Austin Jang

I am a PhD candidate in Statistics & Data Science and Political Science at Yale University. My research lies at the intersection of political methodology, statistics, and computational social science, with a focus on simulation-based inference, diagnostics, and the principled interpretation of statistical quantities.

I develop computational methods and new ways of thinking about familiar statistical practices, helping researchers understand both what they can legitimately claim from their analyses and what they cannot. My work addresses the crucial step of translating statistical output into scientific claims with greater rigor, transparency, and honesty about the limits of what data can support.

Publications

Gnostic notes on temporal validity
with Molly Offer-Westort, Serena Wang, and P.M. Aronow
Research & Politics, 2024

Select Working Papers

On the Foundations of the Design-Based Approach
with P.M. Aronow and Molly Offer-Westort
Under review
Support for Democracy
with Milan Svolik
Why Do Low-Powered Voters Participate in Governance?
with Eliza Oak
Adversarial Parameter Selection for Simulation Studies
A Practical Guide to Influence Functions
Addressing Differential Attrition in the Gary Negative Income Tax Experiment
with Molly Offer-Westort and P.M. Aronow