We study monotone ecological inference, a partial identification approach to ecological inference. The approach exploits information about one or both of the following conditional associations: (1) outcome differences between groups within the same neighborhood, and (2) outcomes differences within the same group across neighborhoods with different group compositions. We show how assumptions about the sign of these conditional associations, whether individually or in relation to one another, can yield informative sharp bounds in ecological inference settings. We illustrate our proposed approach using county-level data to study differences in Covid-19 vaccination rates among Republicans and Democrats in the United States.

More on this topic

BFI Working Paper·Jun 18, 2026

Paying for Power

Fiona Burlig and Anant Sudarshan
Topics: Energy & Environment
BFI Working Paper·Jun 16, 2026

The Local Damages from Global Climate Change

Tamma Carleton, Michael Greenstone, Solomon Hsiang, Andrew Hultgren, Robert E. Kopp, Kelly E. McCusker, Ishan Nath, James Rising, and Ashwin Rode
Topics: Energy & Environment
BFI Working Paper·May 18, 2026

Valuing Disaster Prevention: Desert Locust Monitoring and Control

Joséphine Gantois, Anouch Missirian, Evelina Linnros, Anna Tompsett, Amir Jina, Gordon C. McCord, and Eyal Frank
Topics: Energy & Environment