This study utilizes a recursive dynamic general equilibrium model calibrated with data for Tanzania to explore the link between agricultural and rural development spending and four development outcomes: economic growth, job creation, poverty reduction, and diet quality. Results show that no single expenditure option is the most effective in achieving all four desired development outcomes for Tanzania. Productivity-enhancing agricultural interventions in horticulture are effective at generating growth in the agri-food system (AFS) and improving diets, but have a limited effect on employment. Supporting cereal producers has large effects on growth and poverty reduction, with relatively high returns per dollar invested, but its effect on diet quality is weak. Providing livestock services to milk and poultry farmers consistently ranks high across the outcome indicators, with strong employment effects on downstream AFS. Crop research and development and feeder roads generate moderate impacts on all four outcomes. Partially reallocating the budget towards the most cost-effective spending options can substantially increase the development effectiveness for Tanzania of agriculture sector support expenditures. The approach adopted in this study can help policymakers design and prioritize agricultural interventions and expenditure portfolios that better reflect the country’s broad food system.

Research paper, agricultural development, role in economic development, structural change in the agricultural sector - theoretical aspects, decision making, agricultural production production factors, farm households, agricultural technology issues, agricultural policies for speeding up modernization, etc. Graph, references, tables.

The Innovation for Agribusiness (InovAgro) project, which launched with its first three year phase in 2010, uses a market system development (MSD) approach towards the goal of increasing incomes of men and women small-scale farmers in northern Mozambique. InovAgro interventions promote improved agricultural productivity, participation in selected high-potential value chains and the development of inclusive and sustainable market systems, such that impacts are expected to last long beyond the termination of the project. This paper presents results from a midline quantitative impact evaluation of the second phase of the InovAgro project interventions (2014-2017). In it, we use a carefully designed and executed quasi-experimental study design to credibly attribute changes in market engagement and welfare of participating farmers to exposure to the InovAgro II project, identifying and testing in what respects the intervention was most successful, and what regard it had less impact. Although InovAgro II projects operate in 11 districts of Zambézia and Cabo Delgado provinces, this impact evaluation focuses on two districts in Zambézia province (Alto Molócue and Molumbo), and in terms of value chains, focuses on the soybean and pigeon pea high-potential value chains, while the InovAgro II project interventions focus on these in addition to maize, sesame and groundnut. A baseline survey was undertaken in 2015 covering the 2014/2015 agricultural season and a midline follow-up survey was conducted in 2017, covering the 2016/2017 agricultural season and reaching 1,749 households of the original 1,886 households interviewed in the baseline survey. Using difference-in-difference estimation and propensity score matching, we find that exposure to the InovAgro II project is associated with an increase in the proportion of households selling soybean and pigeon pea by approximately 5% and 16%, respectively (significant at the .01 level). Exposure to the InovAgro II project also results in significantly higher shares of smallholder farmers using improved seed for soybean and pigeon pea (an increase of 6% for soybean and 2% for pigeon pea). We find that the InovAgro II project is also associated with significant increases in access to agricultural output market information from formal sources (5%) and hired labor for farming activities (8%). Despite the significant impacts on short term outcome variables, exposure to the InovAgro II project had limited impact on long term outcome variables, such as on rural-urban migration as well as engagement in the non-farm sector (two proxies for assessing potential welfare implications of the project) however this finding is not surprising given the impact evaluation covers only two years-a short period of time to bring about the long-term impacts expected to eventually emanate from an MSD project.

This framework presents ten interrelated principles/elements to guide Sustainable Agricultural Mechanization in Africa (SAMA). Further, it presents the technical issues to be considered under SAMA and the options to be analysed at the country and sub regional levels. The ten key elements required in a framework for SAMA are as follows: The analysis in the framework calls for a specific approach, involving learning from other parts of the world where significant transformation of the agricultural mechanization sector has already occurred within a three-to-four decade time frame, and developing policies and programmes to realize Africa’s aspirations of Zero Hunger by 2025. This approach entails the identification and prioritization of relevant and interrelated elements to help countries develop strategies and practical development plans that create synergies in line with their agricultural transformation plans. Given the unique characteristics of each country and the diverse needs of Africa due to the ecological heterogeneity and the wide range of farm sizes, the framework avoids being prescriptive.

The Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) scheme aims to provide income support to farmers to facilitate timely access to inputs by easing their liquidity needs. This study, based on 1,406 farmers of Uttar Pradesh and using a binary choice model, examines the scheme’s targeting accuracy and the correlates of farmers’ spending patterns. Triple difference with matching estimators are used to identify the differential impact of PM-KISAN on Krishi Vigyan Kendras (farm science centers, or KVKs) beneficiaries. Results show that PM-KISAN reached to one-third of all the farmers in the first three months of its implementation. Moreover, the study finds no selection bias based on social, economic and agricultural characteristics. The scheme has significantly helped those who are relatively more dependent on agriculture and have poor access to credit. Moreover, scheme has significantly stimulated the KVK ’s impact on the adoption of modern cultivars.