AI wrote 2008-2014 on the image, but actually it was just guessing. The website doesn’t appear to be updated since 2016, so the data are from around that time. This is somewhat before the Republican change into the populist party, so it is possible that some occupations have moved substantially since then. However, for our fertility estimates, the time is sensible because the fertility data is from 2013-2022. To note about these data based on donations is that they reflect people who actually donate money to politicians, which are those who are more invested in politics, and richer. This demographic skews Democrat in modern USA. There may also be issues with shy Republicans who don’t donate publicly (out of fear of reprisals), or just don’t donate at all (surveys show Democrat voters are more interested in politics in general). At least, there seems to be a dearth of activist class jobs with ~100% Republican donations emerging. Every single occupation in the top Democrat list is more skewed towards Democrats than the most Republican occupation is towards Republicans (10% Democrat for Miners vs. 1-9% Republican in all top 25 for Democrats). This is also why many occupations aren’t seen at all despite being large. There are 600k American women working with hand packing things, but they don’t donate a lot of money to politicians, so their leaning cannot be estimated this way.<\/p>\n One of the lowest female fertility occupations was in fact librarian (various subtypes), which we see is in the top list for most left-wing occupations. Using the matching overlap of occupations we get this simple result:<\/p>\n The correlation is a bit better than the other ones we tried, r = -0.23.<\/p>\n Regarding the modeling, there are some thorny questions about measurement\/sampling error and representativeness:<\/p>\n With these caveats in mind, here are some model results:<\/p>\n I’ve tried every modeling approach I could think of, which are:<\/p>\n Looking across the models, we see at least some consistency. All models find that female% of occupations predict higher fertility with about the same effect size around 0.25. The relatively unweighted models find large negative effects of Democrat% support, but these are smaller or not above chance levels in the weighted models. I think this is because the high Democrat% occupations are numerically small and thus imprecise and thus have small importance when using weights. Artistic jobs predict lower fertility with fairly stable slopes around -0.30, but varying p values. These models have only 143 cases because many occupations could not be matched with the OCCP codes or the ones with political donation data, and with weights, the effective sample size is much smaller and thus the results will become unstable.<\/p>\n Regarding the male results, it is tricky. There is a variable for cohabiting opposite sex partner, which is then the father presumably. Any non-cohabiting father is not counted this way. There is another method which is the count of resident children below the age of 1, but this would presumably give about the same result. With this in mind, here are the results across sex:<\/p>\n The correlation is not very strong 0.30. However, this is downwards biased by both the estimation errors for women and the even larger ones for men. The doubly adjusted correlation is 0.45, about 50% larger, based on reliabilities of 0.78 for women and 0.67 for men. Interestingly, the cross-wave stability for both sexes was 0.74 corrected for reliability, so the temporal changes seem to be happening at the same speed in both sexes (between the 2013-2017 and 2018-2022 datasets). Here’s the top and bottom male occupations:<\/p>\n![\"\"](\"https:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/verdant_top_bottom_25.png\")
<\/a><\/p>\n![\"\"](\"https:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/fertility_rr_vs_pct_dem.png\")
<\/a><\/p>\n\n
![\"\"](\"https:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/fertility_regression_compact_5model.png\")
<\/a><\/p>\n\n
![\"\"](\"https:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/fertility_rr_male_vs_female.png\")
<\/a><\/p>\n
![\"\"](\"https:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/fertility_rr_male_pooled.png\")
<\/a><\/p>\n![\"\"](\"https:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/fertility_regression_compact_5model_male.png\")
<\/a><\/p>\n