ONS Earnings User Event Insights
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The document outlines an event programme for an earnings statistics user event, including sessions on recent policy-focused earnings analysis, working together to help develop analyses, and a question and answer period. Several presentations are scheduled on topics like geospatial variation in earnings, low pay in Greater Manchester, measuring low pay and minimum wage underpayment, analysis of job stayers and changers, and exploring commuting distance and the gender pay gap. The event brings together analysts from various government departments and organizations to discuss earnings research.
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ONS Earnings User Event Insights
- 1. Earnings Statistics User Event Programme 29 April 2019 Twitter: @ONS #Econstats Wifi: Username: Password: 29 April 2019
- 2. 13:00 – 14:15 Session 1: Recent policy-focused earnings analysis 13:00 – 13:20 Geospatial variation in earnings: evidence from ASHE – Charlotte Woodacre and Matthew Mitchell, Ministry of Housing, Communities & Local Government 13:20 – 13:40 Low pay in Greater Manchester: A report for the Greater Manchester Independent Prosperity Review – Stephen Clarke, Resolution Foundation 13:40 – 14:00 Measuring low pay and minimum wage underpayment – Harry Ravi, Department for Business, Energy & industrial Strategy 14:00 – 14:15 Question and Answers Session
- 3. Geospatial variation in earnings: evidence from ASHE Ministry of Housing, Communities & Local Government Charlotte Woodacre and Matthew Mitchell 29 April 2019
- 4. April 29@resfoundation 4 Low pay in Greater Manchester for the Independent Prosperity Review ONS Earnings Statistics User Event 29th April 2019 Stephen Clarke, Senior Economic Analyst, Resolution Foundation @stephenlclarke
- 5. 5 The NLW has led to the first significant fall in low-pay in decades Proportion of employee jobs in Greater Manchester below selected low-pay thresholds @resfoundationSource: RF analysis of ONS, ASHE
- 6. 6 The Good: GM is better than average Proportion of employee jobs that are low paid, by city region: 2017 @resfoundationSource: RF analysis of ONS, ASHE
- 7. 7 Proportion of employee jobs that are low paid in Greater Manchester, by local authority: 2017 @resfoundationSource: RF analysis of ONS, ASHE The Bad: where you live matters
- 8. 8 The Ugly: some groups do worse in Greater Manchester @resfoundation Single parents - 42% of single parents in GM are low-paid compared to 33% in the rest of GB Black or black British people - 33% of black or black British people in GM are low-paid compared to 21% in the rest of GB Degree-holders - 9.5% of adults with degrees in GM are low-paid compared to 8.1% in rest of GB Source: RF analysis of ONS, LFS
- 9. 9 Explaining low pay Market power, persistence, industries and occupations @resfoundation
- 10. 10 Large firms play a big part in the low-pay labour market Share of all low-paid employee jobs in firms with 5,000+ employees, GM and GB @resfoundationSource: RF analysis of ONS, ASHE
- 11. 11 But GM performs better than most in this regard Share of sampled low-paid employees jobs that are with the five biggest employers: 2017 @resfoundationSource: RF analysis of ONS, ASHE
- 12. 12 And there is no clear relationship between low-pay and concentration at the sectoral level Sub-sector-weighted CR10s, Greater Manchester and Great Britain: 2016 @resfoundationSource: RF analysis of ONS, Business Structure Database
- 13. 13 We do know that low-pay is ‘sticky’ Proportion of employee jobs that were low paid in 2012 and still low paid in 2016, by city region @resfoundationSource: RF analysis of ONS, ASHE
- 14. 14 Time spent in low-pay when young has lasting effects Change in chance of being in a low-paid occupation for a 3 percentage point increase in the unemployment rate in year after leaving education @resfoundationNotes: RF modelling, forthcoming Source: RF analysis of ONS, ASHE Those who enter the labour market during a recession are 20% more likely to be in a low-paying job
- 15. 15 Time spent in low-pay when young has lasting effects Change in chance of being in a low-paid occupation for a 3 percentage point increase in the unemployment rate in year after leaving education @resfoundationNotes: RF modelling, forthcoming Source: RF analysis of ONS, ASHE Those who enter the labour market during a recession are 20% more likely to be in a low-paying job And this is still the case 8 years after leaving education
