The basic role of the United States government is to: A- maintain control of prices.
B- increase production
C- protect U. S. citizens.
D- limit business startups.

Amachine purchased three years ago for $720,000 has a current book value using straight-line depreciation of $400,000: its operating expenses are $60,000 per year. a replacement machine would cost $480,000, have a useful life of nine years, and would require $26,000 per year in operating expenses. it has an expected salvage value of $130,000 after nine years. the current disposal value of the old machine is $170,000: if it is kept 9 more years, its residual value would be $20,000. calculate the total costs in keeping the old machine and purchase a new machine. should the old machine be replaced?

Walsh company manufactures and sells one product. the following information pertains to each of the company’s first two years of operations: variable costs per unit: manufacturing: direct materials $ 25 direct labor $ 12 variable manufacturing overhead $ 5 variable selling and administrative $ 4 fixed costs per year: fixed manufacturing overhead $ 400,000 fixed selling and administrative expenses $ 60,000 during its first year of operations, walsh produced 50,000 units and sold 40,000 units. during its second year of operations, it produced 40,000 units and sold 50,000 units. the selling price of the company’s product is $83 per unit. required: 1. assume the company uses variable costing: a. compute the unit product cost for year 1 and year 2. b. prepare an income statement for year 1 and year 2. 2. assume the company uses absorption costing: a. compute the unit product cost for year 1 and year 2. b. prepare an income statement for year 1 and year 2. 3. reconcile the difference between variable costing and absorption costing net operating income in year 1.

Using a cps-sample of 7,440 individuals, you estimate the following regression: = 20.91 - 2.61 x female where female is a binary variable that takes on the value of 1 for females and is 0 otherwise. the standard error on the coefficient on female is 0.25. the 95% confidence interval for the gender wage gap, or the amount that females earn less, is: a) [-3.10, -2.12] b) [18.30, 23.52] c) [-3.02, -2.20] d) [-1.96, -1.64]