It's interesting itself that more women graduate than men. But equal pay means equal pay for people with similar qualifications doing similar jobs. This comparison means nothing to me.
At some point the nurses union in Denmark argued that their education was roughly the same length as that of an engineer, so they should be paid the same on that basic. Completely ignoring that engineers spend five years at the university vs. the 3.5 years for nursing school and that engineers are pay wildly different salaries bases on their field of work.
In my mind, equal pay is for people doing the exact same job, and the exact same number of hours, but that just my interpretation. Many will use the equal pay term to advocate for a pay rise, because they feel that their line of work is underpaid.
If someone believe that they should be better compensated, just say that, don't hide it behind "equal pay". One issue of cause it that people don't understand economy, it not necessarily about the hours you work, the responsibility you have, but about the profit you generate for your employer.
Exactly this. At a fundamental level every individual has an infinite number of "dimensions" (in ML parlance) associated with him, and "equal pay" people or groups will try and convince you that expected pay should be the same over a certain subset of dimensions while ignoring all the others. Invariably they will pick the most beneficial to that particular person or influence group. They will give you arguments from moral, while forgetting to mention that like in any midly complex problem, data bias and confounding variables are of paramount importance.
So "equal pay" means whatever you want it to mean because try and you may, you will never have a model with the full infinite set of dimensions that the real world has. Having to pick you pick the ones you want, a choice that others will attack.
I agree with that phrase, and I acknowledge that it's a problem, but you're jumping into conclusions about what I was trying to say. I wasn't trying to say "we don't have complete information, so we should do nothing." Read on:
> you are rationalizing away the preponderance of evidence which shows that, yep, any way you cut it, there's a gender wage gap.
No, that's is precisely my point. It is NOT true that any way you cut it there's a gender gap. If you let me cut it how I want it I can have the gap be anything I want by carefully (as an example) picking which of the omitted variables I adjust for sampling bias and which ones I don't[0]. That is what I was trying to say.
[0] And lets not talk about confounding variables, that problem is at least an order of magnitud harder even than sampling/population bias.
https://www.cia.gov/news-information/featured-story-archive/...
Surely the right response to a study which challenges your existing worldview would be "Hmm, that's interesting - I wonder what is driving that?" rather than "The equal pay people or groups will always try to convince you..."
You wouldn’t have to negotiate a better salary if it would be obvious that you are underpaid.
I have people who work on my teams who are absolutely fantastic and, while already well-paid, probably should make more. I have other people on my team, with the same title, same education, same on-paper responsibilities, same city, same years of experience, who might be below the median pay and are still overpaid based on my estimation of their contributions relative to their peers.
You can't look only at a spreadsheet and determine that it's "obvious that you are underpaid", IMO.
This is 100% a red herring as far as pay transparency is concerned anyway. If you're not being unfair you have no reason to hide anything.
It actually extends to the whole market, too - if all salaries are transparent, then an RN makes x. They can't make more than that, anywhere they go. It gives a floor, sure - if they get hired, they'll get paid the same as everyone else; it just also makes a ceiling, and, I believe, may slow income growth in general.
So I'd see your point as already happening, companies have already capped salaries, except for executives, who basically set their own salaries.
I love seeing this statement. It's true but the people who post it never follow up evaluating whether or not productivity growth has far out-paced the rise in living standards. If productivity growth has been exponential while the rise in living standards has been linear that's a sign that there's a problem regardless of whether or not living standards have risen.
Think of it like this. Will you be willing to post your entire web browsing history to a publicly available archive regularly? It will help prevent a lot of illegal activity if everyone agreed to do that.
That means that transparency works _for_ you, not against you.
* A lot of unavoidable angst as people of less worth to the business are proven to be paid less in no uncertain terms.
* More internal strife as people jockey for identifiable rank within the organization based upon their salaries. "Why is Sue paid $10k more than I am? Sue wasn't at her desk all week last week while I was here busting my butt."
* Eventually, many managers and organizations would just sidestep the battle by paying everyone the same thing based upon easy-to-identify metrics like seniority. As a result, the people with more value to the business will find jobs at companies that pay them according to a better measure of their bottom-line worth. With no one left but the lowest-common-denominator employees, the company flounders and fails.https://news.ycombinator.com/item?id=9907147
Looking further, it appears that Sweden has decreased the amount of transparency by requiring that people make specific requests that notify the taxpayer of the request.
http://www.businessinsider.com/sweden-salaries-freely-availa...
