Srinivasa Vittal Katikireddi - Short-term impacts of Universal Basic Income on population mental health inequalities in the UK: A microsimulation modelling study

  • Presenting author: Srinivasa Vittal Katikireddi (University of Glasgow)

  • Authors: Rachel M Thomson, Daniel Kopasker, Patryk Bronka, Matteo Richiardi, Vladimir Khodygo, Andrew J Baxter, Erik Igelström, Anna Pearce, Alastair H Leyland, S Vittal Katikireddi

  • Session: A02C - Health [1] - Monday 16:30-18:00 Senate Hall

  • Slides: PDF

Background:

Population mental health has deteriorated in many high-income countries over the last decade. Novel welfare policies such as Universal Basic Income (UBI) have been suggested as potential approaches to improve mental health. However, no studies have trialled or modelled UBI in whole populations or considered impacts on inequalities in mental health. We therefore simulated the effects of introducing a UBI on mental health for UK working-age adults.

Methods:

Working aged adults (25-64 years) were simulated from 2022 to 2026 with SimPaths, a discrete-time dynamic stochastic microsimulation model of individual life course social, economic and health trajectories, which draws on representative panel data from the UK Household Longitudinal Study. Three counterfactual UBI scenarios were modelled from 2023: ‘Partial’ (value equivalent to existing benefits), ‘Full’ (equivalent to the UK Minimum Income Standard, defined by the Joseph Rowntree Foundation as enough money to live off) and ‘Full+’ (as per the Full scenario but additionally retaining some means-tested benefits which address additional needs e.g., arising from disabilities). Likely common mental disorder (CMD) was measured using the General Health Questionnaire (GHQ-12, score ≥4). Simulations were run 1,000 times to generate 95% uncertainty intervals. Sensitivity analyses relaxed SimPaths assumptions about reduced employment resulting from Full/Full+ UBI scenarios. Absolute and relative inequalities in the impacts on mental health by education were quantified using slope and relative indices of inequality.

Results:

Partial UBI had little impact on poverty, employment, or mental health. Full UBI scenarios practically eradicated poverty, but decreased employment. Full+ UBI increased CMD prevalence by 0.38% (percentage points; 0.13-0.69) in 2023, equivalent to 157,951 additional CMD cases (54,036-286,805); effects were largest for men (0.63% [0.31-1.01]) and those with children (0.64% [0.18-1.14]). In our sensitivity analysis assuming minimal UBI-related employment impacts, CMD prevalence instead fell by 0.27% (-0.49, -0.05), a reduction of 112,228 cases (20,783-203,673); effects were largest for women (-0.32% [-0.65, 0.00]), those without children (-0.40 [-0.68, -0.15]), and those with least education ( 0.42% [-0.97, 0.15]). In all scenarios, effects waned by 2026. There were no notable impacts on inequalities in mental health (by education) on either absolute or relative scales.

Discussion:

UBI has potential to improve short-term population mental health by reducing poverty, particularly for women, but impacts are highly dependent on whether individuals choose to remain in employment following its introduction. Dynamic microsimulation has allowed exploration of policy impacts, but also identified key uncertainties that are likely to determine overall mental health impacts.

Funding: Chief Scientist Office; European Research Council; Health Foundation; Medical Research Council; Wellcome Trust.