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stat.AP2026

The Role of Confounders and Linearity in Ecological Inference: A Reassessment

Shiro Kuriwaki, Cory McCartan

Estimating conditional means using only the marginal means available from aggregate data is known as the ecological inference problem. We reassess this literature, arguing that it…

stat.AP2026

Generalized Sequential Monte Carlo Sampling for Redistricting Simulation

Philip O'Sullivan, Kosuke Imai, Cory McCartan

Simulation methods have become important tools for quantifying partisan and racial bias in redistricting plans. We generalize the Sequential Monte Carlo (SMC) algorithm of McCartan…

stat.AP2025

Gerrymandering and geographic polarization have reduced electoral competition

Ethan Jasny, Christopher T. Kenny, Cory McCartan +8

Changes in political geography and electoral district boundaries shape representation in the United States Congress. To disentangle the effects of geography and gerrymandering, we…

stat.AP2025

Redistricting Reforms Reduce Gerrymandering by Constraining Partisan Actors

Cory McCartan, Christopher T. Kenny, Tyler Simko +3

Political actors often manipulate redistricting plans to gain electoral advantages, a process known as gerrymandering. Several states have implemented institutional reforms to addr…

stat.AP2024

Estimating Racial Disparities When Race is Not Observed

Cory McCartan, Robin Fisher, Jacob Goldin +2

The estimation of racial disparities in various fields is often hampered by the lack of individual-level racial information. In many cases, the law prohibits the collection of such…