Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach.
Despite the routine collection of annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has integrated these data sources in estimating developing nations' agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 principalMehercrop seasons at the kebele administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. Reflecting on the high interannual variability in output per hectare, we explore whether these changes can be explained by weather, shocks to, and management of rain-fed agricultural systems. The model identifies specific contributors to wheat yields that include farm management techniques (e.g. area planted, improved seed, fertilizer, and irrigation), weather (e.g. rainfall), water availability (e.g. vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their locally attainable wheat yields given their altitude, weather conditions, terrain, and plant health. In conclusion, we believe the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.
Department of Geography, The George Washington University, Washington DC, United States.
Michael L
ML
Mann
International Food Policy Research Institute, Addis Ababa, Ethiopia.
James M
JM
Warner
Agriculture; Data integration; Ethiopia; Panel data estimation; Remote sensing; Smallholder agriculture; Wheat productivity; Yield gaps