{"id":5073,"date":"2023-05-10T18:24:20","date_gmt":"2023-05-10T17:24:20","guid":{"rendered":"https:\/\/marriott-stats.com\/nigels-blog\/?p=5073"},"modified":"2023-06-14T09:28:06","modified_gmt":"2023-06-14T08:28:06","slug":"when-will-the-gender-pay-gap-disappear","status":"publish","type":"post","link":"https:\/\/marriott-stats.com\/nigels-blog\/when-will-the-gender-pay-gap-disappear\/","title":{"rendered":"Pay Gap Trends #6 &#8211; Are we there yet?"},"content":{"rendered":"<p>Has 6 years of mandatory gender pay gap reporting (<strong>GPGR<\/strong>) made a dent in the UK&#8217;s gender pay gap?\u00a0 According to <a href=\"https:\/\/www.bbc.co.uk\/news\/business-65179430\" target=\"_blank\" rel=\"noopener\">a recent BBC article<\/a>, not one bit at all.\u00a0 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.\u00a0 I rebutted this at the time <a href=\"https:\/\/www.linkedin.com\/posts\/nigelmarriottcstat_genderpaygap-paygaps-gender-activity-7049336505319731200-nAeX?utm_source=share&amp;utm_medium=member_desktop\" target=\"_blank\" rel=\"noopener\">with this LinkedIn post<\/a> 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.<\/p>\n<p><!--more--><\/p>\n<h5><span style=\"color: #008000;\"><strong>Employers are not the same as Employees!<\/strong><\/span><\/h5>\n<p>My first complaint about the BBC article is that nowhere do they make these two critical points<\/p>\n<ol>\n<li><a href=\"https:\/\/www.ons.gov.uk\/employmentandlabourmarket\/peopleinwork\/earningsandworkinghours\/bulletins\/genderpaygapintheuk\/previousReleases\" target=\"_blank\" rel=\"noopener\">The official UK gender pay gap is measured by the Office of National Statistics<\/a> (<span style=\"color: #0000ff;\"><strong>ONS<\/strong><\/span>) and has been since 1997.<\/li>\n<li><a href=\"https:\/\/marriott-stats.com\/nigels-blog\/latest-gender-pay-gap-data\/\" target=\"_blank\" rel=\"noopener\">The GPGR dataset<\/a> (using data from 13400+ employers who have reported data since 2017) is incapable of measuring the UK gender pay gap.<\/li>\n<\/ol>\n<p>A brief reminder of the difference between the <span style=\"color: #0000ff;\"><strong>ONS<\/strong><\/span> data and the <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> data which <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/gender-pay-gap-faqs\/\" target=\"_blank\" rel=\"noopener\">I have explained before.<\/a><\/p>\n<ol>\n<li><span style=\"color: #0000ff;\"><strong>ONS<\/strong> <\/span>is a random sample of ~180,000 <span style=\"color: #0000ff;\"><strong>employees<\/strong><\/span> from HMRC&#8217;s PAYE database taken every April.<\/li>\n<li><span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> is a census of 13,400+ large <span style=\"color: #ff0000;\"><strong>employers<\/strong><\/span> (those with a headcount of 250+) based on payroll data as of 31st March (public sector) or 5th April (private sector).<\/li>\n<\/ol>\n<p>Let&#8217;s look into this in more detail.<\/p>\n<h5><span style=\"color: #008000;\"><strong>Gender Pay Gap Reporting by ONS<\/strong><\/span><\/h5>\n<p>The <strong><span style=\"color: #0000ff;\">ONS<\/span><\/strong> pay gap estimates comes from a sample known as <a href=\"https:\/\/www.ons.gov.uk\/employmentandlabourmarket\/peopleinwork\/earningsandworkinghours\/methodologies\/annualsurveyofhoursandearningsashemethodologyandguidance\" target=\"_blank\" rel=\"noopener\"><strong>ASHE<\/strong> (Annual Survey of Hours &amp; Earnings).<\/a>\u00a0 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.\u00a0 The sample size is typically around <strong>180,000<\/strong> employees from around <strong>60,000<\/strong> employers.\u00a0 The sample results are weighted according to age, gender and occupation based on weights derived from a different survey known as <a href=\"https:\/\/www.ons.gov.uk\/employmentandlabourmarket\/peopleinwork\/employmentandemployeetypes\/methodologies\/labourforcesurveylfsqmi\" target=\"_blank\" rel=\"noopener\">the Labour Force Survey (<strong>LFS<\/strong>)<\/a> which produces the official estimates of unemployment, etc.\u00a0 The final set of figures and analysis are published in October of each year.<\/p>\n<p>The ASHE sample is used to derive a considerable number of estimates <a href=\"https:\/\/www.ons.gov.uk\/employmentandlabourmarket\/peopleinwork\/earningsandworkinghours\/bulletins\/annualsurveyofhoursandearnings\/2022\/relateddata?page=1\" target=\"_blank\" rel=\"noopener\">as can be seen in this list<\/a>.