Determinants of soybean adoption and performance in northern Ghana

Soybean has capacity as a development crop to generate new sources of income for smallholder farmers. Yet as an unfamiliar commercial crop, soybean requires farmers to move beyond traditional production practices and market engagements in order to succeed. In this context soybean represents a long-jump agricultural technology, requiring significant, non-incremental changes for smallholder farmers. This research addresses the adoption process for long-jump agricultural technologies like soybean to understand the drivers that enable or hinder farmer participation in this dynamic agricultural market. Specifically, I explore the role experience, space, economies of scale, demographics, market access, and land rights play in understanding adoption and performance in soybean production among smallholder women farmers. I consider three estimation strategies using a primary dataset on smallholder soybean producers in the Upper West region of Ghana. I first employ probit and ordinary least squares (OLS) regression models to understand adoption and performance. I then employ a combined spatial-autoregressive with spatial-autoregressive disturbances (SARAR) model using a generalized spatial two-stage least squares to understand cross-unit interactions in a spatial dimension. I demonstrate that there exists positive, large, and significant spatial autoregressive dependence and knowledge spillover in soybean yields among smallholder female farmers within spatial networks. This finding provides guidance for agricultural development programs about the importance of social interaction and information provision through farmer networks in improving farmer performance in soybean production. Further, I show that larger farms and producers who allocate more land to soybean cultivation are associated with higher yields and sustained soybean adoption, which may indicate economies of scale. Finally, I demonstrate that experience and extension access are important drivers of success in soybean cultivation. These findings ultimately contribute to the understanding of whether soybean as a development crop can directly benefit smallholder farmer livelihoods

Soy dairy performance metrics

Soybean (Glycine max (L. Merr.) has been a crop of interest to address both poverty and malnutrition in the developing world because of its high levels of both protein and oil, and its adaptability to grow in tropical environments. Development practitioners and policymakers have long sought value added opportunities for local crops to move communities out of poverty by introducing processing or manufacturing technologies. Soy dairy production technologies sit within this development conceptual model. To the researchers’ knowledge, no research to date measures soy dairy performance, though donors and NGOs have launched hundreds of enterprises over the last 18 years. The lack of firm-level data on operations limits the ability of donors and practitioners to fund and site sustainable dairy businesses. Therefore, the research team developed and implemented a recordkeeping system and training program first, as a 14-month beta test with a network of five dairies in Ghana and Mozambique in 2016-2017. Learning from the initial research then supported a formal research rollout over 18 months with a network of six different dairies in Malawi and key collaboration from USAID’s Agricultural Diversification activity. None of the beta or rollout dairies kept records prior to the intervention. The formal rollout resulted in a unique primary dataset to address the soy dairy performance knowledge gap. The results of analysis show that the dairies, on average, achieve positive operating margins of 61%, yet cannot cover the fixed costs associated with depreciation, amortization of equipment and infrastructure, working capital, marketing and promotion, and regulatory compliance. The enterprises in our sample operate only at 9% of capacity, which limits their ability to cover the normal fixed costs associated with the business. The challenge is not thetechnology itself, as when operated, it produces a high-quality dairy product. The challenges involve a business that requires too much capital for normal operations relative to a nascent and small addressable market