Types of Research
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Technology filter Technology
- (-) Remove Sustainable Agriculture & Rural Livelihoods filter Sustainable Agriculture & Rural Livelihoods
- (-) Remove Farmer First filter Farmer First
- (-) Remove Smallholder Farmers filter Smallholder Farmers
- (-) Remove Other Datasets filter Other Datasets
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.
This brief explores agricultural data for Tanzania from the LSMS-ISA and Farmer First household surveys. We first present the differences in the LSMS and Farmer First survey design and in basic descriptives from the two data sources. We then present the results of our initial LSMS data analysis using the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), focusing on the agricultural data, before presenting our analysis of farmer aspirations and of gender differences using the Farmer First data.
In Tanzania, agriculture represents approximately 50 percent of GDP, 80 percent of rural employment, and over 50 percent of the foreign exchange earnings. Yet poor soil fertility and resulting low productivity contribute to low economic growth and widespread poverty. Chemical fertilizer has the potential to contribute to crop yield increases. Yet high prices and weaknesses in the fertilizer market keep fertilizer use low. This literature review examines the history of government interventions that have intended to increase access to fertilizers, and reviews current policies, market structure, and challenges that contribute to the present conditions. We find that despite numerous strategies over the last fifty years, from heavy government involvement to liberalization, major weaknesses in Tanzania’s fertilizer market prevent efficient use of fertilizer. High transportation costs, low knowledge level of farmers and agrodealers, unavailability of improved seed, and limited access to credit all contribute to the market’s problems. The government’s current framework, the Tanzania Agriculture Input Partnership (TAIP), acknowledges this interconnectedness by targeting multiple components of the market. This model could help Tanzania tailor solutions relevant to specific road, soil, and market conditions of different areas of the country, contributing to enhanced food security and economic growth.