ENDOGENOUS INFORMATION QUALITY - A JOB-ASSIGNMENT APPLICATION

This paper investigates the optimal acquisition of information in a mo del of job assignment within a firm. We consider a firm with two types of jobs, skilled and unskilled. The firm draws workers randomly from the general population, and a worker is either talented or untalented. Initially, a worker's productivity in the firm is unknown to the work er and the firm. Workers are equally productive in the unskilled job, but talented workers are more productive in the skilled job than in th e unskilled job, and untalented workers are more productive in the uns killed job than in the skilled job. Before assigning a worker to a job , the firm can test whether the employee is talented, and the firm is able to choose the accuracy of this test. We assume that the cost of a test is increasing and convex in test accuracy. We show that (1) the accuracy of the firm's test increases with the cost of a mismatched wo rker; (2) increased optimism about the worker's ability need not lead to less rigorous testing; (3) the probability that a worker is assigne d to the skilled job need not increase as the gain from assigning a ta lented worker to a skilled job increases, or the loss from assigning a n untalented worker to a skilled job decreases, or the fraction of the population that is skilled increases; and (4) a longer testing period , allowing as many as two tests of workers, leads the firm to use a le ss expensive, and less accurate, test initially than when there is onl y one opportunity to gather information.