In: Accounting
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Caiman Distribution Partners is the Brazilian distribution company of a U.S. consumer products firm. Inflation in Brazil has made bidding and budgeting difficult for marketing managers trying to penetrate some of the country's rural regions. The company expects to distribute 450,000 cases of products in Brazil next month. The controller has classified operating costs (excluding costs of the distributed product) as follows:
Account | Operating Cost | Behavior | ||||
Supplies | $ | 1,231,000 | All variable | |||
Supervision | 203,000 | $ | 141,000 | Fixed | ||
Truck expense | 1,270,000 | $ | 178,000 | Fixed | ||
Building leases | 865,000 | $ | 548,000 | Fixed | ||
Utilities | 200,000 | $ | 115,000 | Fixed | ||
Warehouse labor | 845,000 | $ | 139,000 | Fixed | ||
Equipment leases | 777,000 | $ | 582,000 | Fixed | ||
Data processing equipment | 955,000 | All fixed | ||||
Other | 838,000 | $ | 386,000 | Fixed | ||
Total | $ | 7,184,000 | ||||
Although overhead costs were related to revenues throughout the company, the experience in Brazil suggested to the managers that they should incorporate information from a published index of Brazilian prices in the distribution sector to forecast overhead in a manner more likely to capture the economics of the business.
Following instructions from the corporate offices, the controller's office in Brazil collected the following information for monthly operations from last year:
Month | Cases | Price Index | Operating Costs | |
1 | 229,000 | 115 | $5,699,161 | |
2 | 324,000 | 123 | 5,806,660 | |
3 | 230,000 | 121 | 5,849,927 | |
4 | 384,000 | 132 | 5,927,639 | |
5 | 308,000 | 112 | 5,939,157 | |
6 | 361,000 | 132 | 6,043,386 | |
7 | 361,000 | 123 | 5,918,517 | |
8 | 455,000 | 127 | 6,133,890 | |
9 | 359,000 | 131 | 6,126,152 | |
10 | 432,000 | 132 | 6,186,647 | |
11 | 376,000 | 136 | 6,208,821 | |
12 | 456,000 | 140 | 6,362,277 | |
These data are considered representative for both past and future operations in Brazil.
Determine the variable cost per case assuming that 450,000 cases will be shipped next month based on the controller's analysis of accounts. (round your answer to 2 decimal places).
VARIABLE COST PER CASE _______?_____
Prepare an estimate of operating costs
ESTIMATE OF OPERATING COST _________?_________
Use the high-low
method to compute an estimate of operating costs assuming
that,450,000 cases will be shipped next month. (Round variable cost
to 5 decimal places. Round
intermediate calculations and final answer to the nearest whole
dollar amount).
ESTIMATE OF OPERATING COST _____?__________
Enter the regression coefficients. (Round "Cases" to 5 decimal places.)
INTERCEPT
_____?______
CASES ____?_______
Compute the estimation
of operating costs assuming that 450,000 cases will be shipped next
month by using the results of a simple regression
of operating costs on cases shipped. (Round variable costs per unit
to 5 decimal places. Round the intercept and final answer to the
nearest
whole dollar amount)
ESTIMATE OF OPERATING COST _____?___________
Enter the regression coefficients. (Round "Cases" to 5 decimal places and "Price Index" to 5 decimal places.)
INTERCEPT
_______?__________
CASES _______?__________
PRICE INDEX _________?________
Compute the estimation
of operating costs assuming that 450,000 cases will be shipped next
month by using the results of a multiple regression
of operating costs on cases shipped and the price level. Assume a
price level of 146 for next month. (Round "Cases" and "Price Index"
to 5 decimals
places. Round the final answer to the nearest whole dollar
amount.
