Pay And Employment By Sex

 This graphic is all you need know about the gender pay gap (click to enlarge)

By William Collins aka MRA-UK: I have never done a post on the (groan) pay gap. It’s about time, I guess. No, don’t worry. I’m not going to re-iterate for the billionth time the reasons why men earn more on average than women. We all know why – even the feminists. Sure, feminists will claim it’s because “women get paid less for the same work”. But only the very silly foot soldiers actually believe this. The serious feminists – the really dangerous ones – know full well that the main reason is that women are less work focussed than men, and this results mainly from their preferred prioritising of domestic and childcare matters. Most of us sane people have no problem with that. Unfortunately the loonies are in charge.
The reasons for higher male earnings have been laid out clearly in Warren Farrell’s book Why Men Earn More and in the videos by Christina Hoff Sommers and Warren Farrell, or see any number of sources, e.g., here or here . In brief, the main reason is that men work more hours.
They also work more continuous full time years, without career breaks. The underlying reason behind men’s greater working hours and working years is that women, past a certain age, prioritise domestic and childcare matters, whilst men increasingly prioritise earnings in pursuance of the same objective – support of the family. Men’s prioritising of earnings comes at a cost, namely reduced work-life balance. Thus, if faced with an option to increase his pay by taking on a job which is unpleasant, laborious, or dangerous, or involves long commutes or working away from home, men are far more likely to take up the option than women. Men are also more likely to put in overtime when they would prefer not to, in order to enhance promotion prospects. It all comes down to the degree of work-centeredness, which Catherine Hakim has observed is far stronger in men.
Hourly Pay Rates
However, we can cut through all that. The killer graphic is the median hourly pay rate, excluding overtime, for full time workers against age and gender. Figure 1 is exactly that, taken from the ONS “annual survey of hours and earnings 2013″. [The pay gap is defined as (m – w) / m as a percentage]. Figure 2 is the corresponding histogram for 2014. Both are available here. The salient fact is that there is virtually no gender pay gap for people in their twenties and thirties. It’s strange the way the patriarchy selects older women for oppression.

Figure 1: From ONS Annual Survey of Hours and Earnings (2013) click to enlarge

Figure 2: From ONS Annual Survey of Hours and Earnings (2014)

The 2015 ONS Annual Survey of Hours and Earnings does not include the corresponding histogram. Odd, that. However, undeterred, I found an even better graphic lurking within the subsidiary analysis reported in Analysis of factors affecting earnings using Annual Survey of Hours and Earnings: 2015. It is the graphic which heads this post. It’s so important I also reproduce it below as Figure 3. [Unlike Figures 1 and 2, this pay gap is defined as (m – w) / w as a percentage].

Figure 3: From ONS “Analysis of Factors Affecting Earnings using Annual Survey of Hours and Earnings: 2015″ (Click to enlarge)

For the first time we see clearly that women below the age of about 35, working full time, have a higher median hourly pay rate than men of the same age. The histograms of Figures 1 and 2 for 2013 and 2014 indicated only a very slightly greater median pay for women in their twenties, of a percent or so. But Figure 3 indicates clearly for the first time, in 2015, a marked advantage for young women. The median hourly pay rate for women in their twenties working full time is around 8% higher than that for men (average over ages 21-29).
Much has been said about men’s greater earnings being due to their tendency to enter better paid professions. We can see now, without the need for detailed analysis, that this is untrue. By age 35, most graduates will have been working for more than 10 years. The effect of their chosen profession will be evident in earnings data prior to age 35. But it is women that attract the higher hourly pay rate below the age of 35. So, whilst it may be true that some, educationally successful, men enter particularly well paid professions, this is not evident in the median. There must be other men doing less well than women. Although I have not presented evidence to conclusively demonstrate this, there are obvious reasons for what Figure 3 reveals, summarised thus,

1. Young women are being paid more than men because they are better educated, on average;
2. Older men are being paid more than women because they have, by then, put in more continuous years of work, and worked more hours per year, than women of the same age.