- 16. 16 But sectors and occupations can make a difference @resfoundationSource: RF analysis of ONS, ASHE
- 17. April 29@resfoundation 17 Low pay in Greater Manchester for the Independent Prosperity Review ONS Earnings Statistics User Event 29th April 2019 Stephen Clarke, Senior Economic Analyst, Resolution Foundation @stephenlclarke
- 18. Measuring low pay and minimum wage underpayment Department for Business, Energy & Industrial Strategy Harry Ravi 29 April 2019
- 19. Q & A session © Photo by Vicky Gu on Unsplash
- 20. © Photo by Vicky Gu on Unsplash Refreshment break
- 21. 14:35 – 16:15 Session 2: Working together to help develop our analyses 14:35 – 14:55 Analysis of job stayers and changers – Amina Syed, Office for National Statistics 14:55 – 15:15 Exploring commuting distance and the gender pay gap – Vahe Nafilyan, Office for National Statistics 15:15 – 15:25 Question and Answers session 15:25 – 15:45 Taking a partnership approach to earnings research – Felix Ritchie University of West of England and Emma Nelson, Office for National Statistics 15:45 – 16:05 Focus of ONS earnings analysis – Roger Smith, Henry Moore, Samuel Olokesusi, Office for National Statistics 16:05 – 16:15 Question and Answers session
- 22. Economic forum- London Analysis of job changers and stayers Economic Advisor Office for National Statistics Dr Amina Syed 29 April 2019
- 23. Motivation • Looking at the composition and pay growth for job changers is a good way to understand the strength or weakness in the labour market. • The extent of job switching can also signal how well the wage mechanism is working in the labour market or if labour supply is well informed of market conditions. • Pay growth of UK workers changing jobs voluntarily might be expected to be higher than those who stay in their jobs, hence, workers changing jobs also puts upward pressure on wages. • There has been much focus on whether the Phillips Curve has flattened or shifted downwards, reflecting the relatively subdued pickup in wage growth, given the recent record low unemployment. Economic forum- London
- 24. Methodology • The analysis is carried out using the Annual Survey of Hours and Earnings (ASHE) micro dataset. • We match those individuals who were in the ASHE sample in two consecutive years and drop the rest to create a continuously employed ASHE dataset. • We compare the earnings growth between t and t-1 years using the hourly earnings growth variable. • ASHE has a variable “sjd” that identifies people who were in the same job as the year before or not. • Sjd=1: job stayers; those who are in the same job as the previous year. • Sjd=2: job changers; those who are not in the same job as the previous year. • To capture the typical experience of earnings growth, median of hourly earnings growth is calculated. This is the rate of pay growth at the centre of the distribution of earnings growth. Economic forum- London
- 25. Economic forum- London Job stayers earn more compared with job changers Median hourly earnings for job changers and stayers, 2000 to 2018, UK £6.00 £7.00 £8.00 £9.00 £10.00 £11.00 £12.00 £13.00 £14.00 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Stayers Changers
- 26. Economic forum- London Job changers experience higher pay growth compared with job stayers Median growth of hourly earnings for job changers and stayers, 2000 to 2018, UK 0.0 2.0 4.0 6.0 8.0 10.0 12.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Stayers Changers %
- 27. Economic forum- London Upper quartile is the 75th percentile and lower quartile is the 25th percentile. Job changers have a higher variation in pay growth Hourly earnings growth for job changers and stayers, upper and lower quartiles, 2000 to 2018, UK -10.0 -5.0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Lower quartile stayers Upper quartile stayers Lower quartile changers Upper quarttile changers %
- 28. Economic forum- London Between firm job changers experience higher pay growth Median growth of hourly earnings for job changers within and between firms, 2000 to 2018, UK 0.0 2.0 4.0 6.0 8.0 10.0 12.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Between Within %
