Types of Research
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove 2016 filter 2016
- (-) Remove 2013 filter 2013
- (-) Remove Education & Training filter Education & Training
Household survey data are a key source of information for policy-makers at all levels. In developing countries, household data are commonly used to target interventions and evaluate progress towards development goals. The World Bank’s Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) are a particularly rich source of nationally-representative panel data for six Sub-Saharan African countries: Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda. To help understand how these data are used, EPAR reviewed the existing literature referencing the LSMS-ISA and identified 415 publications, working papers, reports, and presentations with primary research based on LSMS-ISA data. We find that use of the LSMS-ISA has been increasing each year since the first survey waves were made available in 2009, with several universities, multilateral organizations, government offices, and research groups across the globe using the data to answer questions on agricultural productivity, farm management, poverty and welfare, nutrition, and several other topics.
This paper is the third in EPAR’s series on Higher Education in Africa. Our research tasks in this phase build on Phase I, in which we sought to identify measurable rates of return on tertiary agricultural education in Africa and describe the current state of African higher agricultural education (HAE), and Phase II, in which we identified countries’ experiences with national higher education capacity building through partnership building, cross-border opportunities such as ‘twinning,’ and various retention and diaspora engagement strategies. In this phase we discuss successful regional education models, particularly in Sub-Saharan Africa. We have organized our findings and analysis into three sections.The first section organizes the literature under categories of regional higher education models or ‘hubs’ and discusses measurement of the regional impact of higher education. The second section provides bibliometric data identifying academically productive countries and universities in Sub-Saharan Africa.The final section provides a list of regional higher education models identified in the literature and through a web-based review of existing higher education networks and hubs. We also include a list of challenges and responses to regional coordination.