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Yesterday we had a question about the alleged underpayment of women in work, asking why employers would hire fewer cheaper female workers and would instead hire a larger number of expensive male workers. A large amount of discussion ensued.

I'd like to approach the same topic from a different angle.

Without doubt many occupations show a gender bias, and across the board it is apparent that women are more concentrated in occupations which attract lower hourly pay.

What are the economic reasons why, when encountering low pay (or anticipating it at the start of their careers), women should not simply respond to economic incentives, and choose to transfer to higher-paid occupations to increase their earnings?

I should say pre-emptively that I'm not satisfied with ideas that merely may explain the effect, as yesterday's question produced a proliferation of rationalisations and claims that lacked rigour.

I'd prefer to see an explanation that attempts to be comprehensive, or supports contentious claims (such as those about women's productivity) with research.

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    – 1muflon1
    Mar 17 at 11:37
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I should say pre-emptively that I'm not satisfied with ideas that merely may explain the effect, as yesterday's question produced a proliferation of rationalisations and claims that lacked rigour.

I'd prefer to see an explanation that attempts to be comprehensive, or supports contentious claims (such as those about women's productivity) with research.

Your question and the yesterday's one are contentious even in the literature, which means there is no consensus among the economists and no one can give an answer that satisfies everybody. Given the complexity of these questions, they can involve and interact with many different issues, all of which matter to some extent. Even in the literature, the common way is to attack them from one specific perspective rather than to offer a "comprehensive" answer. Also a convincing explanation usually requires careful data analysis, qualified modelling and many robustness checks, which suits more to an academic paper rather than to an answer in this forum.

However, I agree with you that we should avoid rationalisations and claims that lack rigour and the support of academic references. In the comments of this question someone has already mentioned that some recent papers argue that commuting requirement can be one potential reason. I thus list some recent papers that suggest other deep-in-root causes below.

Adda, Dustmann, Stevens 2017 finds that different occupations can diverge in the amenity "child raising value" and in the loss of accumulated skills when interrupting work careers. Given the fertility consideration, women would thus more likely to choose the occupations that have lower wage growth.

Occupation choice is also related with education choice. Women's underrepresentation in the math-intensive fields (i.e. STEM fileds) translates into their underrepresentation not only in high-paying occupations but also in occupations where the gender wage gap within the occupation is particularly small. A survey paper by McNally 2020 reviews many arguments behind this gender differences in tertiary education.

Hsieh, Hurst, Jones, Klenow 2019 studies the roles that the discrimination in the labor market, the barriers to forming human capital, and the differences in preferences or social norms play in individuals' occupation choice. They find that the improvement in the discrimination in forming human capital is the most important driver behind the increased participation of women in high-wage occupations in recent decades.

In additional to typical economics reasoning, Bertrand 2020 suggests that endogenous preferences and self-fulfilling prophecies caused by gender stereotypes can be important for the low share of women in STEM careers and occupations. Also, Grosjean & Khattar 2019 shows that cultural persistency can affect womens' occupational choices.

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    $\begingroup$ @Giskard I rephrased the sentence. You can also check the related reference directly if my words are not clear. $\endgroup$ Mar 14 at 19:09
  • $\begingroup$ Can you expand on what "human capital" is? The wikipedia article makes it seems like it's about training/education, which seems to me like it's referring to the underrepresentation in STEM. $\endgroup$
    – csiz
    Mar 16 at 3:18
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I'm hesitant whether to write this as an answer or as a comment for why this question should be closed as off-topic, since the reasons likely have little to do with economics. Since you did specifically ask about economic reasons, though, I'll attempt an answer.

The economic part of your question is:

What are the economic reasons why, when encountering low pay (or anticipating it at the start of their careers), women should not simply respond to economic incentives, and choose to transfer to higher-paid occupations to increase their earnings?

Yet, the assumption that women don't take compensation into account when choosing a field is almost certainly false. It's just that neither men nor women solely consider compensation when choosing a field and the other reasons are mostly psychological and/or sociological in nature, not economic. In particular, people tend to go into fields that they enjoy, that bring them satisfaction, at which they are adept, and/or that are more likely to have work/life balances matching their needs regardless of their gender or the relative compensation levels of those fields.

