I’m still going through some older reruns for the summer due to my travel schedule. This one is an interview with Rocío Titiunik, a quantitative methods political scientist and professor in the department of politics at Princeton University, as well as a researcher that has been at the frontier of work on regression discontinuity designs.

Her name is synonymous with cutting-edge work on regression discontinuity design, developed in close collaboration with scholars like Sebastián Calonico, Matías Cattaneo, and Max Farrell. Together, they’ve shaped the modern landscape of causal inference, not only through groundbreaking theory but also through widely used software tools in R, Stata, and Python. In addition to her contributions to quantitative methodology, Rocío’s applied research — from electoral behavior to democratic institutions — has become a major voice in political science. She also holds a formidable editorial footprint: associate editor for Science Advances, Political Analysis, and the American Journal of Political Science, and APSR. It’s no exaggeration to say she helps steer the field as much as she contributes to it.

In this older interview, Rocío shared how her journey into economics began not with data, but with theory, literature, and the big questions that led her to the discipline. Her path into Berkeley’s PhD program in agricultural and resource economics was anything but linear, and even once there, she wasn’t sure how all the parts of herself — the scholar, the immigrant, the thinker — would fit together. During our conversation, she opened up about moments of uncertainty, of feeling lost in the sheer vastness of academic economics. Her honesty was disarming. It reminded me that no matter how decorated someone’s résumé may be, we’re all just trying to find our way — and sometimes, the most important breakthroughs happen when we admit we haven’t arrived yet.

Thanks again for tuning in! I hope you like listening to this older podcast interview.

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