Has 6 years of mandatory gender pay gap reporting (**GPGR**) made a dent in the UK’s gender pay gap? According to a recent BBC article, not one bit at all. Unfortunately, too many people on social media have been taken in by this misleading article and I will be submitting a formal complaint to the BBC soon to get it amended. I rebutted this at the time with this LinkedIn post and I will now expand on that here to show what the true trend is and whether or not mandatory pay gap reporting has had an impact.

**Employers are not the same as Employees!**

My first complaint about the BBC article is that nowhere do they make these two critical points

- The official UK gender pay gap is measured by the Office of National Statistics (
**ONS**) and has been since 1997. - The GPGR dataset (using data from 13400+ employers who have reported data) is incapable of measuring the UK gender pay gap.

A brief reminder of the difference between the **ONS** data and the **GPGR** data which I have explained before.

**ONS**is a random sample of ~180,000**employees**from HMRC’s PAYE database taken every April.**GPGR**is a census of 13,400+ large**employers**(those with a headcount of 250+) based on payroll data as of 31st March (public sector) or 5th April (private sector).

Let’s look into this in more detail.

**Gender Pay Gap Reporting by ONS**

The **ONS** pay gap estimates comes from a sample known as **ASHE** (Annual Survey of Hours & Earnings). Every year, around April, a random sample of employees who have a PAYE record on the HMRC database are taken and further information is then sought from their employers. The sample size is typically around **180,000** employees from around **60,000** employers. The sample results are weighted according to age, gender and occupation based on weights derived from a different survey known as the Labour Force Survey (**LFS**) which produces the official estimates of unemployment, etc. The final set of figures and analysis are published in October of each year.

The ASHE sample is used to derive a considerable number of estimates as can be seen in this list. For this article, we are interested in the April 2022 ASHE dataset from which I note the following –

- Median
**Gross Annual Earnings**was**£32,917**for men and**£22,776**for women - Median
**Gross Weekly Earnings**was**£622.90**for men and**£449.40**for women - Median
**Weekly Hours Worked**was**37.5**hours for men and**34.9**hours for women - Median
**Gross Pay per Hour**was**£16.01**for men and**£13.56**for women - Median
**Hourly Pay (excluding Overtime)**was**£15.93**for men and**£13.55**for women

It is the last line of numbers which results in the official **ONS** gender pay gap figure for the UK whereby for every **£1** paid per hour (excluding overtime) to the median man in April 2022, the median woman was paid **85.1p** (=13.55/15.93) or **14.9%** less. This is the choice **ONS** made, to use median hourly pay excluding overtime to measure the UK gender pay gap but the other statistics could have been used instead. For example, for every £1 paid** per year** gross to the median man, the median woman is paid **69.2p** (=22776/32917) or** 30.8%** less which is because the median woman works fewer hours than the median man.

**The UK Gender Pay Gap over 25 years.**

The **ONS** pay gap dataset begins in 1997 and has been published for every year since. There are occasional changes in methodology but it does appear the median woman’s hourly pay relative to the median man’s has been rising steadily since then. In 1997, the median woman was paid **72.5p** and in 2017, the year gender pay gap reporting by employers became mandatory, the median woman was paid **81.6p.**

The **9.1p** increase over the 20 year period works out at an average oi **0.46p** per year. If our goal is to eliminate the gender pay gap i.e. the median woman is paid **£1** per hour for every **£1** paid to the median man, then a straight line extrapolation of the fitted line shown in the chart implies this will happen in **2052**. However, history shows progress is not steady and fluctuations can be expected. To allow for such fluctuations, I added a **95%** confidence interval for the projection as shown by the curved brown lines in the chart. These indicate the pay gap could be eliminated anytime between** 2042 & 2063** if the current trend continues.

The above extrapolation assumes nothing changed in 2017. As we know, something did change, the introduction of mandatory **GPGR** for employers with a headcount of 250+. Whilst not covering all employers as the ASHE sample does, it is reasonable to expect that if mandatory **GPGR** is effective for larger employers, the rate at which the median woman’s hourly pay across the UK rises relative to the median man’s should accelerate i.e. the increase should be greater than **0.46p** per year on average. The next chart shows what has actually happened since 2017.

