Mental Health and Employment: A Bounding Approach Using Panel Data*

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

Oxford Bulletin of Economics and Statistics, 2022, vol. 84, issue 5, 1018-1051

Abstract: The effect of mental health on employment is a key policy question, but reliable causal estimates are elusive. Exploiting panel data and extending recent techniques using selection on observables to provide information on selection along unobservables, we estimate that transitioning into poor mental health leads to a 1.6% point reduction in the probability of employment; approximately 10% of the raw employment gap. Selection into mental health is almost entirely based on time‐invariant characteristics, rendering fixed effects estimates unbiased in this context, meaning researchers no longer have to rely on the narrow local average treatment effects of most health/work IV studies.

Date: 2022
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Citations: View citations in EconPapers (7)

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https://doi.org/10.1111/obes.12489

Related works:
Working Paper: Mental health and employment: a bounding approach using panel data (2020)
Working Paper: Mental health and employment: a bounding approach using panel data (2020)
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