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CEGA Senior Program Manager Leah Bridle reviews a research synthesis discussion paper produced with Jeremy Magruder, Craig McIntosh, and Tavneet Suri. The paper is a culmination of more than 5 years of implementation partners’ and donors’ requests for evidence on what randomized evaluations can say about helping farmers adopt technologies and reap benefits. We’ve learned about the range of compounding constraints farmers face as microentrepreneurs, and that the next wave of experimentation should evaluate approaches designed to better include farmers in domestic and global value chains.
How can we improve the profits and welfare of smallholder farmers who make up a majority of the world’s poorest people? These questions aren’t new¹²³ and (perhaps unsurprisingly) it’s complicated. But it’s clear from FAOSTAT data that agricultural production in Sub-Saharan Africa (and to some extent South Asia) remains far below the technological frontier. This suggests missed potential in terms of yields, income, and welfare benefits for many living in poverty. With this in mind, policymakers need to understand what prevents farmers from adopting technologies and effectively accessing markets, and which approaches improve farmers’ livelihoods.
We’ve distilled lessons from a decade of rigorous experimentation, including dozens of randomized evaluations across Sub-Saharan Africa and South Asia — predominantly those that were competitively selected for funding by our Agricultural Technology Adoption Initiative (ATAI, co-managed with J-PAL).*
These evaluations go beyond counting farmers “engaged,” — they identify the effectiveness of specific approaches in shifting farmers’ real-world choices, and measure whether or not (or to what extent) that specific intervention can change farmers’ yields or profits. The core contribution of randomized evaluations is this ability to clearly trace causality. Carefully designed experiments allow us to (1) test whether specific constraints are holding farmers back (access to credit, risk protection, input or output market access, etc.), and (2) measure the real-world impacts of a technology when adopted in farmers’ actual fields. The methodology is one valuable tool for testing important hypotheses, and critically examining common assumptions of what works and why.
We first posted a version in 2016 as our “Emerging Insights” series, later inspiring the 2018 launch of J-PAL’s Policy Insights that similarly highlight lessons emerging across multiple studies and the mechanisms that help explain the results. We’ve found that these syntheses resonate with impact-oriented organizations thinking through how they work with farmers.
Governments in Africa and Asia, as well as multilateral policy advisory units, have requested presentations of these insights to inform real-world policy recommendations (e.g. in partnership with FAO-MAFAP to inform ministries in Uganda). Specific findings have impacted the operations of existing government agricultural programs (scaling improved rice in Odisha) and inspired the founding of new organizations to better support farmers (mobile phone-based agricultural extension; post-harvest storage loans).
Smallholder farmers in rainfed contexts face a range of constraints that limit the modernization of agriculture. Challenges, such as water control and variable prices, make it particularly difficult for farmers to observe, manage, or predict conditions that are key to profitable farm investments in remote markets. We see that:
So far, only a handful of impact evaluations have directly tested interventions designed to fundamentally shift agricultural input and output markets. Farmers’ relationships with market intermediaries (agrodealers, traders, etc.) vary across contexts, as do the costs of doing business. Both affect how value chains are structured and whether and how favorable prices (or other benefits like credit) pass-through to farmers. There is important work to be done to understand the costs of infrastructure, competition among value chain intermediaries, the potential for contract farming and other market linkage arrangements, and how value chain actors respond to market reforms designed to improve input and output quality in supply chains. We are continuing to build the evidence base to better fill these gaps by shifting our focus towards “agricultural transformation.”
See this previous post on ATAI’s renewal, or ATAI’s Framing Paper and de Janvry & Sadoulet (2020) for a discussion of moving beyond technology adoption to an agricultural transformation research agenda.⁴⁵
 World Bank. 2007. World Development Report 2008 : Agriculture for Development. Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/5990
 de Janvry, A. & Sadoulet, E. 2009. Agriculture for Development: Lessons from the World Development Report 2008. QA — Rivista dell’Associazone Rossi Doria, 2009(1):9–24.
 Jack, B.K. 2013. Market inefficiencies and the adoption of agricultural technologies in developing countries. J-PAL and CEGA Agricultural Technology Adoption Initiative White Paper. UC Berkeley: Center for Effective Global Action.
 Evidence for Transformation: Framing a Research Agenda in Agriculture for Development. 2018. J-PAL and CEGA Agricultural Technology Adoption Initiative Framing Paper.
 de Janvry, A., & Sadoulet, E. 2020. Using Agriculture for Development: Supply- and demand-side approaches. World Development, forthcoming.