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1. Use a computer regression package to estimate the following short-run cubic production function: Q = AL3 + BL2 a. Do the parameter estimates have the appropriate algebraic signs? QUESTION 1 b. Are they statistically significant at the 1 percent level of statistical significance? c. How well did the empirical model do in explaining the variation in the number of carts assembled each day? 2. What are the estimated total, average, and marginal product functions from your regression results in Part 1? QUESTION 2 3. At what level of labor usage does average product reach its maximum value? In a day, how many carts per worker are assembled when average product is maximized? What is average variable cost when average product is maximized? QUESTION 3 4. What is short-run marginal cost when average product is maximized? QUESTION 4 5. Beyond what level of labor employment does the law of diminishing returns set in? Beyond what level of output? QUESTION 5Mercantile Metalworks, Inc. manufactures wire carts for grocery stores. The production manager at Mercantile wishes to estimate an empirical production function for the assembly of carts using the following time-series data for the last 22 days of assembly operations. I. is the daily number of assembly workers employed, and Q is the numb: of carts assembled (completely) for that day. Mercantile pays its assembly workers $160 per day in wages and benets. anbarof anbarof Numborof carts Nunberof carts workers ambled mortars assembled W 1 15 75 12 40 2.185 2 21 897 13 21 1.534 3 24 1,280 14 27 835 4 32 1,251 15 20 906 5 38 1,315 18 15 102 8 38 2,837 17 38 1,424 7 18 590 18 14 111 8 18 129 19 24 888 9 41 1,572 20 25 918 10 38 2,005 21 32 1,341 11 44 1,024 22 21 808 1. Use a computer regression package, such as the Student Edition of Statistix 8, to estimate the following short-run cubic production function: Q=AL3+BL1