Gender pay gap is the ratio of women's median earnings to men's median earnings for all full-time, year-round workers. If the ratio is below 1.0, women in that county, on the whole, earn less than men. Ratios greater than 1.0 mean the opposite. That data is compiled by the University of Wisconsin Population Health Institute.

The degree to which a county can be judged increasingly conservative or liberal is derived from the degree of a Trump vs. Harris victory in the 2024 election (available here). Subtracting the percent of Harris' vote from Trump's yields a negative or positive number between 0 and +/-100. The larger the absolute value indicates a larger margin of victory and, I claim, greater political homogeneity, which I use as an indicator of how extreme a community is in its conservativeness or liberalness.

Given large population centers tend to be home to more liberal communities and also offer more employment options, I have also compared the gender pay gap to urban versus rural counties. The US Census defines rural as any area that is not designated as urban, and this metric represents the percent of a county's residents not living in an urban area.

I find that as counties become more conservative, gender pay gap increases (women earn less than men), and as counties become more liberal, women's earnings approach — though do not reach — parity with men. Meanwhile, the gender pay gap is essentially unaffected by the degree to which a county is urban or rural.

This work was done in Excel (but on a Mac so give me a break).

Posted by JaraSangHisSong

11 comments

  1. So does this data take into account differences in employment? If a county has a bunch of women teachers and men lawyers, the data will naturally be skewed because of the profession and not necessarily a wage gap.

  2. Is there a way to break apart primarily white rural counties and primarily black rural counties? Or primarily white urban/suburban countries from primarily black? Or just control for race some other way?

  3. Whats happening in counties where women make more? Women are stay at home mothers than men, so women who are working have to be making a ton more than men for that to even out not to talk of being higher than? No?

  4. Could you make those charts a little smaller and harder to read? I can still see some of the data.

  5. Personally I think putting “decreasing gender pay gap” in the positive y axis increasing direction made this quite confusing. It’s also a bit of an overstatement to paint everything red or blue and not have some sort of color gradient to show the spectrum or distribution a bit more

  6. Change the title to: “Ratio of female earnings to male earnings for the same job.” Then show it in percent. Get rid of the the “vs county political …” it is too confusing. Then on x axis somehow explain how that was determined.

    Right now it is close but no cigar. The second graph doesn’t say much. Delete it.

  7. What counties do women make more?

    What are the errors? What are the slopes? What do the sizes of the circles indicate? Errors or population? If population, then do you consider errors from the University of Wisconsin data and propagate them?

    In the green plot: what’s happen with the behavior at the extremely rural counties? They vary extremely in terms of pay gaps?

    Also how exactly are you defining your rural metric. You just cite the census and don’t explain. Is it simply a population of each county divided by the definitions listed in the census article?

  8. Does earning data include stay at home moms as zero income? If yes – I’d suppose it could easily explain the whole correlation as it’s more of a conservative thing.

  9. Wouldn’t we expect a greater disparity in pay between men and women in more rural areas, where physical labor is likely to be more lucrative than say being a teacher or cashier.

  10. These charts are always so dumb when you don’t normalize for certain variables and factors. Just baiting for engagement.

  11. In other words, every hick, right wing, uneducated state has shit for a minimum wage. Then the well to do wonder why they have so much crime, and drug and alcohol abuse and the dumb crack dealers, just shake there heads and say “How else am I supposed to pay the fuckin rent?”

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