Saweda O. Liverpool-Tasie, Lenis (author), Salim Nuhu, Ahmed (author), Awokuse, Titus (author), Jayne, Thomas (author), Muyanga, Milu (author), Aromolaran, Adebayo (author), and Adelaja, Adesoji (author)
Format:
Journal article
Publication Date:
2022-04-19
Published:
United States: Wiley Online
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 205 Document Number: D12576
27pgs, In spite of mounting evidence about the growth of medium-scale farms (MSFs) across Africa, there is limited empirical evidence on their impact on neighbouring small-scale farms (SSFs). We examine the relationships between MSFs and SSFs, with particular focus on the specific mechanisms driving potential spillover effects. First, we develop a theoretical model explaining two propagating mechanisms: learning effects (training) and cost effects (reduced transactions cost). An empirical application to data from Nigeria shows that SSFs with training from MSFs tend to use higher levels of modern inputs (have higher productivity), and receive higher prices and income. The results also show that purchasing inputs from MSFs reduces the costs of accessing modern inputs and is associated with higher inorganic fertiliser use by SSFs. Our results suggest that the benefits of receiving training and purchasing inputs from MSFs are particularly important for very small-scale producers, operating less than 1 hectare of land. This implies that policies which promote the efficient operation of MSFs and encourage their interaction with SSFs can be an effective mechanism for improving the productivity and welfare of smallholder farms, hence reducing their vulnerability to extreme poverty.
17 Pages., Given the marked heterogeneous conditions in smallholder agriculture in Sub-Saharan Africa, there is a growing policy interest in site-specific extension advice and the use of digital extension tools to provide site-specific information. Empirical ex-ante studies on the design of digital extension tools and their use are rare. Using data from a choice experiment in Nigeria, we elicit and analyze the preferences of extension agents for major design features of ICT-enabled decision support tools (DSTs) aimed at site-specific nutrient management extension advice. We estimate different models, including mixed logit, latent class and attribute non-attendance models. We find that extension agents are generally willing to use such DSTs and prefer a DST with a more user-friendly interface that requires less time to generate results. We also find that preferences are heterogeneous: some extension agents care more about the effectiveness-related features of DSTs, such as information accuracy and level of detail, while others prioritise practical features, such as tool platform, language and interface ease-of-use. Recognising and accommodating such preference differences may facilitate the adoption of DSTs by extension agents and thus enhance the scope for such tools to impact the agricultural production decisions of farmers.
