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What would it cost to end extreme poverty?

Roshni Sahoo · Columbia Business School

Thursday, October 08, 2026 · 3:00 PM - 4:00 PM

CSB 453

We study poverty minimization via direct transfers, framing this as a statistical learning problem while retaining the information constraints faced by real-world programs. Using nationally representative household consumption surveys from 34 countries that together account for 76% of the world's poor, we estimate that reducing the poverty rate to 1% (from a baseline of 13%) would cost $211B nominal per year. This is 4.0 times the corresponding reduction in the aggregate poverty gap, but only 19% of the cost of universal basic income. Extrapolated globally, the results imply a cost of 0.28% of global GDP to (approximately) end extreme poverty.

About the speaker

Roshni Sahoo is assistant professor in the Decision, Risk, and Operations Division at Columbia Business School. She works on data-driven decision making for social impact. Her research develops statistical methodology to address challenges in public health and economic development, combining tools from machine learning, causal inference, and optimization. Her work has appeared in leading operations research journals (such as Operations Research) and machine learning conferences (such as NeurIPS and ICLR), and has been featured by media outlets including The Economist and Vox. Roshni completed her PhD in Computer Science at Stanford University in 2026. She also received Bachelor of Science degrees in Computer Science and Mathematics at MIT in 2020.