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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.
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 F" 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 soil characteristics and soil management, of input use by crop and gender at the plot and household levels, and of improved variety seeds and water management.
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 report provides a summary of Tanzania’s agriculture sector, crop production, agricultural productivity and yield levels, risks, and policies and reforms. This review uses resources found on the University of Washington Libraries system and Google Scholar, as well as the websites of the Government of Tanzania, FAO, and World Bank. We find that Tanzanian agriculture workers comprise 80% of the population and farm a wide variety of crops, ranging from staple crops such as maize, cassava, and rice, to export crops such as coffee, cotton, tobacco, tea, and sugar. Smallholder farmers face increasing risks from climate change, pests, diseases, and land degradation, among others. While they have some resources available, such as farmer groups and limited access to ICTs, they lack important resources such as credit and inputs. We find that Tanzania’s land tenure and agriculture policies may further complicate the lives of smallholders through increased taxes and administrative processes. Through the Agricultural Sector Development Programme (ASDP) reform, however, the Government of Tanzania hopes to empower farmers and improve service delivery.
Without availability and access to a variety of foods, populations in the developing world are suffering from deficiencies in iron, zinc, iodine, vitamin A, and other micronutrients in addition to deficiencies in energy and protein. Supplementation and fortification programs have demonstrated effectiveness, but there is an increasing interest in potentially more sustainable solutions via agricultural interventions. The review examines the literature regarding agricultural interventions and pathways to diet diversification and whether desired nutritional outcomes are achieved. We find a strong sentiment that agricultural interventions can improve dietary diversity, and that dietary diversity can improve nutrition and related health outcomes. The programs with demonstrated ability to improve nutrition outcomes are most often cross-cutting interventions, borrowing from the agriculture, nutrition, and public health traditions. While these multi-platform programs can be costly to evaluate and difficult to implement, the evidence supports their potential to create sustainable quality-of-life improvements in target regions. The pathways by which agricultural interventions achieve impact are not fully clear, however. The greatest knowledge gaps are directly related to the lack of integration between program design and evaluation. Many evaluations are based on small sample sizes, lack control groups or baseline data, are subject to selection bias, or face other challenges to rigorous statistical analysis.
Contract farming (CF) is an arrangement between farmers and a processing or marketing firm for the production and supply of agricultural products, often at predetermined prices. This literature review builds on EPAR's review of smallholder contract farming in Sub-Saharan Africa (SSA) and South Asia (EPAR Technical Report #60) by specifically examining the evidence on impacts and potential benefits of contract farming for women in SSA. Key takeaways suggest women’s direct participation in contract farming is limited, with limited access to land and control over the allocation of labor and cash resources key constraints hindering women’s ability to benefit from CF. Further, we find that the impact of contract farming on women is often mediated by their relative bargaining power within the household.
In recent years, product supply chains for agricultural goods have become increasingly globalized. As a result, greater numbers of smallholder farmers in South Asia (SA) and Sub-Saharan Africa (SSA) participate in global supply chains, many of them through contract farming (CF). CF is an arrangement between a farmer and a processing or marketing firm for the production and supply of agricultural products, often at predetermined prices. This literature review finds empirical evidence that demonstrates that the economic and social benefits of CF for smallholder farmers are mixed. A number of studies suggest that CF may improve farmer productivity, reduce production risk and transaction costs, and increase farmer incomes. However, critics caution that CF may undermine farmers’ relative bargaining power and increase health, environmental, and financial risk through exposure to monopsonistic markets, weak contract environments, and unfamiliar agricultural technologies. There is consensus across the literature that CF has the best outcomes for farmers when farmers have more bargaining power to negotiate the terms of the contract. In reviewing the literature on CF, we find a number of challenges to comparing studies and evaluating outcomes across contracts. This literature review summarizes empirical findings and analyses regarding contract models and best practices to increase farmers’ bargaining power and decrease contract default.
Introducing technology that is designed to be physically appropriate and valuable to women farmers can increase yields and raise income. But gender issues for agricultural technology projects in Sub-Saharan Africa (SSA) are extremely complex. The EPAR series on Gender and Cropping in SSA offers examples of how these issues can affect crop production and adoption of agricultural technologies at each point in the crop cycle for eight crops (cassava, cotton, maize, millet, rice, sorghum, wheat, and yam). This executive summary highlights innovative opportunities for interventions that consider these dimensions of gender. We encourage readers to consult the crop specific briefs for more details. We find that involving both men and women in the development, testing, and dissemination of agricultural technology has been shown to be successful in helping both benefit. Nevertheless, a consistent finding throughout the Gender and Cropping in SSA series is that maximum benefits from technological innovations cannot be realized when upstream factors like education, power, and land tenure heavily influence outcomes. Addressing these more basic upstream causes of gender inequality may be even more important in helping households increase productivity and maximize the benefits of technological interventions.
A widely quoted estimate is that women produce 70 to 80 percent of Sub-Saharan Africa’s (SSA) food. Increasing farmer productivity in SSA therefore requires understanding how these women make planting, harvesting, and other decisions that affect the production, consumption, and marketing of their crops. This brief provides an overview of the gender cropping series highlighting similar themes from the various crops studied, presenting an overarching summary of the findings and conclusion of the individual literature reviews. The studies reviewed suggest that differential preferences and access to assets by men and women can affect adoption levels and the benefits that accrue to men and women. Findings show that women have less secure access to credit, land, inputs, extension, and markets. Similarly, women’s multi-faceted role in household management gives rise to preferences that may very well be different from those of men. Participatory Breeding and Participatory Varietal Selection are two methods shown to be successful in developing technology that is more appropriate and more likely to avoid unintended consequences. Regularly collecting gender-disaggregated statistics can also result in a greater understanding of how technology has affected both men and women. Agricultural technology has the potential to enhance both men’s and women’s welfare and productivity, but unless gender is sufficiently integrated into every step of the development and dissemination process, efforts will only achieve a fraction of their total possible benefit.