Sustainable intensification of agriculture will have to build on various innovations, but synergies between different types of technologies are not yet sufficiently understood. We use representative data from small farms in Kenya and propensity score matching to compare effects of input-intensive technologies and natural resource management practices on household income. When adopted in combination, positive income effects tend to be larger than when individual technologies are adopted alone.
Background
Weather risk is a serious issue in the African small farm sector that will further increase due to climate change. Farmers typically react by using low amounts of agricultural inputs. Low input use can help to minimize financial loss in bad years, but is also associated with low average yield and income. Increasing small farm productivity and income is an important prerequisite for rural poverty reduction and food security. Crop insurance could incentivize farmers to increase their input use, but indemnity-based crop insurance programs are plagued by market failures.
The use of mobile phones has increased rapidly in many developing countries, including in rural areas. Besides reducing the costs of communication and improving access to information, mobile phones are an enabling technology for other innovations. One important example are mobile phone based money transfers, which could be very relevant for the rural poor, who are often underserved by the formal banking system. We analyze impacts of mobile money technology on the welfare of smallholder farm households in Kenya.
Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low.
The recent proliferation of mobile phones in rural Africa has also led to increased interest in mobile financial services (MFS), such as mobile money and mobile banking. Such services are often portrayed as promising tools to improve agricultural finance, especially among smallholders who are typically underserved by traditional banks. However, empirical evidence on the actual use of MFS for agricultural activities is thin. Here, we use nationally representative data from Kenya to analyze the use of mobile payments, mobile savings, and mobile credit among the farming population.
Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low.
Most micro-level studies on the impact of agricultural technologies build on cross-section data, which can lead to unreliable impact estimates. Here, we use panel data covering two time periods to estimate the impact of tissue culture (TC) banana technology in the Kenyan small farm sector. TC banana is an interesting case, because previous impact studies showed mixed results. We combine propensity score matching with a difference-in-difference estimator to control for selection bias and account for temporal impact variability.
This study analyse how agricultural extension can be made more effective in terms of increasing farmers’ adoption of pro-nutrition technologies, such as biofortified crops. In a randomised controlled trial with farmers in Kenya, the authors implemented several extension treatments and evaluated their effects on the adoption of beans biofortified with iron and zinc. Difference-in-difference estimates show that intensive agricultural training can increase technology adoption considerably.
This article investigates determinants and impacts of cooperative organization, using the example of smallholder banana farmers in Kenya. Farmer groups are inclusive of the poor, although wealthier households are more likely to join. Employing propensity score matching, we find positive income effects for active group members. Yet price advantages of collective marketing are small, and high-value market potentials have not yet been tapped. Beyond prices, farmer groups function as important catalysts for innovation adoption through promoting efficient information flows.