Question: E. It often happens that just before putting a job up for auction. DDGT realizes that the project requirements have changed. For example. DDOT may

 E. It often happens that just before putting a job up

E. It often happens that just before putting a job up for auction. DDGT realizes that the project requirements have changed. For example. DDOT may learn that one more pedestrian bridge is needed than originally planned. For a common type of project it is known that an additional bridge does not aect job duration or road length but that it will increase fixed costs {FxCos by 15 percent and overall estimated costs {FairPr} by 5 percent. Your goal is to estimate the percentage increase in the \"inning bid {the Price of the contract] that will ultimately result 'om the change in projected costs in such projects. {a} What regression W'Dllld you use to estimate the increase inPriha? Write down the estimated regression equation and explain how you arrived at that regression. {b} Using this regression. what is your estimate for the percentage increase in the Price of this contract? 9. ODDT realizes that bid rigging is a problem that viill not go away. UDOT has asked you to come up with a model to help determine the likelihood that bid rigging will occur so that it can focus its \"DO NOT mess with ODOT\" message on projects where bid rigging is highly probable. {a} When. besides the observable characteristics of the project. the number of interested bidders is known. how would a Logit specication be written? Which variables are signicant at the 10 percent level? {b} What is the probability that the average project is rigged? {c} What effect does the introduction of an additional bidder to the average project have on likely collusion? (d) All else being equal {and as above}. for what number of bidders would you expect a bidder increase to most decrease the probability of collusion? {e} Suppose that a variable like Biggest {indicating whether an auction was rigged) did not exist and the attorney general asked you to identify projects on which bidders might have colluded so she could focus her inquiiy on these projects. How would you develop a statistical method to detect collusion? Explain your method and compare your results with the variable Riggad

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