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Suppose that there are two types of workers in the world: Charlie Hustles, who are highproductivity workers, and Lazy Susans, who are low-productivity workers. The market would pay $70,000 (this and all numbers in this question are in present value terms) to hire a Charlie Hustle, but only $20,000 to hire a Lazy Susan. The problem, of course, is that a firm cannot tell on sight whether a job applicant is a Charlie or a Susan. One way to attempt to separate the Chucks and the Suzies is to require a college degree. It is easy for a Charlie Hustle to obtain a degree (the degree takes four years to complete and costs $40,000 in total). It is harder for a Lazy Susan to obtain a degree (six years and a cost of $60,000). Assume that a college education adds nothing to either worker's productivity.

a. If the company, operating blindly with no degree requirements, were to pay an average wage of $45,000, what would most of its applicants look like?

b. Suppose that the company announces that it will pay $70,000 to those with college degrees, and $20,000 to those without. What is the net benefit of a college education to a Charlie? To a Susan? Does the degree requirement allow the firm to filter out low-quality applicants?

c. Suppose that a new federal subsidy to assist low-productivity workers reduces the cost of obtaining a degree to $46,000. What is the net benefit of a college education to a Charlie? To a Susan? Does the degree requirement allow the firm to filter out low-quality applicants?

d. In light of your answers to (b) and (c), discuss the following assertion: To be effective, a signal must be costly, but it must be more costly for a low-productivity applicant.

e. Colleges and universities have been accused of practicing grade inflation. In fact, some colleges have actually outlawed awarding a grade of "F." Given your answer to (d), discuss the impact of this practice on the signaling value of a college diploma. Is this practice good for students? Does your answer depend on the quality of the student? Explain.

Econometrics, Economics

  • Category:- Econometrics
  • Reference No.:- M92088995

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