\u00a0 For this article, we are interested in the <a href=\"https:\/\/www.ons.gov.uk\/file?uri=\/employmentandlabourmarket\/peopleinwork\/earningsandworkinghours\/datasets\/ashe1997to2015selectedestimates\/current\/selectedestimates19972022.xlsx\" target=\"_blank\" rel=\"noopener\">April 2022 ASHE dataset<\/a> from which I note the following &#8211;<\/p>\n<ul>\n<li>Median <strong>Gross Annual Earnings<\/strong> was <strong>\u00a332,917<\/strong> for men and <strong>\u00a322,776<\/strong> for women<\/li>\n<li>Median <strong>Gross Weekly Earnings<\/strong> was <strong>\u00a3622.90<\/strong> for men and <strong>\u00a3449.40<\/strong> for women<\/li>\n<li>Median <strong>Weekly Hours Worked<\/strong> was <strong>37.5<\/strong> hours for men and <strong>34.9<\/strong> hours for women<\/li>\n<li>Median <strong>Gross Pay per Hour<\/strong> was<strong>\u00a0\u00a316.01<\/strong> for men and <strong>\u00a313.56<\/strong> for women<\/li>\n<li>Median <strong>Hourly Pay (excluding Overtime)<\/strong> was<strong>\u00a0\u00a315.93<\/strong>\u00a0for men and <strong>\u00a313.55<\/strong>\u00a0for women<\/li>\n<\/ul>\n<p>It is the last line of numbers which results in the official <span style=\"color: #0000ff;\"><strong>ONS<\/strong><\/span> gender pay gap figure for the UK whereby for every <strong>\u00a31<\/strong> paid per hour (excluding overtime) to the median man in April 2022, the median woman was paid <strong>85.1p<\/strong> (=13.55\/15.93) or <strong>14.9%<\/strong> less.\u00a0 This is the choice <span style=\"color: #0000ff;\"><strong>ONS<\/strong><\/span> made, to use median hourly pay excluding overtime to measure the UK gender pay gap but the other statistics could have been used instead.\u00a0 For example, for every \u00a31 paid<strong> per year<\/strong> gross to the median man, the median woman is paid <strong>69.2p<\/strong> (=22776\/32917) or<strong> 30.8%<\/strong> less which is because the median woman works fewer hours than the median man.<\/p>\n<h5><span style=\"color: #008000;\"><strong>The UK Gender Pay Gap over 25 years.<\/strong><\/span><\/h5>\n<p>The <span style=\"color: #0000ff;\"><strong>ONS<\/strong> <\/span>pay gap dataset begins in 1997 and has been published for every year since.\u00a0 There are occasional changes in methodology but it does appear the median woman&#8217;s hourly pay relative to the median man&#8217;s has been rising steadily since then.\u00a0 In 1997, the median woman was paid <strong>72.5p<\/strong> and in 2017, the year gender pay gap reporting by employers became mandatory, the median woman was paid <strong>81.6p.<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-5091 aligncenter\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Pre-GPGR-b.png\" alt=\"\" width=\"643\" height=\"471\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Pre-GPGR-b.png 1204w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Pre-GPGR-b-300x220.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Pre-GPGR-b-1024x751.png 1024w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Pre-GPGR-b-768x563.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Pre-GPGR-b-450x330.png 450w\" sizes=\"auto, (max-width: 643px) 100vw, 643px\" \/><\/p>\n<p>The <strong>9.1p<\/strong> increase over the 20 year period works out at an average oi <strong>0.46p<\/strong> per year.\u00a0 If our goal is to eliminate the gender pay gap i.e. the median woman is paid <strong>\u00a31<\/strong> per hour for every <strong>\u00a31<\/strong> paid to the median man, then a straight line extrapolation of the fitted line shown in the chart implies this will happen in <strong>2052<\/strong>.\u00a0 However, history shows progress is not steady and fluctuations can be expected.\u00a0 To allow for such fluctuations, I added a <strong>95%<\/strong> confidence interval for the projection as shown by the curved brown lines in the chart.\u00a0 These indicate the pay gap could be eliminated anytime between<strong> 2042 &amp; 2063<\/strong> if the current trend continues.<\/p>\n<p>The above extrapolation assumes nothing changed in 2017.\u00a0 As we know, something did change, the introduction of mandatory <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> for employers with a headcount of 250+.