The Effect of Mental Health on Employment:Accounting for Selection Bias

Mark Bryan (), Jennifer Roberts and Cristina Sechel ()

Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York

Abstract: This paper estimates the influence of mental health on the probability of being in employment for prime age workers in England and Wales. We use longitudinal data and fixed effects models, and employ techniques generalised by Oster (2013, 2017) to estimate an unbiased effect of changes in mental health in the presence of unobserved confounders. Our results suggest that selection into mental health is almost entirely based on time-invariant characteristics, and hence fixed effects estimates are unbiased in this context. Our preferred specifications indicate that transitioning into poor mental health leads to a reduction of 1.4 percentage points in the probability of employment. The relatively small effect is comparable to estimates from studies around the world that use similar methods. However, it is substantially smaller than the typical instrumental variable estimates, which dominate the literature, and often provide very specific estimates of a local average treatment effect based on an arbitrary exogenous shock that is unlikely to be a policy target. These findings should provide some reassurance to practitioners using fixed effects methods to investigate the impacts of health on work. They should also be useful to policy makers as the average effect of mental health on employment for those whose mental health changes is a highly relevant policy parameter.

Keywords: mental health; employment; fixed effects; UKHLS (search for similar items in EconPapers)
JEL-codes: I12 J14 J24 (search for similar items in EconPapers)
Date: 2019-07
New Economics Papers: this item is included in nep-lma
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:yor:hectdg:19/14

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