Heterogeneous demand and supply for an insurance-linked credit product in Kenya: A stated choice experiment approach

We employ a discrete choice experiment to elicit demand and supply side preferences for insurance- linked credit, a promising market-based tool for managing agricultural weather risks and providing access to credit for farmers. We estimate preference heterogeneity using primary data from smallholder farmers and managers of lenders/insurers combined with household socio-economic survey data in Kenya. We analyse the choice data using maximum simulated likelihood and Hierarchical Bayes estimation of a mixed logit model. Although there are some similarities, we find that there is conflicting demand and supply side preferences for credit terms, collateral requirements, and loan use flexibility. We also analyse willingness to buy and willingness to offer for farmers and suppliers, respectively for the risk premium for different attributes and their levels. Identifying the preferred attributes and levels for both farmers and financial institutions can guide optimal packaging of insurance and credit providing market participation and adoption motivation for insurance-bundled credit product

Review of solar PV policies, interventions and diffusion in East Africa

Previous research on the diffusion of solar PV in Africa has mainly focused on solar home systems (SHS) in individual countries and thus overlooked developments in other PV market segments that have recently emerged. In contrast this paper adopts a regional perspective by reviewing developments in supportive policies, donor programs and diffusion status in all PV market segments in Kenya, Tanzania and Uganda, as well as identifying the key factors put forward in the literature to explain differences in the diffusion of SHS in these three countries. The paper finds two emerging trends: (i) a movement from donor and government-based support to market-driven diffusion of solar PV; and (ii) a transition from small-scale, off-grid systems towards mini-grids and large-scale, grid-connected solar power plants. The paper points out three generic factors that have contributed to encouraging SHS diffusion in all three countries: (i) the decline in world market prices for PV modules; (ii) the prolonged support from international donors; and (iii) conducive framework conditions provided by national governments. The paper also identifies five key factors that have been elaborated in the literature to explain the higher level of SHS diffusion in Kenya compared to Tanzania and Uganda: (i) a growing middle-class; (ii) geographical conditions; (iii) local sub-component suppliers; (iv) local champions; and (v) business culture. Finally, the paper discusses the lack of attention in the literature given to analysing the amount, nature and timing of donor and government support across countries, processes of learning and upgrading in local PV industries and the interaction between the different explanatory factors

The relationship between agricultural biodiversity, dietary diversity, household food security, and stunting of children in rural Kenya

CITATION: M’Kaibi, F. K., et al. 2017. The relationship between agricultural biodiversity, dietary diversity, household food security, and stunting of children in rural Kenya. Food Science and Nutrition, 5(2):243–254, doi:10.1002/fsn3.387.The original publication is available at https://onlinelibrary.wiley.comThe study was to determine the role of Dietary diversity (DD), household food security (HFS), and agricultural biodiversity (AB) on stunted growth in children. Two cross‐sectional studies were undertaken 6 months apart. Interviews were done with mothers/caregivers and anthropometric measurements of children 24–59 months old. HFS was assessed by household food insecurity access scale (HFIAS). A repeated 24‐h recall was used to calculate a dietary diversity score (DDS). Agricultural biodiversity (AB) was calculated by counting the number of edible plants and animals. The study was undertaken in resource‐poor households in two rural areas in Kenya. Mothers/Care givers and household with children of 24–59 months of age were the main subjects. The prevalence of underweight [WAZ <−2SD] ranged between 16.7% and 21.6% and stunting [HAZ <−2SD] from 26.3% to 34.7%. Mean DDS ranged from 2.9 to 3.7 and HFIAS ranged from 9.3 to 16.2. AB was between 6.6 and 7.2 items. Households with and without children with stunted growth were significantly different in DDS (P = 0.047) after the rainy season and HFIAS (P = 0.009) in the dry season, but not with AB score (P = 0.486). The mean AB for households with children with stunted growth were lower at 6.8, compared to 7.0 for those with normal growth, however, the difference was insignificant. Data indicate that households with children with stunted growth and those without are significantly different in DDS and HFIAS but not with AB. This suggests some potential in using DDS and HFIAS as proxy measures for stunting.https://onlinelibrary.wiley.com/doi/full/10.1002/fsn3.387Publisher's versio