Types of Research
- (-) Remove West Africa Region and Selected Countries filter West Africa Region and Selected Countries
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- (-) Remove Food Security & Nutrition filter Food Security & Nutrition
- (-) Remove Health filter Health
- (-) Remove Market & Value Chain Analysis filter Market & Value Chain Analysis
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- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
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Cereal yield variability is influenced by initial conditions such as suitability of the farming system for cereal cultivation, current production quantities and yields, and zone-specific potential yields limited by water availability. However, exogenous factors such as national policies, climate, and international market conditions also impact farm-level yields directly or provide incentives or disincentives for farmers to intensify production. We conduct a selective literature review of policy-related drivers of maize yields in Ethiopia, Kenya, Malawi, Rwanda, Tanzania, and Uganda and pair the findings with FAOSTAT data on yield and productivity. This report presents our cumulative findings along with contextual evidence of the hypothesized drivers behind maize yield trends over the past 20 years for the focus countries.
The review consists of a summary of the emergence of agribusiness clusters, SEZs and incubators since 1965 (with a focus on smallholder agriculture-based economies in Latin America, Africa, and Asia), followed by a series of brief case studies of example programs with particular relevance for guiding proposed clusters/incubators in the countries of Ethiopia, Tanzania, Nigeria and the Eastern Indian states of Uttar Pradesh, Bihar, and Odisha. Summary conclusions draw upon published reports and primary analysis of case studies to highlight apparent determinants of success and failure in agribusiness investment clusters and incubators, including characteristics of the business environment (markets, policies) and characteristics of the organizational structure (clusters, accelerators) associated with positive smallholder outcomes.
This report reviews the current body of peer-reviewed scholarship exploring the impacts of morbidity on economic growth. This overview seeks to provide a concise introduction to the major theories and empirical evidence linking morbidity – and the myriad different measures of morbidity – to economic growth, which is defined primarily in terms of gross domestic product (GDP) and related metrics (wages, productivity, etc.). Through a systematic review of published manuscripts in the fields of health economics and economic development we further identify the most commonly-used pathways linking morbidity to economic growth. We also highlight the apparent gaps in the empirical literature (i.e., theorized pathways from morbidity to growth that remain relatively untested in the published empirical literature to date).
Donors and governments are increasingly seeking to implement development projects through self-help groups (SHGs) in the belief that such institutional arrangements will enhance development outcomes, encourage sustainability, and foster capacity in local civil society – all at lower cost to coffers. But little is known about the effectiveness of such institutional arrangements or the potential harm that might be caused by using SHGs as ‘vehicles’ for the delivery of development aid. This report synthesizes available evidence on the effectiveness of Self-Help Groups (SHGs) in promoting health, finance, agriculture, and empowerment objectives in South Asia and Sub-Saharan Africa. Our findings are intended to inform strategic decisions about how to best use scarce resources to leverage existing SHG interventions in various geographies and to better understand how local institutions such as SHGs can serve as platforms to enhance investments.
The purpose of this analysis is to provide a measure of marketable surplus of maize in Tanzania. We proxy marketable surplus with national-level estimates of total maize sold, presumably the surplus for maize producing and consuming households. We also provide national level estimates of total maize produced and estimate “average prices” for Tanzania which allows this quantity to be expressed as an estimate of the value of marketable surplus. The analysis uses the Tanzanian National Panel Survey (TNPS) LSMS – ISA which is a nationally representative panel survey, for the years 2008/2009 and 2010/2011. A spreadsheet provides our estimates for different subsets of the sample and using different approaches to data cleaning and weighting. The total number of households for Tanzania was estimated with linear extrapolation based on the Tanzanian National Bureau of Statistics for the years 2002 and 2012. The weighted proportions of maize-producing and maize-selling households were multiplied to the national estimate of total households. This estimate of total Tanzanian maize-selling and maize-producing households was then multiplied by the average amount sold and by the average amount produced respectively to obtain national level estimates of total maize sold and total maize produced in 2009 and 2011.