The Role of Communication Channels on Food Production and Household Welfare : Empirical Evidence from Northern Ghana

Lack of information on innovative agricultural technologies continue to be a major constrain and cause of low technology adoption and productivity among farmers in sub-Saharan Africa. The emergence of new communication channels such as ICTs offer some prospects to boost agricultural extension delivery and lower the barriers to information diffusion among farmers. However, not much is known about the impact of the new communication channels on food production and welfare via its role in improving farmers’ technology adoption. This study in chapter two contributes to literature by employing copula functions, to examine the impact of participation in ICT-based extension channels on improved technology adoption, specifically the new Rhizobia inoculant technology, and its impact on farmers’ technical knowledge, yields and farm net returns. Low technology adoption persist among smallholder farmers in developing countries. This has been attributed to lack of understanding about the adoption decision-making behavior of farmers, leading to inability to develop appropriate extension policies that can enhance technology adoption. In chapter three, this study contributes to knowledge by employing dynamic treatment effect model to analyze farmers’ adoption decision-making as a dynamic process, one that comprises a series of multiple decisions made over several stages or periods. The inability to develop appropriate extension policies has also been attributed to the disconnection between empirical studies that examine adoption of technological packages and studies that analyze management practices of those packages. Chapter four of this study attempts to bridge the knowledge gap by employing the stochastic frontier treatment effect with endogenous mediator model to simultaneously estimate the impact of technology adoption and extension participation and decompose their interaction effect into direct and indirect effects. The use of farmers’ egocentric information or social networks to diffusion information about new technologies leading to adoption is voluminous in the literature. However, the impact of the egocentric information networks on the technical efficiency of farmers appears to be over looked in the literature. This study in chapter five contributes to literature by employing spatial stochastic frontier analysis to investigate the impact of egocentric information networks on farmers’ technical efficiency, productivity and its distributive mechanisms among farmers in the network. The findings in chapter two reveal that ICT-based extension channels are equally effective as the conventional extension channels, and in some instances, outperform them. The study found that ICT extension channels lead to higher yields, farm net returns, and knowledge gained, relative to conventional extension channels and non-participation in extension programs. The study in chapter three further reveal the existence of significant impact heterogeneities across different adoption stages, with the long-term benefits of adoption outweighing the short-term benefits. The study found that there exist unrealized potential gains at some stages in the adoption process, in particular, at knowledge acquisition and trial stages, which extension policymakers can target in order to maximize adoption impacts and save resources to expand extension outreach to benefit more farmers. Chapter four of the results show that the direct impact of technology adoption alone contributes 72% to farm productivity and 73% indirectly due to improvement in farmers’ efficiency, leading to overall welfare improvement of 77%. Similarly, the direct impact of extension participation alone contributes 28% to farm productivity and 27% indirectly due to improvement in farmers’ efficiency, resulting in 23% improvement in farmers’ welfare. The findings suggest that, it is insufficient and less beneficial to provide extension services to farmers without the provision of improved technology. Finally, the study in chapter five reveal that 19% of farmers’ technical inefficiency depend on the inefficiency of the farmers from whom they seek farming advice. The results also show that inefficient farmers tend to depend on efficient farmers in their egocentric information networks to improve their level of efficiency. In general, the study provides empirical evidence to inform effective extension service delivery policies, towards attainment of the Sustainable Development Goals (SDGs), in particular goal two and five, which seek to achieve zero hunger and equal access to extension services by all for enhance agricultural productivity.


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