Until 2021, there was no research available on the income levels of Guji coffee farmers, and no living income benchmark had been established.
In a multi-year programme Fairfood is working with Trabocca, a Dutch specialty coffee trader, to bring 300 coffee farmers in Guji Ethiopia to a living income. In the design phase, KIT was engaged by Fairfood to provide three of its living income services:
1. Data collection and calculation of actual incomes for selected farming households
2. Calculating the gap between the actual income and the living income benchmark
3. Providing preliminary actionable advice for data-driven interventions to close the farmers’ income gaps.
Living income benchmark for Guji, Ethiopia
A living income benchmark study using the Anker methodology was performed in 2021 in Guji, Zone, Oromia Region, from which KIT derived a reference living income benchmark of USD 2,665 per household per year, for a household of six members. The next step was for KIT to collect data on farmers’ actual incomes, to calculate how many families reach a living income, and how large the gaps between actual incomes and the living income benchmarks may be.
Household income survey
KIT and its local partner MMA Development Consultancy surveyed 140 Suke Quto and 63 Shakisso outgrowers. Farmers were asked for data on their production of coffee (Oct 2020 to Jan 2021 harvest), costs and revenues, as well as data on other crops, activities and sources of income, diversification and land use, productivity and farm practices. The household survey followed KIT’s approach to estimate net household income from primary data.
Results and income gaps
Fairfood and Trabocca are currently using the results from this study to design interventions following a segmented approach. These can vary widely, for example: price interventions, targeting of ambitious farmers who aim to optimize productivity with trainings on good agricultural practices or climate-smart practices, tailored agricultural inputs, focusing on diversification, or addressing gender divisions of labor to increase the efficiency of the coffee farms.