Date on Honors Thesis

Spring 4-23-2025

Major

Economics

Minor

Political Science

Examining Committee Member

Ayesha Jamal, Phd, Advisor

Examining Committee Member

Brittany Wood, Phd, Committee Member

Examining Committee Member

Beau Sauley, Phd, Committee Member

Examining Committee Member

Jessica Naber, Phd, Committee Member

Abstract/Description

This study examines how macroeconomic indicators influence state‐level suicide rates in the United States and, critically, how those effects differ by gender. Drawing on annual data from all fifty states over 2010–2020, I merge age‐adjusted suicide rates from CDC WONDER with five key economic indicator: real hourly compensation, labor productivity, employment rate, median income, and logged state GD, from the Bureau of Labor Statistics, Census Bureau, and the Bureau of Economic Analysis. After comparing pooled OLS, random‐effects, first‐difference, and two‐way fixed‐effects specifications, I adopt a two-way, state‐and‐year fixed‐effects model for its superior fit and capacity to control for unobserved heterogeneity. In the general population, higher GDP and productivity are associated with significantly lower suicide rates. Separating the model by gender reveals that men’s suicide rates respond to GDP shocks approximately five times and to productivity shocks about three times more strongly than women’s. Median income, which shows no robust effect in general models, emerges as having a positive relationship with women’s suicide rates. These gendered patterns suggest that broad economic improvements yield uneven mental health impacts. By highlighting pronounced gender differences in economic sensitivity, this study contributes to the design of suicide‐prevention strategies. It underscores the necessity of integrating gender‐specific considerations into economic policy and mental health interventions during periods of economic change.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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