- 29. Economic forum- London Job changers represent around 10% of the workforce Proportion of job changers and stayers, 2000 to 2018, UK 80.00 82.00 84.00 86.00 88.00 90.00 92.00 94.00 96.00 98.00 100.00 stayers changers %
- 30. Economic forum- London Younger people are more likely to change jobs Proportion of workers in each age bracket changing jobs, 2000 to 2018, UK 0% 5% 10% 15% 20% 25% 30% 35% 16 to 20 years 21 to 24 years 25 to 34 years 35 to 49 years 50 to 64 years 65 years and over
- 31. Economic forum- London Younger workers experience higher pay growth regardless of whether they change jobs or not Median growth of hourly earnings for job stayers, by age group, 2000 to 2018, UK 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 16 to 20 years 21 to 24 years 25 to 34 years 35 to 49 years 50 to 64 years 65 years and over %
- 32. Economic forum- London Younger workers experience higher pay growth regardless of whether they change jobs or not Median growth of hourly earnings for job changers, by age group, 2000 to 2018, UK -5.0 0.0 5.0 10.0 15.0 20.0 25.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 16 to 20 years 21 to 24 years 25 to 34 years 35 to 49 years 50 to 64 years 65 years and over %
- 33. Economic forum- London Male job changer pay growth was more sensitive to the downturn Median growth of hourly earnings for job changers and stayers, by sex, 2000 to 2018, UK 0 2 4 6 8 10 12 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Male stayers Male changers Female stayers Female changers %
- 34. Economic forum- London Full-time job changers experience the highest pay growth Median growth of hourly earnings for job changers and stayers, by contract type, 2000 to 2018, UK 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 % Full-time stayers Full-time changers Part-time stayers Part-time changers
- 35. Economic forum- London Private sector pay growth is quicker to react to economic situations Median growth of hourly earnings for job changers and stayers, public and private sector, 2000 to 2018, UK 0.0 2.0 4.0 6.0 8.0 10.0 12.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 % Private Stayers Private changers Public stayers Public changers
- 36. Economic forum- London Most workers changed jobs within the same region Proportion of job changes within and between regions, from 2017 to 2018, UK 2018 2017 North East North West Yorkshire and the Humber East MidlandsWest Midlands South West East London South East Wales Scotland Northern Ireland North East 82.0 0.7 2.3 0.4 0.3 0.6 0.6 1.0 0.6 0.0 0.7 0.2 North West 2.8 83.8 2.8 2.2 3.2 1.1 1.0 2.1 1.3 4.4 0.7 0.7 Yorkshire and the Humber 3.0 2.4 80.5 5.1 0.7 1.0 1.0 1.9 1.3 0.4 0.9 0.3 East Midlands 1.0 1.4 3.9 74.5 4.8 1.4 2.4 1.8 1.6 1.4 0.9 0.0 West Midlands 1.2 2.4 2.1 5.0 77.4 3.1 1.7 1.7 2.2 2.2 1.2 0.2 South West 1.9 1.5 1.3 1.5 1.9 81.9 1.2 1.6 2.6 3.3 0.6 0.5 East 0.4 1.7 2.4 6.0 2.9 2.1 77.8 4.2 3.3 1.5 0.8 0.9 London 2.3 1.6 1.9 1.2 3.2 2.2 7.3 74.8 8.2 2.1 1.6 0.6 South East 4.3 2.2 1.8 3.1 3.0 5.3 5.4 9.1 76.7 1.8 1.0 0.8 Wales 0.0 0.6 0.1 0.4 1.0 0.9 0.5 0.6 1.0 82.9 0.2 0.2 Scotland 0.8 1.2 0.7 0.4 1.2 0.4 0.9 0.9 1.0 0.0 91.3 0.2 Northern Ireland 0.3 0.5 0.1 0.1 0.4 0.1 0.2 0.2 0.3 0.0 0.0 95.4
- 37. Conclusion • Job stayers on average earn a higher hourly wage compared with those who change jobs. However, workers who switch jobs experience higher pay growth compared with those who do not. • The relatively weak pickup in wage growth in recent years, despite record low unemployment, has been driven by job stayers – who represent most of the sample. • Job changers moving between firms have higher pay growth than those moving within firms. • Full-time job changers experienced higher earnings growth compared with job stayers, while part-time stayers and changers experienced similar growth to each other. • Most job changers switch jobs within the same region. Economic forum- London
- 38. Limitations • There are no weights available for longitudinal ASHE, hence job weights are used. • ASHE methodology is not specifically designed to model earnings growth for employees over time. Economic forum- London
- 39. Find out more For further information please read the Analysis of job changers and stayers paper in the Economic review: April 2019.
