In many African countries there is a substantial gap between realised and potential yield. This project explores the use of new large scale households surveys and geospatial data to investigate the impact of socio-economic and infrastructural constraints to explain the yield gap in Sub-Saharan Africa (SSA).
There are only a few studies that related the yield gap to a number of explanatory socio-economic and infrastructural variables, such as distance to roads and population density However, due to the high level of aggregation these studies are not able to address underlying micro-mechanisms, i.e. how plot, farm and village level factors (e.g. plot size, farmer experience and market conditions) relate to realised production and efficiency. In this project a ‘bottom-up’ methodology is used that uses survey data and crop models that take into account local conditions. In order to increase agricultural productivity, it is important to better understand the multiple levels of biophysical and socioeconomic determinants, and their interactions that prevent closing the yield gap.
The main source of data in this project are Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA), which recently have been published by the World Bank for seven SSA countries. The LSMS-ISA are nationally representative panel household surveys that cover a wide range of agricultural and socio-economic household and village level indicators including geo-referenced plot level data that can be linked with the Global Yield Gap Atlas (GYGA). The innovative linking and econometric analysis of micro-level household data with agronomic yield gap assessments will provide new insights and enhanced understanding of the determinants and constraints that determine the yield gap. The results will be useful to derive targeted policy and farming recommendations that account for the complex environments in which farmers in the SSA-region operate.