ESTIMATE OF OPERATING COST ________?______________
1) | |||
Operating Cost | Fixed | Variable | |
Supplies | $ 12,31,000.00 | $ - | $ 12,31,000.00 |
Supervision | $ 2,03,000.00 | $ 1,41,000.00 | $ 62,000.00 |
Truck expense | $ 12,70,000.00 | $ 1,78,000.00 | $ 10,92,000.00 |
Building leases | $ 8,65,000.00 | $ 5,48,000.00 | $ 3,17,000.00 |
Utilities | $ 2,00,000.00 | $ 1,15,000.00 | $ 85,000.00 |
Warehouse labor | $ 8,45,000.00 | $ 1,39,000.00 | $ 7,06,000.00 |
Equipment leases | $ 7,77,000.00 | $ 5,82,000.00 | $ 1,95,000.00 |
Data processing equipment | $ 9,55,000.00 | $ 9,55,000.00 | $ - |
Other | $ 8,38,000.00 | $ 3,86,000.00 | $ 4,52,000.00 |
Total | $ 71,84,000.00 | $ 30,44,000.00 | $ 41,40,000.00 |
a) VARIABLE COST PER CASE = Total variable cost/ TotalCases Produced = $4140000/ 450,000 | $ 9.20 | ||
b) ESTIMATE OF OPERATING COST = Total Fixed Cost + Variable cost per case x Number of cases produced | |||
ESTIMATE OF OPERATING COST = 3044000 + $9.20 x 450,000 | $ 71,84,000.00 | ||
2) | |||
High-low method | |||
Step 1 | Number of Cases | Total cost | |
High Month | Month 12 | 4,56,000 | $ 63,62,277.00 |
Low Month | Month 1 | 2,29,000 | $ 56,99,161.00 |
Difference | 2,27,000 | $ 6,63,116.00 | |
Step - 2 Variable cost per cases = $663116/227000 | $ 2.92122 | ||
Step-3 | |||
Fixed Cost = Total cost + Variable cost per case x no. of cases | |||
Fixed Cost = 6362277 + $2.92 x 456000 | $ 50,30,202.57 | ||
Cost Equation is | |||
Overhead cost = $5030202.57 + $2.92 x No. of cases | |||
For 450,000 cases | |||
ESTIMATE OF OPERATING COST = $5030202.57 + $2.92 x 450,000 | $ 63,44,749.70 | ||
3) | |||
Enter the regression coefficients. (Round "Cases" to 5 decimal places.) | |||
Simple regression based on Cases | |||
Cases = x | Operating Costs = y | ||
2,29,000 | 56,99,161 | ||
3,24,000 | 58,06,660 | ||
2,30,000 | 58,49,927 | ||
3,84,000 | 59,27,639 | ||
3,08,000 | 59,39,157 | ||
3,61,000 | 60,43,386 | ||
3,61,000 | 59,18,517 | ||
4,55,000 | 61,33,890 | ||
3,59,000 | 61,26,152 | ||
4,32,000 | 61,86,647 | ||
3,76,000 | 62,08,821 | ||
4,56,000 | 63,62,277 | ||
SUMMARY OUTPUT | |||
Regression Statistics | |||
Multiple R | 0.830061651 | ||
R Square | 0.689002345 | ||
Adjusted R Square | 0.657902579 | ||
Standard Error | 112642.3207 | ||
Observations | 12 | ||
ANOVA | |||
df | SS | MS | |
Regression | 1 | 2.81104E+11 | 2.81104E+11 |
Residual | 10 | 1.26883E+11 | 12688292402 |
Total | 11 | 4.07987E+11 | |
Coefficients | Standard Error | t Stat | |
Intercept | 5259218.186 | 164215.3493 | 32.0263496 |
X Variable 1 = Cases | 2.126693748 | 0.451828022 | 4.706865548 |
ESTIMATE OF OPERATING COST = $5259218.186 + $2.12669 x 450,000 | $ 62,16,230.37 | ||
4) Multiple Regresion based on cases and price level | |||
Cases (x) | Price Index (x) | Operating Costs (y) | |
2,29,000 | 115 | 56,99,161 | |
3,24,000 | 123 | 58,06,660 | |
2,30,000 | 121 | 58,49,927 | |
3,84,000 | 132 | 59,27,639 | |
3,08,000 | 112 | 59,39,157 | |
3,61,000 | 132 | 60,43,386 | |
3,61,000 | 123 | 59,18,517 | |
4,55,000 | 127 | 61,33,890 | |
3,59,000 | 131 | 61,26,152 | |
4,32,000 | 132 | 61,86,647 | |
3,76,000 | 136 | 62,08,821 | |
4,56,000 | 140 | 63,62,277 | |
SUMMARY OUTPUT | |||
Regression Statistics | |||
Multiple R | 0.878899697 | ||
R Square | 0.772464678 | ||
Adjusted R Square | 0.721901273 | ||
Standard Error | 101560.8179 | ||
Observations | 12 | ||
ANOVA | |||
df | SS | MS | |
Regression | 2 | 3.15155E+11 | 1.57578E+11 |
Residual | 9 | 92831397663 | 10314599740 |
Total | 11 | 4.07987E+11 | |
Coefficients | Standard Error | t Stat | |
Intercept | 4300291.035 | 548143.663 | 7.845189729 |
X Variable 1 = Cases | 1.3126128 | 0.605561611 | 2.167595791 |
Price Level | 9834.200698 | 5412.488232 | 1.816946343 |
Equation = 4300291.035 + 1.3126 x Cases +$9834.200 x Price level | |||
ESTIMATE OF OPERATING COST = 4300291.035 + 1.3126 x 450,000 + 9834.200 x 146 | $ 63,26,760.10 | ||