Home > Research > Publications & Outputs > Measuring the health impact of Universal Basic ...

Electronic data

  • Main_Document_E_P_Revised_Tracked_Final_Clean

    Rights statement: 12m

    Accepted author manuscript, 235 KB, PDF document

    Embargo ends: 1/01/50

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Text available via DOI:

View graph of relations

Measuring the health impact of Universal Basic Income as an upstream intervention: Holistic trial design that captures stress reduction is essential

Research output: Contribution to journalJournal article

Forthcoming
Close
<mark>Journal publication date</mark>4/02/2020
<mark>Journal</mark>Evidence and Policy : A Journal of Research Debate and Practice
Publication statusAccepted/In press
Original languageEnglish

Abstract

In the context of the UK Government’s ‘prevention agenda’, Laura Webber and colleagues have called for a ‘health in all policies’ approach. Universal Basic Income (UBI) is a system of cash transfers to citizens and recent research suggests it may have a significant impact on health, including via an underexplored role in reduced stress. However, debate has been influenced by a recent Finnish trial of a policy with similarities to UBI. This was reported as a failure due to a policy objective of reducing unemployment, despite demonstrating significant benefits to wellbeing. In this article, we advance this debate by exploring the current evidence and proposing a practical way forward. We propose a need to refocus evidence collection in UBI trials on improved health – via reduced stress – to provide policymakers with the means of producing an accurate cost-benefit analysis. We argue that previous trials have either not reflected likely UBI policy or have not measured a sufficient range of impacts to enable accurate analysis of its cost-benefit. We contend that interdisciplinary work is needed in order to establish trials that observe key factors driving the social health gradient. Finally, we argue that statistical modelling is needed to extrapolate short-term findings to long-term population-level outcomes. One implication is that substantial allocation of resource is required from Government and/or major research funders. On the other hand, this presents an opportunity to pioneer an interdisciplinary approach resulting in joined-up evidence and policy for UBI and ‘upstream’ interventions.