Unpacking how hiring discrimination affects UK workers’ skills

This blog by Kathyrn Fair, an ADR UK Research Fellow and Senior Research Fellow at The Alan Turing Institute, discusses her project on the relationship between hiring discrimination and the skills landscape in the UK. It highlights how systemic biases in hiring practices not only affect individual workers but also have far-reaching consequences for industries and the broader economy.

The UK is facing numerous challenges that touch on the world of work – trying to increase economic productivity, adapting to emerging technologies such as artificial intelligence (AI), and combatting climate change. Rising to these challenges is dependent on UK workers having the right skills to work in ‘green’ jobs, leverage AI, and increase the productivity of UK industries.

One factor impacting the UK’s skills landscape is hiring discrimination, where an individual’s personal characteristics (e.g. their gender or ethnicity) are – consciously or unconsciously – factored into a hiring decision. This shapes the skills developed by individuals who experience discrimination, particularly if they are denied opportunities to learn skills that could open paths to further career development. These individuals could miss out on important job opportunities, resulting in lower earnings and worsened career outcomes.

Hiring discrimination also poses problems for UK industries. If individuals are not able to develop suitable skills, employers will not have access to appropriately skilled workers, and productivity will suffer.

There is large amount of research around how structural inequalities – those embedded in the fabric of our institutions and governments - impact earnings (e.g. gender wage gaps). However, the way structural inequalities influence workers’ skills is not well understood. This creates difficulties for policymakers: programmes to develop workers’ skills may be ineffective, or have unintended consequences, if they do not account for the impacts of these inequalities.

Modelling discrimination’s impact on career trajectories

I have developed a model that simulates the movement of workers through the UK economy. These workers search for and apply to new jobs, and we can track them over the course of their careers.

During their careers, workers tend to become better at skills they use in their jobs, while becoming worse at skills they do not need. Workers have characteristics, such as gender and ethnicity, that may be the basis for hiring discrimination. Thus, I’m able to simulate different scenarios to see what outcomes look like for workers when they do (or do not) experience discrimination at the point of hiring.

This allows me to ask questions like whether workers develop different skills because their career paths were impacted by discrimination? Or how their careers could have developed if they hadn’t experienced discrimination – could they have earned more money for example?

This model will use de-identified data from the Annual Survey of Hours and Earnings linked to Census 2011 dataset, a novel dataset developed by the Wage and Employment Dynamics team, and funded by ADR UK.

Understanding the large-scale impact

My project will be the first to examine the impact of hiring biases on the skillset of workers at a large scale. This has not previously been possible, due to the limitations of conventional methods for assessing the impacts of hiring biases, as well as data availability issues.

Guiding policy discussions with the evidence

My research will guide discussions on how to address the impacts of hiring biases.  It will shape the construction of policy interventions aimed at developing workers’ skills, in service of improving outcomes for both workers and the economy.

The model I develop will also provide a tool for government and voluntary and community sector, and I am particularly excited to work with these stakeholders. Delivering policymakers these insights and tools, so that they can develop data-driven policy, is especially important in current times when governments are facing strong pressures to transform labour markets.

Find out more about Kathyrn’s project.