In 2022, the median woman was paid **85.1p** which is up **3.5p** on 2017. However, if mandatory **GPGR **had not come into effect, the straight line extrapolation would have expected the median woman to be paid **85p** in 2022. So I conclude the pay gap in the UK is continuing to narrow since pay gap reporting became mandatory but not at a rate faster than was observed in the 20 years beforehand.

For me to conclude mandatory **GPGR** is having an effect and accelerating the trend, median woman’s hourly pay in 2022 would have to have been **87.5p** or higher. i.e. it breaks out of the range shown by the curved brown lines. We’re not at that point yet and so the timeline for closing the UK’ hourly pay gender pay gap remains **30 +/- 10** years from 2022.

**UK GPGR Median Employer Pay Gap 2017 to 2022**

In the BBC article, this chart stated the gender pay gap in 2022 was **9.4%** i.e. the median woman was paid **90.6p** for every **£1** paid to the median man at the median reporting employer. The BBC calculated this by sorting the** 10,217** employers who had reported their 2022 data by that point in time in order of their median gender pay gap and then selecting the employer in the middle of this line (the **5,109th** employer). This process was repeated in the previous 5 years and the results shown in the chart is what the BBC used to state “*The pay gap has failed to narrow*.”

I was able to replicate these numbers at the time and with a further **350** employers reporting 2022 data (late) since then, the 2022 median employer now pays their median woman **9.2%** less than their median man which doesn’t change the picture shown in the chart. However, this **Naive** calculation (as I call it) is unsuitable for measuring the trend since 2017 and is in fact misleading.

This is because the **10,567** employers reporting 2022 data are not the same employers as the** 10,217** employers who reported 2017 data. Only** 7.980** employers reported data for both 2017 & 2022 with **5,361** reporting data for all 6 years in that timeframe. That means **2,238** employers who reported in 2017 were no longer reporting by 2022 (d*ue to bankruptcy, merger or falling below the 250+ headcount threshold*) and **2,588** employers who reported in 2022 were not reporting in 2017 (*due to being new employer or now having headcount above 250+ threshold*). This makes the BBC’s naive comparison of median employers across all years is a comparison between apples and bananas and cannot be relied to give a meaningful indication of the underlying trend in the **GPGR** dataset.

**GPGR Data = Within-Employer Trends **

The only way to use **GPGR** data to measure trends is to compare apples with apples. We do this by measuring the change in our chosen statistic (median gender pay gap using hourly pay) between 2 separate years within each employer. Thus the **GPGR** dataset is converted into a set of **within-employer trends**. This is the dataset the BBC should have used to estimate the underlying trend and I will now show how I used it but my method isn’t the only option.

Of the **13,402 GPGR** employers who have submitted data for at least one year, **1,577** only submitted data for a single year. These cannot give any insight on trends and so will be ignored from now on. That leaves **11,825** employers with data for at least 2 years thus enabling at least one trend figure to be calculated. Of these, **9,900** are still reporting in 2022 which means **1,925** employers have stopped reporting by 2022 but can provide at least one trend estimate in a year before 2022.

The next step is to group employers by the years they have reported in. I will call these** Year Groups** and the largest year group with **5,361** employers is those who reported in all 6 years which I denote as **171819202122**. The next largest year group with **2,446** employers is the **1718__202122** group who reported for all years except 2019 when enforcement was suspended due to the COVID19 pandemic. In total there are **57** year groups in the **GPGR** dataset.

Within each year group, I can now apply the naive BBC method of finding the pay gap of the median employer in each year. It is these medians by year per year group that are plotted on the chart below for **9** year groups consisting of –

- The
**5**largest year groups of employers who are still reporting in 2022 (shown as black lines & markers) - The
**4**largest year groups of employers who stopped reporting before 2022 (shown as white lines & markers). - The label in the first year of each year group represents the number of employers in the year group.

