Co-blogger John Lee has written an interesting post on the place premium — the extent to which a person’s current location affects that person’s earnings — and how it compares with various estimates for the “gender premium” — the estimates for how much less females earn than males with the same skills and qualifications. John focused on the gender premium, but pretty much the same observations can be made about the “race premium” — for instance, about the wage differences between whites and blacks in the United States with the same skills and qualifications. I was planning to write this current post before I saw John’s, but since he’s already written his, I’ll stick to a few points that I think are important but that I think were not salient in John’s post.

My main point is this: race and gender are intrinsic to a person’s identity. Sex change operations are rare, though not unheard of. Race change isn’t possible — though a person can change the race he/she self-identified with, the person’s race as perceived by others cannot be changed through an act of fiat. This is important in two ways.

Measurement uncertainty

The ideal way to measure a “premium” (place, race, or gender) is to take a fixed person, start that person in one place (respectively race, gender), then change the person’s place (respectively race, gender) and then measure how much this affected that person’s earnings. Now, in the case of race and gender, this type of ideal “controlled experiment” is almost impossible. In the gender case, it’s impossible unless you can persuade people to undergo sex change operations — but people who undergo sex change operations are likely to not be representative either before or after their operations. In the race case, it’s also impossible or nearly so.

There is considerable debate on the gender premium in the United States, for instance, largely because it’s very difficult to figure out what exactly it means for a female and a male to be identical in all respects other than gender. Are we accounting for various unobserved characteristics? Different choices of how to break the data down (by profession, sub-profession, years of experience) yield different estimates. Which of these choices is justified? The Atlantic interview that John linked to from his blog post highlights some of the points of contention. Bryan Caplan, who is skeptical of the existence of a huge gender premium or race premium in the United States, has lecture notes on the key points of contention. Continue reading Place premium versus race premium →