- 40. Exploring commuting distance and the gender pay gap Office for National Statistics Vahe Nafilyan 29 April 2019
- 41. Q & A session © Photo by Vicky Gu on Unsplash
- 42. Taking a partnership approach to earnings research Building a Wage and Employment Spine Felix Ritchie, UWE Alex Bryson, UCL John Forth, City University Emma Nelson, ONS Bristol Centre for Economics and Finance ONS Earnings Workshop p 29th April 2019
- 43. Theory
- 44. wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … What explains earnings? wages hours industry location bonuses occupation etc … gender ethnicity nationality age education occupation etc … income support pensions child support disability housing etc … work history
- 45. Data sources - ASHE • Positive: o high quality data o available and linkable back to 1975 (ish) o linkable to firms (in theory) o large pool of expert analysts • Negative: o not longitudinally linked by person or job o few personal characteristics o point-in-time o quality employment only
- 46. Data sources – ONS business data • Positive: o wide range of data o available and linkable back to 1998 o large pool of expert analysts • Negative: o stratified sampling ̶ limited data on small firms ̶ data intermittent except for largest firms
- 47. Data sources - HMRC • Positive: o complete coverage: all workers, all the time o employment and self-employment o employment linkable to firms o available back to 2010ish o small pool of expert analysts • Negative: o few personal characteristics o few employment characteristics o focus on totals rather than rates/hours etc
- 48. Data sources - DWP • Positive: o many personal characteristics o family units linkable o available back to 2010ish o information on hours of work o total personal and family income data o pensions data • Negative: o few employer characteristics o data limited to claimants o few analysts outside DWP
- 49. Data sources – Census 2011 • Positive: o complete coverage o detailed personal characteristics/family structure • Negative: o single point in time o little workplace information o not directly linkable – requires matching o not analysed for these purposes yet
- 50. ASHE NINo IDBR ref ONS business data IDBR ref Census no unique refs DWP data NINo HMRC data NINo UTR Company PAYE VAT ref (=IDBR ref)
- 51. ASHE NINo IDBR ref ONS business data IDBR ref Census no unique refs DWP data NINo HMRC data NINo UTR Company PAYE VAT ref (=IDBR ref)
- 52. Is it worth it? • evaluating major welfare reform • informing public sector pay determination • understanding the dynamics of wage inequality • improving knowledge of individual and household labour supply • pension planning • identifying and tackling wage stagnation • …etc etc…
- 53. Reality
- 54. Likely stages Jul 2019 Dec 2019 Jun 2020 Dec 2020 ASHE data discovery longitudinal linking IDBR linking HESA link Census augment ASHE with personal characteristics DWP/HMRC proof-of-concept spine from fixed data set build analysis datasets Wage & employment spine sustainable devt analyst training develop research partnership
- 55. Need for research partnership • Very large project • Interest and expertise across govt/academia • Significant risks: o not getting data o not being able to use data o not being able to demonstrate long-term value wide stakeholder engagement essential
- 56. Developing research partnership • Govt stakeholder roundtables • ESCoE and other research networks • Structure bid to support auxiliary projects o integration with other Strategic Impact Programmes o publicise via academic networks eg WPEG
- 58. ONS Earnings statistics user event The focus of ONS earnings analysis Head of Earnings Statistics, Labour Market & Households Division Roger Smith 29 April 2019
- 59. We recently changed focus for regular publications, moving to theme based Previously: ASHE publication Employee Earnings Gender Pay Gap Low and High Pay
- 60. Do you have comments about the focus of our publications?
