An empirically driven theory of poverty reduction
Summary
This project uses secondary data from four countries to develop a "middle-range" theory of individual economic growth. We use evaluation data from four government unconditional cash transfer programs, and combine them with secondary data on the micro-environment such as market access, climate, and land cover. The country programs are from Zimbabwe, Malawi, Ghana and Zambia. We use the cash transfers as exogenous liquidity injections to understand the economic responses of households, and how these responses interact with the micro-environment. We track the effects of the liquidity injections on psychological states and time discounting, and compare the relative effects of behavioral or psychological constraints versus environmental constraints in generating improvements in economic conditions (consumption, productivity and assets). Machine learning algorithms will allow us to make sense of a large set of variables. The results will provide an understanding of the mix of interventions necessary to help the poor "graduate" from poverty.