Panel Paper: Moving Teachers to Malawi’s Remote Communities: A Data-Driven Approach to Teacher Deployment

Saturday, November 9, 2019
Plaza Building: Concourse Level, Governor's Square 12 (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Salman Asim1, Joseph Chimombo2,3, Dmitry Chugunov1 and Ravinder Madron Casley Gera1, (1)World Bank, (2)Formerly Ministry of Education, Science and Technology, (3)U.S Agency for International Development

There are severe geographical disparities in pupil-teacher ratios (PTR) across Malawi, with most teachers concentrated near commercial centers and in rural schools with better amenities. Most of the variation in PTR is concentrated in small sub-district areas, suggesting a central role for micro-geographic factors in teacher distribution. Employing administrative data from several government sources, regression analysis reveals that school-level factors identified by teachers as desirable are closely associated with PTR, including access to roads, electricity, and water, and distance to the nearest trading center, suggesting a central role for teachers’ interests in PTR variation. Political economy network mapping reveals that teachers leverage informal networks and political patronage to resist placement in remote schools, while administrative officials are unable to stand up to these formal and informal pressures, in part because of a lack of reliable databases and objective criteria for the allocation of teachers.

This study, published in the International Journal of Educational Development in January 2019, curates a systematic database of the physical placement of all teachers in Malawi and links it with data on school facilities and geo-spatial coordinates of commercial centers. The study develops a consistent and objective measure of school remoteness, which can be applied to develop policies to create rules for equitable deployments and targeting of incentives. Growing awareness of disparities in PTRs among district education officials is already showing promising improvements in targeting of new teachers. Simulation results of planned policy applications show significant potential impacts of fiscally-neutral approaches to targeted deployments of new cohorts, as well as retention of teachers through data-calibrated incentives.