ONS data shows that the longer a person stays in a given job, the higher the hourly pay rate becomes, see Figure 4. So point 2, above, naturally leads to improving men’s pay. Over all ages, point 2 wins over point 1 – but only just, and only for now.
Figure 3 also reveals that the best quantification of the gender hourly pay gap is 4.6% (based on median pay and median age). Men are in their forties before they realise this advantage, after perhaps 20 years or more of full time work.

Figure 4: Effect of Years-in-Job on Hourly Pay Rate

Greater male earnings are presented in the media as male privilege. But it is clear that the greater earnings men eventually achieve is actually due to decades of effort. This is not to suggest that women are putting in any less effort – but less of their effort is directed towards paid employment. In contrast, the earnings advantage enjoyed by young women is (probably) due to their superior educational attainment compared to men. There are reasons to believe that the educational disadvantage to boys and young men is systemic (e.g., see here and here and here and here and here and here and here). Consequently, the higher hourly earnings of women under 35 could more reasonably be regarded as female privilege.
If my hypothesis is correct – that young women’s better median pay is due to their better education – then it is certain to become more marked over the next decade or so, because male educational under-performance is partly determined by early schooling (and society at large). It will become increasingly difficult to hide young women’s greater pay rates over the next few years. Others will inevitably make the link with failing male education, a matter which is already causing concern in quarters not contaminated by feminism.
But nothing will be done until the government becomes aware of the threat to the economy. At present the government is locked into a mindset that ‘”what’s good for women’s employment is good for the economy”. With men contributing 72.7% of income tax revenue into the exchequer, blithely ignoring the challenge to male employment must ultimately come forcibly to government attention as the economy nose-dives or as the swelling ranks of the unemployable male underclass gives rise to serious civil unrest.
The actual median hourly pay rates for full time workers of all ages can be obtained from the ONS report “Patterns of Pay: Results from the Annual Survey of Hours and Earnings, 1997 to 2012“. I have plotted these against year in Figure 5. Figure 6 shows the same data converted to real terms using 2015 £ (conversion using CPI).

Figure 5: Full time hourly pay rates across all ages

Figure 6: Full time hourly pay rates across all ages (real terms)

Women part time workers of all ages are paid more per hour than men
The median gender pay gap across all ages is shown against year, from 1997 to 2015, in Figure 7 for both full time and part time workers (taken from the 2015 ONS Annual Survey of Hours and Earnings). For full time workers it has reduced from 17.4% to 9.6% over this period. The 9.6% figure based on average pay compares with the figure of 4.6% from Figure 3 based on median age. Take your pick. But the true figure is certainly not the 20% figure you may read in the press.
For part time workers, women have earned more per hour than men for the last 18 years. The part time working gender pay gap in favour of women now stands at 7%.
NB: Part-time work is defined as employees working not more than 30 paid hours per week (or less than 25 hours for the teaching professions).
The uppermost line on Figure 7 is meaningless. Ostensibly it applies to “all workers”, i.e., both full time and part time. But since the gender pay gaps for full time and part time working in 2015 were 9.6% and -7% respectively, it is clearly bonkers to suppose that a figure of nearly 20% applies for all workers. What this uppermost data actually reflects is the fact that the hourly rate for full time workers (of both sexes) considerably exceeds the hourly rate for part time workers (of both sexes). Because far more women work part time, averaging over all workers inevitably makes the (apparent) gender pay gap look to be large and in men’s favour. But the uppermost line in Figure 7 really just reflects the premium anyone (of either sex) gets for working full time. It is not a gender pay gap for equivalent working at all. It is statistical legerdemain. I’m surprised the ONS thought it appropriate to include it.