\u00a0 Whilst not covering all employers as the<span style=\"color: #008000;\"><strong> ASHE<\/strong><\/span> sample does, it is reasonable to expect that if mandatory <strong><span style=\"color: #ff0000;\">GPGR<\/span><\/strong> is effective for larger employers, the rate at which the median woman&#8217;s hourly pay across the UK rises relative to the median man&#8217;s should accelerate i.e. the increase should be greater than <strong>0.46p<\/strong> per year on average.\u00a0 The next chart shows what has actually happened since 2017.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-5092 aligncenter\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Post-GPGR-2022-b.png\" alt=\"\" width=\"635\" height=\"466\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Post-GPGR-2022-b.png 1203w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Post-GPGR-2022-b-300x220.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Post-GPGR-2022-b-1024x752.png 1024w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Post-GPGR-2022-b-768x564.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/ONS-GPG-Long-Term-Trends-Post-GPGR-2022-b-450x330.png 450w\" sizes=\"auto, (max-width: 635px) 100vw, 635px\" \/><\/p>\n<p>In 2022, the median woman was paid <strong>85.1p<\/strong> which is up <strong>3.5p<\/strong> on 2017.\u00a0 However,\u00a0 if mandatory <strong><span style=\"color: #ff0000;\">GPGR<\/span> <\/strong>had not come into effect, the straight line extrapolation would have expected the median woman to be paid <strong>85p<\/strong> in 2022.\u00a0 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.<\/p>\n<p>For me to conclude mandatory <span style=\"color: #ff0000;\"><strong>GPGR<\/strong> <\/span>is having an effect and accelerating the trend, median woman&#8217;s hourly pay in 2022 would have to have been <strong>87.5p<\/strong> or higher. i.e. it breaks out of the range shown by the curved brown lines.\u00a0 We&#8217;re not at that point yet and so the timeline for closing the UK&#8217; hourly pay gender pay gap remains <strong>30\u00a0+\/- 10<\/strong> years from 2022.<\/p>\n<h5><span style=\"color: #008000;\"><strong>UK GPGR Median Employer Pay Gap 2017 to 2022<\/strong><\/span><\/h5>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5093 alignright\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Overall-trends-NAIVE-BBC.png\" alt=\"\" width=\"338\" height=\"236\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Overall-trends-NAIVE-BBC.png 899w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Overall-trends-NAIVE-BBC-300x210.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Overall-trends-NAIVE-BBC-768x536.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Overall-trends-NAIVE-BBC-450x314.png 450w\" sizes=\"auto, (max-width: 338px) 100vw, 338px\" \/><a href=\"https:\/\/www.bbc.co.uk\/news\/business-65179430\" target=\"_blank\" rel=\"noopener\">In the BBC article, this chart<\/a> stated the gender pay gap in 2022 was <strong>9.4%<\/strong> i.e. the median woman was paid <strong>90.6p<\/strong> for every <strong>\u00a31<\/strong> paid to the median man at the median reporting employer.\u00a0 The BBC calculated this by sorting the<strong> 10,217<\/strong> 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 <strong>5,109th<\/strong> employer).\u00a0 This process was repeated in the previous 5 years and the results shown in the chart is what the BBC used to state &#8220;<em>The pay gap has failed to narrow<\/em>.&#8221;<\/p>\n<p>I was able to replicate these numbers at the time and with a further <strong>350<\/strong> employers reporting 2022 data (late) since then, the 2022 median employer now pays their median woman <strong>9.2%<\/strong> less than their median man which doesn&#8217;t change the picture shown in the chart.\u00a0 However, this <strong>Naive<\/strong> calculation (as I call it) is unsuitable for measuring the trend since 2017 and is in fact misleading.<\/p>\n<p>This is because the <strong>10,567<\/strong> employers reporting 2022 data are not the same employers as the<strong> 10,217<\/strong> employers who reported 2017 data.\u00a0 Only<strong> 7.980<\/strong> employers reported data for both 2017 &amp; 2022 with <strong>5,361<\/strong> reporting data for all 6 years in that timeframe.\u00a0 That means <strong>2,238<\/strong> employers who reported in 2017 were no longer reporting by 2022 (d<em>ue to bankruptcy, merger or falling below the 250+ headcount threshold<\/em>) and <strong>2,588<\/strong> employers who reported in 2022 were not reporting in 2017 (<em>due to being new employer or now having headcount above 250+ threshold<\/em>).