Targeting Impact versus Deprivation
Johannes Haushofer, Paul Niehaus, Carlos Paramo, Edward Miguel, Michael Walker
American Economic Review · 2025 · Volume 115 · Issue 6
Abstract
A large literature has examined how best to target antipoverty programs to those most deprived in some sense (e.g., consumption). We examine the potential trade-off between this objective and targeting those most impacted by such programs. We work in the context of an NGO cash transfer program in Kenya, employing recent advances in machine learning methods and dynamic outcome data to learn proxy means tests that jointly target both objectives. Targeting solely on the basis of deprivation is not attractive in this setting under standard social welfare criteria unless the planner's preferences are extremely redistributive.
Keywords
Neural Networks and Related Topics, Equity, Justice, Inequality, and Other Normative Criteria and Measurement, General Welfare, Well-Being, Welfare, and Poverty: Government Programs, Provision and Effects of Welfare Programs, Nonprofit Institutions, NGOs, Social Entrepreneurship, Economic Development: Human Resources, Human Development, Income Distribution, Migration
Enable JavaScript for citation tools and additional paper interactions.