Take a look at this graphic with 6 fictional employers, each with 12 employees.\u00a0 In each employer, the median woman earns the same as the median man and the average woman earns the same as the average man (slight difference for Office Cleaning & Co).\u00a0 3 employers have male dominated workforces and 3 employers have female dominated workforces and there are 36 men & 36 women in total.\u00a0 Assume these 6 employers represent the entire economy that the ONS reports on, how much do the median man and the median woman earn?<\/p>\n
![\"\"](\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2021\/04\/ONS-v-GPG-example-gender-1024x717.png\")
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The answer is given by the table on the right which lists the frequency distributions for men & women.\u00a0 The median man\/woman are the averages of the 18th & 19th employees of those genders when they stand in a line in order of their hourly pay.\u00a0 The median man earns \u00a330 and the median woman earns \u00a325 per hour and thus for every \u00a31 earned by the median man, the median woman earns 83p, a pay gap of 17p in the pound.\u00a0 A similar pay gap exists when the average man & woman are compared.<\/p>\n
Why does this happen when none of the 6 employers had a pay gap?\u00a0 The answer should be obvious from the graphic since the 6 employers were displayed in order of average pay.\u00a0 Men are more likely to be found in high paying employers and women are more likely to be found in low paying employers.\u00a0 So it is no surprise that the national median woman will be earning less than the national median man.<\/p>\n
The same effect is already apparent in the ONS pay gap figures.\u00a0 If we look at the 2020 gender pay gap, ONS estimate that the median women earns 84.5p for every \u00a31 earned by the median man<\/a>.\u00a0 Among full time employees, the median woman earns 92.6p for every \u00a31 earned by the median man and among part time employees, the median woman earns \u00a31.03 for every \u00a31 earned by the median man.\u00a0 Note how the pay gaps for full time and part time employees are much smaller than the pay gap for all employees.\u00a0 Again the reason is obvious and follows the same effect as above.\u00a0 Women are more likely to work part time and part time roles earn less per hour on average than full time roles.\u00a0 Consequently, the median women’s pay is dragged down and the median man’s pay is dragged up when full & part time roles are combined.\u00a0 See this blog by the ONS published in 2019<\/a> for more details about this paradox and how a Bletchley Park codebreaker from WW2 is able to resolve this.<\/p>\n The bottom line is that any employer that seeks to compare their pay gap with the ONS pay gap is making a false comparison.\u00a0 ONS pay gaps can never be comparable with pay gaps from GPG reporting and such efforts should be discontinued.\u00a0 Should we ever get to a situation where no employer has a gender pay gap, I would still be expecting the ONS to be reporting a pay gap against women of around 5-10p in the pound.<\/p>\n <\/p>\n In 2019, ONS reported the median ethnic minority employee earns 97.7p for every \u00a31 earned by the median white British employee<\/a>.\u00a0 I have seen some scepticism of this figure which appears to be a narrower pay gap than those reported by a number of employers.\u00a0 Again it turns out there an obvious reason why the ONS will always report a more favourable pay gap for ethnic minorities and once again, no employer should ever be comparing their ethnicity pay gap with the ONS figure.<\/p>\n Unlike gender, ethnicity is not uniform across the UK.\u00a0 Some areas are very white, other areas are ethnically very diverse.\u00a0 However, none of this would matter if the average pay was the same across the UK.\u00a0 As we all know though, pay in London is much higher with the ONS currently estimating the London premium to be at least 30%.\u00a0 At the same time, London is much more diverse than the rest of the UK.\u00a0 Consequently it is more likely that a non-white employee will be living in London and earning a premium compared to a white employee who is more likely to be living outside of London and not earning a premium.\u00a0 Thus it is not surprising that the national ethnicity pay gap should be so small.<\/p>\n To demonstrate this, I will again assume that no employer in the UK has an ethnicity pay gap.\u00a0 Rather than creating fictional employers, this time I have imagined each of the 632 parliamentary constituencies in Great Britain are employers (with approximately 100k employees including children!) and within each constituency, the median white employee earns the same as the median non-white employee.\u00a0 From the 2011 census, we know what % of the population in each constituency is white British and the ONS also report the median full time weekly wage by constituency.\u00a0 Whilst later data is available, my point still stands using the latest data I have in my possession which is for 2017.