- 61. The main focuses of our publications are gender pay gap, wage inequality/distribution and pay progression Gender pay gap Other pay gaps Wage inequality Low pay Pay progression Returns to job tenure Composition Public/private
- 62. There are numerous ways of looking at pay (e.g. in ASHE tables) Gross Excl. Overtime Overtime Basic Incentive Weekly Hourly Annual All by both median and mean. Real terms versus nominal
- 63. ONS Earnings statistics user event Contributions to Weekly Earnings Growth Economic researchers Economic Advice and Analysis Henry Moore & Samuel Olokesusi 29 April 2019
- 64. In the year leading up to April 2018 median gross weekly earnings growth was 3.5% ONS publication: Employee earnings in the UK: 2018
- 65. Growth in mean weekly earnings at the median rose to 2.6% in the year leading up to April 2018
- 67. Average Weekly earnings growth in the lowest quartile is smoothed through changes in hours & Variable pay
- 69. Males and Females experience very similar contributions to earnings growth.
- 71. Variable pay contributes more to earnings growth in the public sector than the private sector.
- 73. Contributions to earnings growth differ significantly by region
- 75. © Photo by Hermes Rivera on Unsplash The Lower quartile of earnings growth never rises above 0% Year to Year there is no big changes in the contributions to earnings growth Males and Females experience similar contributions to wage growth Public Sector employees experience higher growth of variable pay The biggest differences to contributions are by region. Conclusions
- 76. Find out more Read the Article about Contributions to weekly earnings And the Office for National Statistics Ashe methodology at ASHE QMI
Editor's Notes
- For example, pay growth for job changers is more cyclical and quicker to react to the economic downturn than pay growth for job stayers, who are more closely tied to pay settlements that lag the cycle. More people switching jobs suggests an awareness of the labour market, reducing the likelihood of asymmetric information. When workers changing jobs secure a pay rise, the average overall wage growth increases. Consequently, companies are pressured into paying higher wages to existing staff, as well as the new staff, to encourage them to stay in the job rather than change jobs. There will also be some workers who change jobs involuntarily due to redundancies. This may be because the pay growth or job-to-job flows for job changers has been subdued compared with historical rates. Similarly, pay growth for those staying in the same job has remained subdued – which would need to increase to support a broader rise in labour cost pressures.
- Although median earnings growth is a good summary measure of changing labour market conditions, it masks variation in experiences. As workers move between posts, or experience changes in their pay, the earnings of some individuals will rise in each period, while others will see their earnings fall. To get a more detailed perspective of wage pressure, we also examine the hourly earnings growth at the lower and upper quartiles. Job stayers experience no hourly earnings growth at the lower quartile, and around 10% pay growth at the upper quartile across the series. Job changers, on the other hand, have a much greater variation in pay growth, with pay falling at the lower quartile, and around 25% growth at the upper quartile.
