Year Published
- 2008 (0)
- 2009 (2) Apply 2009 filter
- 2010 (3) Apply 2010 filter
- 2011 (8) Apply 2011 filter
- 2012 (12) Apply 2012 filter
- 2013 (6) Apply 2013 filter
- 2014 (2) Apply 2014 filter
- 2015 (4) Apply 2015 filter
- (-) Remove 2016 filter 2016
- 2017 (6) Apply 2017 filter
- 2018 (0)
- (-) Remove 2019 filter 2019
- 2020 (0)
- 2021 (0)
Research Topics
Populations
- Countries/Governments (0)
- Rural Populations (1) Apply Rural Populations filter
- Smallholder Farmers (0)
- Women (0)
Types of Research
Geography
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Global filter Global
- South Asia Region and Selected Countries (0)
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (1) Apply Sub-Saharan Africa filter
- West Africa Region and Selected Countries (0)
Dataset
Current search
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Education & Training filter Education & Training
- (-) Remove Agricultural Inputs & Farm Management filter Agricultural Inputs & Farm Management
- (-) Remove Global filter Global
- (-) Remove Market & Value Chain Analysis filter Market & Value Chain Analysis
- (-) Remove 2019 filter 2019
- (-) Remove 2016 filter 2016
While literature on achieving Inclusive Agricultural Transformation (IAT) through input market policies is relatively robust, literature on the effect of output market policies on IAT is rarer. We conduct a selective literature review of output market policies in low- and middle-income countries to assess their influence on IAT and find that outcomes are mixed across all policy areas. We also review indicators used to measure successful IAT, typologies of market institutions involved in IAT, and agricultural policies and maize yield trends in East Africa. This report details our findings on these connected, yet somewhat disparate elements of IAT to shed more light on a topic that has not been the primary focus of the literature thus far.
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.
There is a wide gap between realized and potential yields for many crops in Sub-Saharan Africa (SSA). Experts identify poor soil quality as a primary constraint to increased agricultural productivity. Therefore, increasing agricultural productivity by improving soil quality is seen as a viable strategy to enhance food security. Yet adoption rates of programs focused on improving soil quality have generally been lower than expected. We explore a seldom considered factor that may limit farmers’ demand for improved soil quality, namely, whether farmers’ self-assessments of their soil quality match soil scientists’ assessments. In this paper, using Tanzania National Panel Survey (TZNPS) data, part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA), we compare farmers’ own assessments of soil quality with scientific measurements of soil quality from the Harmonized World Soil Database (HWSD). We find a considerable “mismatch” and most notably, that 11.5 percent of survey households that reported having “good” soil quality are measured by scientific standards to have severely constrained nutrient availability. Mismatches between scientific measurements and farmer assessments of soil quality may highlight a potential barrier for programs seeking to encourage farmers to adopt soil quality improvement activities.