representatives of local stakeholders, such as farmers’ associations, traders, researchers, extension workers, NGOs, and government policy makers, meet regularly to share views, identify problems and prioritize solutions. The program was rolled out in eight countries in Sub-Saharan Africa and within each country, program locations were randomly selected at the village or higher administrative level. The study finds evidence of adoption of crop management innovations but also considerable heterogeneity in the impact across research sites. Other higher-level outcomes such as yields or household welfare were not included in the study.

Another approach that attempts to overcome some weaknesses of traditional extension systems is Farmer Field Schools (FFS), where farmers attend weekly field school sessions throughout the season. Through observation and learning-by-doing, farmers are meant to internalize the advantages of improved technology and adopt new practices on their own fields (Waddington et. al, 2014). Davis et al. (2012) evaluate the impact of the scaling up of FFS in Kenya, Tanzania, and Uganda. Using matching estimators and a difference in differences approach, they find that productivity and income increase significantly in Kenya and Tanzania, but not in Uganda. One of the main limitations of that study is the lack of detailed baseline data on the outcomes of interest, relying on recall data instead, and non-random placement of FFS. Kondylis _et al_ (2017) evaluate the impact of two different modalities of the T&V extension delivery system, using a randomized control trial methodology in Mozambique. They compare the traditional decentralized system in which extension agents train contact farmers (who are then supposed to train other farmers in their communities) to an alternative in which contact farmers receive an additional centralized 3-day training. They find that directly trained contact farmers are more likely to adopt techniques. However, these higher levels of adoption by contact farmers did not encourage higher diffusion to other farmers in the community.

Extension services are one of several possible sources of information about new technologies that farmers can use. Other strands of research have investigated how information can be passed on to farmers through alternative modes. For example, there is a growing body of literature that focuses on social learning, which describes how information spreads within one’s network (see e.g.: Jack, 2013; Munshi, 2004; Conley and Udry, 2001; Bandiera and Rasul, 2006). Information can also be made cheaper to supply and acquire, for example through the use of new information and communication technologies, such as mobile-phone based service or internet kiosks (Aker, 2010; Cole & Fernando, 2012).

Among the literature on extension, two papers have analyzed the impact of extension services in Ethiopia. Dercon et al. (2010) use longitudinal household survey data from 1994 to 2004 to study the impact of public investments in road quality and extension services on the welfare of farmers. Using household fixed effects and an instrumental variable strategy, they find that receiving at least one extension visit during the last cropping season increased consumption growth by 7.1 percent. Krishnan and Patnam (2014) make use of later waves of the same survey to compare the role of extension services and peer learning on improved seeds and fertilizer adoption between 1999 and 2009. To identify the impacts of neighbors on adoption, they use farmers’ spatial distribution within villages. They also control for unobserved heterogeneity in the placement of extension services and household characteristics by including household and village fixed effects. They find that extension services had a significant initial impact on adoption but that by 2009, adoption mainly takes place through social learning and extension services become irrelevant.

4