Types of Research
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Women filter Women
- (-) Remove Global & Regional Public Goods filter Global & Regional Public Goods
- (-) Remove Risk, Preferences, & Decision-Making filter Risk, Preferences, & Decision-Making
- (-) Remove Labor & Time Use filter Labor & Time Use
- (-) Remove Poverty filter Poverty
- (-) Remove Sub-Saharan Africa filter Sub-Saharan Africa
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.
A large and growing body of scholarship now suggests that many household outcomes, including children’s education and nutrition, are associated with a wife’s bargaining power and control over household decision-making. In turn, bargaining power in a household is theorized to be driven by a wife’s financial and human capital assets – in particular the degree to which these assets contribute to household productivity and/or to the wife’s exit options. This paper draws on the detailed Farmer First dataset in Tanzania and Mali to examine husband and wife reports of a wife’s share of decision-making authority in polygynous households, where multiple wives jointly contribute to household productivity, and where exit options for any single wife may be less credible. We find that both husbands and wives assign less authority to the wife in polygynous households relative to monogamous households. We also find that a wife’s assets are not as strongly associated with decision-making authority in polygynous versus monogamous contexts. Finally, we find that responses to questions on spousal authority vary significantly by spouse in both polygynous and monogamous households, suggesting interventions based on the response of a single spouse may incorrectly inform policies and programs.
A growing body of evidence suggests that empowering women may lead to economic benefits (The World Bank, 2011; Duflo, 2012; Kabeer & Natali, 2013). Little work, however, focuses specifically on the potential impacts of women’s empowerment in agricultural settings. Through a comprehensive review of literature this report considers how prioritizing women’s empowerment in agriculture might lead to economic benefits. With an intentionally narrow focus on economic empowerment, we draw on the Women’s Empowerment in Agriculture Index (WEAI)’s indicators of women’s empowerment in agriculture to consider the potential economic rewards to increasing women’s control over agricultural productive resources (including their own time and labor), over agricultural production decisions, and over agricultural income. While we recognize that there may be quantifiable benefits of improving women’s empowerment in and of itself, we focus on potential longer-term economic benefits of improvements in these empowerment measures.
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.
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.
Estimates suggest that women grow 70-80 percent of Africa’s food crops, which may constrain their involvement in cash crop production, if food crop production places additional demands their time, resources and labor. There is little evidence regarding women’s motivations or decisions to grow cash versus food crops. Similarly, the policy literature on cotton production and markets in Sub-Saharan Africa (SSA) does not explicitly address the issue of gender, further limiting the information available on the impact of cotton production on women. This brief provides an overview of the role of women in cotton production, and provides a framework for analyzing barriers to women and technology’s impact on women throughout the cropping cycle. We find that women are typically not the primary cultivators of cotton, and that cotton production is a household cultivation strategy, especially in West and Central Africa. Cotton cultivation often provides access to fertilizers, pesticides and extension services that are otherwise unavailable to households. Women have benefitted from household cotton income when they have input in intra-household resource allocation decisions or when they are able to grow cotton on personal plots and have control over the income it generates. Women also benefit from cotton when it offers them the opportunity to engage in paid labor. The data suggests, however, that cotton cultivation can negatively impact women when it increases their unpaid agricultural labor burden or exposes them to harmful chemicals.
Yam is a major staple in West and Central Africa and an important supplementary food in East Africa. In Sub-Saharan Africa (SSA), virtually all yams are produced for human consumption, with women responsible for processing yams for consumption. This brief provides an overview of the role of women in yam production, and provides a framework for analyzing barriers to women and technology’s impact on women throughout the cropping cycle. We find that though yam was traditionally considered a man’s crop, it is clear that women farmers contribute greatly to yam cultivation, especially during weeding, harvesting, and processing. Propagation of improved varieties with resistance to pests and diseases like yam mosaic disease has great potential to benefit women farmers. Increased yields and lower post-harvest losses will increase household food security. However, because yams extract high amounts of nutrients from the soil, soil and land management techniques are necessary to ensure future gains in yield. Women’s groups serve as potential venues for dissemination of new yam cultivation and processing technologies. Additionally, women’s groups can undertake new propagation techniques as income generating activities. Women farmers need increased extension efforts to fully benefit from technology improvements.
Though not indigenous to Sub-Saharan Africa (SSA), cassava plays, to varying degrees, five major roles in African development: famine-reserve crop, rural food staple, cash crop for urban consumption, livestock feed, and industrial raw material. Cassava production in SSA was historically a significant staple crop for smallholder farmers and continues to be the second most important food crop in Africa (after maize) in terms of calories consumed. Subsistence crops such as cassava are often considered women’s crops with the standard explanation that women are responsible for feeding the family and thus prefer to grow crops for the household. This brief reviews the role that women play in cassava production, and considers ways to better address gender issues from planting through post-harvest production. We find that the potential gains to cassava production made possible through improved technology will not be fully realized without the participation of women farmers and without women farmers having access to credit, markets, and extension services. Additionally, evidence from SSA suggests that labor for harvesting and processing, rather than labor for weeding, has become the key labor constraint for cassava, and addressing this concern may be more important than further yield increases for raising production levels.