Types of Research
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove Agricultural Inputs & Farm Management filter Agricultural Inputs & Farm Management
- (-) Remove FAOSTAT filter FAOSTAT
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Poverty filter Poverty
- (-) 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.
Self-Help Groups (SHGs) in Sub-Saharan Africa can be defined as mutual assistance organizations through which individuals undertake collective action in order to improve their own lives. “Collective action” implies that individuals share their time, labor, money, or other assets with the group. In a recent EPAR data analysis, we use three nationally-representative survey tools to examine various indicators related to the coverage and prevalence of Self-Help Group usage across six Sub-Saharan African countries. EPAR has developed Stata .do files for the construction of a set of self-help group indicators using data from the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA), Financial Inclusion Index (FII), and FinScope.
We compiled a set of summary statistics for the final indicators using data from the following survey instruments:
- Ethiopia Socioeconomic Survey (ESS), Wave 3 (2015-16)
- Kenya FinScope, Wave 4 (2015)
- Kenya FII, Wave 4 (2016)
- Nigeria FII, Wave 4 (2016)
- Rwanda FII, Wave 4 (2016)
- Tanzania National Panel Survey (TNPS), Wave 4 (2014-15)
- Tanzania FinScope, Wave 4 (2017)
- Tanzania FII, Wave 4 (2016)
- Uganda FinScope, Wave 3 (2013)
- Uganda FII, Wave 4 (2016)
The raw survey data files are available for download free of charge from the World Bank LSMS-ISA website, the Financial Sector Deepening Trust website, and the Financial Inclusion Insights website. The .do files process the data and create final data sets at the household (LSMS-ISA) and individual (FII, FinScope) levels with labeled variables, which can be used to estimate summary statistics for the indicators.
All the instruments include nationally-representative samples. All estimates from the LSMS-ISA are household-level cluster-weighted means, while all estimates from FII and FinScope are calculated as individual-level weighted means. The proportions in the Indicators Spreadsheet are therefore estimates of the true proportion of individuals/households in the national population during the year of the survey. EPAR also created a Tableau visualization of these summary statistics, which can be found here.
We have also prepared a document outlining the construction decisions for each indicator across survey instruments and countries. We attempted to follow the same construction approach across instruments, and note any situations where differences in the instruments made this impossible.
The spreadsheet includes estimates of the following indicators created in our code files:
- Proportion of individuals who have access to a mobile phone
- Proportion of individuals who have official identification
- Proportion of individuals who are female
- Proportion of individuals who use mobile money
- Proportion of individuals who have a bank account
- Proportion of individuals who live in a rural area
- Individual Poverty Status
- Two Lowest PPI Quintiles
- Middle PPI Quintile
- Two Highest PPI Quintiles
Coverage & Prevalence
- Proportion of individuals who have interacted with a SHG
- Proportion of individuals who have used an SHG for financial services
- Proportion of individuals who depend most on SHGs for financial advice
- Proportion of individuals who have received financial advice from a SHG
- Proportion of households that have interacted with a SHG
- Proportion of households in communities with at least one SHG
- Proportion of households in communities with access to multiple farmer cooperative groups
- Proportion of households who have used an SHG for financial services
In addition, we produced estimates for 29 indicators related to characteristics of SHG use including indicators related to frequency of SHG use, characteristics of SHG groups, and individual/household trust of SHGs.
In this brief, we report on measures of economic growth, poverty and agricultural activity in Ethiopia. For each category of measure, we first describe different measurement approaches and present available time series data on selected indicators. We then use data from the sources listed below to discuss associations within and between these categories between 1994 and 2017.
There is a wide gap between realized and potential yields for many crops in Sub-Saharan Africa (SSA). Experts identify poor soil quality as a primary constraint to increased agricultural productivity. Therefore, increasing agricultural productivity by improving soil quality is seen as a viable strategy to enhance food security. Yet adoption rates of programs focused on improving soil quality have generally been lower than expected. We explore a seldom considered factor that may limit farmers’ demand for improved soil quality, namely, whether farmers’ self-assessments of their soil quality match soil scientists’ assessments. In this paper, using Tanzania National Panel Survey (TZNPS) data, part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA), we compare farmers’ own assessments of soil quality with scientific measurements of soil quality from the Harmonized World Soil Database (HWSD). We find a considerable “mismatch” and most notably, that 11.5 percent of survey households that reported having “good” soil quality are measured by scientific standards to have severely constrained nutrient availability. Mismatches between scientific measurements and farmer assessments of soil quality may highlight a potential barrier for programs seeking to encourage farmers to adopt soil quality improvement activities.