- We construct a within and between firm variable to examine whether job changers can receive higher pay growth by staying in a similar job to the one they were previously in or not. Movement of workers “between” firms is defined as those workers who work in a different location compared with the year before, or have changed the industry they work in, or are in a different occupational category. In this sense, “between firm” is more a proxy for how different a job the workers are in compared with the previous year. “Within firm” will then be all the remaining individuals. Of the job changers, those who moved within their own firm consistently received higher median earnings compared with those who moved between firms. The reverse is true for the growth of earnings; job changers between firms experience higher pay growth than within firm movers. This could be due to firms willing to pay more to acquire staff that have already been trained. Alternatively, it may reflect the higher risk premium workers attach to changing employer or that those who change industry or occupational category are generally doing so to move towards a post that is a better match for their skills. Only when a firm is willing to pay more than the existing firm (other things being similar), is a worker likely to switch between firms. In 2018, around 75.4% of job changers moved between firms, while 24.6% moved within firms.
- In 2018 the proportion of job changers was around 10.9%. The percentage of workers changing jobs was the lowest in 2010, at around 5.7%, following the economic downturn, possibly reflecting a risk-averse attitude of workers following the crisis. The labour market has since become more dynamic, with the proportion of people changing jobs increasing. This coincides with: an unemployment decrease for the 16 years and over age group of 44.7% an employment increase for 16- to 64-year olds of 9.9% workforce jobs increasing by 11.0%
- Data split by age show the starkest difference between changers, with people below the age of 35 years more likely to change jobs. This could be due to a greater proportion of younger workers in part-time, unstable or temporary jobs. From 2017 to 2018, 51.0% of 16- to 20-year-old job changers switched jobs from part-time to another part-time job.
- Earnings typically reflect career progression, with younger workers earning less than the older workers. Hence, younger workers experience higher pay growth regardless of whether they change jobs or not. The uptick in earnings growth in 2016 for younger job stayers (aged less than 25 years), coincides with the introduction of the national living wage. Although the living wage was not applicable to these workers, there is some evidence for upward pressure on their wages. Since 2010, growth in earnings for people aged 35 years and older has been subdued, with those not changing jobs earning a median hourly earnings growth between 0.9% and 3.0%,
- … while those who changed jobs received between 0.0% and 6.5%.
- Earnings growth for men was more sensitive to the 2008 to 2009 economic downturn. This is especially pronounced for the job changers but can also be seen for the job stayers. This may be because more men are in full-time contracts and wage growth for full-time changers was affected by the downturn more. Women and men get similar pay growth if they stay in the same job. But women get lower pay rises than men when they change job. In 2018, both men and women experienced earnings growth below their pre-downturn average. This is especially pronounced for job stayers.
- Full-time job changers had higher median earnings growth than job stayers. Their earnings growth was more strongly affected by the 2008 economic downturn. However, it remained above stayers’ growth. Fewer full-time workers changed jobs during this period. On the other hand, median wage growth for part-time stayers and changers is similar, except for 2016 when the changers experienced stronger growth. This coincides with the introduction of the living wage, which resulted in greater upward pressure on part-time changers’ wage but also some pressure on the part-time stayers’ wage. Before 2016, part-time changers experienced wage growth similar to both part-time and full-time stayers. These workers experienced a protracted slowdown in earnings growth following the economic downturn, with median earnings growth remaining flat for four years after 2010 at about 2.2%. Around 32.0% of workers moved from a full-time job in 2017 to a part-time job in 2018, and their wage decrease will be reflected in the part-time job changers’ earnings growth, which may explain why it is lower than that of full-time changers. Around 17.2% of workers moved from a part-time job to a full-time job in 2018, and their wage increase will be part of the full-time job changers’ earnings growth. Thus, there was a higher proportion of people moving from full-time to part-time in 2018, which if involuntary, reflects an increase in underemployment.
- Private sector job changers were more strongly affected by the 2008 economic downturn than stayers. However, their earnings growth remained above that of the stayers. Since the downturn, private sector changers have more or less recovered their earnings growth. Whereas for the stayers, while the earnings growth has started increasing, it remains below the pre-downturn trend. On the other hand, both public sector changers and stayers experienced a slowing in earnings growth during the downturn, although changers experienced a faster recovery than stayers. Both types of public sector workers are still receiving earnings growth below the pre-downturn trend, which may be a result of the government budget cuts following the economic downturn.