***Important** Before plotting the chart below, I excluded any year for an employer where an obvious mathematical error in the data they submitted was evident. I will write a separate post explaining my error detection algorithm but it is similar to what I wrote about back in 2018. The number of multi-year employers remaining was only slightly lower at 11,597 but there was a disproportionate impact on the all 6 year group 171819202122 which now only has 4,303 employers. This is a necessary step to avoid distortions in the trends but the conclusions I would draw from the chart below would not change if I had not undertaken this step.*

Two things should strike you immediately from this chart –

- All 9 year groups show a narrowing of the gender pay gap which can be seen by comparing the latest year with the first year shown.
- The 5 black lines for employers who are still reporting in 2022 have larger pay gaps than the 4 white lines for employers who had stopped reporting before 2022.

The second point is not the first time I’ve seen this effect whereby employers who stop reporting had smaller pay gaps than those who continue to report. I plan to investigate this in more depth as it is not obvious why this should be the case. However, it does explain why the naive BBC method in their article is misleading when it claims no trend overall. That is because whilst there is a consistent trend within year groups, in earlier years these employers were combined with small pay gap employers who stopped reporting and in later years (when their pay gap had got smaller) they were combined with newly reporting employers with large pay gaps.

The light purple bar in the chart is a weighted average of the trends observed in the 57 year groups identified. There are many ways to compile this weighted average which I explained in this article on trends as of 2020 and each method give slightly different answers. The labels in the bar show I estimate the median gender pay gap at the median **GPGR** employer has narrowed from **11.2%** in 2017 to** 9.8%** in 2022 i.e. the median woman’s hourly pay increased from **88.8p** in 2017 to **90.2p** in 2022, an increase of **1.4p** or **0.28p** per year**. **If this trend continues in a straight line, then the median woman at the median GPGR employer would be paid £1 for every £1 paid to the median man in **33** (=9.2/0.28) years time i.e. **2055**.

You may have noticed my estimated underlying **GPGR** trend of **0.28p** per year is less than the **ONS **underlying trend of **0.46p** per year. As I explain in more depth in my article “*No employer has a gender pay gap! Let’s celebrate!*“, **GPGR** is incapable of measuring the UK national gender pay gap partly because **GPGR** is derived from large employers only whereas **ONS** covers all employers but mostly because as I have just demonstrated, **GPGR** can only measure trends within employers. However, the two datasets do agree that it will take **30** years or so at current trends for the median woman to be paid the same as the median man so they are not yet contradicting each other when it comes to the ultimate goal of eliminating pay gaps.

So is there evidence from the GPGR dataset that mandatory reporting is having an effect on accelerating the closing the gender pay gap? I addressed this question last year where I showed there was evidence that engaged employers were 20% more likely to have narrowed their pay gap than disengaged employers. I intend to update this analysis when I get a chance.

**GPGR Data = Net Improvement**

The way I’ve derived the underlying trend using **GPGR** data does take some work and may not be easy for the BBC to explain in an article. For this reason, I want to revive & simplify a method of assessing progress in **GPGR** data which I first looked at in 2018. This is a metric which I will now call **Net Improvement **which is derived from the data shown in this table.

Net Improvement is an easy metric to calculate and should be straightforward for the BBC to do themselves and explain in an article.

- For each year,
**count the number of employers who reported data for that year and the previous year**e.g. in 2022,**9,766**employers had reported data for 2021 & 2022.- Within each of these employers, the year on year change in the median gender pay gap using hourly pay is calculated.

- Count the
**number of employers whose pay gap is narrower than the previous year**e.g. in 2022,**50%**of the 9,766 employer pay gaps were now smaller than 2021.- No distinction is made between pay gaps favouring men or women.
- For example, the London Borough of Hackney had a pay gap of 3% in favour of women in 2021 whilst London Borough of Hounslow had a pay gap 3% in favour of men in 2021.
- In 2022, both had no pay gap so both are said to have narrowed their pay gap.

- Count the
**number of employers whose pay gap is the same as the previous year**e.g. in 2022,**7%**of the 9,766 employers pay gaps were the same as 2021.- Again no distinction is made between gaps favouring men and women.
- So Associated British Ports who went from 2% in favour of men to 2% in favour of women are counted as having an unchanged pay gap.

- Count the
**number of employers whose pay gap is wider than the previous year**e.g. in 2022,**43%**of the 9,766 employers pay gap was now larger than it was in 2021.- Again no distinction is made between gaps favouring men and women.

