| This denialism is not compatible with the facts. While part of the gender pay gap can be explained by the factors you describe, not all of it can. This unexplained part is often assumed to be (largely) due to discrimination. This unexplained part has also been shrinking over time, indicating that discrimination has decreased. (See
https://link.springer.com/article/10.1007%2Fs13524-014-0320-... ) Here are journal articles on the topics, showing that economic researchers are covering the topic: https://www.journals.uchicago.edu/doi/abs/10.1086/209845 https://www.tandfonline.com/doi/pdf/10.1080/0077995020954435... https://journals.aom.org/doi/abs/10.5465/AMP.2007.24286161 https://journals.sagepub.com/doi/abs/10.1177/073088848601300... https://journals.sagepub.com/doi/abs/10.1177/001979390606000... https://www.journals.uchicago.edu/doi/abs/10.1086/344125 You can find more publications here: https://scholar.google.co.uk/scholar?hl=en&as_sdt=0%2C5&q=di... For a start, the Wikipedia article unifies many sources: https://en.wikipedia.org/wiki/Gender_pay_gap_in_the_United_S... |
It is the adjusted pay gap that is disputed. No one is really disputing unadjusted pay gap, through some consider that unadjusted pay gap should include everyone including those unemployed. The problem with unadjusted pay gap is that it ignore context.
With context we get a very large variation in the data sets, and large variation in control variables. There is no standard in what variable to use with adjusted pay gap.
Variables commonly cited when comparing full time employed men and women is that men work almost an hour longer per day than women for the same job. Women also use about 50% more sick days, and if I remember right from a study from Norway, about 200% more likely to have children compared to men. Those that have children are then also more likely to stay at home to take care of them, which is a related issue but not the same as pay gap. Overtime is an other factor which correlates with pay raise, as is moving work location and changing employer.
A good sign when I look at such studies is if they can use the same data to predict whom will get a pay raise within the same gender group. The better they can do that the better they can account for those factors when comparing the gender groups to each other. Sadly very few studies does this.