\u00a0 This makes the BBC&#8217;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 <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> dataset.<\/p>\n<h5><span style=\"color: #008000;\"><strong>GPGR Data = Within-Employer Trends\u00a0<\/strong><\/span><\/h5>\n<p>The only way to use <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> data to measure trends is to compare apples with apples.\u00a0 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.\u00a0 Thus the <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> dataset is converted into a set of <strong>within-employer trends<\/strong>.\u00a0 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&#8217;t the only option.<\/p>\n<p>Of the <strong>13,402 <span style=\"color: #ff0000;\">GPGR<\/span><\/strong> employers who have submitted data for at least one year, <strong>1,577<\/strong> only submitted data for a single year.\u00a0 These cannot give any insight on trends and so will be ignored from now on.\u00a0 That leaves <strong>11,825<\/strong> employers with data for at least 2 years thus enabling at least one trend figure to be calculated.\u00a0 Of these, <strong>9,900<\/strong> are still reporting in 2022 which means <strong>1,925<\/strong> employers have stopped reporting by 2022 but can provide at least one trend estimate in a year before 2022.<\/p>\n<p>The next step is to group employers by the years they have reported in.\u00a0 I will call these<strong> Year Groups<\/strong> and the largest year group with <strong>5,361<\/strong> employers is those who reported in all 6 years which I denote as <span style=\"color: #993300;\"><strong>171819202122<\/strong><\/span>.\u00a0 The next largest year group with <strong>2,446<\/strong> employers is the <span style=\"color: #993300;\"><strong>1718__202122<\/strong><\/span> group who reported for all years except 2019 when enforcement was suspended due to the COVID19 pandemic.\u00a0 In total there are <strong>57<\/strong> year groups in the <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> dataset.<\/p>\n<p>Within each year group, I can now apply the naive BBC method of finding the pay gap of the median employer in each year.\u00a0 It is these medians by year per year group that are plotted on the chart below for <strong>9<\/strong> year groups consisting of &#8211;<\/p>\n<ul>\n<li>The <strong>5<\/strong> largest year groups of employers who are still reporting in 2022 (shown as black lines &amp; markers)<\/li>\n<li>The<strong> 4<\/strong> largest year groups of employers who stopped reporting before 2022 (shown as white lines &amp; markers).<\/li>\n<li>The label in the first year of each year group represents the number of employers in the year group.<\/li>\n<\/ul>\n<p><em>**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.\u00a0 I will write a separate post explaining my error detection algorithm but <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/1-in-10-orgs-published-incorrect-gender-pay-gap-data\/\" target=\"_blank\" rel=\"noopener\">it is similar to what I wrote about back in 2018<\/a>.\u00a0 The number of multi-year employers remaining was only slightly lower at <strong>11,597<\/strong> but there was a disproportionate impact on the all 6 year group <span style=\"color: #993300;\"><strong>171819202122<\/strong><\/span> which now only has <strong>4,303<\/strong> employers.\u00a0 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.<\/em><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-5094 aligncenter\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/gpg-trend-17-to-22-medians.png\" alt=\"\" width=\"576\" height=\"560\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/gpg-trend-17-to-22-medians.png 576w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/gpg-trend-17-to-22-medians-300x292.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/gpg-trend-17-to-22-medians-360x350.png 360w\" sizes=\"auto, (max-width: 576px) 100vw, 576px\" \/><\/p>\n<p>Two things should strike you immediately from this chart &#8211;<\/p>\n<ol>\n<li>All <strong>9<\/strong> year groups show a narrowing of the gender pay gap which can be seen by comparing the latest year with the first year shown.<\/li>\n<li>The <strong>5<\/strong> black lines for employers who are still reporting in 2022 have larger pay gaps than the <strong>4<\/strong> white lines for employers who had stopped reporting before 2022.