By 2013, there was remarkable achievement in Malawi in terms of bean varietal output, but information on farm level use of these varieties, their contribution to bean productivity and household food security was lacking. An ex-post study was conducted to assess the extent of adoption of improved bean varieties and their associated impacts on food security among the adopting bean growing households. The study also generated sex disaggregated data on labour contributions, access to extension services & credit, group networks and control over income from beans; that was used to examine gender biases in bean production and identify feasible interventions to enhanced gender equality. Also of interest was to understand the progress on seed systems measured by improved seed availability and affordability by those who need it as well as the degree of bean commercialization. The information was gathered through a survey of a sample of 611 households selected from 48 villages across twelve bean producing districts across the three regions (northern, central and southern) of Malawi. The sample design was motived by the need to identify representative samples of adopters and non-adopters so as to draw inferences on impact while controlling for confounding factors. A stratified multi stage sampling was followed in selecting the households for the survey
This household survey was conducted across 322 households in the four sub counties of Nwoya district (Anaka, Alero, Purongo and Kochgoma) in December 2017. This was an end line survey that was conducted as part of the project increasing food security and farming systems resilience through wide scale adoption of climate smart agricultural (CSA) technologies. The main aim for this survey was to link CSA adoption with nutrition and resilience. This knowledge could potentially policy makers and development practitioners about the influence of CSA on nutrition and livelihoods of farmers in Nwoya district. Since CSA technologies as well as dissemination methods are context specific, such knowledge would provide information on promoting the most relevant CSA technologies. That is CSA technologies that have a positive impact on nutrition, resilience and other livelihood indicators.
Types of data collected include:
- Geographical location of the farmers,
- Shocks that affected farmers economically,
- Market Access,
- Food household basket and food expenditure,
- Non-food expenditure,
- Food insecurity experience scale,
- Food scarcity and seasonality.
- Market Access,