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Information on both earnings and non-pecuniary rewards is needed to understand the occupational dispersion of wellbeing. We analyse subjective wellbeing in a large UK sample to construct a measure of "full earnings", the sum of earnings and the value of non-pecuniary rewards, in 90 different occupations. Labour-market inequality is underestimated: the dispersion of full earnings is one-third larger than the dispersion of earnings. Equally, the gender and ethnic gaps in the labour market are larger than those in earnings alone, and the full returns to education on the labour market are underestimated. These results are similar in data on US workers. In neither cross-section nor panel data do we find evidence of compensating differentials.

Which occupations are best for wellbeing? There is a large literature on earnings differentials, but less attention has been paid to occupational differences in non-pecuniary rewards. However, information on both types of rewards is needed to understand the dispersion of wellbeing across occupations. We analyse subjective wellbeing in a large representative sample of UK workers to construct a measure of “full earnings”, the sum of earnings and the value of non-pecuniary rewards, in 90 different occupations. We first find that the dispersion of earnings underestimates the extent of inequality in the labour market: the dispersion of full earnings is one-third larger than the dispersion of earnings. Equally, the gender and ethnic gaps in the labour market are larger than data on earnings alone would suggest, and the true returns to completed secondary education (though not to a degree) are underestimated by earnings differences on their own. Finally, we show that our main results are similar, and stronger, for a representative sample of US workers.

In choosing when to end the lockdown, policy-makers have to balance the impact of the decision upon incomes, unemployment, mental health, public confidence and many other factors, as well as (of course) upon the number of deaths from COVID-19. To facilitate the decision it is helpful to forecast each factor using a single metric. We use as our metric the number of Wellbeing-Years resulting from each date of ending the lockdown. This new metric makes it possible to compare the impact of each factor in a way that is relevant to all public policy decisions.

Although correlates of mental wellbeing have been extensively studied, relatively little is known about how to effectively raise mental wellbeing in local communities by means of intervention. We conduct a randomised controlled trial of the "Exploring What Matters" course, a scalable social-psychological intervention aimed at raising general adult population mental wellbeing and pro-sociality. The manualised course is run by non-expert volunteers in their local communities and to date has been conducted in more than 26 countries around the world. We find that it has strong, positive causal effects on participants' selfreported subjective wellbeing (life satisfaction increases by about 63% of a standard deviation) and prosociality (social trust increases by about 53% of a standard deviation) while reducing measures of mental ill health (PHQ-9 and GAD-7 decrease by about 50% and 42% of a standard deviation, respectively). Impacts seem to be sustained two months post-treatment. We complement self-reported outcomes with biomarkers collected through saliva samples, including cortisol and a range of cytokines involved in inflammatory response. These move consistently into the hypothesised direction but are noisy and do not reach statistical significance at conventional levels