Apparently, there were issues. I'd like to see this experiment run for a longer period of time in more culturally diverse environments, though.
In most fields, there are already companies which pay wildly different amounts for the same jobs, so the people contributing more in those similar roles are already highly incentivized to leave for higher-paying pastures.
You might argue that a specific study or meta-analysis contains a bias or misinterpretation, but only if you've actually examined their methodology, data, and reasoning. You cannot argue that all studies of complex topics are invalid simply because their topics are complex.
This simply means it's not rigorous. See Omitted-variable bias - from [1]: The bias results in the model attributing the effect of the missing variables to the estimated effects of the included variables. For example, including gender but not education or hours worked will result in attributing pay differences to gender, but including all relevant variables shows that's gender is irrelevant.
This doesn't mean statistics is useless.
This is the meaning of the phrase "the map is not the territory". All models are flawed, but some are useful.
If you take a random sample of studies you can make a statistical analysis. You don't need to examine every cow to make an argument that there are no pink cows, but you do need to do a random sample. And that's if you only want to meet the highest standards of evidence. Much lower standards can be far easier to meet.
Your comparison of this problem with pink cows shows that you haven't given it two seconds thought. Estimating the number of pink cows in the world is a very simple problem. Determining pay gap is a very very complex problem that starts with defining what the question really is and associated fights between different interest groups which might prefer one or another definition, then goes on to the (social, privacy, and rights) problem of obtaining the data, and moving on into with the data analysis itself which is just hellish if you want to have any semblance of rigour, and finally policy take aways from the analysis which hinges crucially on how you defined the question initially.
Stop adding to the noise please.
If by 'estimating' you mean a scientific study that tries to answer the question, then it isn't simple at all. First we need a rigorous definition of pink cows. If I dye my cow pink, does that count? What if other people don't agree with my definition? A pig whose skin is pink is considered pink, so should I only rely on hair color? And what counts as pink? Are we only going with stereotypical hot pink? There is a red cow, but it is a really brownish red. Would a brownish pink be enough to qualify as a pink cow?
So once we solved all those problems, we need to come up with a methodology, and it likely won't be the same everywhere. We could make the problem a lot simpler by reducing our search space to say, only cows on ranches in the state of Montana. But to do a global sampling isn't easy.
>associated fights between different interest groups which might prefer one or another definition
To my knowledge (and with no peer reviewed research to back up my view), there is no groups who have a political stake in what counts as a pink cow. So for that reason it is simpler because there aren't political complications.
But you seem to be confusing something. You appear to be talking about studying wage gap. I was talking about studying studies of wage gaps.
So for my plan, it would work like this:
Taking all the studies of wage gap in the last n years, pick x at random. For each of these, determine if each one does or does not account for some factor that impacts pay regardless of gender (say height of employee). You can then compute what percentage of studies took this factor into account.
Then you repeat this with a few other factors, each time repicking the studies investigated. From those percentages, you can determine how often your selection of factors are taken into account, and from that you might be able to make the argument that the data is biased enough to not be usable.
Doesn't replication crisis prove 'that all studies of complex topics are invalid simply because their topics are complex.'
The replication crisis is a result of the misuse or misunderstanding of the statistics, and the current nature of journals.
And of course, this applies not just to people but to most complex entities or ideas. The problem is, when dealing with humans, even intelligent ones, good luck getting them accept this approach when it interferes with their political/emotional/fiscal beliefs or desires. For reference, see recent discussions here on topics like trade tariffs.
Ideally maybe, but it's just market forces. How much does an employer want you and how hard are you to get and retain?
In addition, women are usually the primary caregiver and disproportionately spend more time doing domestic labour (raising children, taking care of the home) which they are not compensated financially for. Women (or whomever is the primary caregiver in a family or does more domestic labor at home) should be paid more for fewer hours in the workplace.
I think you have to work a bit more to support that assertion. I'm not opposed to the idea of some kind of compensation for home-makers, but putting that on employers seems backwards. Why should that not be a form of social support?
This experiment has been tried and it failed miserably, read up on the Soviet Union.