<\/p>\n The chart below plots weekly full time wage by % white British for all 632 seats.\u00a0 I’ve split England into 3 parts and plotted Scotland & Wales separately.<\/p>\n The chart may look messy but it is the open blue circles representing London that you need to concentrate on.\u00a0 On average, the 78 seats in London are 49:51 white:non-white whereas the rest of England is 87:13 white:non-white and Scotland\/Wales are 93:7 white:non-white.\u00a0 At the same time, the average weekly wage in London \u00a3662 is 32% higher than that seen in Wales.\u00a0 The majority of seats in London have average weekly wages above \u00a3600 whereas the majority of seats outside of London have averages less than \u00a3600.<\/p>\n If we make the assumption that within each seat, there is no ethnicity pay gap, then one can take a weighted average of the weekly wages using the %white british as the weight to estimate that the average weekly wage for White British would be \u00a3545 and for non-white British, it would be \u00a3585.\u00a0 Thus for every \u00a31 earned by a white British employee, a non-white British employee would be earning \u00a31.073.\u00a0 Given that the ONS currently estimate this to be 97.7p instead, that implies that within each seat on average, the median non-white person is earning 90.4p for every \u00a31 earned by a white person.<\/p>\n Indeed the ONS data shows that by region (see figure 8 of this link<\/a>), non-white employees earn on average 7.5% less than white employees once the region is taken into account but this varies considerably between regions.\u00a0 In London, the median non-white person earns 73p for every \u00a31 earned by the median white employee but note that non-white employees in London still earn more than non-white employees in any other region (bar the East).\u00a0 It just goes to show why an employer cannot compare their ethnicity pay gap with the ONS which is measuring something different.<\/p>\n <\/p>\n Over my 30 years as a statistician I have lost count of how many times I have said “Objectives! Objectives! Objectives!<\/em><\/span>“.\u00a0 The question posed here is incomplete, what you need to ask instead is “what am I trying to do?<\/em><\/span>” and “which measure is more meaningful given my objectiv<\/span>e”<\/em>.<\/p>\n For an employer, the ONS figure is irrelevant.\u00a0 Indeed I argue far too much time is spent comparing one employer with another when employers should be comparing themselves over time to see if they are improving.\u00a0 I’ve said before that pay gap analytics is all about Continuous Improvement<\/strong><\/a> and is not about your place in a league table.\u00a0 Employer reported data is the best data to use if one is interested in trends over time as it allows a lot of true like for like comparisons as I did recently when estimating the trend for 2020<\/a>.<\/p>\n On the other hand, if I want to see if the earning power of women or a specific ethnicity is improving, then the ONS figure is more meaningful.\u00a0 The fact that ethnic minorities are more likely to be in London does indeed boost their earning power and the ONS figure reflects that.\u00a0 Of course, it should be noted that ONS pay calculations exclude overtime, most bonuses, pensions and non-monetary rewards so they should be included if we truly want to know what the earning power of a group is.\u00a0 Indeed I would also argue that hourly pay which puts full time & part time employees on the same basis is misleading and the fact that women are more likely to work part time reduces their total earnings.\u00a0 So for me, earning power should in fact be total annual remuneration regardless of hours.<\/p>\n I am sure there are other objectives that would lead to different decisions but I hope I’ve made my point.\u00a0 What is reported by the ONS is sound and what is reported by employers is also sound.\u00a0 They are just not measuring the same thing and nor should they ever be expected to measure the same thing.<\/p>\n <\/p>\n Please do leave your comments on either of these Twitter<\/a> <\/strong><\/span>or LinkedIn<\/strong><\/a><\/span> threads.<\/p>\n If you would like to receive notifications from me of news, articles and offers relating to diversity & pay gaps, please click here to go to my Newsletter Subscription page<\/a><\/strong><\/span> and tick the Diversity category and other categories that may be of interest to you.\u00a0 You will be able to unsubscribe at anytime.<\/p>\n You will find a full list of my pay gap & diversity related articles here which are grouped by theme<\/a><\/strong><\/span>.<\/p>\n I offer the following services.\u00a0 Please click on the headings for more details.<\/p>\nWhy ONS Ethnicity Pay Gap is more favourable for ethnic minorities<\/strong><\/span><\/h4>\n
![\"\"](\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2021\/04\/ONS-v-GPG-example-ethnicity-1024x669.png\")
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