Accounting for firms in ethnicity wage gaps across the wage distribution
25 August 2023
Authors: Van Phan, Felix Ritchie, Damian Whittard (University of West of England), Carl Singleton (University of Reading), Alex Bryson (University College London and IZA), John Forth (City, University of London and IZA) and Lucy Stokes (National Institute of Economic and Social Research)
Date: May 2022
Researchers used new linked data to examine the role of the employer in accounting for ethnicity wage gaps across the earnings distribution. Where employees work often makes a big difference to ethnicity wage gaps, but the importance of the employer varies across ethnic groups and different parts of the wage distribution.
This research was carried out as part of the Wage and Employment Dynamics project, which is funded by ADR UK. The main purpose of the project was to link data from various official surveys and administrative datasets to provide new insights into the dynamics of earnings and employment in the UK. The project was sponsored by the Low Pay Commission and Government Equalities Office, both of which are members of the government stakeholder group for the project.
The project accessed the Annual Survey of Hours and Earnings (ASHE) linked to 2011 Census dataset through the ONS Secure Research Service. This de-identified dataset links the payroll-based ASHE to the 2011 Census of England and Wales and contains just under 0.5% of the population of employees in England and Wales.
The ASHE is the most comprehensive source of information on the structure and distribution of earnings in the UK. It provides information about the levels, distribution, and make-up of earnings and paid hours worked for employees in all industries and occupations. The 2011 Census, meanwhile, includes an abundance of information on the characteristics of individuals and the households they occupy.
Digital Object Identifier (DOI): Office for National Statistics, released 08 September 2022, ONS SRS Metadata Catalogue, dataset, Annual Survey of Hours and Earnings linked to 2011 Census – England and Wales, https://doi.org/10.57906/80f7-te97
Researchers examined pay differences between ethnic minority groups, along with white employees, based on their main job observed in ASHE. Six broad ethnic minority groups for England and Wales were considered in this study. These correspond to the largest ethnic minority groups recorded by the Census: Indian, Pakistani, Bangladeshi, Chinese, Black African, and Black Caribbean. Due to small sample sizes, employees who reported mixed or other ethnicities on the Census were not included.
The analysis was restricted to employees aged 25 to 64 years old, who were not paid at an apprenticeship rate or incurred any loss of pay in April 2011, and who worked 1-99 hours per week. The analysis excluded overtime and shift premium pay rates, and instead focused on basic hourly wages, due to self-selecting or choosing overtime and shift premium work.
Before undertaking any analysis, the researchers trimmed the top and bottom 0.5 percentiles of the overall basic hourly wage distribution over all employees remaining in the ASHE-Census linked dataset, following the sample selection criteria detailed above.
To account for the role of employers in the wage gaps between ethnic minority and white employees, the analysis sample was restricted to employees for whom at least one other co-worker is observed in the new linked dataset. This enabled the team to identify employer-specific wage effects completely, as compared to any prior research using the household survey. To do so, the researchers estimated regression models for log basic hourly wages and applied a Blinder-Oaxaca style decomposition method: a type of methodology used to study labour market outcomes by groups. The decompositions were carried out for the gaps between the sample mean log wages of ethnic minority and white employees, as well as selected quantiles of the respective estimated wage distributions (10th, 25th, 50th, 75th, and 90th percentiles).
Disparities in wages between ethnicities among employees were found to differ significantly, both on average and across the wage distribution. The extent of these gaps depends on the minority group being compared to white workers. Findings also showed that the workers’ employers were more crucial to understanding these gaps than individual characteristics. In fact, the impact of individual observable characteristics (such as age, education, occupation, and region) in these gaps tended to reduce when accounting for employer-specific wage effects. This is because these are correlated with the average wages paid by employers.
In addition, employer-specific wage effects contributed to ethnicity wage gaps differently across ethnicity minority groups. In particular, Indian and Chinese employees were more likely than white employees to be employed by firms that offer relatively higher wages - even after other worker and job characteristics were taken into account.
Firm-specific wage effects did not tend to contribute to the differences between Pakistani and white employee wage distributions, but they did contribute positively for relatively high-earning Bangladeshi employees. Firm-specific wage effects significantly advantage white employees over Black African employees, but Black Caribbean employees, in general, earned more than white employees (except among high-earners).
After accounting for the employer-specific wages and other worker characteristics, significant unexplained (or residual) penalties remained, for example between some ethnic minority employee and white employee wage distributions.
This research has been presented at the Royal Economics Society, Scottish Economic Society, and the Work, Pensions, and Labour Economics Study Group. It has also been presented at various seminars around the country. The working paper was published as an IZA Institute of Labour Economics discussion paper, and has generated great interest from both the academic and policy communities. The research article is currently under consideration with the Journal of Human Resources.
Tim Butcher, Chief Economist at the Low Pay Commission, said of the research: “This project addresses weaknesses in our evidence base – improving the quality of longitudinal earnings data and extending coverage to a broader range of characteristics – that should enable researchers to give new and innovative insights into the wage and employment dynamics of the lowest paid.”
Publications and reports
- IZA Institute of Labor Economics discussion paper, May 2022: Accounting for Firms in Ethnicity Wage Gaps throughout the Earnings Distribution
Blogs, news posts, and videos
- Wage Dynamics blog, September 2022: ASHE – 2011 Census: New linked dataset available to provide insights into earnings and employment in Britain
- Wage Dynamics blog, November 2021: New Linked Payroll-Census Data Reveal Large Ethnic Wage Gaps
Presentations and awards
- Royal Economic Society, April 2022
- Scottish Economic Society, April 2022
- Work, Pensions and Labour Economics Study Group, July 2022
- European Association of Labour Economists, September 2022
- Nottingham University Business School, May 2023
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