What can we learn about the effect of mental health on labor market outcomes under weak assumptions? Evidence from the NLSY79

Giuseppe Germinario, Vikesh Amin, Carlos A. Flores, Alfonso Flores-Lagunes

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number102258
JournalLabour Economics
Volume79
DOIs
StatePublished - Dec 2022

Keywords

  • Bounds
  • Depression
  • Earnings
  • Employment
  • Mental health
  • Partial identification

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