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Introduced in the United Kingdom in 2012, Universal Credit (UC) is a welfare benefit that replaces six working-age 'legacy' benefits for out-of-work and low-income people. Designed with the aim of simplifying benefits and incentivising paid work, UC represents a deepening of conditionality in the British welfare state. Considering these developments, this paper quantitatively investigates the effect of UC on recipients' life satisfaction. Data from the United Kingdom Household Longitudinal Study is analysed, primarily using a fixed-effects regression approach. Results reveal a significantly negative effect of UC recipience on life satisfaction. Robustness checks and alternative model specifications, including difference-in-differences and inverse probability weighting, confirm this finding. Additionally, mediation models give credence to the idea that UC also negatively affects life satisfaction indirectly by increasing psychological distress. Heterogeneity tests indicate that UC has a less negative effect on single parents' life satisfaction compared to non-parents. Meanwhile, UC has a significantly more negative effect on the life satisfaction of people not in paid work (for reasons other than unemployment) than those in paid work. Discussion focuses on the potential effect of welfare conditionality specifically, and implications for future research and policy are explored. [ABSTRACT FROM AUTHOR]

Scoring rules measure the deviation between a forecast, which assigns degrees of confidence to various events, and reality. Strictly proper scoring rules have the property that for any forecast, the mathematical expectation of the score of a forecast p by the lights of p is strictly better than the mathematical expectation of any other forecast q by the lights of p. Forecasts need not satisfy the axioms of the probability calculus, but Predd et al. [9] have shown that given a finite sample space and any strictly proper additive and continuous scoring rule, the score for any forecast that does not satisfy the axioms of probability is strictly dominated by the score for some probabilistically consistent forecast. Recently, this result has been extended to non-additive continuous scoring rules. In this paper, a condition weaker than continuity is given that suffices for the result, and the condition is proved to be optimal. [ABSTRACT FROM AUTHOR]