Work, Welfare and Mental Health: a longitudinal analysis of trends in working conditions, welfare provision and inequalities in mental health

Work intensity in the UK is much higher than other European countries such as France and Germany but productivity is approximately 20% lower and has barely improved over the last decade. Compared to their European counterparts, UK companies have underinvested in new technologies meaning that workers need to work harder and faster to make up for it [1]. This can put significant strain on workers impacting on their mental health. Mental health problems at work cost approximately £1300 per year for every worker in the UK. The cost of putting people under stress and strain at work has spillover effects to people's homes, health and families. In the extreme, people with poor mental health may no longer be able to work. In 2016, over 50% of people claiming incapacity-related benefits reported poor mental health (anxiety, depression, stress or anxiety) as their main health condition compared to only 33% of claimants in 2000. There are also significant geographical, socio-economic and gender inequalities in work-related mental health conditions.
The aim of this PhD project is to use advanced longitudinal quantitative methods and secondary data sources to better understand how working conditions, the welfare system, social position, and geography impact on mental health. Understanding this will help contribute to the development of health and well-being policy at work and mental health friendly welfare policy.
Specifically, this PhD dissertation will focus on the following research questions:
1) How does job type, working hours, length of time in the job, job tenure, and commuting time impact on mental health?
2) Are their inequalities in the mental health effects of (1) by age, gender, educational attainment, or geography?
3) Have (1) and (2) been changing over time particularly in relation to recession and austerity?
4) Does the changing nature of welfare provision have any impact on the relationship between working conditions and mental health?
To address these research questions, a number of UK datasets will be used. The main dataset used to obtain information on individuals would come from the British Household Panel Survey and Understanding Society Survey covering the period 1991-2016 to look at the evolution of the relationship between mental health and work over time. Additional data from NOMIS on welfare benefits payments and neighbourhood characteristics will be appended to this data. In addition, we will also utilise data from UK Crime Statistics to capture neighbourhood factors that are likely to impact on mental health.
The analysis will employ a number of econometric techniques for panel data. The PhD student will gain familiarity with applying standard estimation techniques such as randomised generalised least squares and fixed effects models. In addition, she will apply more novel methods for identifying pathways using seemingly unrelated regressions and decomposing the variance/covariance matrix of the correlation coefficient. Causal models will also be estimated to identify the relationship between the welfare state and mental health. Overall, this project will provide the student with the necessary skills to pursue a career in quantitative social sciences developing capacity in an area which currently has a skills shortage.