While there are obviously both men and women who enjoy almost every field, it shouldn't come as an especially large surprise that those don't occur at equal rates in every field or even in most fields. Far more women than men prefer being school teachers or nurses or doing clerical work, while far more men than women prefer being engineers, airline pilots, or construction workers, for example. A quick look at gender enrollment rates by major at any university which teaches those subjects will confirm this, in addition to data on people actually in the workforce.

For the United States, the U.S. Department of Labor produces detailed statistics on gender breakdown by occupation.

According to this dataset, women constitute 46.8% of the U.S. workforce in 2020. Of the detailed occupations listed for which % female data is available for 2020, only 106 of the 358 had female percentages that were even within 15% on either side of the 46.8% average. 131 of the fields had less than 31.8% females, while 121 of them had more than 61.8% females. Looking at fields within 5% on either side of the average, less than 10% - only 34 - of those 358 detailed fields were between 41.8% and 51.8% female, compared to 159 below 41.8% and 165 above 51.8%

In general, female percentages are incredibly low (mostly under 10%) for occupations that involve large amounts of manual labor and especially heavy lifting. Given the risk involved in these fields, their pay levels tend to be higher than other fields that require equivalent amounts of experience or education. For example, among all occupations in the "Installation, Maintenance, and Repair Occupations" category, only 4.1% of workers are female. In the "Construction and Extraction" (i.e. mining) category, only 4.0% of workers are female. Only 4.4% of firefighters and 17.1% of police officers were female.

On the flip side, for the "Office and Administrative Support" category, 72.7% of workers are female, while "Personal Care and Service Occupations" have 77% females. For "Healthcare Support Occupations" (think home health aids, nursing assistants, and other medical aids, but not doctors or nurses,) 85.3% are female. These fields largely require similar amounts of experience and education as those in the previous paragraph (generally ranging from no experience to trade school, but almost all less than Bachelor's degree requirements,) yet most have much lower personal risk and more personal interaction and/or direct caretaking.

For fields requiring a college degree (Bachelor's, but not Doctorate,) STEM fields tend to attract relatively few females, but have the highest starting salaries of all such fields. Only 16.5% of Architecture and Engineering occupation workers were female and only 25.2% of those in the Computer and Mathematical occupations category. Of the latter category, only statisticians were majority female at 50.3% and the only other groups near the overall workforce average were web and digital interface designers (44.8%) and operations research analysts (42.9%.)

On the other hand, Community and Social Service occupations had 68.8% female workers. In the Education, Training, and Library occupations, 73.5% of workers are female, but the numbers vary dramatically in regards to the age of the people being taught. Post-secondary education is actually pretty equitable at 51.1% female (though this almost certainly varies dramatically based on field being taught, which is not listed in the data.) On the opposite extreme, 98.8% of preschool and kindergarten teachers were female. 79.6% of elementary and middle school teachers and 58.8% of secondary school teachers were female.

Going too far into why women and men, on average, prefer different fields at different rates is not really on-topic here, as it's more a question of psychology or sociology than economics. Those reasons could include innate differences, differences in gender roles taught by society, or, seemingly much more likely, some combination of both. But what is very clear from the data is that men and women have very different average preferences on occupation, regardless of compensation.

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    $\begingroup$ Comments are not for extended discussion; this conversation has been moved to chat. $\endgroup$
    – Kitsune Cavalry
    Mar 16 at 15:23
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There have been several good answers that tackle the economic reasons already; but let me take a different approach. More or less the same approach of INNONOTING, but he got downvoted probably because he didn't really back up his claims.

It is often said that occupations have a gender bias because men and women are raised to fit a certain role-pattern and that it's hard to escape.

However, studies have shown that these role patterns aren't necessarily taught but are born. They are part of our biology. When giving children a certain set of toys the girls will usually pick toys that simulate something (dolls, play-kitchen, ...), while the boys will pick something that has some kind of "mechanic" attached to it, like spinning wheels (toy cars, lego/duplo, ...)

There have been numerous experiments performed on this, and the outcome was always the same. Even more so... the experiment has even been performed on Rhesus monkeys, and even there the results were clear. The male and female monkeys had different preferences for the toys that were left in their habitat.

Here is a video demonstrating the experiment.