- Calculate the
**difference between %Narrowing and %Widening**which is the**Net Improvement**statistic e.g. in 2022 this was**+7%**(=50%-43%)

As the table shows, all years since GPGR became mandatory have shown Net Improvements of between **4%** &** 8%** of employers. The last column of numbers in the table is the Net Improvement across all years. For each employer here I compare the median gender pay gap in their latest year of reporting with their first year of reporting and this shows a Net **10%** of employers have narrowed their pay gap.

I consider Net Improvement to be a more robust measure of whether progress is being made and it is clear from the table that has been the case in every year since 2017. What Net Improvement doesn’t show is if progress is any faster than would have been the case had gender pay gap reporting not been made mandatory. However, I note Net Improvement in 2022 was higher than all previous years with the exception of 2019 which was probably distorted by non-enforcement due to COVID19. If we continue to see Net Improvement figures of **7%** or more in future years then that could be taken as an indication of employers getting to grips with tackling their gender pay gaps.

**9 Key Points**

**ONS**use a random sample of employees to provide the official estimate of the UK gender pay gap.- The
**ONS**pay gap has narrowed since 1997 at a rate of**0.46**pence in the pound per year. - The trend is unchanged since
**GPGR**became mandatory in 2017 and at that rate, the pay gap will close in**2052**. **GPGR**is a census of larger employers with headcounts of 250 or more and it cannot provide an estimate of the UK gender pay gap.**GPGR**provides insight into trends within employers and these show the median employer is narrowing their pay gap at the rate of**0.28**pence in the pound.- At that rate, the pay gap at the median
**GPGR**employer will close in**2055**similar to what**ONS**implies so**GPGR**&**ONS**trends are broadly consistent with each other. - The BBC’s article failed to realise that 6% of employers stop reporting every year and their observed lack of a
**GPGR**trend was the result of an inappropriate apples v bananas comparison. - The BBC’s should look at the
**Net Improvement**score instead, the difference between the % of employers narrowing their gap & number of employers widening their gap. - In every year since 2017, more employers have narrowed their pay gap than widened it and this difference was larger in 2022.

**Postscript – 27th May 2023**

**Postscript – 27th May 2023**

My complaint to the BBC about their article has now been submitted (case reference number **CAS-7551036-T9R2J3**). The BBC’s normal procedure is to respond within 30 days. Their complaint form has a maximum of 2000 characters so below is what I submitted under a Factual Inaccuracy heading. I will post the BBC’s reply once received.

“**Incorrect to state gender pay gap is unchanged** ag

*Dear Sir/Madam,*

*I am writing to complain about factually incorrect statements made in this article, particularly the chart with the title “The pay gap has failed to narrow”.*

*I have 2 specific grounds of complaint.*

*1. The UK gender pay gap has in fact narrowed from 18.4% in 2017 to 14.9% in 2022 as measured by the Office of National Statistics. This is the official gender pay gap statistic.*

*2. The employer reported data used in this article is incapable of measuring the UK gender pay gap.*

*The chart I refer to is the result of an apples v bananas comparison whereas if one compares apples with apples, it is obvious the pay gap has narrowed since 2017. I explain in more detail what I mean by this in these two posts.*

*1. A LinkedIn post I made on the day after the article appeared – https://www.linkedin.com/posts/nigelmarriottcstat_genderpaygap-paygaps-gender-activity-7049336505319731200-nAeX?utm_source=share&utm_medium=member_desktop*

*2. A more in-depth article I wrote on my blog 2 weeks ago where I explain how the BBC could have presented the data instead – https://marriott-stats.com/nigels-blog/when-will-the-gender-pay-gap-disappear/*

*Basically, employers come and go all the time, so the correct way to analyse this data set is to only look at trends within employers and then find a suitable statistic that combines the multiple within-employer trends. My blog above explains how I’ve done this but there are other methods. What one cannot do is what was done is this article which is statistically invalid.*

*I would like the article amended to include the points I make above or with all references to trends removed.*

*For background, I am a professional independent statistician, fellow of the Royal Statistical Society and professionally active in the gender and ethnicity pay gap field. I have worked with the Cabinet Office on revising gender pay gap guidance & recently wrote the 1st draft of the ethnicity pay gap guidance published last month by the government. ”*

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