Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach.

Area of Science:

• Agricultural Economics
• Geospatial Analysis
• Agronomy

Background:

• Econometric research has underutilized integrated agricultural surveys, GIS, and remote sensing for developing nations' yield estimation.
• Annual agricultural surveys and advanced spatial data products are routinely collected but rarely combined for yield analysis.

Purpose of the Study:

• To explore determinants of wheat output per hectare in Ethiopia using integrated data sources.
• To analyze factors influencing wheat yields at the kebele administrative level during the 2011-2013 Meher seasons.

Main Methods:

• Panel data approach combining national agricultural field surveys with GIS and remote sensing data.
• Econometric modeling to explain variations in wheat output per hectare.

Main Results:

• The model explains approximately 40% of the variation in wheat output per hectare.
• Key yield determinants include farm management (area planted, improved seed, fertilizer, irrigation), weather (rainfall), water availability (vegetation and moisture deficit indexes), and policy.
• Woredas achieve 9.8–86.5% of locally attainable wheat yields, influenced by altitude, weather, terrain, and plant health.

Conclusions:

• Integrating field surveys with spatial data is effective for identifying management priorities in agriculture.
• This approach can guide efforts to improve wheat production at various administrative levels in Ethiopia.