We provide a test for statistical discrimination or "rational" stereotyping in environments in which agents learn over time. Our application is to the labor market. If profit maximizing firms have limited information about the general productivity of new workers, they may choose to use easily observable characteristics such as years of education to "statistically discriminate" among workers. As firms acquire more information about a worker, pay will become more dependent on actual productivity and less dependent on easily observable characteristics or credentials that predict productivity.
When you start out on a job, employers have to make do with easily available information about you (years of education, race, etc). As the employer observes individual productivity first-hand, however, this information becomes obsolete. So, if employers are fully rational and internalise the additional information efficiently, education and other easily observable characteristics should become increasingly weaker predictors of wages. The way they test for this is by utilising additional variables for characteristics that are not easily observable but are correlated with productivity:
Consider a wage equation that contains both the interaction between experience and a hard-to-observe variable that is positively related to productivity and the interaction between experience and a variable that firms can easily observe, such as years of education. We show that the wage coefficient on the unobservable productivity variable should rise with time in the labor market and the wage coefficient on education should fall. We investigate this proposition using panel data on education, the AFQT test, father’s education, and wages for young men and their siblings from NLSY. [...] Our results support the hypothesis of statistical discrimination.
So far, so good. But the authors also go on to test for discrimination on the basis or race; econometric specification issues aside, their results are worrying:
We use a similar methodology to investigate whether employers statistically discriminate on the basis of race. If our model is taken literally, the small race differentials for new workers and the spread in the race gap with experience is most consistent with the view that race is negatively correlated with productivity and the productivity gap becomes reflected in wages as fims acquire additional information that can legally be used to differentiate among workers. We wish to stress however, that other factors are probably as or more important in differences between whites and blacks in wage profiles, and race differences in human capital accumulation accounts for at least part of our findings.