Caiman Distribution Partners is the Brazilian distribution company of a U.S. consumer products firm. Inflation...
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Accounting
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 | $ | 1,596,000 | All variable | |||
Supervision | 235,000 | $ | 145,000 | Fixed | ||
Truck expense | 1,310,000 | $ | 172,000 | Fixed | ||
Building leases | 866,000 | $ | 552,000 | Fixed | ||
Utilities | 234,000 | $ | 112,000 | Fixed | ||
Warehouse labor | 855,000 | $ | 121,000 | Fixed | ||
Equipment leases | 770,000 | $ | 589,000 | Fixed | ||
Data processing equipment | 956,000 | All fixed | ||||
Other | 861,000 | $ | 356,000 | Fixed | ||
Total | $ | 7,683,000 | ||||
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 | 255,000 | 116 | $5,699,173 | |
2 | 339,000 | 112 | 5,806,672 | |
3 | 256,000 | 109 | 5,849,939 | |
4 | 435,000 | 129 | 5,927,651 | |
5 | 343,000 | 113 | 5,939,169 | |
6 | 380,000 | 124 | 6,043,398 | |
7 | 460,000 | 124 | 5,918,529 | |
8 | 483,000 | 123 | 6,133,902 | |
9 | 341,000 | 143 | 6,126,164 | |
10 | 418,000 | 134 | 6,186,659 | |
11 | 408,000 | 133 | 6,208,833 | |
12 | 484,000 | 143 | 6,362,289 | |
These data are considered representative for both past and future operations in Brazil.
rev: 11_25_2017_QC_CS-108812
References
Section BreakProblem 5-61 Methods of Cost Analysis: Account Analysis, Simple and Multiple Regression Using a Spreadsheet (Appendix A) (LO 5-3, 4, 5, 7, 8)
5.
value: 0.25 points
Required information
Problem 5-61 Part a
Required:
a-1. 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.)
a-2. Prepare an estimate of operating costs.
References
eBook & Resources
WorksheetProblem 5-61 Part a
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6.
value: 0.25 points
Required information
Problem 5-61 Part b
b. 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 nearest whole dollar amount.)
References
eBook & Resources
WorksheetProblem 5-61 Part b
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7.
value: 0.25 points
Required information
Problem 5-61 Part c
c-1. Enter the regression coefficients. (Round "Cases" to 5 decimal places.)
c-2. 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.)
rev: 10_06_2016_QC_CS-64489
References
eBook & Resources
WorksheetProblem 5-61 Part c
Check my work
8.
value: 0.25 points
Required information
Problem 5-61 Part d
d-1. Enter the regression coefficients. (Round "Cases" to 5 decimal places and "Price Index" to 5 decimal places.)
d-2. 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 149 for next month. (Round "Cases" and "Price Index" to 5 decimal places. Round the final answer to the nearest whole dollar amount.)
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