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Sunday, April 29, 2007

Wage gap as compensating differential?

The recent release that women still earn about 77 cents on the dollar compared to men is an annual source of consternation amongst some navel-gazers. The labor economists have long tried to explain the wage gap by looking at work force participation rates, the time taken off for children, levels of education, years of on-the-job experience, and the riskiness of the jobs taken by men relative to women. My understanding is that the unexplained portion of the wage gap between men and women is about 5 cents on the dollar.

To many, that five cents is five cents too many, and as the father of two girls, I might agree. Suze Orman has an interesting hypothesis that women tend to be weaker negotiators and tend not to demand raises at the same rate and the same vociferousness as men - this alone might explain the majority of the remaining wage gap. An interesting idea, though one that is very difficult to test.

However, the compensating differential for job riskiness is one of the things that interests me the most when it comes to the wage gap. A couple of weeks ago, I pointed to CDC data that men die on the job at considerably higher rates than women. This might mean that women are safer than men, but likely reflects that men work in more dangerous jobs.

Today, the CDC released data concerning on-the-job illness and injury from 2004.



A bit different from the mortality data, men tend to get hurt/ill more than women from 19 to 45 years of age. In the other age groups, especially the older age groups, women tend to get hurt/ill more than men. I wonder what if that reflects survivorship - those men who survive later in life are stronger/healthier and therefore less prone to injury/illness? Perhaps it reflects more women in the workplace among those age groups?

Comments:
I suspect that most workers between ages 15-17 are working in the service industry (wait staff, hosts, ushers, etc), and are financially dependant on family. Also, I suspect that females make up a larger portion of wait staff positions than males and that waiting tables is more dangerous than other service positions. Furthermore, it’s customary for young men to pay for things like dates (although this is gradually changing). So, a large group of young females who work in disproportionately more dangerous jobs and have less to lose by calling in sick may contribute to the gender gap seen in the 15-17 ranges.

This could be tested for by surveying a large group of teens of ages 15-17 and asking A) What is the participant’s job title? B) Does the participant typically pay for dates? C) How many days per month/year does the participant typically miss work due to injury or illness? D) How many hours per week does the participant typically work? and E) What is the participants’ gender? A few other attributes like race may need to be controlled for as well.

In order to avoid bias, it would be preferable to obtain A, C, and D from the participants’ employers. B might be expanded into several more specific questions mixed with placebo questions.

If there were a positive significant relationship between “server” and “days missed” controlling for gender, that would indicate that being a server is associated with missing more days of work. If there were a negative significant relationship between “pays for dates” and “days missed” controlling for gender, that would indicate that workers who pay for dates miss fewer work days because missing work could potentially weaken their value in the dating game.
 
The explained wage gap could be the education, but what part of the gap could be due to discrimination? This is a hot topic in economics right now as our society looks to continuously reduce the wage gap across the board.
 
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