Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Understanding the gender pay gap within the UK public sector

Kaya, Ezgi and Jones, Melanie 2019. Understanding the gender pay gap within the UK public sector. [Project Report]. Office of Manpower Economics.

[img]
Preview
PDF - Accepted Post-Print Version
Download (3MB) | Preview

Abstract

By applying established regression and decomposition methods to secondary data from the 2018 Annual Survey of Hours and Earnings (ASHE) and the 2016-2018 Quarterly Labour Force Survey (QLFS) this report aims to enhance our understanding of the drivers of the contemporary gender pay gap (GPG) within the UK public sector. This is done in several stages, including through comparisons between the public and private sector, and within the public sector on the basis of occupations covered by Pay Review Bodies (PRBs). In both cases we consider GPGs at the mean and then across the earnings distribution. Throughout our analysis we separate the raw hourly GPG into two elements to better understand its drivers. The first element is that part of the raw gap which can be explained by differences in observable personal and work-related characteristics between men and women, such as job tenure or contract type. The second element is that part of the raw gap which is not explained by the observable characteristics in our model and is closer to a measure of unequal treatment on the basis of similar characteristics. Evidence of the latter, or what we refer to as an unexplained GPG, is of particular interest given the remit of PRBs in relation to anti-discrimination legislation under the Equality Act (2010). Confirming previous evidence, our analysis of ASHE confirms that the raw GPG in the UK in 2018 is narrower within the public (19 per cent) than the private (21 per cent) sector. However, and in contrast to earlier studies, the unexplained component estimated using the Oaxaca–Blinder decomposition method is found to be at least as large within the public sector as the private sector. This questions the extent to which, as has previously been claimed, the public sector remains a ‘beacon of good practice’ in terms of gender equality and suggests renewed emphasis might be required. Further exploration of the GPG across the distribution highlights a prominent ‘glass ceiling’ in the public, but not in the private sector. That is, the unexplained GPG is particularly pronounced towards the top end of the wage distribution in the public sector, where it accounts for most of the GPG. This suggests that, despite evidence of a compressed wage distribution, public sector employers need to pay particular attention to gender inequality among higher earners. Comparisons within the public sector indicate that, on average, there is a narrower GPG in occupations covered by the five PRBs considered here, than those occupations that are not covered by PRBs. However, the GPG in PRB occupations is largely unexplained. As a result, the unexplained GPG is actually at least as large in PRB occupations as in non-PRB occupations, despite the remit of the PRBs. This reinforces the important distinction between the GPG as a measure of the average wage gap and the adjusted or unexplained GPG as a measure of earnings inequality. Analysis across the wage distribution also indicates a pronounced ‘glass ceiling’ in PRB occupations, confirming the need for attention beyond the mean GPG, and particularly towards the top end of the earnings distribution, within PRBs. There is, however, considerable heterogeneity identified across the five PRB occupations analysed, consistent with the increasing emphasis on within occupation analysis of the GPG and highlighting the need for greater recognition and exploration of differences within the public sector. The largest raw GPG is within the Review Body on Doctors’ and Dentists’ Remuneration (DDRB) (20 per cent) and it is narrowest in the NHS Pay Review Body (NHSPRB) (5 per cent) and Police Remuneration Review Body (PRRB) (8 per cent). The extent to which these can be explained by gender differences in productivity-related characteristics is relatively small and, as such, an unexplained GPG exists across all of the PRBs. The magnitude of the unexplained GPG continues to vary across PRBs and is largest within the DDRB (15 per cent) suggesting the current review of the GPG in medicine is particularly timely. Although the analysis highlights substantial and largely unexplained gender differences in workforce composition across PRBs, including in the NHSPRB which is predominately female (nearly 80 per cent) and the PSPRB and PRRB which are predominately male (about 65-70 per cent), the contribution of gender differences in the allocation of women into and across PRBs within the public sector is found to play a relatively minor role in determining the public sector GPG. Indeed, while the raw public sector GPG would be 15 per cent if there was no gender difference in the probability of working across PRBs, it would only be 4 per cent if there were no GPGs within public sector occupations. Although Performance Related Pay (PRP) is much less prevalent in the public than the private sector and, within PRBs in particular, there is evidence of an unexplained gender gap in the probability of receipt of PRP, with females less likely to receive PRP, particularly in the public sector. Conditional on receipt of PRP, there is also a gender gap in the amount of PRP, but this is considerably larger within the private sector. On this basis, future plans to introduce PRP in the public sector should pay particular attention to the potential drivers of the observed gender gap in receipt of PRP, that is, who receives PRP. The availability of reliable information on pay, and personal and work-related characteristics in our data is key to separating the explained and unexplained components of the GPG. Nevertheless, despite the comprehensiveness of the approach which combines analysis of ASHE and the QLFS, there will inevitably be important productivity-related characteristics which are unobserved (e.g. personality) or only partially captured within our analysis (e.g. actual labour market experience). As such, the unexplained gap can only ever be a proxy for wage inequality, and we cannot directly measure unequal pay or discrimination within this analysis. We further condition on the observable characteristics of workers in different sectors and occupations without accounting for the complex selection processes that determine who is in work and where they work, and the role of the employer, through for example occupational barriers, in such outcomes. More detailed analysis of gender differences in the probability of working across PRBs, which takes into account the complex relationships with subject choice and parental occupation, may be useful in this regard. The use of large scale, nationally representative, secondary data permits analysis across the public and private sector and facilitates comparison across PRBs. Nevertheless, to enhance the depth of analysis within specific PRB occupations it should be supplemented by further examination of specific occupations, including those within PRBs not covered by this report. This would be best achieved by using organisational administrative payroll data and a census of workers, rather than the relatively small samples available within these specific occupations in broader surveys. This would also facilitate a more detailed understanding of the role of the nature of pay scales and pay awards to gender pay equality, aligned to recent requirements in terms of reporting organisational GPGs.

Item Type: Monograph (Project Report)
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > HB Economic Theory
Publisher: Office of Manpower Economics
Related URLs:
Date of First Compliant Deposit: 19 November 2019
Last Modified: 21 Nov 2019 15:28
URI: http://orca.cf.ac.uk/id/eprint/126851

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics