Types of Research
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This document is an initial scoping of the theory and evidence linking digital services to women’s rural-to-urban migration. The document contains (1) a survey of the literature on digital financial services to discern how often this body of literature considers gender-disaggregated impacts on migration, (2) a detailed review of 13 hypotheses regarding the effects of digital services on women’s migration to cities, and (3) an illustrative overview of rural-urban migration patterns and digital technology usage in two East African countries (Ethiopia and Tanzania).
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.
In this report we analyze three waves nationally-representative household survey data from Kenya, Uganda, Tanzania, Nigeria, Pakistan, Bangladesh, India, and Indonesia to explore sociodemographic and economic factors associated with mobile money adoption, awareness, and use across countries and over time. Our findings indicate that to realize the potential of digital financial services to reach currently unbanked populations and increase financial inclusion, particular attention needs to be paid to barriers faced by women in accessing mobile money. While policies and interventions to promote education, employment, phone ownership, and having a bank account may broadly help to increase mobile money adoption and use, potentially bringing in currently unbanked populations, specific policies targeting women may be needed to close current gender gaps.
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.
This brief presents an overview of EPAR’s previous research related to gender. We first present our key takeaways related to labor and time use, technology adoption, agricultural production, control over income and assets, health and nutrition, and data collection. We then provide a brief overview of each previous research project related to gender along with gender-related findings, starting with the most recent project. Many of the gender-related findings draw from other sources; please see the full documents for references. Reports available on EPAR’s website are hyperlinked in the full brief.
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.