- Consider an individual. Ideally we would want to know: personal characteristics details of their employment other relevant information on benefits, support etc and we’d like to know this over time But we’d also like to know about family relationships – how does a couple or family manage overall income/work/retirement choices? the firms that the employee works for – what sort of business is it, how is it managing in the market, and (if self-employed) how does this compare to earned income/benefits what are the population effects? and again, all of this is needed over time
- By way of introduction, I head up the Earnings branch in ONS’s labour market division, and we publish the monthly Average weekly Earnings estimates and data tables, plus the Annual Survey of Hours and Earnings publications and data on the main publication day in October. I want to talk very briefly about the different measures of pay that are available and we use.
- Firstly, just to flag that the main ASHE publication was revised in 2018. The reason for this was a desire to align what we publish with the interests of and terms used by the broad range of users. Previously the publication was referred to as ASHE, but for gender pay gap for example, going via search engines didn’t lead you to the official GPG figures that were contained in that bulletin. The change, to have three different theme pages, had the effect of increasing number of visits to the publications, attracting more access from mobile devices, and visitors spending more time reading. This was true for the gender pay gap, in particular.
- But beyond publication day, the data is accessed by numerous analysts, and published. You’ve seen examples of publications from analysts in ONS, today. There are varying amounts of consultation around what’s published, but we’re always keen to consult more. So I thought I’d do a quick interjection and raise this question about ONS’s earnings analyses. Do you have any comments about a) the topics that we publish analyses on, and b) the measures of earnings (that is hourly versus weekly etc) that we lead with? We have a few minutes at the end of this session for questions and answers. But in addition, there are feedback sheets to put in any comments or thoughts that you might have.
- When it comes to focus of our broader range of publications based on ASHE, we currently have more emphasis on topics like gender pay gap, wage inequality/distribution, and increasingly pay progression. Does that reflect users’ interests? If not, where is the emphasis out of balance with your interests?
- And secondly, we publish data tables based on numerous dimensions – the dimensions in this chart being for ASHE. But the headline indicators used in publications tend to be more limited, focusing on median, with either growth in the median or for some more detailed analyses median growth. Use of mean pay is restricted pretty much to the AWE monthly estimates. And our approach is typically to lead with single measures – to avoid confusion – but reference others as appropriate. For topics where we’re comparing basic pay conditions we tend to use hourly pay – for example the gender pay gap – and where there’s more of a focus on living standards we use weekly. Vahe’s presentation showed that the different measures can produce different pictures. As I say, marrying up use of single measures to avoid confusion with giving a more complete picture is sometimes a challenge. So, I wanted to raise a question of whether there are instances where there’s a feeling that our focus should be wider? And to help demonstrate the point, we thought we’d finish today with a paper from Henry and Sam at ONS, in which they look beneath the headline measures into various components of pay growth.
- Just for a quick introduction I’m Samuel Olokesusi and I’m joined by my colleague Henry Moore, both economic researchers in the economic advice and analysis division of ONS I think It’s really good to identify the kind of information that can be taken from the different forms of earning statistics that the ONS produces. Where hourly earnings might provide indication of basic earnings growth it can give a narrow view of the labour market as it isn’t effect by hours worked. Therefore using weekly earnings gives us a more indicative view of earnings. Are increased hourly earnings incentivising an increase in hours worked or an increase in worker leisure time We aim to identify the distribution of weekly earnings growth and contributions towards it Our work on contributions to mean growth in weekly earnings breakdowns earnings growth by 3 components Basic pay which is nominal weekly pay excluding bonuses and overtime Variable pay, identified by incentive pay, shift pay, overtime pay and other types variable types of pay all over a week. & hours given by hours worked in a week.
