Economic insecurity is an emerging topic that is increasingly relevant to the labour markets of developed economies. This paper uses data from the British Household Panel Survey to assess the causal effect of various aspects of economic insecurity on mental health in the UK. The results support the idea that economic insecurity is an emerging socioeconomic determinant of mental health, although the size of the effect varies across measures of insecurity. In particular, perceived future risks are more damaging to mental health than realised volatility, insecurity is more damaging for men, and the negative effect of insecurity is constant throughout the income distribution. Importantly, these changes in mental health are experienced without future unemployment necessarily occurring.

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Evidence of significant variation in the perceived utility of treatments across patients highlights the importance of taking individual patient preferences into account to improve AK treatment acceptability and adherence.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This paper studies the effect of the firm-size distribution on the relationship between employment and output. We construct a theoretical model, which predicts that changes in demand for industry output have larger effects on employment in industries characterised by a distribution that is more skewed towards smaller firms. Industry-specific shape parameters of the firm size distributions are estimated using firmlevel data from Germany, Sweden and the UK, and used to augment a relationship between industry-level employment and output. Our empirical results align with the predictions of the theory and confirm that the size distribution of firms is an important determinant of the relationship between changes in output and employment. Terms of use: Documents in EconStor may

Background Addressing poverty through taxation or welfare policies is likely important for public mental health; however, few studies assess poverty’s effects using causal epidemiology. We estimated the effect of poverty on mental health. Methods We used data on working-age adults (25–64 years) from nine waves of the UK Household Longitudinal Survey (2009–19; n = 45 497/observations = 202 207 following multiple imputation). We defined poverty as a household equivalized income <60% median, and the outcome likely common mental disorder (CMD) as a General Health Questionnaire-12 score ≥4. We used double-robust marginal structural modelling with inverse probability of treatment weights to generate absolute and relative effects. Supplementary analyses separated transitions into/out of poverty, and stratified by gender, education, and age. We quantified potential impact through population attributable fractions (PAFs) with bootstrapped standard errors. Results Good balance of confounders was achieved between exposure groups, with 45 830 observations (22.65%) reporting poverty. The absolute effect of poverty on CMD prevalence was 2.15% [%-point change; 95% confidence interval (CI) 1.45, 2.84]; prevalence in those unexposed was 20.59% (95% CI 20.29%, 20.88%), and the odds ratio was 1.17 (95% CI 1.12, 1.24). There was a larger absolute effect for transitions into poverty [2.46% (95% CI 1.56, 3.36)] than transitions out of poverty [–1.49% (95% CI –2.46, –0.53)]. Effects were also slightly larger in women than men [2.34% (95% CI 1.41, 3.26) versus 1.73% (95% CI 0.72, 2.74)]. The PAF for moving into poverty was 6.34% (95% CI 4.23, 8.45). Conclusions PAFs derived from our causal estimates suggest moves into poverty account for just over 6% of the burden of CMD in the UK working-age population, with larger effects in women.