<\/li>\n<\/ol>\n<p>The second point is not the first time I&#8217;ve seen this effect whereby employers who stop reporting had smaller pay gaps than those who continue to report.\u00a0 I plan to investigate this in more depth as it is not obvious why this should be the case.\u00a0 However, it does explain why the naive BBC method in their article is misleading when it claims no trend overall.\u00a0 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.<\/p>\n<p>The light purple bar in the chart is a weighted average of the trends observed in the 57 year groups identified.\u00a0 There are many ways to compile this weighted average which I explained<a href=\"https:\/\/marriott-stats.com\/nigels-blog\/pay-gap-trends-did-the-uk-gender-pay-gap-narrow-in-2020\/\" target=\"_blank\" rel=\"noopener\"> in this article on trends as of 2020<\/a> and each method give slightly different answers.\u00a0 The labels in the bar show I estimate the median gender pay gap at the median <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> employer has narrowed from <strong>11.2%<\/strong> in 2017 to<strong> 9.8%<\/strong> in 2022 i.e. the median woman&#8217;s hourly pay increased from <strong>88.8p<\/strong> in 2017 to <strong>90.2p<\/strong> in 2022, an increase of <strong>1.4p<\/strong> or <strong>0.28p<\/strong> per year<strong>.\u00a0 <\/strong>If this trend continues in a straight line, then the median woman at the median GPGR employer would be paid \u00a31 for every \u00a31 paid to the median man in <strong>33<\/strong> (=9.2\/0.28) years time i.e. <strong>2055<\/strong>.<\/p>\n<p>You may have noticed my estimated underlying <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> trend of <strong>0.28p<\/strong> per year is less than the <strong><span style=\"color: #0000ff;\">ONS<\/span> <\/strong>underlying trend of <strong>0.46p<\/strong> per year.\u00a0 As I explain in more depth in my article &#8220;<a href=\"https:\/\/marriott-stats.com\/nigels-blog\/pay-gaps-no-gender-or-ethnicity-pay-gap-in-2029\/\" target=\"_blank\" rel=\"noopener\"><em>No employer has a gender pay gap! Let&#8217;s celebrate!<\/em><\/a>&#8220;, <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> is incapable of measuring the UK national gender pay gap partly because <span style=\"color: #ff0000;\"><strong>GPGR<\/strong> <\/span>is derived from large employers only whereas <span style=\"color: #0000ff;\"><strong>ONS<\/strong><\/span> covers all employers but mostly because as I have just demonstrated, <span style=\"color: #ff0000;\"><strong>GPGR<\/strong> <\/span>can only measure trends within employers.\u00a0 However, the two datasets do agree that it will take <strong>30<\/strong> 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.<\/p>\n<p>So is there evidence from the GPGR dataset that mandatory reporting is having an effect on accelerating the closing the gender pay gap?\u00a0 I addressed this question last year where I showed there was evidence that e<a href=\"https:\/\/marriott-stats.com\/nigels-blog\/has-pay-gap-reporting-improved-the-gender-pay-gap\/\" target=\"_blank\" rel=\"noopener\">ngaged employers were 20% more likely to have narrowed their pay gap than disengaged employers<\/a>.\u00a0 I intend to update this analysis when I get a chance.<\/p>\n<h5><span style=\"color: #008000;\"><strong>GPGR Data = Net Improvement<\/strong><\/span><\/h5>\n<p>The way I&#8217;ve derived the underlying trend using <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> data does take some work and may not be easy for the BBC to explain in an article.\u00a0 For this reason, I want to revive &amp; simplify a method of assessing progress in <strong><span style=\"color: #ff0000;\">GPGR<\/span><\/strong> data <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/gender-pay-gap-trends-2018\/\" target=\"_blank\" rel=\"noopener\">which I first looked at in 2018<\/a>.\u00a0 This is a metric which I will now call <strong>Net Improvement <\/strong>which is derived from the data shown in this table.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-5098 aligncenter\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Net-Improvement-ALL.png\" alt=\"\" width=\"863\" height=\"166\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Net-Improvement-ALL.png 863w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Net-Improvement-ALL-300x58.