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Author: Germinario, Giuseppe
Resulting in 2 citations.
1. Germinario, Giuseppe
Three Essays on Partial Identification for Applied Health Economics
Ph.D. Dissertation, Department of Economics, Syracuse University, 2022
Cohort(s): NLSY79
Publisher: ProQuest Dissertations & Theses (PQDT)
Keyword(s): Depression (see also CESD); Earnings; Employment; Health, Mental/Psychological; Labor Market Outcomes

Permission to reprint the abstract has not been received from the publisher.

This dissertation consists of three chapters which explore the usefulness of partial identification methods for estimating treatment effects in applied health economics research. Each one applies the methodology to different settings in which establishing causality has traditionally been difficult, and seeks to demonstrate when a bounding approach can--and cannot--aid researchers in learning about causal relationships.

The second chapter aims to understand the relationship between mental health and labor market outcomes. We bound the impact depressive symptom severity has on both the probability of employment and on earnings.

Bibliography Citation
Germinario, Giuseppe. Three Essays on Partial Identification for Applied Health Economics. Ph.D. Dissertation, Department of Economics, Syracuse University, 2022.
2. Germinario, Giuseppe
Amin, Vikesh
Flores, Carlos A.
Flores-Lagunes, Alfonso
What Can We Learn About the Effect of Mental Health on Labor Market Outcomes Under Weak Assumptions? Evidence from the NLSY79
Labour Economics published online (18 September 2022): 102258.
Also: https://www.sciencedirect.com/science/article/pii/S0927537122001488
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Depression (see also CESD); Earnings; Employment; Health, Mental/Psychological; Labor Market Outcomes

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.
Bibliography Citation
Germinario, Giuseppe, Vikesh Amin, Carlos A. Flores and Alfonso Flores-Lagunes. "What Can We Learn About the Effect of Mental Health on Labor Market Outcomes Under Weak Assumptions? Evidence from the NLSY79." Labour Economics published online (18 September 2022): 102258.