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Does psychological distress moderate earning trajectories? Evidence from longitudinal data in the UK

What are we trying to do?

  • Examine whether mental health problems affect wages, including changes in wages over time.
  • Explore whether the effects depend on people’s characteristics e.g., gender and age.



Why is this important?

Evidence suggests that poor mental health can negatively affect economic outcomes, but studies exploring this relationship tend to focus on employment as the only economic outcome of interest. While this is insightful, it is also restrictive. It fails to consider the effect of mental health on working adults, many of whom may not be realising their economic potential. This could be due to, for example, mental health problems preventing them from completing the kinds of emotionally intensive tasks required for higher-paying jobs.


Studies exploring the relationship between mental health and economic outcomes also rarely consider how mental health problems can compound over time. For example, individuals may experience a self-reinforcing cycle of poor mental health, which causes, and is caused by, an inability to earn more. To help people maximise their economic potential, it’s important that mental health interventions take this into account.


Because of the gaps in the available evidence, we have are examining the relationship between mental health and economic outcomes using changes in wages over time. This measure will provide some indication of the financial wellbeing of employed individuals and can capture the compounding impact of mental health.



How are we doing it?

To examine how mental health affects wages and changes in wages over time, we are using data on 27,505 employed people from the UK Household Longitudinal study (collected from 2009-2020).


This study repeatedly collects information on all aspects of people’s lives over time. In particular, we use information on their wellbeing and hourly wage. We use changes in wellbeing over time to model the effect of mental health on wage growth.


We perform this modelling according to people’s gender, age, and the type of household they live in to see whether the effect is more intense for certain groups of people.



More information



Senior Programme Lead

Mike Spence

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