Types of Research
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove Monitoring & Evaluation filter Monitoring & Evaluation
- (-) Remove 2016 filter 2016
- (-) Remove 2015 filter 2015
- (-) Remove Risk, Preferences, & Decision-Making filter Risk, Preferences, & Decision-Making
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.
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.
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 reviews approaches to results measurement used by multilateral and bilateral donor organizations and highlights trends and gaps in how donors measure and report on their performance. Our review consists of assessing donor organizations in terms of their institutional design and levels of evaluation for results measurement, their organizational processes for measuring types of results including coordination and alignment with recipients, outputs and implementation, outcomes and impacts, and costs and effectiveness, and their processes for reporting and using results information. We collect evidence on 12 bilateral organizations and 10 multilateral organizations. The evidence review includes multi-country reviews of aid effectiveness, peer reviews by other donor organizations, donor evaluation plans and frameworks, and donor results and reporting documents. The report is based on an accompanying spreadsheet that contains the coded information from the 22 donor organizations. We find that donors report several types of results, but that there are challenges to measuring certain results at the aggregate donor level, due to challenges with funding and coordination for results measurement at the project, country, portfolio, and donor levels. Approaches to results measurement vary across donor organizations. We identify some trends and differences among groups of donors, notably between bilateral and multilateral donors, but overall there are no clear delineations in how donors approach results measurement.
Aid results information is often not comparable, since monitoring and evaluation frameworks, information gathering processes, and definitions of “results” differ across donors and governments. This report reviews approaches to results monitoring and evaluation used by governments in developing countries, and highlights trends and gaps in national monitoring and evaluation (M&E) systems. We collect evidence on 42 separate government M&E systems in 23 developing countries, including 17 general national M&E systems and 25 sector-specific national M&E systems, with 14 focused on HIV/AIDS, 8 on health, and 3 on agriculture. The evidence review includes external case studies and evaluations of M&E systems, government M&E assessments, M&E plans, strategic plans with an M&E component, and multi-country reviews of M&E, accountability, and aid effectiveness. We evaluate harmonization of government and development partner M&E systems, coordination and institutionalization of government M&E, challenges in data collection and monitoring, and analysis and use of results information. We also report on key characteristics of M&E systems in different sectors.