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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:
- Ethiopia Socioeconomic Survey (ESS), Wave 3 (2015-16)
- Kenya:
- Kenya FinScope, Wave 4 (2015)
- Kenya FII, Wave 4 (2016)
- Nigeria
- Nigeria FII, Wave 4 (2016)
- Rwanda:
- Rwanda FII, Wave 4 (2016)
- Tanzania:
- Tanzania National Panel Survey (TNPS), Wave 4 (2014-15)
- Tanzania FinScope, Wave 4 (2017)
- Tanzania FII, Wave 4 (2016)
- Uganda:
- 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:
Sub-Populations
- 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
Characteristics
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 brief analyzes the indicators used by the World Bank in its Project Appraisal Documents (PAD) to measure the outputs and outcomes of 44 Water, Sanitation and Hygiene projects in Africa and Asia from 2000-2010. This report details the methods used to collect and organize the indicators, and provides a brief analysis of the type of indicators used and their evolution over time. A searchable spreadsheet of the indicators used in this analysis accompanies this summary. We find that some patterns emerge over time, though none are very drastic. The most common group of indicators used by the World Bank are “management” oriented indicators (28% of indicators). Management indicators are disproportionately used in African projects as compared to projects in Asia. Several projects in Africa incorporate indicators relating to legal/regulatory/policy outcomes, while projects in Asia do not. In recent years, the World Bank has used fewer indicators that measure service delivery, health, and education and awareness.
Water supply and sanitation is the responsibility of sub-national state governments under the Indian Constitution. At present, the national government sets water supply and sanitation policy while states plan, design, and execute water supply schemes accordingly. Furthermore, while state governments are in charge of operation and maintenance, they may pass the responsibility to village or district levels. Given the highly decentralized provision of water and sanitation services, there is no autonomous regulatory agency for the water supply and sanitation sector in India at the state or national level. This report reviews literature on India’s urban sanitation policy. The methodology includes Google, Lexis-Nexis, and University of Washington Library searches, searches of two major Indian newspapers, and searches of websites and blogs sponsored by non-governmental organizations. Sources also include the India Sanitation Portal, a forum on sanitation in India used by governmental and nongovernmental organizations, and WASH Sanitation Updates, a sanitation news feed with considerable material on India. We find that urban sanitation policy, as embodied in the National Urban Sanitation Plan of 2008, remains focused on decentralized approaches. Our research reveals no evidence of a change in official policy, nor evidence suggesting that government sanitation programs conflict with official policy.
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.