Figure 7: Gender pay gap over all ages showing the reducing full time pay gap and the increasing part time pay gap in favour of women (click to enlarge)

Public Versus Private Employment
Over twice as many women as men are employed in the public sector (due primarily to education and health), see Figure 8. Conversely, men dominate in the private sector.
However, as of April 2015, hourly pay rates in the private sector were lower than those in the public sector for 90% of staff, see Figure 9. Only in the upper decile do private sector pay rates exceed the public sector.
Putting together the above two statements implies that, if men and women were equally distributed in seniority (i.e., in pay grade) then women would, on average, be paid more per hour by virtue of dominating in the public sector. That men still command a greater hourly pay rate, when taken across all ages, can only be due to more men than women moving into the upper decile due to working more years and gaining seniority.

Figure 8:

Figure 9:

Hours Worked
The following working hours data are taken from ONS datafile Actual weekly hours of work: People (not seasonally adjusted) May 2016, and the equivalent at June 2014. Data are for the whole UK.
Average for year July 2013 to June 2014

• Number of men employed 15.64 million; number of women employed 13.55 million (includes full time and part time workers).
• Hours worked per week by men: 595.6 million
• Hours worked per week by women: 378.8 million

Table 1: Average hours worked per week per person (June 2014)

(hours)	Full time	Part time	Second job
Men	39.5	16.2	10.4
Women	34.4	16.0	8.7

Average for year April 2015 to March 2016

• Hours worked per week by men: 608.9 million
• Hours worked per week by women: 393.9 million

Table 2: Average hours worked per week per person (March 2016)

(hours)	Full time	Part time	Second job
Men	39.1	16.2	10.0
Women	34.0	16.2	9.0

The trend in average hours worked per week since 1997 is shown in Figure 10. Whilst women’s average working hours have not changed, men’s have been trending down. This is not due to the 2008 recession. The trend started well before that. Whilst I have not definitively established the reason for the decline in men’s working hours, I note that it is what would be expected to accompany a reduction in marriage rates – because men tend to prioritise paid work even more when married.
If classical economics applied, the alternative explanation for men’s reducing working hours, namely that the demand for men’s labour has declined, would be ruled out. This is because a reduction in demand would be accompanied by a reduction in pay rate, but the real-terms pay rate is actually higher now than in 1997 (see Figure 6). However, it is possible that the operation of the minimum pay statute has subverted this reasoning so it is possible that the decline in men’s working hours is demand-side driven. (This would align with the conclusion for the USA in Wayward Sons).

