New publication showing a causal link between college tuition subsidies and voting

Igor Geyn
Data (+ Social) Scientist

Hello! My name is Igor. I'm a data scientist and social science researcher specializing in causal inference using large observational data sets, advanced econometrics methods, and machine learning. My PhD research focuses on answering local political economy questions such as "do partisan elections lead to partisan-biased outcomes?" (they don't), "does going to college cause attendees to paricipate in politics?" (it does), and "can/do voters learn from local ballot measures and propositions?" (work in progress).

I used a leave of absence during academic year 2024-25 to automate tools for risk analysis and perform causal analysis of wildfire mitigation programs at Pacific Gas & Electric Company (PG&E).

Before grad school, I was a researcher and data analyst consulting with Fortune 500 companies across healthcare, government contracting, defense, and other industries. I have also spent time as a freelance journalist, people manager, philanthropic organizer, and survey researcher.

Contact: igorgeyn at gmail dot com
CV: [link]

Current Work

I'm a PhD candidate in Political Science at UCLA (focused on American politics and methods/political methodology), where I developed expertise in experimental design, statistical analysis, policy evaluation, and assessing/using game theoretic models of behavior. I am working towards completing my dissertation by winter 2026.

I am also working as a data science consultant for several companies/organizations—including a major web3 project—on topics surrounding causal inference/spillover effects, and as a data science trainer for several individuals working on their own independent data science project.

If you or your organization have a need for similar work, don't hesitate to reach out.

During academic year 2024-25, I took a leave of absence to work as a data scientist at Pacific Gas & Electric (PG&E), where I used advanced econometric methods to evaluate company programs and inform risk management strategies. I applied the same rigorous causal inference techniques (double ML, regression discontinuity (RD) design, etc.) used in cutting-edge academic research to real-world policy and operational challenges.

Recent Research/Publications

My academic work has been published in leading journals including the American Political Science Review and is forthcoming in the American Economic Journal: Economic Policy. At a high level, this research applies rigorous quantitative methods to understand the effects of institutions and policies on democratic participation and governance.

My published work:

analyzes the effects of local partisan election administration in the U.S. (published at the American Political Science Review; co-authored with Joshua Ferrer and Dan Thompson),
provides causal evidence of the effect of higher education on political participation (conditionally accepted at the American Economic Journal: Economic Policy; co-authored with Daniel Firoozi).

Other work in progress examines the effect of political institutions (e.g., ballot propositions) on voters' ability to learn about policy as well as the effect of partisan alignment between members of Congress and the President on disaster relief outcomes.

Past analytical work includes policy publications on regional disparities in the behavioral health workforce, forecasts of primary care supply and demand in California, and workforce analyses of health providers in Washington, D.C.; work published through UCSF and the D.C. Policy Center, respectively.

Let's Connect!

Contact: igorgeyn at gmail dot com
CV: [link]

Click here to go straight to my published work.
A selection of my freelance projects can be found here.
My teaching experience—including some YouTube materials—can be found here.

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Igor GeynData (+ Social) Scientist

Current Work

Recent Research/Publications

Let's Connect!

Igor Geyn
Data (+ Social) Scientist