- I thought we’d have this up as im sure you’re all very keen on being reminded of the latest ASHE stat In the year leading up to April 2018 median gross weekly earnings was at £569, 3.5% up from the previous year This stat is taking a look at the gross weekly earnings for the middle earner. The growth rate referred to throughout our work is the mean growth in mean weekly earnings which is distinctly different from the above stat Which leads nicely on to our next figure
- Median growth in average weekly earnings rose to 2.6% in the year leading up to April 2018. It’s highest since pre-downturn levels Although recovery from the downturn has been relatively slow this stat highlights that currently for employees in full-time employment, 50% of their average weekly earnings growth lies above this 2.6% value. A closer look at this distribution of growth would give us the following chart
- Hopefully this provides a clearer image of the figure provided in the previous slide. Here the first, second and third quartiles (inter quartile range) refer to the 25th , 50th and 75th percentiles in the earnings growth distribution. Which I know can be difficult to grasp so to clarify: This is simply the growth rate of earnings at each year not the growth rate of income groups. Earnings growth is at it’s highest since pre-crisis levels for all 3 quartiles of growth. You already know the headline value for the median, so I will discuss the other two instead. The third quartile given by the red /maroon line shows that the top 25% of average earnings growth in the year leading to April 2018 lies above 9.3% for those workers in full time employment. This is up from 8.5%, a notably steeper increase than seen in the previous post crisis-years The lower quartile of average earnings growth has seemingly stagnated just below 0% for this whole period. Earnings growth in 2018 is still up from the previous year although remains negative This graph gives the general picture of growth distribution. Decomposing this allows for further analysis
- The rise after 2017 in the 3rd quartile has been driven primarily by basic pay, where the contributions from variable pay and hours have remained largely unchanged What we cant be sure of is how much these quartiles represent income groups. So The 3rd quartile isn’t higher incomes it is just higher growth and likely will contain people who have low incomes but have had high growth. It is even possible that for those on higher wages, there is a strong income effect. Where as wages rise beyond a certain point, employees are likely to work fewer hours, and retain the same income, substituting income for leisure time. Therefore the first quartile could actually contain plenty of high earners who are using earnings growth to reduce their hours, and increase leisure time with the same earnings. (backwards bending supply) I will now hand over to Henry for the break down of earnings growth by different workers of: Sex, sector and work region
- Use these as headline stories
- We know there are differences in earnings between males and females, however our analysis shows that in terms of contributions for growth they are very similar. There are small differences such as at the median and third quartile of growth, females experience higher basic pay, but the opposite is true for the first quartile. Overall Males are not getting significantly higher contributions from variable pay, namely bonuses and overtime. However, still distinctly more in comparison to females. When we look at the role of hours we can see that there is no significant inequality in the increase or decrease of hours worked by either sex. But this does not display the actually number of hours worked by each sex.
- The most notable finding here is that even though bonuses and overtime pay is associated with the private sector, variable pay actually contributes less to earnings growth. For the Third quartile, we can see that variable pay grew by 2.1% in the public sector but only just over 1% in the private sector. Its is still possible and likely that these nominal rates of variable pay are still higher in the private sector, they just contribute less to earnings growth. At median growth there is a small difference in hours where in the public sector employees are actually working reduced hours The idea that earnings are only starting to rise as employees in the private sector, specifically the gig economy, take on a large amount of hours is not supported here. As on average, hours are not increasing in the private sector at a rate that would support this. Other than this the first quartile and median are very similar across these sectors.
- Regionally here you can see there is much bigger differences than any of the other break downs. (just note that each bar is just the median for each region) For example London, has a basic pay increase of 3.1% and at the same time a reduction of hours at -0.2% and variable pay at -0.1%. As you can see this make up is actually most similar to Northern Ireland and Yorkshire and the Humber. These regions have very different economies and are not geographically close but experience similar contributions to earnings growth. These regions are very different to the West Midlands for example. Here, hours rose by 0.7% Variable Pay by 0.2%,. But Basic Pay growth was over half a Percent lower than that of London, Norther Ireland or Yorkshire.