Figure 10

The Gender Income Tax Gap
Men contribute 72.7% of income tax revenue, i.e., the gender income tax gap to men’s detriment is 166%. That makes the pay gap pale into insignificance, doesn’t it?
A Pay Gap Tax?
The gross disproportion in income tax payment is not enough for the feminists. Nor are the above observations on the true nature of the pay gap – especially the fact that the pay gap is in young women’s favour. There is a growing movement to simply bump up women’s pay to that of men. All pretence of meritocracy or fairness is being abandoned. The University of Essex has recently given all its female professors a pay rise to make their average pay the same as that of the male professors. Age, years of experience, performance and contribution – all irrelevant.
The Director of a company, Brainlabs, Sophie Newton, has made a video promoting their adoption of a pay gap tax. At the end of the year, the average pay of men and women is worked out and, assuming the former is larger, the difference is presented to the women as a bonus. This will be done, Newton tells us, “regardless of performance or position”. When asked whether this discriminates against men, Newton replied with a smirk worthy of Jess Philips, claiming the move is justified because of the centuries of oppression. Oh really. This answers the obvious question – would men be the beneficiaries if women were paid more initially? No, of course not. If this initiative catches on we can anticipate young women looking to join companies which are top-heavy with older, senior men – the ultimate free ride.
And in Australia, the bank ANZ is putting an extra $500 per year into female staff’s superannuation pot. Same reward for the same work? Nope, it isn’t.
I wonder what would happen in any of the above institutions if a biological male claimed to identify as female in gender? I think we know. His/her claim to the female-bonus would be declined – because if they gave it to him, suddenly every man would be identifying as female – and there would no longer be a bonus to be had! Oops – the gender gibberish would stand revealed as subterfuge – only the possession of female genitalia counts.
It will be interesting to see if this type of flagrant unfairness becomes widespread. And if so, whether this, finally, will be enough to wake up the somnolent, bovine masses of men.
Employment and Unemployment
Data in this section are relative to the UK population of working age. This is defined as from 16 years old to state pension age (with due allowance for how that has changed in recent years). Three categories are used in national statistics: employed, unemployed and economically inactive. The ’employed’ category includes full time and part time workers.
People not working are classed as unemployed if they have been looking for work within the last four weeks and are able to start work within the next two weeks. There is no requirement to be claiming any form of benefit in order to be classed as unemployed.
Jobless people who have not been looking for work within the last four weeks or who are unable to start work within the next two weeks are classed as economically inactive. This category includes people who have retired prior to state pension age as well as people simply not wishing to work, e.g., those favouring full time domestic duties.
Belinda Brown in “Reviewing gendered employment policies” (2014) has observed that whilst the government strategy of encouraging increasing female employment has been successful, it has the unfortunate effect of reducing male employment. There is no doubt that this is true of employment rate, defined as the percentage of the working age population who are employed. Brown’s data, from 1971 to 2011 (referenced as being from here),  is reproduced in graphical form in Figure 11, in comparison with data from the ONS Labour Force Survey datasets, “participation in employment in UK 1993 to 2014″.
Figure 11 may be compared with Figure 12, ultimately from the same source (the ONS Labour Force Survey) but Figure 12 normalises the data by the whole population aged 16 and over, not just the working age population. Finally, Figure 13 confirms Figure 11.
The striking thing about the employment data is that the male employment rate has reduced by almost the same as the female employment rate has increased (roughly 14% to 16%). I stress this is in terms of employment rate, which is a percentage of the working age population. Because the working age population has increased, the change in absolute numbers of people employed is different. I estimate that the number of employed men has reduced by about 8% since 1971, whereas the number of employed women has increased by about 40%. The benefit to the economy, in terms of increased GDP due to a larger employed workforce, would appear to depend upon an increasing population. Conversely, increasing female participation in the workplace does not, in itself, increase economic activity. And yet this appears to be the driver behind the endless initiatives to improve female academic performance, increase female representation on Boards, increase women-in-STEM, etc. etc.
The government really does seem to believe in the economic magic of getting more women into paid work. Nicky Morgan, for example, has claimed that,
“Equalising women’s productivity and employment to the same level as men’s could add almost £600 billion to our economy, clearing a third of our national debt”
It doesn’t give one much confidence in the government that a Minister can make such a moronic statement. This is the employment version of fiat money, is it? Fiat GDP? We’d be better off with Mr Bean in charge.

Figure 11: Employment rate against year (Brown & ONS data)

Figure 12: Employment rate against year (ONS data), normalised using the whole population aged 16+

Figure 13: Employment rate against year (unknown provenance)

The flip side of employment are the economically inactive people. Figure 14 shows the number of inactive people as a proportion of the working age population from 1993 to 2015. The number of inactive women was double the number of inactive men in 1993. By 2015 the number of inactive women had become only 50% greater than  the number of inactive men.

Figure 14

And finally…since the EU Referendum is just 12 days away, here’s yet another reason to vote Brexit – Figure 15.

Figure 15

Prognosis
The government, like the rest of society, is in the grip of a feminist enchantment. They believe that economic salvation lies in increasing female employment. The main engine of the economy continues to be male effort, just as it ever was. But in the name of female empowerment our society is content to let boys and young men flounder. By the time that educational disadvantage of males has unambiguously impacted on the economy it will be too late to enact immediate rectification. A two decade time lag, at least, must ensue. But the worst case scenario is that, by then, men will have ceased to be interested in being an economic engine at all.

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