Experimental Design Details
We will test our hypotheses using a lab experiment:
- Each session consists of 32 subjects, which are randomly divided into two metagroups of 16 subjects each.
- In each pool, we randomly assign the roles of 4 employers, 2 workers of high ability and yellow type, 3 workers of medium ability and yellow type, 1 worker of low ability and yellow type, 2 workers of high ability and orange type, 2 workers of high ability and orange type, and 2 workers of low ability and orange type.
- There are 60 rounds. In each round, 4 of the 6 workers of each colour are selected and form a pool. For example, in a given round, the pool of the yellow workers might consist of 1 high ability, 2 medium abilities, and 1 low ability, and the pool of the orange workers might consist of 1 high abilities, 1 medium abilities, and 2 low abilities. The pools are formed such that the expected ability of the workers in the yellow pool is higher than the expected ability of the workers in the orange pool.
- Each employer is matched with one yellow and one orange worker. The employer knows the pool composition from which the workers have been drawn, be she does not know their ability. The workers know their own ability, and see the pool from which they have been drawn, but do not know the ability of the other worker.
- Each round consists of two stages. In the first stage, each worker decides whether to pay a cost to pursue education. If the worker pursues education, the probability that he graduates is 0% if he is low ability, 80% if he is medium ability, and 100% if he is high ability. In the second stage, the employer sees whether each worker graduated. She then decides whether to hire one worker or none of them. The payoffs are such that employers are not interested in hiring non-graduated workers. But if they graduated, they prefer that the worker has as high ability as possible.
- The matching is done such that, if both workers graduated, bayesian employers will pick yellow 50% of the times and orange 50% of the times. However, naive employers will only pick yellow.
The main treatment variation takes place in round 31:
- In round 31, the computer counts the number of times that each of the 8 employers chose to hire the yellow worker. Using this as a proxy for naiveté, it re-matches the employers in the two metagroups: it assigns the 4 more naive employers to the first metagroup, and the 4 more bayesian employers to the second metagroup. Hence, on expected terms workers in each metagroup are as likely to face a naive employer during rounds 1-30. However, in rounds 31-60, workers in the first metagroup are more likely to be matched with naive employers, while workers in the second metagroup are more likely to be matched with bayesian employers.