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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 is "Section B" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of household characteristics by gender and by administrative zone, considering landholding size, number of crops grown, yields, livestock, input use, and food consumption.
This is "Section E" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of livestock and livestock by-product characteristics by gender of household head and by zones, as well as our analyses of livestock disease, vaccines, and theft.
This is "Section D" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of basic farm characteristics, land and labor productivity, crop sales, yield measures, intercropping, and pre- and post-harvest losses, including comparisons by gender of household head and by zone.
This is the introductory section of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present an overview of report sections, as well as an executive summary of findings on crops and livestock, constraints to productivity, and productivity and nutrition outcomes.
This is "Section C" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of the basic characteristics of household heads and other household members, as well as our analyses of education for adults, children, and household heads by gender and zone.
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.
This report combines analyses from four previous EPAR briefs on the effects of climate change on maize, rice, wheat, sorghum, and millet production in Sub-Saharan Africa (SSA). In addition, this brief presents new analysis of the projected impact of climate changes in SSA. We include comparisons of the importance of each crop, of their vulnerability to climate change, and of the research and policy resources dedicated to each. Especially with respect to climatic susceptibility, these rankings provide a comparative summary based upon the analysis conducted in the four previous EPAR briefs, statistical analyses of historical yield and climate data, and future climate model predictions. According to the indicators analyzed, our research suggests that maize leads the cereal crops in terms of importance within SSA and in terms of research and policy attention. Our analysis of climate conditions and the crop’s physical requirements suggests that many maize-growing areas are likely to move outside the range of ideal temperature and precipitation conditions for maize production. Rice is the third most important crop in terms of consumption dependency, fourth in terms of production, but second only to maize in terms of research funding and FTEs. Sorghum and millet rank second and third in production importance and second and fifth in consumption importance, but rank below maize and rice in terms of FTE researchers. Their role is complicated by the fact that they are often considered inferior goods; SSA consumers often substitute away from sorghum and millet consumption if they are able to do so. Wheat is the least-produced crop of the five, and the second to last in terms of consumption importance. However, it still ranks above millet in terms of FTE researchers.