Angelo Dalisay Raymond Ye Yang Zheng

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Presentation transcript:

Angelo Dalisay Raymond Ye Yang Zheng Total Cost Analysis Angelo Dalisay Raymond Ye Yang Zheng

Evaluating Pricing Policy Costs % change output change in in output q TC -20 2000 -5250 34750 -10 2250 -2500 37500 2500 40000 10 2750 2450 42450 20 3000 4700 44700 Revenues % change change in in price p sales q -20 16 1500 4000 -10 18 500 3000 20 2500 10 22 -400 2100 24 -800 1700 costs: TC = 9.94q + 15030 demand: p= -.0035q + 29.22 profit=pq-TC profit = (-.0035q^2+29.22q)-9.94q-15030 profit = -.0035q^2 +19.28q -15030 max profit : 0 = -.007q+19.28 q = 2754 Reinserting q= 2754 gives TC = 42404.76 Using demand function, we set p = $19.58

Demand Rises by 10% Should demand rise by 10%: Rewrite demand function costs: TC = 9.94q + 15030 demand: p= -.0035q + 32.14 profit=pq-TC profit = (-.0035q^2+32.14q)-9.94q-15030 profit = -.0035q^2 +22.2q -15030 max profit : 0 = -.007q + 22.2 q = 3171 We revise our profit maximizing production to q = 3171 This changes TC to 46549.74 Using demand function, p = 21.0415

Sensitivity Analysis Assuming actual demand was 10% less than reported: Revised demand function costs: TC = 9.94q + 15030 demand: p= -.0035q + 26.3 profit=pq-TC profit = (-.0035q^2+26.3q)-9.94q-15030 profit = -.0035q^2 +16.3q -15030 max profit : 0 = -.007q+16.3 q = 2337 Comparing to our first case, we see that quantity produced was too high and is now revised down to 2337. Reinserting q = 2337 into the demand function we get p = 18.12. We would have set price too high had we used the optimistic predictions.