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. 509, April 2017
Decentralization and Efficiency of Subsidy Targeting: Evidence from Chiefs in Rural Malawi Pia Basurto, Pascaline Dupas, Jonathan Robinson Abstract Developing countries spend vast sums on subsidies. Beneficiaries are typically se- lected via either a proxy-means test (PMT) or through a decentralized identification process led by local leaders. A decentralized allocation may offer informational ad- vantages, […]
BREAD Working Paper No. 570, January 2020
Decentralized Targeting of Agricultural Credit Programs: Private versus Political Intermediaries Pushkar Maitra, Sandip Mitra, Dilip Mookherjee, Sujata Visaria Abstract We compare two different methods of appointing a local commission agent as an intermediary for a credit program. In the Trader-Agent Intermediated Lending Scheme (TRAIL), the agent was a randomly selected established private trader, while in […]
BREAD Working Paper No. 579, July 2021
Expanding Access to Clean Water for the Rural Poor: Experimental Evidence from Malawi Pascaline Dupas, Basimenye Nhlema, Zachary Wagner, Aaron Wolf and Emily Wroe Abstract Using data from an 18-month randomized trial, we estimate large and sustained impacts on water purification and child health of a program providing monthly coupons for free water treatment solu- […]