This report provides a genderal overview of the sweet potato value chain in Ethiopia. The first section describes trends in sweet potato production and consumption since the early 1990s. The second section describes the uses and importance of sweet potatoes in Ethiopia. The final section discuss major issues in production, post-production, and marketing. The literature available on sweet potetoes in Ethiopia was quite limited and draws on the wider literature on sweet potatoes in East Africa where needed. We find that Ethiopia ranks fifteenth in the world in terms of sweet potato production. Production has been rising quickly since 2008, following a period of slow decline in the early 2000s. Yields have also been rising slowly since 2008, but are below their peak from 2001. Sweet potato roots are consumed domestically, mostly by poor rural households. The vines also provide an important source of feed for livestock during the dry season. Major constraints to sweet potato production in Ethiopia include a lack of quality planting materials, pests and disease, and underdeveloped markets.
Uganda is the biggest sweet potato producer in Africa in terms of area harvested and production, although Burundi, Rwanda and Madagascar have significantly higher yields. Sweet potato is a major crop in Uganda, ranking third in cultivated area following plantains and cassava. Sweet potato ranks fourth in gross agricultural production value. The Government of Uganda has recognized sweet potatoes as an important crop for the country and a research priority, especially through establishing the National Agricultural Research Organization potato center. This report provides a general overview of the sweet potato value chain in Uganda. The first section describes trends in sweet potato production and consumption since 1996. The second section describes the varieties grown and their uses. The final section summarizes current practices and constraints in production, processing, and marketing.
This report provides a general overview of the sweet potato value chain in Tanzania. The first section describes trends in sweet potato production and consumption since 1990. The second section describes the uses and importance of sweet potatoes in Tanzania. The final section outlines current practices and constraints in production, post-production, and marketing. Tanzania ranks fifth in the world in quantity of sweet potatoes produced. Production and consumption of sweet potatoes have been relatively constant over the past 10 years, although both production and consumption in this period have been high in comparison to earlier decades. We find that sweet potato yields increased in the early 2000s, but have stagnated since, and are far short of potential yields. Sweet potato consumption is almost entirely domestic and plays an important role in nutrition and food security for smallholder farmers. Sweet potato production faces a variety of constraints, including pests and disease, short shelf life, lack of planting materials, damage during handling, and lack of market access.
Cassava is a tuber crop originating in South America and grown in tropical and subtropical areas throughout the world. Cassava use varies significantly by region. In Africa, cassava is primarily grown for food. In Asia, production is typically for industrial purposes, including ethanol, while in Latin America and the Caribbean it is commonly used in animal feed. Both roots and leaves are consumed, though most information on production focuses on roots. There are bitter and sweet varieties; bitter cassava has a high cyanide content and must be processed prior to consumption, while sweet varieties can be eaten directly. This report presents information about current production, constraints, and future potential of cassava. We discuss cassava’s importance in Africa, current worldwide production, projections for supply and demand, production constraints, and current policies affecting cassava production and trade. We include global information but focus on Africa, particularly Nigeria, Ghana, Uganda, and Tanzania.
Over the past 20 years, global wheat production and consumption have increased significantly. Production has increased 28%, or about 1.3% annually, and consumption has increased about 24%, or 1.1% annually. A small number of countries consistently account for over 90% of the export market, but the import market is more diversified and involves many more countries. Wheat is primarily used for food, seed, and industry; only 20% of wheat production is used for animal feed. This brief provides a global overview of the wheat value chain, but with specific attention to three focus countries: Ethiopia, India (specifically the Bihar region), and Bangladesh. While these three countries currently have a limited impact in the global wheat market, projections of wheat production and demand suggest that over the next 20 years demand in Bangladesh and Ethiopia will increasingly exceed supply, while India will become a net importer by 2030.