Objective
Half of the world's extreme poor or over 430 million people live in Sub-Saharan Africa. The vast majority live in rural areas and work in agriculture, where productivity is desperately low. This keeps welfare low now and in the future as agricultural productivity increases are seen as a condition for both structural transformation and to avoid the worst impacts of climate change. This is the motivation for bringing the green revolution which has so far bypassed the continent to Sub-Saharan Africa. Despite the logic being compelling, the results from a decade of research on technology adoption in African agriculture have been largely disappointing. Interventions aimed at increasing farmers ability to invest in inputs to produce more of what they already do have not proven transformative. In this research proposal, I will investigate a complementary explanation why income and productivity in African agriculture remain low: it is what farmers produce precisely the quality and value added of their output that keeps them poor, and they produce low quality because there is no demand for smallholders to produce high quality or higher value-added outputs. As low quality limits price and thus farmers' potential income, missing markets for quality can help explain the low returns to farming. At the core of this research proposal is the hypothesis that markets for quality are missing because of a fundamental information problem: quality is a difficult to observe characteristic. I will rely on three multi-wave randomized controlled field trials to study technological and institutional solutions to overcome this information problem, which hamper demand for high quality products in the export market (work package I) and at home (work package II). In the final work package, I will complete the cycle and study how increases in demand for high quality outputs, and access to high quality inputs, can jump-start a green revolution in rural Africa.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- social sciencespolitical sciencespolitical transitionsrevolutions
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
10691 Stockholm
Sweden