Taking a wellbeing-years approach to policy choice

Every day, policy makers have to decide whether a policy is desirable. They do so by examining its impact on a whole range of outcomes. But the problem is how to aggregate these disparate outcomes. For example, as covid-19 cases rise sharply again, some lockdown measures are gradually being re-introduced across the UK. These policy choices will lead to outcomes which are good (fewer covid-19 deaths, less commuting, better air quality, etc.) and some which are bad (unemployment, income losses, loneliness, domestic abuse, etc.). How can policy-makers aggregate these disparate effects in order to arrive at some overall assessment? To do so requires a “common currency” in which to measure all the effects. The currency we propose is the change in years of human wellbeing resulting from the policy. 

At present, the most commonly used currency is money. This is the method used in traditional cost-benefit analysis. Each of the various outcomes is valued by the amount of money which those affected would be willing to pay in order to produce that outcome. However, for many of the most important outcomes, including health and unemployment, it is difficult to estimate such a “willingness-to-pay.” 

By contrast, measuring the effect of a policy on human wellbeing could provide a promising approach to inform public policy priorities, as outlined in a recent article in The BMJ by Cylus and Smith. [1] Here we propose a way to assess policy options in terms of their net effect on years of human wellbeing, or wellbeing-years (WELLBYs). 

By wellbeing we mean how people feel about their lives—“subjective wellbeing.” The most commonly used measure of this is life satisfaction. People are asked “Overall, how satisfied are you with your life these days?” on a scale of 0-10 (0 = ‘not at all satisfied,’ 10 = ‘extremely satisfied’). Such a measure is well-correlated with biomarkers and third-party reports, and it has strong predictive powers—it is, for example, one of the best predictors of life-expectancy. [2] It is also reliable—people give consistent answers when retested. [3]

Over the past 30 years we have learned much in quantitative terms about how different outcomes affect wellbeing. This enables us to translate impacts on each outcome into impacts on a single over-arching outcome—wellbeing. For example, a 10% change in income alters wellbeing by around 0.02 points (on the 0-10 scale). When a person becomes unemployed, their wellbeing drops by 0.7 points. A person diagnosed with depression and anxiety has, on average, 0.7 points lower life-satisfaction. [4] There are now tables of coefficients that analysts can use for looking at the wellbeing effects of a whole range of outcomes. [5] And of course, since every outcome has a time dimension, the wellbeing outcome has to be measured in terms of the change in wellbeing x its duration—in other words, the change in wellbeing-years (or WELLBYs). 

There then remains the issue of how to combine changes in the wellbeing of those who are alive with changes in the length of life. The average life-satisfaction in the British population is approximately 7.5 on the 0-10 scale. [6] So if an average person dies one year earlier, the loss of WELLBYs is 7.5. If that person dies 10 years earlier than otherwise, the loss is 75 WELLBYs. 

Any healthcare professional will immediately recognise the similarities between the concept of WELLBYs and the concepts of Quality-Adjusted Life-Years (QALYs) and Disability-Adjusted Life-Years (DALYs). There are, however, substantial differences. In QALYs and DALYs the only outcomes which are counted are changes in the patients’ health or in the length of life of the person affected by disease. In WELLBYs we include effects of every kind and look at them throughout the population. 

When the covid-19 lockdown was first introduced on 23 March 2020, we applied the wellbeing-years approach described here to analyse when and how to gradually release it. We consulted widely with economists and epidemiologists over the likely benefits of gradually releasing the lockdown (more income, less unemployment, better mental health, more trust in government, and more schooling) and the costs (more deaths from covid-19, more road deaths, more commuting, more emissions, and worse air quality). We then applied a valuation to each outcome, based on the wellbeing research literature, in order to suggest an optimal timing for releasing lockdown measures. The results and assumptions of this case study are detailed in a paper and can be applied once again as a likely second wave of covid-19 cases demands further policy action.[7] 

We believe the wellbeing-years approach provides a framework for any policy choice. One opportunity is the upcoming Spending Review in the UK. For public expenditure, one has to start with the assumption that the total of public expenditure is a prior political decision. The issue then is how to spend the money in order to maximise the wellbeing of the population (possibly by giving special weight to those who score lowest on the wellbeing score). In other words, policies should be evaluated by their WELLBYs per pound of expenditure. 

As a report by the All Party Parliamentary Group (APPG) on Wellbeing Economics has argued, the wellbeing benefits per pound of expenditure would generally be much higher in re-building our social infrastructure than our physical infrastructure.[8] Areas where wellbeing benefits would result include mental health, wellbeing in schools, further education, and social care of the disabled and the elderly. More generally, applying a wellbeing lens to policy-making helps societies move “beyond GDP” in terms of measuring and achieving progress on what ultimately matters most to most people. Societies that have started applying this more holistic framework to policy-making, such as New Zealand that now explicitly focusses its annual budget on improving wellbeing, are well-placed to navigate public health crises such as covid-19 that cut across all areas of government.  

See also:

Jan-Emmanuel De Neve, Saïd Business School, University of Oxford and Wellbeing Research Centre, University of Oxford.

Andrew E. Clark, Centre for Economic Performance (CEP), London School of Economics and Paris School of Economics.

Christian Krekel, Centre for Economic Performance (CEP), London School of Economics and Department of Psychological and Behavioural Science, London School of Economics.

Richard Layard, Centre for Economic Performance (CEP), London School of Economics.

Gus O’Donnell, Centre for Economic Performance (CEP), London School of Economics and Frontier Economics.

Competing interests: None declared.


  1. Cylus J, and Smith P. The economy of wellbeing: What is it and what are the implications for health? BMJ 2020;369:m1874. doi: 10.1136/bmj.m1874
  2. De Neve J-E, Diener E, Tay L, Xuereb C. The objective benefits of subjective well-being. In: Helliwell J, Layard R, Sachs J, editors. World Happiness Report 2013. New York: Columbia Earth Institute; 2013. p. 58-89.
  3. Krueger A, Schkade D. The reliability of subjective well-being measures. Journal of Public Economics. 2008;92(8-9):1833-45.
  4. Clark A, Flèche S, Layard R, Powdthavee N, and Ward G. The origins of happiness: The science of wellbeing over the life course: Princeton University Press; 2018.
  5. Frijters P, Clark A, Krekel C, and Layard, R. A happy choice: Wellbeing as the goal of government. Behavioural Public Policy, 1-40, 2020. 
  6. Office for National Statistics. Personal well-being in the UK; 2019. 
  7. Layard R, Clark A, De Neve J-E, Krekel C, Fancourt D, Hey N, and O’Donnell G. When to release the lockdown? A wellbeing framework for analysing costs and benefits. 2020. Centre for Economic Performance, Occasional Paper No. 49. http://cep.lse.ac.uk/pubs/download/occasional/op049.pdf
  8. Wellbeing Economics APPG. A Spending Review to Increase Wellbeing: an open letter to the Chancellor. London, UK: UK Parliament; 2019.