Year Published
- 2008 (1) Apply 2008 filter
- 2009 (16) Apply 2009 filter
- 2010 (14) Apply 2010 filter
- 2011 (8) Apply 2011 filter
- 2012 (2) Apply 2012 filter
- 2013 (6) Apply 2013 filter
- 2014 (3) Apply 2014 filter
- 2015 (8) Apply 2015 filter
- (-) Remove 2016 filter 2016
- 2017 (5) Apply 2017 filter
- 2018 (1) Apply 2018 filter
- 2019 (1) Apply 2019 filter
- 2020 (1) Apply 2020 filter
- 2021 (2) Apply 2021 filter
Research Topics
Populations
- Countries/Governments (0)
- Rural Populations (0)
- Smallholder Farmers (0)
- Women (0)
Types of Research
- Data Analysis (1) Apply Data Analysis filter
- Literature Review (2) Apply Literature Review filter
- Portfolio Review (0)
- Research Brief (0)
Geography
- East Africa Region and Selected Countries (1) Apply East Africa Region and Selected Countries filter
- (-) Remove Global filter Global
- South Asia Region and Selected Countries (0)
- Southern Africa Region and Selected Countries (1) Apply Southern Africa Region and Selected Countries filter
- (-) Remove Sub-Saharan Africa filter Sub-Saharan Africa
- West Africa Region and Selected Countries (0)
Dataset
- ASTI (1) Apply ASTI filter
- FAOSTAT (1) Apply FAOSTAT filter
- Farmer First (0)
- LSMS & LSMS-ISA (2) Apply LSMS & LSMS-ISA filter
- Other Datasets (0)
Current search
- (-) Remove Sub-Saharan Africa filter Sub-Saharan Africa
- (-) Remove 2016 filter 2016
- (-) Remove Development Finance & Policy filter Development Finance & Policy
- (-) Remove Sustainable Agriculture & Rural Livelihoods filter Sustainable Agriculture & Rural Livelihoods
- (-) Remove Aid & Other Development Finance filter Aid & Other Development Finance
- (-) Remove Research & Development filter Research & Development
- (-) Remove Global filter Global
This research considers how public good characteristics of different types of research and development (R&D) and the motivations of different providers of R&D funding affect the relative advantages of alternative funding sources. We summarize the public good characteristics of R&D for agriculture in general and for commodity and subsistence crops in particular, as well as R&D for health in general and for neglected diseases in particular, with a focus on Sub-Saharan Africa and South Asia. Finally, we present rationales for which funders are predicted to fund which R&D types based on these funder and R&D characteristics. We then compile available statistics on funding for agricultural and health R&D from private, public and philanthropic sources, and compare trends in funding from these sources against expectations. We find private agricultural R&D spending focuses on commodity crops (as expected). However contrary to expectations we find public and philanthropic spending also goes largely towards these same crops rather than staples not targeted by private funds. For health R&D private funders similarly concentrate on diseases with higher potential financial returns. However unlike in agricultural R&D, in health R&D we observe some specialization across funders – especially for neglected diseases R&D - consistent with funders’ expected relative advantages.
Common estimates of agricultural productivity rely upon crude measures of crop yield, typically defined as the weight harvested of a crop divided by the area harvested. But this common yield measure poorly reflects performance among farm systems combining multiple crops in one area (e.g., intercropping), and also ignores the possibility that farmers might lose crop area between planting and harvest (e.g., partial crop failure). Drawing on detailed plot-level data from the LSMS-ISA in Tanzania, Nigeria, and Ethiopia, we show how various yield measurement decisions affect estimates of smallholder yields for a variety of crops. We consider the effect of measuring production by plot area, area planted, and area harvested, of trimming the top 1% and 2% of values, and of considering different groups of farmers according to total area planted.
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.