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