Informed Choices: A Model of Occupational Licensing and Statistical Discrimination

We develop a model of statistical discrimination in occupational licensing. In the model, there is endogenous occupation selection and wage determination that depends on how costly it is to obtain the license and the productivity of the human capital that is bundled with the license. Under these assumptions, we find a unique equilibrium with sharp comparative statics for the licensing premiums. The key theoretical result in this paper is that the licensing premium is higher for workers who are members of demographic groups that face a higher cost of licensing. The intuition for this result is that the higher cost of licensing makes the license a more informative labor market signal. (This is a similar insight to Spence 1973). The predictions of the model can explain, for example, the empirical finding in the literature that occupational licenses that preclude felons close the racial wage gap among men by conferring a higher premium to black men than to white men (Blair and Chung 2018). Moreover, we show that in general the optimal cost of licensing is nonzero: an infinitely costly licenses screens out all workers, while a costless license is no screen at all.