Accounting 3020 Chapter 5 – Cost Behavior: Analysis and Use

Cost Behavior Patterns Variable –Changes in total –Same per unit –Depends on activity base –True variable vs. Step-Variable Costs Relevant Range Fixed –Same in total –Vary per unit (inversely) –Committed fixed costs –Discretionary fixed costs

Cost Behavior Patterns Cost Structure Mixed costs – part variable and part fixed Cost Formula – must break mixed costs into variable per unit and fixed in total Cost Formula (Y = A + Bx) –Y = Total cost –A = Fixed cost –B = Variable cost –x = Activity or cost driver

Methods of Estimating Costs Account Analysis Method Engineering Method Quantitative Analysis Methods –Scattergraph –High-low method –Regression analysis

Scattergraph Method Observe data points in a graph Plot cost formula line to get equation Difficult to accurately draw correct line

High-Low Method 1) Choose highest and lowest activity. 2) Subtract lowest from highest activity and related cost. 3) Difference = variable costs Determine variable cost per unit by dividing cost difference/ activity difference 4) Determine fixed cost by subtracting var. costs from total costs of either highest or lowest points.

High-low Method 5) Determine cost formula. Example - Exercise 5.3 1) High activity 2,406, low 124 2) Electrical Costs Occupancy days $5,148 2,406 $1, Diff.$3,560 2,282

High-low Method 3) Variable cost per guest-day = $3,560/2,282 = $1.56 per occupancy-day 4) Fixed cost = Total cost - var. cost Var. cost (1.56 x 2,406 = $3,753) Total $5,148 – 3,753 = $1,395 fixed 5) Cost formula = $1,395 + $1.56 per occupancy-day

High-Low Method Advantages –Simple –Easy to understand Disadvantages –Only two points used to set formula –What if points were misrepresentative of data?

Regression Analysis All points considered Y = dependent variable X = independent variable Input x and y on a spreadsheet Determine intercept (fixed costs) Determine slope (variable cost per unit) R 2 is a measure of how reliable the independent variable is at describing the variation. –The higher the R 2, the better.

Regression Analysis Advantages –More accurate –Considers all data points Limitations of regression analysis –More difficult to implement –Best to have a lot of data points