Year Published
- 2008 (0)
- 2009 (1) Apply 2009 filter
- 2010 (0)
- 2011 (0)
- 2012 (0)
- 2013 (0)
- 2014 (0)
- 2015 (0)
- 2016 (0)
- 2017 (1) Apply 2017 filter
- 2018 (0)
- 2019 (1) Apply 2019 filter
- 2020 (0)
- 2021 (0)
Research Topics
Populations
Types of Research
- (-) Remove Data Analysis filter Data Analysis
- Literature Review (4) Apply Literature Review filter
- Portfolio Review (0)
- (-) Remove Research Brief filter Research Brief
Geography
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- Global (0)
- South Asia Region and Selected Countries (1) Apply South Asia Region and Selected Countries filter
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (1) Apply Sub-Saharan Africa filter
- (-) Remove West Africa Region and Selected Countries filter West Africa Region and Selected Countries
Dataset
- ASTI (0)
- (-) Remove FAOSTAT filter FAOSTAT
- Farmer First (0)
- LSMS & LSMS-ISA (4) Apply LSMS & LSMS-ISA filter
- (-) Remove Other Datasets filter Other Datasets
Current search
- (-) Remove West Africa Region and Selected Countries filter West Africa Region and Selected Countries
- (-) Remove Research Brief filter Research Brief
- (-) Remove Political Economy & Governance filter Political Economy & Governance
- (-) Remove Food Security & Nutrition filter Food Security & Nutrition
- (-) Remove FAOSTAT filter FAOSTAT
- (-) Remove Other Datasets filter Other Datasets
- (-) Remove Data Analysis filter Data Analysis
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
Studies of improved seed adoption in developing countries almost always draw from household surveys and are premised on the assumption that farmers are able to self-report their use of improved seed varieties. However, recent studies suggest that farmers’ reports of the seed varieties planted, or even whether seed is local or improved, are sometimes inconsistent with the results of DNA fingerprinting of farmers' crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted in fields. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use, including seed, fertilizer, and labor allocations, reveals that farmers tend to treat improved maize differently, depending on whether they correctly perceive it as improved. This suggests that errors in farmers' seed type awareness may translate into suboptimal management practices. In econometric analysis, the measured yield benefit of improved seed use is smaller in magnitude with a DNA-derived categorization, as compared with farmer reports. The greatest yield benefit is with correctly identified improved seed. This indicates that investments in farmers' access to information, seed labeling, and seed system oversight are needed to complement investments in seed variety development.
Nigeria’s experience with fertilizer subsidy programs has been different than that of other countries in Sub-Saharan Africa. Nigeria is one of the only African countries capable of producing fertilizer domestically. But Nigeria is also large and densely populated. This makes national agricultural policy difficult due to logistical problems with implementation and the unique fertilizer needs of the various agro-ecological zones. This research brief discusses the effects of Nigeria’s input subsidy programs on maize production and fertilizer consumption. It focuses on the years 2000 to 2007, but also includes a discussion of Nigeria’s subsidy history from the early 1970s to 2009. Researchers have had difficulty studying Nigeria’s subsidy schemes due to a lack of data. In spite of decades of authoritarian, centralized leadership, Nigeria’s states have significant power to implement their own subsidies. This complicates any evaluation of a program’s effectiveness, in part due to the variety of subsidies at any given time, as well as inconsistent accounting practices.