Sam Trejo is a PhD candidate in Economics and Education at Stanford University and an NSF and IES Graduate Research Fellow. He is simultaneously pursuing two MA degrees at Stanford, in Economics and in Sociology. Before coming to Stanford, Sam received his bachelor’s degree from The University of Texas with a double-major in Economics and Plan II Honors, as well as minors in Math and Arabic.
Sam specializes in applied econometrics and causal inference; he has two main bodies of active research, which often overlap. The first body of work focuses the role of educational and health policy in reducing economic and social inequality. The second body of work investigates how combining social science and biological methods can inform public policy. Sam is an active member of the budding field of social science genomics, where he explores the uses and misuses of integrating genetic data into social models of human behavior.
Sam has extensive experience tackling questions using large, restricted-use datasets; in-progress and past work have utilized genetic data from longitudinal surveys (Wisconsin Longitudinal Survey, Add Health, Born in Bradford) as well as population-level administrative data (National Center for Educational Statistics EdFacts, San Francisco Unified School District student-level, Optum medical records claim-level). Apart from quantitative social science research, Sam enjoys camping, bikes, board games, and Chinese food.
Daphne Martschenko*, Sam Trejo*, and Benjamin W. Domingue*. 2019. “Genetics and Education: Recent Developments in the Context of an Ugly History and an Uncertain Future.” AERA Open 5: 1-15. DOI: 10.1177/2332858418810516
Trejo, Sam*, Daniel W. Belsky, Jason D. Boardman, Jeremy Freese, Kathleen Mullan Harris, Pam Herd, Kamil Sicinski, and Benjamin W. Domingue*. 2018. “Schools as Moderators of Genetic Associations with Life Course Attainments: Evidence from the WLS and Add Heath.” Sociological Science 5: 513-540. DOI: 10.15195/v5.a22
Sam Trejo and Benjamin W. Domingue. 2019. “Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores.”
*denotes equal authorship
Dissertation committee: Benjamin Domingue, Caroline Hoxby, Jeremy Freese, and Brian Jacob (University of Michigan)
Research interests: Economics of Education, Public Economics, Health Economics, Social Policy, Social & Economic Inequality, Social Science Genomics
Contact Info: Office 508, Center for Educational Research at Stanford 520 Galvez Mall, Stanford University Stanford, CA 94305 email@example.com