Year Published
- 2008 (0)
- 2009 (6) Apply 2009 filter
- 2010 (1) Apply 2010 filter
- 2011 (1) Apply 2011 filter
- 2012 (0)
- 2013 (1) Apply 2013 filter
- (-) Remove 2014 filter 2014
- 2015 (3) Apply 2015 filter
- (-) Remove 2016 filter 2016
- 2017 (3) Apply 2017 filter
- 2018 (2) Apply 2018 filter
- (-) Remove 2019 filter 2019
- 2020 (1) Apply 2020 filter
- 2021 (2) Apply 2021 filter
Research Topics
Populations
- (-) Remove Countries/Governments filter Countries/Governments
- Rural Populations (1) Apply Rural Populations filter
- (-) Remove Smallholder Farmers filter Smallholder Farmers
- Women (3) Apply Women filter
Types of Research
- Data Analysis (1) Apply Data Analysis filter
- Literature Review (1) 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
- Global (0)
- South Asia Region and Selected Countries (0)
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (0)
- West Africa Region and Selected Countries (1) Apply West Africa Region and Selected Countries filter
Dataset
- ASTI (0)
- FAOSTAT (0)
- Farmer First (0)
- LSMS & LSMS-ISA (0)
- Other Datasets (1) Apply Other Datasets filter
Current search
- (-) Remove Market & Value Chain Analysis filter Market & Value Chain Analysis
- (-) Remove 2014 filter 2014
- (-) Remove Poverty filter Poverty
- (-) Remove Health filter Health
- (-) Remove Finance & Investment filter Finance & Investment
- (-) Remove 2016 filter 2016
- (-) Remove Development Finance & Policy filter Development Finance & Policy
- (-) Remove Aid & Other Development Finance filter Aid & Other Development Finance
- (-) Remove Countries/Governments filter Countries/Governments
- (-) Remove Smallholder Farmers filter Smallholder Farmers
- (-) Remove 2019 filter 2019
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.
Common aid allocation formulas incorporate measures of income per capita but not measures of poverty, likely based on the assumption that rising average incomes are associated with reduced poverty. If declining poverty is the outcome of interest, however, the case of Nigeria illustrates that such aid allocation formulas could lead to poorly targeted or inefficient aid disbursements. Using data from the World Bank and the Nigerian National Bureau of Statistics, we find that while the relationship between economic growth and poverty in Nigeria varies depending on the time period studied, overall from 1992-2009 Nigeria’s poverty rate has only declined by 6% despite a 70% increase in per capita gross domestic product (GDP). A review of the literature indicates that income inequality, the prominence of the oil sector, unemployment, corruption, and poor education and health in Nigeria may help to explain the pattern of high ongoing poverty rates in the country even in the presence of economic growth. Our analysis is limited by substantial gaps in the availability of quality data on measures of poverty and economic growth in Nigeria, an issue also raised in the literature we reviewed, but our findings support arguments that economic growth should not be assumed to lead to poverty reduction and that the relationship between these outcomes likely depends on contextual factors.