An empirically driven theory of poverty reduction
Programme of work
Increasing evidence transferability
Carolina Population Center, University of North Carolina at Chapel Hill
Centre for Social Research, University of Malawi
School of Education and Leadership, University of Ghana
Department of Agricultural Economics and Extension, University of Zambia
January 2020 to January 2022 (TBC)
Secondary data analysis
Malawi, Ghana, Zambia
This study will develop a middle-range theory of economic growth to un-derstand how cash transfers (an external liquidity injection) affect psychological states and household behavioural responses to produce different effects among households with different characteristics.
The study will use recent developments in machine learning to identify groups of households with different treatment effects.
Using household consumption as the key outcome, machine-learning tools will identify the key subset from a very large set of pre-treatment variables that enables some households to realise large gains in consumption. The specific actions of this set of households will then be analysed to understand what they did to achieve those large gains in consumption.
The study will draw on secondary data from impact evaluations of the four countries’ national unconditional cash transfer programmes merged with a large set of secondary variables on the microenvironment (i.e. market access, climate, topology and land cover).
The results will provide insights on which households are candidates to graduate out of poverty, and the pathways for doing so. It will help inform the design and targeting of future cash transfer programmes.