Types of Research
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Sub-Saharan Africa filter Sub-Saharan Africa
- (-) Remove Research & Development filter Research & Development
- (-) Remove Food Security & Nutrition filter Food Security & Nutrition
- (-) Remove Labor & Time Use filter Labor & Time Use
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.
An ongoing stream of EPAR research considers how public good characteristics of different types of research and development (R&D) and the motivations of different providers of R&D funding affect the relative advantages of alternative funding sources. For this project, we seek to summarize the key public good characteristics of R&D investment for agriculture in general and for different subsets of crops, and hypothesize how these characteristics might be expected to affect public, private, or philanthropic funders’ investment decisions.
Labor is one of the most productive assets for many rural households in developing countries. Despite the importance of labor—and time use more generally—little research has empirically examined the quality of time-use data in household surveys. Many household surveys rely on respondent recall, the reliability of which may decrease as recall length increases. In addition, respondents often report on time allocation for the entire household, which they may not know or recall as clearly as their own time allocation. Finally, simultaneous activities such as tending children while preparing dinner, may lead to the systematic underestimation of certain activities, particularly those that tend to be performed by women. This paper examines whether the identity of the survey respondent affects estimates of time allocation within the household. Drawing on the Ugandan LSMS-ISA household survey, we find that individuals responding for themselves report higher levels of time use over the previous week than when responding for other household members. Moreover, male respondents tend to underreport time allocation for females over the age of 15 as compared to female respondents, especially time spent on domestic activities. In addition, an analysis of the effects of two economics shocks—having a baby and floods or droughts—suggests that the identity of the respondent can affect substantive conclusions about the effects of shocks on household time use.
Household survey data are a key source of information for policy-makers at all levels. In developing countries, household data are commonly used to target interventions and evaluate progress towards development goals. The World Bank’s Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) are a particularly rich source of nationally-representative panel data for six Sub-Saharan African countries: Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda. To help understand how these data are used, EPAR reviewed the existing literature referencing the LSMS-ISA and identified 415 publications, working papers, reports, and presentations with primary research based on LSMS-ISA data. We find that use of the LSMS-ISA has been increasing each year since the first survey waves were made available in 2009, with several universities, multilateral organizations, government offices, and research groups across the globe using the data to answer questions on agricultural productivity, farm management, poverty and welfare, nutrition, and several other topics.
This brief provides an overview of the national and zonal characteristics of agricultural production in Tanzania using the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). More detailed information and analysis is available in the separate EPAR Tanzania LSMS-ISA Reference Report, Sections A-G.
This brief presents a comparative analysis of men and women and of male- and female-headed households in Tanzania using data 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 compare farm activity, productivity, input use, and sales as well as labor allocations by gender of the respondent and of the household head. In households designated “female-headed” a woman was the decision maker in the household, took part in the economy, control and welfare of the household, and was recognized by others in the household as the head. For questions regarding household labor (both non-farm and farm), the gender of the individual laborer is recorded, and we use this to illustrate the responsibilities of male and female household members. An appendix provides the details for our analyses.
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 H" 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 analysis of nutrition and malnutrition, and of the variation across agricultural and non-agricultural households, gender, age, and zones. For example, we find that stunting (low height for age) was the most prevalent indicator of malnutrition, with 43% of the under-five population categorized in the moderate to severe range, while less than 17% children under the age of five were reported to be underweight (low weight for age). A higher proportion of children in female-headed households experienced stunting (46% versus 42% in male-headed households) and were underweight (19% versus 16% in male-headed households).
This is "Section G" 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 data related to consumption of priority foods, total value of consumption, levels of food consumption and production, including analyses by zone in Tanzania. We find, for example, that the mean total value of household consumption was higher for agricultural households (US$27.28) compared to non-agricultural households (US$26.59), but the mean per capita value of household consumption was higher for non-agricultural households (US$7.32) compared to agricultural households (US$5.24). The mean per capita value of weekly consumption for the Southern zone was only US$5.34, compared to the highest mean per capita value of US$6.63 in the Eastern zone. The Central zone still had the lowest per capita value of consumption at US$4.40.