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Net-Improvement-ALL-768x148.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2023\/05\/6y-GPGR-Net-Improvement-ALL-450x87.png 450w\" sizes=\"auto, (max-width: 863px) 100vw, 863px\" \/><\/p>\n<p>Net Improvement is an easy metric to calculate and should be straightforward for the BBC to do themselves and explain in an article.<\/p>\n<ol>\n<li>For each year, <strong>count the number of employers who reported data for that year and the previous year<\/strong> e.g. in 2022, <strong>9,766<\/strong> employers had reported data for 2021 &amp; 2022.\n<ul>\n<li>Within each of these employers, the year on year change in the median gender pay gap using hourly pay is calculated.<\/li>\n<\/ul>\n<\/li>\n<li>Count the <strong>number of employers whose pay gap is narrower than the previous year<\/strong> e.g. in 2022, <strong>50%<\/strong> of the 9,766 employer pay gaps were now smaller than 2021.\n<ul>\n<li>No distinction is made between pay gaps favouring men or women.<\/li>\n<li>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.<\/li>\n<li>In 2022, both had no pay gap so both are said to have narrowed their pay gap.<\/li>\n<\/ul>\n<\/li>\n<li>Count the <strong>number of employers whose pay gap is the same as the previous year<\/strong> e.g. in 2022, <strong>7%<\/strong> of the 9,766 employers pay gaps were the same as 2021.\n<ul>\n<li>Again no distinction is made between gaps favouring men and women.<\/li>\n<li>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.<\/li>\n<\/ul>\n<\/li>\n<li>Count the <strong>number of employers whose pay gap is wider than the previous year<\/strong> e.g. in 2022, <strong>43%<\/strong> of the 9,766 employers pay gap was now larger than it was in 2021.\n<ul>\n<li>Again no distinction is made between gaps favouring men and women.<\/li>\n<\/ul>\n<\/li>\n<li>Calculate the <strong>difference between %Narrowing and %Widening<\/strong> which is the <strong>Net Improvement<\/strong> statistic e.g. in 2022 this was <strong>+7% <\/strong>(=50%-43%)<\/li>\n<\/ol>\n<p>As the table shows, all years since GPGR became mandatory have shown Net Improvements of between <strong>4%<\/strong> &amp;<strong> 8%<\/strong> of employers.\u00a0 The last column of numbers in the table is the Net Improvement across all years.\u00a0 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 <strong>10%<\/strong> of employers have narrowed their pay gap.<\/p>\n<p>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.\u00a0 What Net Improvement doesn&#8217;t show is if progress is any faster than would have been the case had gender pay gap reporting not been made mandatory.\u00a0 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.\u00a0 If we continue to see Net Improvement figures of <strong>7%<\/strong> or more in future years then that could be taken as an indication of employers getting to grips with tackling their gender pay gaps.<\/p>\n<p>&nbsp;<\/p>\n<h5><span style=\"color: #008000;\"><strong>9 Key Points<\/strong><\/span><\/h5>\n<ol>\n<li><span style=\"color: #0000ff;\"><strong>ONS<\/strong><\/span> use a random sample of employees to provide the official estimate of the UK gender pay gap.<\/li>\n<li>The <span style=\"color: #0000ff;\"><strong>ONS<\/strong> <\/span>pay gap has narrowed since 1997 at a rate of <strong>0.46<\/strong> pence in the pound per year.<\/li>\n<li>The trend is unchanged since <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> became mandatory in 2017 and at that rate, the pay gap will close in <strong>2052<\/strong>.<\/li>\n<li><strong><span style=\"color: #ff0000;\">GPGR<\/span><\/strong> is a census of larger employers with headcounts of 250 or more and it cannot provide an estimate of the UK gender pay gap.<\/li>\n<li><span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> provides insight into trends within employers and these show the median employer is narrowing their pay gap at the rate of <strong>0.28<\/strong> pence in the pound.<\/li>\n<li>At that rate, the pay gap at the median <strong><span style=\"color: #ff0000;\">GPGR<\/span><\/strong> employer will close in <strong>2055<\/strong> similar to what <span style=\"color: #0000ff;\"><strong>ONS<\/strong><\/span> implies so <strong><span style=\"color: #ff0000;\">GPGR<\/span><\/strong> &amp; <span style=\"color: #0000ff;\"><strong>ONS<\/strong> <\/span>trends are broadly consistent with each other.