BREAD Working Paper No. 593, July 2021

Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance Emily Aiken, Suzanne Bellue, Dean Karlan, Chris Udry, Joshua Blumenstock Abstract The COVID-19 pandemic has devastated many low- and middle-income countries (LMICs), causing widespread food insecurity and a sharp decline in living standards. In response to this crisis, governments and humanitarian organizations […]

BREAD Working Paper No. 533, February 2020

Unpacking a Multi-Faceted Program to Build Sustainable Income for the Very Poor Abhijit Banerjee, Dean Karlan, Robert Osei, Hannah Trachtman, Christopher Udry Abstract A multi-faceted program comprising a grant of productive assets, training, coaching, and savings has been found to build sustainable income for those in extreme poverty. We focus on two important questions: whether […]

BREAD Working Paper No. 561, May 2019

Assessing the Benefits of Long‐Run Weather Forecasting for the Rural Poor: Farmer Investments and Worker Migration in a Dynamic Equilibrium Model Mark R. Rosenzweig, Christopher Udry Abstract The livelihoods of the majority of the world’s poor depend on agriculture. They face substantial risk from fluctuations in weather conditions. Better risk, credit and savings markets can […]

BREAD Working Paper No. 572, March 2020

How Political Insiders Lose Out When International Aid Underperforms: Evidence from a Participatory Development Experiment in Ghana Kate Baldwin, Dean Karlan, Christopher Udry, Ernest Appiah Abstract Participatory development is designed to mitigate problems of political bias in pre-existing local government but also interacts with it in complex ways. Using a five-year randomized controlled study in […]