Golodfish discrimination
However, there are extensions of statistical discrimination models that generate group discrimination. For example, Aigner and Cain (1977) show that if a minority group has a less reliable signal, and employers are risk averse, then the minority group will earn a lower average wage despite identical average productivity. Rothschild and Stiglitz (1982) obtain a similar result by positing a production function in which productivity depends on the quality of the match of the worker to the job. Another line of research considers ’’self-fulfilling prophecies” in statistical discrimination models, in which initially incorrect prior beliefs of lower productivity for a group results in lower human capital investment among that group, hence rationalizing and perpetuating the prior beliefs (Farmer and Terrell, 1996). internet payday loans

Whether or not some form of statistical discrimination leads to group discrimination, in all of these models imperfect information implies that the most productive members of a group with lower actual or assumed average productivity (e.g., a minority group) will be paid less than equally-able members of the non-minority group. Even though the minority group as a whole may not be treated unfairly, there is an obvious sense in which this highly-productive individual suffers from discrimination—in that he or she is paid less by virtue of identification with that group—although the least-able members of this group (and any group) likely benefits from statistical discrimination. Of course, if there is group discrimination then the implications are even more apparent.