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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 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.
Water is a critical input for significantly enhancing smallholder farmer productivity in Sub-Saharan Africa (SSA) where less than 5% of farm land is irrigated, and in India where 42% of farm land is irrigated. For many years, donors have invested in human-powered treadle pump technologies as a point of entry for smallholder farmers unable to afford motorized pumps. In spite of some successes in treadle pump promotion, however, there is a widespread perception that as soon as smallholder farmers can afford to they quickly transition to motorized diesel- powered pumps. While diesel pumps substantially ease farmers’ workload, they pollute excessively (both in terms of local air quality and greenhouse gas emissions), pump excessive amounts of water, and put farmers at the mercy of cyclical spikes in fuel prices. This brief provides an overview of state-of-the-art alternative energy pumps, including technologies available and implementation lessons learned from China, India, Africa, South America and other regions. Through a literature review, written surveys and phone interviews with water pump producers and non-governmental organizations (NGOs) we evaluate the availability, affordability, and adoption rates of alternative energy technologies in developing countries. Our findings suggest that no single alternative energy water pumping system is a “silver bullet” for rural smallholder irrigation needs. Biofuels may prove a successful short- to intermediate-term solution for farmers who already have access to diesel pumps, but other problems associated with diesel engines, including high maintenance costs and excessive water use remain even when biofuels are used. Solar systems eliminate pollution almost entirely, reduce water consumption, and eliminate the need to purchase fuels. However solar systems are typically prohibitively expensive for smallholder farmers. Wind powered pumping solutions have not proven successful to date, with high costs and irregular wind patterns (either too little or too much wind) proving substantial barriers to widespread adoption.