<\/li>\n<li>The BBC&#8217;s article failed to realise that 6% of employers stop reporting every year and their observed lack of a <span style=\"color: #ff0000;\"><strong>GPGR<\/strong><\/span> trend was the result of an inappropriate apples v bananas comparison.<\/li>\n<li>The BBC&#8217;s should look at the <strong>Net Improvement<\/strong> score instead, the difference between the % of employers narrowing their gap &amp; number of employers widening their gap.<\/li>\n<li>In every year since 2017, more employers have narrowed their pay gap than widened it and this difference was larger in 2022.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<h5><span style=\"color: #993300;\"><em><strong>Postscript &#8211; 27th May 2023<\/strong><\/em><\/span><\/h5>\n<p>My complaint to the BBC about their article has now been submitted (case reference number <strong>CAS-7551036-T9R2J3<\/strong>).\u00a0 The <a href=\"https:\/\/www.bbc.co.uk\/contact\/how-we-handle-your-complaint\" target=\"_blank\" rel=\"noopener\">BBC&#8217;s normal procedure is to respond within 30 days<\/a>.\u00a0 Their complaint form has a maximum of 2000 characters so below is what I submitted under a Factual Inaccuracy heading.\u00a0 I will post the BBC&#8217;s reply once received.<\/p>\n<p>&#8220;<em><strong>Incorrect to state gender pay gap is unchanged<\/strong> ag\u2009<\/em><\/p>\n<p><em>Dear Sir\/Madam,<\/em><\/p>\n<p><em>I am writing to complain about factually incorrect statements made in this article, particularly the chart with the title &#8220;The pay gap has failed to narrow&#8221;.<\/em><\/p>\n<p><em>I have 2 specific grounds of complaint.<\/em><\/p>\n<p><em>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.<\/em><br \/>\n<em>2. The employer reported data used in this article is incapable of measuring the UK gender pay gap.<\/em><\/p>\n<p><em>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.<\/em><\/p>\n<p><em>1. A LinkedIn post I made on the day after the article appeared &#8211; <a href=\"https:\/\/www.linkedin.com\/posts\/nigelmarriottcstat_genderpaygap-paygaps-gender-activity-7049336505319731200-nAeX?utm_source=share&amp;utm_medium=member_desktop\">https:\/\/www.linkedin.com\/posts\/nigelmarriottcstat_genderpaygap-paygaps-gender-activity-7049336505319731200-nAeX?utm_source=share&amp;utm_medium=member_desktop<\/a><\/em><\/p>\n<p><em>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 &#8211; <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/when-will-the-gender-pay-gap-disappear\/\">https:\/\/marriott-stats.com\/nigels-blog\/when-will-the-gender-pay-gap-disappear\/<\/a><\/em><\/p>\n<p><em>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&#8217;ve done this but there are other methods. What one cannot do is what was done is this article which is statistically invalid.<\/em><\/p>\n<p><em>I would like the article amended to include the points I make above or with all references to trends removed.<\/em><\/p>\n<p><em>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 &amp; recently wrote the 1st draft of the ethnicity pay gap guidance published last month by the government.\u2009&#8221;<\/em><\/p>\n<h5><span style=\"color: #993300;\"><em><strong>Update &#8211; 31st May 2023<\/strong><\/em><\/span><\/h5>\n<p><em>The BBC replied saying they would not consider my complaint as it was out of time.\u00a0 Apparently the complaint must be submitted within 30 working days of the article appearing and I submitted my complaint 36 working days after the article.\u00a0 Highly annoying.<\/em><\/p>\n<p>&nbsp;<\/p>\n<h5><strong><span style=\"color: #993300;\">&#8212; Would you like to comment on this article? &#8212;-<\/span><\/strong><\/h5>\n<p>Please do leave your comments on either of these <a href=\"https:\/\/www.linkedin.com\/posts\/nigelmarriottcstat_genderpaygap-paygaps-gender-activity-7049336505319731200-nAeX?utm_source=share&amp;utm_medium=member_desktop\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #008000;\"><strong>LinkedIn<\/strong><\/span><\/a> \u00a0or <a href=\"https:\/\/twitter.com\/MarriottNigel\/status\/1643889029639700480\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #008000;\"><strong>Twitter<\/strong><\/span><\/a> threads.