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August 13, 2008
Interesting words of the day
Bryan Caplan offers a motivation for discrimination on the basis of statistical features of the group being discriminated against.
A key building block of statistical discrimination is the assumption of stereotype accuracy. For statistical discrimination to be stable, the stereotypes that market participants rely upon must be accurate statistical generalizations. ... The upshot is that stereotypes may actually be self-reversing rather than self-fulfilling. The marginal payoff of distinguishing yourself from the pack is high if people think poorly of the typical member of the pack. ...Some young women are 100% focused on their careers, and don't want kids. Most young women, however, do want kids, and intend to strike a balance between work and family. That balance often involves receiving expensive job training from a firm, then quiting before the firm can recoup its expenses.
Under current law, an employer isn't even allowed to ask about a female applicant's child-bearing plans. If you wanted to blow up the glass ceiling, though, you should not only allow employers to ask; you should allow them to offer deals like "We'll hire you, but your health insurance doesn't cover pregnancy." The career woman would be happy to sign, reassuring the employer.
How will that help women? It won't! On average, it's a wash: It will help career-minded women, and hurt the rest. And if you want to judge female workers on the basis of individual productivity, that is exactly what should happen.
The Truth Hurts: What Harford Didn't Say About Statistical Discrimination
Posted by OneEyedMan at August 13, 2008 8:24 AM
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