Case Study F: The Disability Expert
Ben Baumberg Geiger is a professor in Social Science and Health in the Department of Global Health and Social Medicine at King's College London and a research associate at the Resolution Foundation. His research focuses on issues at the intersection of employment dynamics, welfare policy, and disability.
One area of interest to Ben is the disability employment gap, which is conventionally measured as the percentage-point difference in employment rates between disabled and non-disabled people. Conceptually, this gap is relevant to understanding how far disabled people are systematically disadvantaged in the labour market relative to the rest of the country. It is therefore understandable that various governments have wanted to use this as a simple, headline indicator around disability and employment.
Unfortunately, as Ben has argued in an OECD working paper, the conventional disability employment gap is of limited value for policymakers. This is because it is based on data that measure disability by asking one or two questions about whether individuals are limited in the activities that they usually do, and this will change over time. Ben notes that “conventional disability measures are affected by how inclusive society is—so they cannot be then used to measure if society is more inclusive.”
This means that the typical measures of who is disabled—and consequently our calculations of the disability employment gap—may produce results that cannot be interpreted meaningfully for many policy questions. For instance, a policy designed to support disabled people into work may successful reduce barriers, reducing the number of people reporting an activity-limiting disability. The people that still report a disability are therefore likely to have greater barriers to work and have a lower employment rate. It is therefore possible that this successful policy will produce a higher disability employment gap as conventionally measured, substantially misleading policymakers.
To help address some of these issues, Ben’s work makes use of a “prevalence-adjusted” disability employment gap, which multiplies the conventional gap by the rate of disability prevalence within the population. One result of using this adjusted measure is that the gap’s trend over the last 15 years looks considerably different: rather than showing gradual shrinking of the gap, we roughly see stagnation after 2010 followed by an increase since the pandemic. Additionally, the UK goes from an average performer compared to its international peers to a poor one.*
However, the use of a prevalence-adjusted measure does not fully compensate for the underlying issue around our inability to precisely identify the disabled population—the true trend is likely to be bounded by the picture shown by the prevalence-adjusted measure and the conventional measure, but we want to know exactly what the true picture is. Researchers and policymakers are therefore in need of a more stable, trustworthy way of identifying disabilities.
The main challenge to getting better measures is that it is likely to be resource-intensive. More robust measures require questions about all of the impairments that potentially influence people’s capacity for work and ability to participate in society. Ben suggests that the most cost-effective way of collecting this data would be to do a periodic calibration of the conventional measure against the more robust measures, perhaps every 3-4 years. He suggests two ways of doing this:
- A new module in the Health Survey for England to look at trends.
- A follow-up survey of disabled people in the Family Resources Survey to look at the link with poverty.
However, any solution at the scale of these proposals will require investment and political will for action.
Nevertheless, the benefits of identifying disability in a better way are not limited to making the disability employment gap more accurate and useful. For example, it could facilitate improvements in accurately measuring poverty among disabled people; and more broadly it could help track trends in health and disability, particularly in the context of societal debates about deteriorating health and medicalisation. Currently, there are no data tracking trends in ill-health among the working-age population in a trustworthy way.
Noting the resources necessary for implementing any solution (and the wider challenges noted at our workshops), government departments will need to be proactively involved in driving progress in this space. In partnership with the diverse user groups that rely on disability data, departments should take a central role in developing plans for addressing the gap in our understanding of disability, especially because the salience of this topic is likely to increase in the coming years.
*For further detail, see Figures 3 and 4 in Ben’s recent work for the Resolution Foundation.