<\/p>\n<h5><strong><span style=\"color: #993300;\">&#8212; Subscribe to my newsletter to receive more articles like this one! &#8212;-<\/span><\/strong><\/h5>\n<p>If you would like to receive notifications from me of news, articles and offers relating to diversity &amp; pay gaps, please <span style=\"color: #008000;\"><strong><a style=\"color: #008000;\" href=\"https:\/\/marriott-stats.com\/nigels-blog\/subscribe-to-our-newsletter\/\" target=\"_blank\" rel=\"noopener\">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<h5><span style=\"color: #993300;\"><strong>&#8212; Want to know more about pay gaps?\u00a0 &#8212;<\/strong><\/span><\/h5>\n<p>You will find a full list of my pay gap &amp; diversity related articles <span style=\"color: #008000;\"><strong><a style=\"color: #008000;\" href=\"https:\/\/marriott-stats.com\/nigels-blog\/stats-training-materials-pay-gap-analytics\/\" target=\"_blank\" rel=\"noopener noreferrer\">here which are grouped by theme<\/a><\/strong><\/span>.<\/p>\n<h5><span style=\"color: #993300;\"><strong>&#8212; Can I help you to close your pay gap? &#8212;<\/strong><\/span><\/h5>\n<p>I offer the following services to my clients who want to define, measure, analyse, improve &amp; control their pay gaps.<\/p>\n<ol>\n<li><a href=\"https:\/\/marriott-stats.com\/pay-gap-analytics\/\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #993300;\"><strong><span style=\"color: #008000;\">Analysis<\/span><\/strong><\/span> <\/a>&#8211; I can dig deep into your data to identify the key drivers of your pay gaps.\u00a0 I can build a model using a large number of variables such as pay band, seniority, job function, location, etc and use this to identify the priority areas for closing your gaps.<\/li>\n<li><a href=\"https:\/\/marriott-stats.com\/introduction-to-pay-gap-analytics\/\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #993300;\"><strong><span style=\"color: #008000;\">Training<\/span><\/strong><\/span><\/a> &#8211; I run training courses in basic statistics which are designed for non-statisticians such as people working in HR.\u00a0 The courses will show you how to perform the relevant calculations in Microsoft Excel, how to interpret what they mean for you and how to incorporate these in an action plan to close your gaps.<\/li>\n<li><a href=\"https:\/\/marriott-stats.com\/expert-witness\/\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #993300;\"><strong><span style=\"color: #008000;\">Expert Witness<\/span><\/strong><\/span><\/a> &#8211; Has your gender pay gap data uncovered an issue resulting in legal action?\u00a0 Need an expert independent statistician who can testify whether the data supports or contradicts a claim of discrimination?\u00a0 I have experience of acting as an expert witness for either plaintiff or defendant and I know how to testify and explain complex data in simple language that can be easily understood by non-statisticians.<\/li>\n<\/ol>\n<p>If you would like to have a no-obligation discussion about how I can help you, <strong><span style=\"color: #008000;\"><a style=\"color: #008000;\" href=\"https:\/\/marriott-stats.com\/contact-us\/\" target=\"_blank\" rel=\"noopener noreferrer\">please do contact me<\/a><\/span><\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Has 6 years of mandatory gender pay gap reporting (GPGR) made a dent in the UK&#8217;s gender pay gap?\u00a0 According to a recent BBC article, not one bit at all.\u00a0 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 [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":5092,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[64,6],"tags":[63,122,179,190,46,183],"class_list":{"0":"post-5073","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-diversity","8":"category-forecasting","9":"tag-gender-pay-gap","10":"tag-median","11":"tag-ons","12":"tag-pay-gap-trends","13":"tag-trend-analysis","14":"tag-trend-extrapolation","15":"entry","16":"override"},"_links":{"self":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/5073","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/comments?post=5073"}],"version-history":[{"count":21,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/5073\/revisions"}],"predecessor-version":[{"id":5178,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/5073\/revisions\/5178"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/media\/5092"}],"wp:attachment":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/media?parent=5073"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/categories?post=5073"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/tags?post=5073"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}