http://faculty.haas.berkeley.edu/berk/papers/disc.pdf

Discrimination in the labor market has always been a hot topic. Characteristics such as race or sex which do not affect the ability of the employee are used in determining whether the applicant gets the job. Statistical discrimination occurs in many ways. In cases where a person applies to a job where they know they are being discriminated against, they apply because they think the profit of getting that job is worth it despite the amount of effort to apply. Being discriminated they have to be over qualified or more qualified than the rest of the applicants to have a chance at being hired. In other cases there is discrimination that favors the worse qualified group. Some of the reasons identified for the discrimination is in the employers ability to access the skill level of the applicant. For example the employer may be more familiar with working with men and is familiar with their abilities at the job so they end up discriminating against women that are applying because they are not familiar with the skill levels of women. This paper focused on two main factors for statistical discrimination in the labor market: (1) differences in the quality of the applicants and (2) differences in the employer’s ability to measure that quality. They found that the second factor is the main reason behind discrimination but favors the applicants where their quality is less known. There are many other interesting findings in this paper along with proofs for those more interested.