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    – Kitsune Cavalry
    Mar 16 at 3:19
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    $\begingroup$ Many people criticize the empirics in Economics, but apparently Biology is another level. Why would you do an experiment with N = 34? $\endgroup$
    – Papayapap
    Mar 16 at 16:44
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    $\begingroup$ Because the total population was only 135 according to the article. That's 25% of the total population. Also: the experiment has been conducted over and over and over again. Both on humans and on monkeys. Always the same conclusion. $\endgroup$
    – Opifex
    Mar 16 at 16:57
  • $\begingroup$ @Opifex if there are more experiments pointing to similar conclusions, I would suggest you giving more evidence especially on human. First of all this one paper published in low-ranking journal with small sample size raises questions of internal validity. Secondly, external validity to humans is another question to make with these studies on animal behaviour. Third, you seem to be confused about the word "population". If this study aims to make conclusion about rhesus monkeys, let alone humans, then population are all rhesus monkeys, not the one tribe. The tribe would be one cluster. $\endgroup$
    – Papayapap
    Mar 23 at 17:06
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Slate Star Codex has a long, well researched article. TL DR: It is very likely that women as a group have more members who care about persons / living things and men as a group have more members who prefer things / concepts. There is a strong correlation between prenatal testosterone and interested in things. Women with a high prenatal testosterone production due to a genetic mutation (CAH), are more likely to be interested in things.

In their own study, they compare 125 such women and find a Things-People effect size of -0.75 – that is, the difference between CAH women and unaffected women is more than half the difference between men and unaffected women. They write:

The results support the hypothesis that sex differences in occupational interests are due, in part, to prenatal androgen influences on differential orientation to objects versus people. Compared to unaffected females, females with CAH reported more interest in occupations related to Things versus People, and relative positioning on this interest dimension was substantially related to amount of prenatal androgen exposure.

Jobs which are prefered by more women than men are btw. not always paid worse.

Whenever I ask this question, I get something like “engineering and computer science are two of the highest-paying, highest-status jobs, so of course men would try to keep women out of them, in order to maintain their supremacy”. But I notice that doctors and lawyers are also pretty high-paying, high-status jobs, and that nothing of the sort happened there. And that when people aren’t using engineering/programming’s high status to justify their beliefs about gender stereotypes in it, they’re ruthlessly making fun of engineers and programmers, whether it’s watching Big Bang Theory or reading Dilbert or just going on about “pocket protectors”.

Meanwhile, men make up only 10% of nurses, only 20% of new veterinarians, only 25% of new psychologists, about 25% of new paediatricians, about 26% of forensic scientists, about 28% of medical managers, and 42% of new biologists.

Note that many of these imbalances are even more lopsided than the imbalance favoring men in technology, and that many of these jobs earn much more than the average programmer. For example, the average computer programmer only makes about \$80,000; the average veterinarian makes about \$88,000, and the average pediatrician makes a whopping \$170,000.

https://slatestarcodex.com/2017/08/07/contra-grant-on-exaggerated-differences/

James Damor (Phd. Candidate in Havard with evolution as research field) has written a nice memo about it. And was fired from google for it.

Differences in distributions of traits between men and women (and not “socially constructed oppression”) may in part explain why we don’t have 50% representation of women in tech and leadership.

https://firedfortruth.com/

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    – 1muflon1
    Mar 16 at 19:01
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I don't consider myself an expert and will not attempt a full answer.. Just wanted to add an interesting and in my view empirically quite convincing paper I recently saw (Brenøe and Zölitz, 2020) which points to non-trivial differences in peer effects among male and female youth as one channel impacting occupation differences. Here is the abstract:

"We investigate how high school gender composition affects students’ participation in STEM at college. Using Danish administrative data, we exploit idiosyncratic within-school variation in gender composition. We find that having a larger proportion of female peers reduces women’s probability of enrolling in and graduating from STEM programs. Men’s STEM participation increases with more female peers present. In the long run, women exposed to more female peers are less likely to work in STEM occupations, earn less, and have more children. Our findings show that the school peer environment has lasting effects on occupational sorting, the gender wage gap, and fertility."

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    $\begingroup$ To make the answer self-contained, please consider adding a bit more description of the linked article (eg. the abstract). $\endgroup$
    – Herr K.
    Mar 23 at 16:39

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