Types of Research
This four-part analysis describes the current suite of food security measures, then analyzes the respective relationships between food security and poverty, GDP, and crop yields using findings from in-depth literature reviews. Food security measures are criticized for inaccurately characterizing food security at individual, household, and national scales, yet guidelines exist to prescribe a food security measure for a given situation. Some authors see the potential of a combination of indicators that apply at different scales rather than a single, universal food security measure. Limited literature exists on the relationship between food security and poverty, GDP, or crop yields. The relationship between food security and poverty is particularly challenging because neither term has a consistent definition, and the limited literature suggests a lack of consensus among experts. Little empirical research exists on the relationship between food security and GDP, though studies generally note an association between the two Studies that evaluate food security and crop yields provide limited evidence that the two are associated, though many studies use measures of crop yield as food security indicators and vice versa. More research is needed to establish whether there are preferred food security measurement tools for specific scales and situations, and to further explore the relationship between food security and poverty, GDP, and crop yields.
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).
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.
Our initial agriculture capacity building search revealed best practices including institutional partnership building, cross-border opportunities such as ‘twinning,’ and views that these practices are most effective when accompanied by appropriate policies and regulatory frameworks to incentivize return on education to home countries. In addition, the literature explained the historical and political context in which some countries successfully built higher educational capacity, suggesting a set of socio-political conditions necessary for a ‘surge’ in capacity building to occur. Our results raised questions about challenges shaping these best practices (e.g. “brain drain” leading to the need for cross-border opportunities) as well as possible approaches to address these underlying issues. To further examine identified challenges from our initial findings, we re-oriented our search to investigate retention strategies, regional or intra-national network capacity building approaches, and whether there is in fact a need for higher education capacity in all countries through comparative advantage or otherwise. This report presents a review of the literature on the best and worst practices for national agricultural capacity building when investing in a country's higher education system or when investing directly in national or relevant global research capacity. We find that several countries have successfully employed a variety of retention, return, and diaspora strategies to build capacity by capitalizing on the feedback loops of international mobility. In addition, several countries in Africa have employed strategies to address the rural-to-urban “brain drain” by prioritizing education of students with post-secondary rural agricultural work experience and strong ties to rural communities in order to return the benefit of this education to local communities. The report discusses these and other strategies as well as analysis related to the ‘whole system effect’ of higher education and subsequent ‘need’ for Higher Agricultural Education (HAE) capacity in all countries.
This literature review examines the returns to tertiary agricultural sciences education, particularly in Sub-Saharan Africa (SSA). We include information from organizations’ program documents and gray literature, including the World Bank, UNESCO, ILO, IFPRI, ASTI, various Ministries of Education, country-specific NARS, and ADBG. We find no calculated rate of return (RoR) to tertiary agricultural science, including in SSA. We do find estimates for the return on tertiary education in general, ranging from 12-30% in SSA, along with qualitative support for the value of agricultural science education. The private value of this education can be somewhat inferred from the unmet demand of African students for agricultural science training in North America, Europe, and Australia, and the private and social value from the demand for educated researchers in NARS and SSAQ labor markets. Educated agricultural scientists are hypothesized to affect agricultural productivity via research and development and their influence on policy. Despite the dearth of quantitative ROR evidence, we do find several articles describing the need for increased higher agricultural education and proposing recommendations toward this aim. In this report, we summarize these qualitative results as evidence of the value of tertiary education.
This brief provides an overview of the national and zonal characteristics of agricultural production in Tanzania using the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). More detailed information and analysis is available in the separate EPAR Tanzania LSMS-ISA Reference Report, Sections A-G.
This brief presents a comparative analysis of men and women and of male- and female-headed households in Tanzania using data from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We compare farm activity, productivity, input use, and sales as well as labor allocations by gender of the respondent and of the household head. In households designated “female-headed” a woman was the decision maker in the household, took part in the economy, control and welfare of the household, and was recognized by others in the household as the head. For questions regarding household labor (both non-farm and farm), the gender of the individual laborer is recorded, and we use this to illustrate the responsibilities of male and female household members. An appendix provides the details for our analyses.
This is "Section B" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of household characteristics by gender and by administrative zone, considering landholding size, number of crops grown, yields, livestock, input use, and food consumption.
This is "Section H" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analysis of nutrition and malnutrition, and of the variation across agricultural and non-agricultural households, gender, age, and zones. For example, we find that stunting (low height for age) was the most prevalent indicator of malnutrition, with 43% of the under-five population categorized in the moderate to severe range, while less than 17% children under the age of five were reported to be underweight (low weight for age). A higher proportion of children in female-headed households experienced stunting (46% versus 42% in male-headed households) and were underweight (19% versus 16% in male-headed households).
This is "Section G" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of data related to consumption of priority foods, total value of consumption, levels of food consumption and production, including analyses by zone in Tanzania. We find, for example, that the mean total value of household consumption was higher for agricultural households (US$27.28) compared to non-agricultural households (US$26.59), but the mean per capita value of household consumption was higher for non-agricultural households (US$7.32) compared to agricultural households (US$5.24). The mean per capita value of weekly consumption for the Southern zone was only US$5.34, compared to the highest mean per capita value of US$6.63 in the Eastern zone. The Central zone still had the lowest per capita value of consumption at US$4.40.