Solving the living income challenge together

Living income is a complex, multi-sector issue that requires a complex, multi-sector solution. Many development practitioners are coming together to solve this challenge, and SCOPEinsight is helping these efforts with a predictive model for development professionals who work with agribusinesses. We are convinced that farmers in emerging markets can achieve a living income through coordinated and sustained effort.

The living income challenge

Current estimates indicate that one in ten people worldwide live on under $1.90 a day, the threshold for extreme poverty. Approximately 80% of these people live in rural areas. Since living income is region-specific, it is challenging to calculate global percentages. Still, it can be safely assumed that the proportion of people worldwide who earn less than a living income is significantly higher than one in ten. It can also be assumed that many smallholder farmers worldwide fall into this category.

The living income gap arises when actual income is less than what it costs to afford a decent standard of living for all household members.

It is imperative to increase global income levels for many reasons, including to reach the UN’s Sustainable Development Goal (SDG) of No Poverty by 2030. Unfortunately, increasing the incomes of smallholder farmers sustainably is a complex issue that smallholder farmers cannot solve alone. Instead, it must involve many actors who work in complementary ways. A proper solution to the living income challenge will require coordinated, well-designed efforts from all stakeholders involved.

It is also essential to be aware of unintended results of some interventions. Many short-term solutions can create additional challenges in the long term. For example, a price increase can unwittingly induce oversupply and indirectly cause harmful effects on the environment. This may lead to companies changing their sourcing strategies. It is vital that solutions are environmentally sustainable and not, for example, increasing farm size and yields through deforestation. If all relevant aspects are not considered, then efforts can do more harm than good.

Using data and machine learning to predict living income

After eleven years and nearly 6,000 agribusiness assessments – each with over 200 data points – SCOPEinsight wanted to see what evidence we had to predict living income for farmers. While we do not collect farmer-level data, we collect a significant amount of information about agribusiness members. To develop the Living Income Predictor, we worked with NewForesight to first develop a theory of assessment. We then put the SCOPE data through a machine learning process to validate the theory and develop the model. By analyzing specific data from these dimensions, our model can assess the likelihood that the assessed agribusiness can play a role in helping its members earn a living income. If the likelihood is low, it also provides insight into what efforts the agribusiness should take to reach that level.

When working with agribusinesses, we can increase on farm income and therefore lessen the living income gap.

While agribusiness professionalism on its own is not enough to ensure a living income, we believe it can play a role in pushing the needle further and increasing overall income. A professional agribusiness can ensure a higher net farm income, bringing farmers closer to an overall living income. We are currently conducting a household study in Côte d’Ivoire to further validate our model.

We are interested in getting even more proof points. Do you have farmer-level data that we can cross-reference? Contact us today to discuss co-development opportunities.

Read more about our living income model on the Living Income Community of Practice blog.

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