Types of Research
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- (-) Remove Risk, Preferences, & Decision-Making filter Risk, Preferences, & Decision-Making
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- (-) Remove Global & Regional Public Goods filter Global & Regional Public Goods
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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.
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.
Previous research has shown that men and women, on average, have different risk attitudes and may therefore see different value propositions in response to new opportunities. We use data from smallholder farm households in Mali to test whether risk perceptions differ by gender and across domains. We model this potential association across six risks (work injury, extreme weather, community relationships, debt, lack of buyers, and conflict) while controlling for demographic and attitudinal characteristics. Factor analysis highlights extreme weather and conflict as eliciting the most distinct patterns of participant response. Regression analysis for Mali as a whole reveals an association between gender and risk perception, with women expressing more concern except in the extreme weather domain; however, the association with gender is largely absent when models control for geographic region. We also find lower risk perception associated with an individualistic and/or fatalistic worldview, a risk-tolerant outlook, and optimism about the future, while education, better health, a social orientation, self-efficacy, and access to information are generally associated with more frequent worry— with some inconsistency. Income, wealth, and time poverty exhibit complex associations with perception of risk. Understanding whether and how men’s and women’s risk preferences differ, and identifying other dominant predictors such as geographic region and worldview, could help development organizations to shape risk mitigation interventions to increase the likelihood of adoption, and to avoid inadvertently making certain subpopulations worse off by increasing the potential for negative outcomes.
We use OLS and logistic regression to investigate variation in husband and wife perspectives on the division of authority over agriculture-related decisions within households in rural Tanzania. Using original data from husbands and wives (interviewed separately) in 1,851 Tanzanian households, the analysis examines differences in the wife’s authority over 13 household and farming decisions. The study finds that the level of decision-making authority allocated to wives by their husbands, and the authority allocated by wives to themselves, both vary significantly across households. In addition to commonly considered assets such as women’s age and education, in rural agricultural households women’s health and labour activities also appear to matter for perceptions of authority. We also find husbands and wives interviewed separately frequently disagree with each other over who holds authority over key farming, family, and livelihood decisions. Further, the results of OLS and logistic regression suggest that even after controlling for various individual, household, and regional characteristics, husband and wife claims to decision-making authority continue to vary systematically by decision – suggesting decision characteristics themselves also matter. The absence of spousal agreement over the allocation of authority (i.e., a lack of “intrahousehold accord”) over different farm and household decisions is problematic for interventions seeking to use survey data to develop and inform strategies for reducing gender inequalities or empowering women in rural agricultural households. Findings provide policy and program insights into when studies interviewing only a single spouse or considering only a single decision may inaccurately characterize intra-household decision-making dynamics.
In this report, we analyze the evidence that improved and expanded access to financial services can be a pathway out of poverty in Bangladesh and Tanzania. A brief background review of finance and poverty reduction evidence at the country, household, and individual level emphasizes the importance of a functioning financial system and the need to remove individual and household barriers to capital accumulation. We follow with an in-depth literature review on studies that link poverty reduction in Bangladesh or Tanzania with one or more of five financial intervention categories: remittances; government subsidies; conditional and unconditional cash transfers; credit; and combination programs. The resulting empirical evidence from these sources reveal a high share (61%) of positive reported associations between a financial intervention and outcome measure related to our five chosen financial interventions. The remaining studies found insignificant or mixed associations, but very few (3 out of 56) indicate that access to a financial mechanism was associated with worsened poverty. The heterogeneity of study types and interventions makes it difficult to draw conclusions about the efficacy of one intervention over another, and more research is needed on whether such approaches constitute a durable, long-term exit from poverty.
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 report provides a general overview of trends in public and private agricultural research and development (R&D) funding and expenditures in Sub-Saharan Africa (SSA). The request is divided into two sections, covering public funding and private funding. Within each section, relevant data is presented on historical funding patterns, the types of research conducted, and which countries within SSA are financing R&D at the highest level. We find that the majority of growth in African public agricultural research funding took place in the 1960s, when real public spending on agricultural research increased 6% a year. From 1971 to 2000 annual growth averaged 1.4% a year. Public financing of agricultural R&D experienced a moderate shift in the 1990s from bilateral and multilateral donor funding to domestic government financing. The shift varied by country, but donor funding dropped for all SSA countries an average of 10%. Private research and development funding is heavily concentrated in developed countries with the United States and Japan the two biggest spenders. Within SSA, private R&D expenditures comprise 2% of all R&D spending. The main private actors in SSA are companies based in South Africa and Nigeria. The private sector is focused on research areas that involve marketable inputs, such as chemicals, seeds, and machines/
Special Economic Zones (SEZs) are generally defined as geographically delimited areas administered by a single body, offering certain incentives (duty-free importing and streamlined customs procedures, for instance) to businesses that physically locate within the zone. This literature review provides a baseline analysis of SEZs and their potential impacts on smallholder farmers in SSA. Criticism on SEZs is distinctly divided between those who criticize on social or environmental grounds versus those who question the economic impact of SEZs. SEZs are often criticized based on perceived negative socio-economic impacts—particularly their negative impact on women, labor, and working conditions. This review includes several country-specific studies that find evidence that SEZs actually have higher environmental standards and higher worker satisfaction than outside the SEZ. Most responses to criticisms do note, however, that the case studies’ results are not necessarily generalizable to SEZs throughout the world. The literature review includes key elements of successes and failures pulled from the case studies of SEZs in SSA. Though the evidence is insufficient to conclusively determine if smallholder farmers receive direct benefits from SEZs and their associated agroindustrial contracts, this review finds that resources provided to farmers (credit at rates lower than bank rates, technical or managerial assistance, pesticides, seeds, and fertilizer on credit) tend to be concentrated among larger farmers. The report concludes with a note on donor involvement as well as recommendations for further research.