princeton industrial relations section

Explore the lineage of Silvia Helena Barcellos

Headshot of Silvia Barcellos

Silvia Helena Barcellos Biography

Current Institution name
University of Southern California
Date of PhD completion
2010
Institution where PhD was completed
Princeton University
Research area
Education
Mobility
Social insurance

I am an Associate Professor (Research) of Economics at the Center for Economic and Social Research and the Economics Department at the University of Southern California. I am also a Faculty Research Fellow at the NBER and an International Research Associate at the Institute for Fiscal Studies (IFS). I earned my Ph.D. and M.A. in Economics from Princeton University. My research interests span Health and Labor Economics. My work aims to understand the interplay between socio-economic status (SES) and health across the lifespan, with a focus on the role public policy plays on such relationships. A strand of my research investigates how education (and different educational policies) affects health and SES at older ages, including how individual genetics help shape such relationships. This research exploits the increasing availability of genetic data linked to household surveys and administrative health records, as well as advances in behavioral genetics -- namely the development of polygenic indices (PGIs) for behavioral traits such as education. By doing so, it can shed new light on a question that has captured the interest of social scientists for many decades: what are and what drives the pecuniary and non-pecuniary returns to education? A second longstanding focus of my research investigates the effect of health insurance coverage (and different types of coverage) on medical expenditure risk, access to care, psychological well-being, and health outcomes. I have studied different aspects of large public insurance programs such as Medicaid, Medicare and the health insurance marketplaces introduced by the Affordable Care Act. A common thread throughout my work is the use of novel (survey, biomarker and administrative) data combined with econometric methods for causal inference, including experimental and quasi-experimental methods.