Caiman Distribution Partners is the Brazilian distribution company of a U.S. con
ID: 2427078 • Letter: C
Question
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 $360,000 All variable
Supervision $220,000 $160,000 Fixed
Truck Expense $1,185,000 $180,000 Fixed
Building Leases $840,000 $540,000 Fixed
Utilities $210,000 $115,000 Fixed
Warehouse Labor $870,000 $145,000 Fixed
Equipment Leases $755,000 $600,000 Fixed
Data Processing Equipment $980,000 All Fixed
Other $850,000 $400,000 Fixed
Total $6,270,000
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
1 350,000 117 $5,739,139
2 367,000 119 $5,846,638
3 363,000 120 $5,889,905
4 385,000 124 $5,967,617
5 379,000 126 $5,979,135
6 400,000 127 $6,083,364
7 372,000 130 $5,958,495
8 417,000 135 $6,173,868
9 403,000 135 $6,166,130
10 426,000 134 $6,226,625
11 422,000 138 $6,248,799
12 437,000 141 $6,402,255
Compute an estimate 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 to five decimal places. Round your other intermediate calculations and final answer to nearest whole dollar value.)
Compute an estimate 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 141 for next month. (Round variable costs to five decimal places. Round your other intermediate calculations and final answer to nearest whole dollar value.)
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
1 350,000 117 $5,739,139
2 367,000 119 $5,846,638
3 363,000 120 $5,889,905
4 385,000 124 $5,967,617
5 379,000 126 $5,979,135
6 400,000 127 $6,083,364
7 372,000 130 $5,958,495
8 417,000 135 $6,173,868
9 403,000 135 $6,166,130
10 426,000 134 $6,226,625
11 422,000 138 $6,248,799
12 437,000 141 $6,402,255
Compute an estimate 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 to five decimal places. Round your other intermediate calculations and final answer to nearest whole dollar value.)
Compute an estimate 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 141 for next month. (Round variable costs to five decimal places. Round your other intermediate calculations and final answer to nearest whole dollar value.)
Explanation / Answer
Answer:
a. Estimating equation based on account analysis:
Cost Item Operating Cost Fixed Cost Variable
Supples $ 360,000 $ 0 $ 360,000
Supervision $ 220,000 $ 160,000 $ 60,000
Truck Expenses $ 1,185,000 $ 180,000 $ 1,005,000
Building Leases $ 840,000 $ 540,000 $ 300,000
Utilities $ 210,000 $ 115,000 $ 95,000
Warehouse Labour $ 870,000 $ 145,000 $ 725,000
Equipment Lease $ 755,000 $ 600,000 $155,000
Data Processing equipment $ 980,000 $ 980,000 $ 0
Other $ 850,000 $ 400,000 $ 450,000
Total $ 6,270,000 $ 3,120,000 $ 3,150,000
Variable cost per case = Total Variable cost / Cases produced
= $ 3,150,000 / 450,000 = 7 Per cases
Estimated overhead = Fixed Overhead + Variable overhead per cases * Number of cases
= 3,120,000 + $ 7 * 450,000
= $ 6,270,000
Simple regression based on cases:
Multiple R 0.98034501
R Square 0.96107634
Standard Error 39850.1391
Observations 12
Coefficients
Intercept $ 3,411,468
Cases $ 6.70765
Operating Costs = $ 3,411,468 + $ 6.70765 * Cases
= $ 3,411,468 + $ 6.70765 * 450,000
= $ 6,429,911
Multiple Regression based on cases and price level:
Multiple R 0.9905
R Square 0.9810
Adjusted R Square 0.9768
Standard Error 29315.827
Observation 12
Coefficient
intercept $ 3,176,995
Cases $ 4.41892
Price Index $ 8,857.73
Operating Costs = $ 3,176,995 + $ 4.41892 * Cases + $ 8,857.73 * Price Level
= $ 3,176,995 + $ 4.41892 * 450,000 + $ 8,857.73 * 141
= $ 3,176,995 + $ 1,988,514 + $ 1,248,939.93
= $ 6,414,449
The multiple regression appears to improve the fit but the rationale for the inclusion of the price level as a cost driver is unclear.