These proceedings relate to a regional workshop which was held in Muscat, Oman, in January 2008.
This publication aims to inform the debate on the status of food security in Arab countries, and provide policy options for enhancing food security in the future, in line with the overarching directions of the 2030 Agenda for Sustainable Development. Given the heterogeneity of the Arab region, both in terms of natural endowment, particularly in water resources, and economic capabilities, the report’s analysis divides the region into four subregions, each consisting of a more homogeneous group of countries.
This regional workshop was designed to strengthen the capabilities of representatives of NIFUs for analyzing the situations of their NAIS, and to use their national experiences to identify strengths, weaknesses, and threats/challenges affecting seven key areas influencing development of NAIS, namely: (i) strategy/policy, (ii) institutional aspects, (iii) stakeholders, (iv) content, (v) people, (vi) infrastructure, and (vii) financial aspects. Possible solutions for the key weaknesses and threats /challenges were defined by participants.
This paper synthesizes Component 2 of the Regoverning Markets Programme. It is based on 38 empirical case studies where small-scale farmers and businesses connected successfully to dynamic markets, doing business with agri-processors and supermarkets. The studies aimed to derive models, strategies and policy principles to guide public and private sector actors in promoting greater participation of small-scale producers in dynamic markets. This publication forms part of the Regoverning Markets project.
The impact of the COVID-19 pandemic will vary for different groups of rural population, with the highest impact expected to be on farmers and other vulnerable groups, especially women and youth. Targeted support is feasible only by activating a network of actors or organizations within agricultural innovation systems (AIS) and promoting customized technologies and practices suitable for location specific contexts.
Mobile phone based money services have spread rapidly in many developing countries. We analyze micro level impacts using panel data from smallholder farmers in Kenya. Mobile money use has a large positive net impact on household income. One important pathway is through remittances, which contribute to income directly but also help to reduce risk and liquidity constraints, thus promoting agricultural commercialization. Mobile money users apply more purchased inputs, market a larger proportion of their output, and have higher farm profits.
Enhancing the diversity of agricultural production systems is increasingly recognized as a potential
means to sustainably provide diversified food for rural communities in developing countries, hence
ensuring their nutritional security. However, empirical evidences connecting farm production
diversity and farm-households’ dietary diversity are scarce. Using comprehensive datasets of
market-oriented smallholder farm households from Indonesia and Kenya, and subsistence farmers
Supermarkets and high-value exports are currently gaining ground in the agri-food systems of many developing countries. While recent research has analyzed income effects in the small farm sector, impacts on farming efficiency have hardly been studied. Using a survey of Kenyan vegetable growers and a stochastic frontier approach, we show that participation in supermarket channels increases mean technical efficiency by 19%. This gain is bigger at lower levels of efficiency, suggesting the potential for positive income distribution effects.
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.