that taxi are fixed costs.
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Time Span Whether a cost is variable or fixed with respect
to a particular activity depends on the time span. More costs are variable with longer time spans.
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Relevant Range Variable and fixed cost behavior patterns are
valid for linear cost functions only within the given relevant range. Costs may behave nonlinear outside the range.
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Cost Estimation What is cost estimation?
It is the attempt to measure a past cost relationship between costs and the level of an activity. Past cost-behavior functions can help managers make more accurate cost predictions.
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The Cause-and-Effect Criterion In Choosing Cost Drivers
Physical relationship Contractual agreements Implicitly established by logic
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Understand various approaches
Learning Objective 3 Understand various approaches to cost estimation.
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Cost Estimation Approaches
Industrial engineering method Conference method Account analysis method Quantitative analysis methods
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Account Analysis Example
The cost analyst uses experience and judgment to separate total costs into fixed and variable. Avisha & Co. sells software programs. Total sales = $390,000 The company sold 1,000 programs.
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Account Analysis Example
Cost of goods sold = $130,000 Manager’s salary = $60,000 Secretary’s salary = $29,000 Commissions = 12% of sales What is the total fixed cost? $60,000 + $29,000 = $89,000 What is the fixed cost per unit sold?
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Account Analysis Example
$89,000 ÷ 1,000 = $89.00 What is the variable cost per unit sold? Cost of goods sold: $130,000 Commissions: $390,000 × .12 = $46,800 ($130,000 + $46,800) ÷ 1,000 = $176.80
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Outline six steps in estimating a cost function on the basis
Learning Objective 4 Outline six steps in estimating a cost function on the basis of past cost relationships.
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Steps In Estimating A Cost Function
Choose the dependent variable. Step 2: Identify the independent variable cost driver(s). Step 3: Collect data on the dependent variable and the cost driver(s).
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Steps In Estimating A Cost Function
Plot the data. Step 5: Estimate the cost function. Step 6: Evaluate the estimated cost function.
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High-Low Method Example
High capacity December: 55,000 machine-hours Cost of electricity: $80,450 Low capacity September: 30,000 machine-hours Cost of electricity: $64,200 What is the variable rate?
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High-Low Method Example
($80,450 – $64,200) ÷ (55,000 – 30,000) $16,250 ÷ 25,000 = $0.65 What is the fixed cost?
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High-Low Method Example
$80,450 = Fixed cost + (55,000 × $0.65) Fixed cost = $80,450 – $35,750 = $44,700 $64,200 = Fixed cost + (30,000 × $0.65) Fixed cost = $64,200 – $19,500 = $44,700 y = a + bx y = $44,700 + ($0.65 × Machine-hours)
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Regression Analysis It is used to measure the average amount of
change in a dependent variable, such as electricity, that is associated with unit increases in the amounts of one or more independent variables, such as machine-hours. Regression analysis uses all available data to estimate the cost function.
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Regression Analysis Simple regression analysis estimates the
relationship between the dependent variable and one independent variable. Multiple regression analysis estimates the relationship between the dependent variable and multiple independent variables.
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Regression Analysis The regression equation and regression line
are derived using the least-squares technique. The objective of least-squares is to develop estimates of the parameters a and b.
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Regression Analysis The vertical difference (residual term) measures
the distance between the actual cost and the estimated cost for each observation. The regression method is more accurate than the high-low method.
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Describe three criteria used to evaluate and choose cost drivers.
Learning Objective 5 Describe three criteria used to evaluate and choose cost drivers.
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Criteria to Evaluate and Choose Cost Drivers
Economic plausibility Goodness of fit Slope of the regression line
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Goodness of Fit The coefficient of determination (r2)
expresses the extent to which the changes in (x) explain the variation in (y). An (r2) of 0.80 indicates that more than 80% of the change in the dependent variable can be explained by the change in the independent variable.
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Slope of Regression Line
A relatively steep slope indicates a strong relationship between the cost driver and costs. A relatively flat regression line indicates a weak relationship between the cost driver and costs.
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Slope of Regression Line
The closer the value of the correlation coefficient (r) to ±1, the stronger the statistical relation between the variables. As (r) approaches +1, a positive relationship is implied, meaning the dependent variable (y) increases as the independent variable (x) increases.
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Slope of Regression Line
As (r) approaches –1, a negative, or inverse, relationship is implied, meaning the dependent variable (y) decreases as the independent variable (x) increases.
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Explain and give examples of nonlinear cost functions.
Learning Objective 6 Explain and give examples of nonlinear cost functions.
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Nonlinearity and Cost Functions
A nonlinear cost function is a cost function in which the graph of total costs versus the level of a single activity is not a straight line within the relevant range. Economies of scale Quantity discounts Step cost functions
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Nonlinearity and Cost Functions
Economies of scale in advertising may enable an advertising agency to double the number of advertisements for less than double the cost. Quantity discounts on direct materials purchases produce a lower cost per unit purchased with larger orders.
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Nonlinearity and Cost Functions
A step function is a cost function in which the cost is constant over various ranges of the level of activity, but the cost increases by discrete amounts as the level of activity changes from one range to the next.
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Distinguish the cumulative average-time learning model
Learning Objective 7 Distinguish the cumulative average-time learning model from the incremental unit-time learning model.
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Learning Curves A learning curve is a function that shows
how labor-hours per unit decline as units of output increase.
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Experience Curve This is a function that shows how the costs
per unit in various value chain areas decline as units produced and sold increase.
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Cumulative Average-Time Learning Model
Cumulative average time per unit is reduced by a constant percentage each time the cumulative quantity of units produced is doubled.
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Incremental Unit-Time Learning Model
The time needed to produce the last unit is reduced by a constant percentage each time the cumulative quantity of units produced is doubled.
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Be aware of data problems encountered in estimating
Learning Objective 8 Be aware of data problems encountered in estimating cost functions.
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Data Collection and Adjustment Issues
The ideal database for cost estimation has two characteristics: 1. It contains numerous reliably measured observations of the cost driver(s) and the cost that is the dependent variable. 2. It considers many values for the cost driver that span a wide range.
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Data Collection and Adjustment Issues
Time periods do not match. Fixed costs are allocated as if they were variable. Data are either not available or not reliable. Inflation may play a role.
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Data Collection and Adjustment Issues
Extreme values of observations occur from errors in recording costs. Analysts should adjust or eliminate unusual observations before estimating a cost relationship. There is no homogeneous relationship. The relationship between the cost driver and the cost is not stationary.
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Data Collection and Adjustment Issues
The most difficult task in cost estimation is collecting high-quality, reliably measured data on the dependent variable and the cost driver(s).
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End of Chapter 10
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