 What can we learn about the effect of mental health on labor market outcomes under weak assumptions? Evidence from the NLSY79Giuseppe Germinario, Vikesh Amin, Carlos A. Flores and Alfonso Flores-Lagunes () Labour Economics, 2022, vol. 79, issue C Abstract: We employ a nonparametric partial identification approach to bound the causal effect of poor mental health on employment and earnings using the National Longitudinal Study of Youth 1979. Our approach allows us to provide bounds on the population average treatment effect based on relatively weak, credible assumptions. We find that being categorized as depressed decreases employment by 10% and earnings by 27% at most, but we cannot statistically rule out a zero effect. We also provide insights into the heterogeneity of the effects on labor market outcomes at different levels of adverse mental health experienced (no, little, mild, moderate, and severe depressive symptoms). We find that going from having no (little) to severe depressive symptoms reduces employment by 3–18% (3–16%) and earnings by 11–44% (12–36%). The estimated bounds statistically rule out null effects for earnings but not for employment. Keywords: Depression; Mental health; Employment; Earnings; Partial identification; Bounds (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:labeco:v:79:y:2022:i:c:s0927537122001488 DOI: 10.1016/j.labeco.2022.102258 Access Statistics for this article Labour Economics is currently edited by A. Ichino More articles in Labour Economics from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.