Establishing a living income baseline for coffee farmers

Carble helps coffee brands reduce their carbon footprint by rewarding coffee farmers for the carbon they store in forest canopies. In order to monitor carbon storage, as well as how farmer livelihoods are impacted by these carbon-payments, Carble needs reliable data on carbon storage, income, and the living income gap. Together with Carble, Akvo piloted an approach to measuring income and estimating the living income gap using a short survey. This reduces the burden of data collection on farmers while saving resources and improving data quality. 

Above: Photo by Clint Mckoy on Unsplash.

 

 


Partners

Carble


Locations

Guji region, Ethiopia


Sector

Agriculture


Services

Data analysis

The challenge

In order to provide its clients with reporting on carbon storage and livelihood outcomes, Carble needed to establish both an income and carbon baseline for each area of interest its clients are sourcing from. From our experience with measuring income, we know that income measurement surveys can be very long, ranging from 350-700 questions, and take about 1-2 hours. One of the objectives of this pilot was therefore to test a lean survey to measure the living income gap. 

 

The solution

Akvo designed an approach to calculating living income and the living income gap using a survey that could be conducted in less than 30 minutes. The data was collected among a sample of 75 small scale farmers. We consulted all partners involved in order to develop a lean income measurement survey that excluded irrelevant questions while tailoring the answer options for farmers. In the next phase, we calculated the living income gap using the Consumer Price Indices (CPI), inflation rate, and the OECD modified equivalence scale. We analysed the gap by disaggregating the data on farm size and type of coffee. 

The impact

From this pilot, we have learned that estimating the living income gap is possible using a shorter survey, although we cannot assess the quality of the data due to limited secondary data sources available. We encourage other actors to publish or share data on the living income of coffee farmers in Ethiopia so that we can compare our results. Likewise, we are interested in collaborating with other actors to pilot a short income measurement survey in other contexts.

Are you interesting in collaborating with us?