Yes. And if more people want to become engineers, and if becoming an engineer is easier, then engineers will end up getting less money than nurses.
I mean... the more fun a job is, the more people will want to do it despite getting little money, right?
> In addition, women are usually the primary caregiver and disproportionately spend more time doing domestic labour (raising children, taking care of the home) which they are not compensated financially for.
I recall reading some statistics that (in germany) 80% of domestic spending is done by women. Seems about right.
> Women should be paid more for fewer hours in the workplace.
Uh. That's outright discrimination there. Either against men or against childless people.
Biology has already discriminated and made her life hard, should we make it worse? Should we make having children as difficult as possible for our fellow citizens?
Paternal leave is important too.
Why should anyone be compensated anything for routine life-management work? What you're asking is akin to saying everyone should be paid to sleep. Sleeping, bathing, eating, maintaining the home -- these are all parts of functioning as a human. Taking care of children is a function of having chosen to have offspring - I would say it's a voluntary hobby, even.
And that's the fault of the employer . . . how? If they have a child, it shouldn't be subsidized by their employer. Everyone in the West could abstain from having children for three generations and immigrants would make up the numbers - there's no need for most people to have children.
Pregnancy is a natural consequence of sex. There's no such thing as a truly unexpected pregnancy. Undesired and unplanned perhaps, but not unexpected. In the event it does happen, there are options for either continuing or ending the pregnancy, I still see no reason why anyone should be compensated for voluntarily choosing to continue the pregnancy.
Under a plan where people are being paid unequal amounts simply for being alive, that's where it's wrong.
More explanation, for anyone who wants it, is at https://news.ycombinator.com/item?id=16402648, https://news.ycombinator.com/item?id=16185062, and plenty more at https://hn.algolia.com/?sort=byDate&dateRange=all&type=comme....
They slice and dice budgets in many different ways to ensure that the overall business can maximize profits/productivity.
So if the contract specifies that the company gets paid $200/hr for developer labor up to 40 hr/week, you pay the developers $50/hr to $67/hr by the rule of thumb. If there were no support staff, they would each have to spend 2 hours a week on personnel management, which couldn't be billed to the contract. So an HR employee could support 25 other employees, since they can do the same work in 90 minutes (and still have to do the personnel management for themselves). Cleaning saves the specialists 30 minutes a week, so each supporting up to 119 other employees, since they can do the same work in 20 minutes (and still have to clean their own workspace). A manager saves each developer 8 hours a week, but can handle 10 developers (or 5 managers), since they can do that management work in half the time (and someone else manages them). The CEO is an otherwise uncounted manager of managers, paid out of the owner's share, so the first 5 managers don't require an additional manager to manage them.
You add as many support employees as are necessary to ensure that the employees directly measurable as making money spend all their working hours on making money, instead of something else. They get paid out of the fraction you didn't already pay to the revenue employee, and then the owners take what's left over. The closer you get to optimal productivity, the more calculations you have to do to get even better.
This would all go into a very complicated spreadsheet that changes the numbers based on how many direct-revenue employees there are, and how much support staff. Then I'd add a fudge factor so that if a measurable employee quits, nobody gets an automatic pay cut. This requires a lot of speculative hiring and firing in different categories. Everyone has to be paid according to the maximum they could be paid, if there were one more of them.
In this hypothetical, 20 developers have 2 managers, 1 HR, and 1 cleaner. Weekly revenue is $160k. Developers get $53333 of that, for $2667 each at $67/hr. Managers could get up to $10667 of that, for $5333 each at $133/hr. The HR person can get up to $2667, for $67/hr. The cleaner gets up to $667, for $17/hr. But the managers are operating at capacity, one more developer would require one more manager, for 3 managers over 21 developers, maxing out at $93/hr. So you target that instead. The same speculative calculation for the HR person means that one more developer adds one more manager, which puts the only HR employee at their workload limit of 26 (21+3+1+1). One more developer would require one more HR (22+3+2+1), which maxes out at $37/hr, so that's what you pay the one you have. You wouldn't need another cleaner until 102 developers (102+13+5+2), which would be as much as $43/hr. You never see cleaners paid that much, though, because cleaners have more competition as less-skilled labor, and they never hit the maximum any given company could afford to pay them. So you end up with payroll of about $63k/week, leaving $97k/week to pay the building lease, utilities, depreciation, taxes, etc. with the remainder to the owners.
