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This is bullshit. You forgot to control for so many factors.

1) These numbers are not for same jobs. Men and women choose to study in different fields, and end up working in different fields.

2) Men work longer hours

3) Men take fewer sick days

4) Men negotiate salaries better

5) Men take on more dangerous jobs

I don't think you made it past the first table of numbers, which the author wasn't satisified with.

Later in the article, Matthew Prestifilippo accounts for the factors you mention (except salary negotiation) and lists various occupations in which women or men have pay advantages in the aggregate.

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from what I know that's what wage gap refers to, not gaps in payment for the same job. From your reasoning it seems like you're part of the problem
I wouldn't go as far as imaginenore, but you do really need to control for "years of experience" or "job title", not simply "occupation". Sadly, job titles vary a lot, but it would help.

_Nevertheless_ the numbers are getting better as you control for things! It suggests that, as you control for more factors, the wage gap will shrink to nothing.

Or: discrimination is baked into the assignment of job titles.
Right. How would we tease that apart? When two people have the same years of experience in the same job title, but then one of them gets a new title and the other one doesn't-- what is that? Just from the data, we won't really know whether it's discrimination or difference in ability.

It'd be cool if we could have objective measurements of productivity. But if we could have objective measures of productivity, I wouldn't be wasting my time with macro data analysis, I would be selling the system to companies and trying to get rid of subjective employee reviews.