Types of Research
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The private sector is the primary investor in health research and development (R&D) worldwide, with investment annual investment exceeding $150 billion, although only an estimated $5.9 billion is focused on diseases that primarily affect low and middle-income countries (LMICs) (West et al., 2017b). Pharmaceutical companies are the largest source of private spending on global health R&D focused on LMICs, providing $5.6 billion of the $5.9 billion in total private global health R&D per year. This report draws on 10-K forms filed by Pharmaceutical companies with the U.S. Securities and Exchange Commission (SEC) in the year 2016 to examine the evidence for five specific disincentives to private sector investment in drugs, vaccines and therapeutics for global health R&D: scientific uncertainty, weak policy environments, limited revenues and market uncertainty, high fixed costs for research and manufacturing, and imperfect markets. 10-K reports follow a standard format, including a business section and a risk section which include information on financial performance, investment options, lines of research, promising acquisitions and risk factors (scientific, market, and regulatory). As a result, these filings provide a valuable source of information for analyzing how private companies discuss risks and challenges as well as opportunities associated with global health R&D targeting LMICs.
In this brief, we report on measures of economic growth, poverty and agricultural activity in Ethiopia. For each category of measure, we first describe different measurement approaches and present available time series data on selected indicators. We then use data from the sources listed below to discuss associations within and between these categories between 1994 and 2017.
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.