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

B-Tier
Journal: Oxford Bulletin of Economics and Statistics
Year: 2022
Volume: 84
Issue: 5
Pages: 1018-1051

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:bla:obuest:v:84:y:2022:i:5:p:1018-1051
Journal Field
General
Author Count
4
Added to Database
2026-01-24