Discrimination and Market Fragmentations

1. Discrimination and Market Fragmentations Theory and Evidence based on Darity and Mason (1998)

2. Background • Discrimination was pretty much persistent up until the Civil Rights movement • Observed in wages and prices • Directly observed in newspaper adds • Disparities seemed to close until the mid 70’s or early 80’s at best but then there has been a halt. • Wage gaps are the same today as they were in 1979, as are our explanations for these gaps • (we may be able to get evidence of this ourselves in class)

3. Theory • Standard neoclassical competitive models are forced by their own assumptions to the conclusion that discrimination only can be temporary • Taste based discrimination may or may not cause wage differences. Think of a model of white and black business owners that are able to sell their goods in a common market. • With competitive enough markets there may be segregation of labor but not wage differentials. • The result is similar to Factor Price Equalization in models with free trade • Consumer discrimination theory (the consumer being discriminatory makes it profitable for the business to discriminate) • Cannot sustain long term differences if there is an “anonymous” sector with no client contact

4. Statistical Discrimination • A story of imperfect information • Unobserved, perceived group differences can lead to discrimination • Have to be Unobserved and don’t have to be “average” differences. • Wider variance and non-risk neutral agents will work too • Still there is the question of why don’t employers learn? • “…It seems implausible that with all the resources that corporations put into hiring decisions, the remaining differentials are due to an inability to come up with a suitable set of questions or qualifications for potential employees.”

5. Is there empirical evidence of Discrimination? • Labor markets, housing, credit, durables and services • Legal cases, audit studies, statistical analyses • Statistical • Census data find a wage gap • NLSY data close 2/3 of the gap for men and all for women by adding AFQT. • Only 40%-50% of the gap is closed if AFQT is adjusted for education and age • Sometimes it is difficult to adjust for both • Have to wonder why men but not women • Unlikely to be related to schooling quality

6. More evidence • Skin shade research finds significant skin shade effects • black racial identity and a dark skin tone reduces an individual's odds of working by 52 percent, after controlling for education, age, and criminal record • Audits find evidence of large gaps in interviewing and hiring • White testers were close to 10 percent more likely to receive interviews than blacks. • Among those interviewed, half of the white testers received job offers versus a mere 11 percent of the black testers. • When both testers received the same job offers, white testers were offered 15 cents per hour more than black testers. • Black testers also were disproportionately "steered" toward lower level positions after the job offer was made, and white testers were disproportionately considered for un-advertised positions at higher levels than the originally advertised job. • Critique by Heckman is that one can’t really create identical candidates (mannerisms, first impressions, etc.) • To avoid this they do in-personal tests and same pair many businesses test (mostly worked for gender)

7. Alternative Theories • Self Fulfilling Prophecy: A mistaken prior introduces a labor market disruption that creates an actual disadvantage for the discriminated group • Problem: Why not “Blondes”? • “Group Monopoly” theory. Group A finds itself to gain from discrimination and achieves enough group cohesion to keep this going • Educated blacks were punished at some point • No evidence of discrimination in the part of brazil where blacks were uneducated but there was discrimination in parts where Blacks were educated • This suffers from the same critique; why don’t some make a profit out of hiring the discriminated individuals?

8. What do you think? • Orchestras and women • One male-female pair in many restaurants • Income in businesses and discrimination (Taste) • Employer learning doesn't seem to reduce racial gap (consider turnover as well) • Evidence based on names • Evidence based on language • Evidence based on game shows