I'm with you here, but I think you also missed another point: at the same level of productivity. Equal hours at work doesn't mean equal productivity.
I find that hard to quantify in many professional settings. Say Sally and Tim are both project managers. They have basically the same education and experience levels. But Sally has more tact and is more organized. So she gets all the complicated and risky projects. Should Tim and Sally make the same? I'd argue, no.
I have a more simple view on this: the job market is just like any other market, with supply and demand. Those are the factors that will determine the price.
However, given the "women earn ~70 cents for every dollar a man earns" rhetoric we traditionally hear about unequal pay, which compares female earnings to male earnings outright without controlling for education, qualifications, or the "same job"[1], it would seem this comparison is done in the same spirit.
1. http://www.politifact.com/truth-o-meter/statements/2014/jan/...
At the end of the day, the problem is that most people (voters) wouldn't even begin to understand or appreciate the distinction between demagoguery and intellectual integrity.
Of course it doesn't seem the government would be interested in having such an educated populace.
I agree completely, but would education really fix the 20% gender pay gap myth?
I find it very difficult to believe that most of the people who continually reinforce this myth actually believe it to be true. They simply can't all be that ill-educated and/or stupid. And yet the same articles appear in the media every single year. It's become one of those taboo subjects where dogma trumps facts.
The worst part is that it stifles discussion of the earnings gap that actually does exist, and stops us from having meaningful conversations about society's expectations of both men and women.
That is totally irrelevant to their decision process. People keep repeating these statistics because it's useful to make others believe that women are discriminated against in the workplace.
I have to admit, conversations about critical thought in society invariably make me depressed.
I've met several people who treat my tendency to value critical thought as if it's nothing more than a quirky personality trait, and acting based on emotions and feelings is just as valid. It's infuriating.
This analysis doesn't show us that woman make more given equal background/education/etc. However, it does provide the interesting information that women (of that age group) are generally better educated. If we take out of it the desire to find out why they're better educated (and ways we can balance it out), we're better off.
The same is true of studies that show women are paid less, but then the real reason (behind the results highlighted in that study) is that they tend to take lower paying jobs [1]. Sure, you can't take out of that "employers aren't paying them enough", but you can take out of it "why are women generally in the lower paying jobs?", and look for ways to change that fact.
[1] I'm not saying there is or is not a gender gap for equal jobs, just discussing the useful takeaways of studies that ignore the difference in jobs when analyzing the gender gap.
The latter is at least a possibility.
I would argue it is because female-dominated professions tend to have schooling requirements, by law. Male-dominated professions are less apt to.
Anecdotally speaking, I was able to start as a software developer, a male-dominated profession, when I was in high school and soon moved into doing it full time after that. As a result, I do not rank well when measured by my schooling. I later started farming and it did not require schooling either. Both jobs only required the desire to do them. In contrast, a female in my cohort interested in nursing, a female-dominated profession, would legally be prevented from doing so until completing many years of post-secondary schooling. And if that person wants to become a teacher, another female dominated career, later in life even more legal schooling requirements are necessary.
On the assumption that females have more schooling because they have to, in order to pursue the careers they want to do. Is the correction in easing the legal requirements for these jobs, or is the correction to enforce more stringent legal requirements on male-dominated jobs?
And you would base this off what data? Surely we shouldnt just be using our guts here.
The data that shows that female-dominated professions are more apt to have legal requirements.
> Surely we shouldnt just be using our guts here.
Well, why not? We're not writing formal research papers here. Only writing comments for personal pleasure in our spare time.
Not according to the UK government: https://www.gov.uk/guidance/gender-pay-gap-reporting-overvie...
This is a wonderful example of a double standard: when a study finds that men earn more than women, people say it doesn't matter that they aren't working in the same jobs because (as they say) discrimination keeps women from getting those jobs, but when women earn more then men, it's fine and dandy because they aren't working in the same jobs or experience levels, so no discrimination exists.
The gender distribution for the top 0.2% doesn't matter since most men and women will never reach that income.
You can have equal or better qualifications than someone else with less or no degrees.
Just not formal qualifications...
If you're comparing degreed vs non-degreed folks, how is the comparison in the peer group?