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Recent research has used typologies to classify rural households into categories such as “subsistence” versus “commercialized” as a means of targeting agricultural development interventions and tracking agricultural transformation. Following an approach proposed by Alliance for a Green Revolution in Africa, we examine patterns in two agricultural transformation hallmarks – commercialization of farm output, and diversification into non-farm income – among rural households in Ethiopia, Nigeria, and Tanzania from 2008-2015. We classify households into five smallholder farm categories based on commercialization and non-farm income levels (Subsistence, Pre-commercial, Transitioning, Specialized Commercial, and Diversified Commercial farms), as well as two non-smallholder categories (Largeholder farms and Non-farm households). We then summarize the share of households in each of these categories, examine geographic and demographic factors associated with different categories, and explore households’ movement across categories over time. We find a large amount of “churn” across categories, with most households moving to a different (more or less commercialized, more or less diversified) category across survey years. We also find many non-farm households become smallholder farmers – and vice versa – over time. Finally, we show that in many cases increases in farm household commercialization or diversification rates actually reflect decreased total farm production, or decreased total income (i.e., declines in the denominators of the agricultural transformation metrics), suggesting a potential loss of rural household welfare even in the presence of “positive” trends in transformation indicators. Findings underscore challenges with using common macro-level indicators to target development efforts and track progress at the household level in rural agrarian communities.
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.
An ongoing stream of EPAR research considers how public good characteristics of different types of research and development (R&D) and the motivations of different providers of R&D funding affect the relative advantages of alternative funding sources. For this project, we seek to summarize the key public good characteristics of R&D investment for agriculture in general and for different subsets of crops, and hypothesize how these characteristics might be expected to affect public, private, or philanthropic funders’ investment decisions.
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.
The commercial alcohol industry in Africa may provide opportunities to increase market access and incomes for smallholder farmers by increasing access to agriculture-alcohol value chains. Despite the benefits of increased market opportunities, the high costs to human health and social welfare from increased alcohol use and alcoholism could contribute to a net loss for society. To better understand the tradeoffs between increased market access for smallholders and societal costs associated with harmful alcohol consumption, this paper provides an inventory of the societal costs of alcohol in Sub-Saharan Africa (SSA). We examine direct costs associated with addressing harmful effects of alcohol and treating alcohol-related illnesses, as well as indirect costs associated with the goods and services that are not delivered as a consequence of drinking and its impact on personal productivity. We identified resources using Google Scholar and the University of Washington libraries, and utilized the Global Burden of Disease (GBD) database by the Institute for Health Metrics and Evaluation (IHME) and the World Health Organization’s Global Information System on Alcohol and Health (GISAH) database. We also utilized FAOSTAT to retrieve raw data on national-level alcohol production and export statistics. We find that hazardous alcohol use contributes to early mortality and morbidity, loss of productivity, property damage, and other social costs and harms for drinkers and those around them. Drinking also affects vulnerable segments of the population disproportionately. Policymakers, local authorities, and donor agencies can use the information presented in this paper to plan and prepare for the higher consumption levels and subsequent social costs that may follow through agricultural development and economic growth in the region.
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.
EPAR’s Political Economy of Fertilizer Policy series provides a history of government intervention in the fertilizer markets of eight Sub-Saharan African countries: Côte d’Ivoire, Ghana, Kenya, Malawi, Mozambique, Nigeria, Senegal, and Tanzania. The briefs focus on details of present and past voucher programs, input subsidies, tariffs in the fertilizer sector, and the political context of these policies. The briefs illustrate these policies’ effect on key domestic crops and focus on the strengths and weaknesses of current market structure. Fertilizer policy in SSA has been extremely dynamic over the last fifty years, swinging from enormous levels of intervention in the 1960s and 70s to liberalization of markets of the 1980s and 1990s. More recently, intervention has become more moderate, focusing on “market smart” subsidies and support. This executive summary highlights key findings and common themes from the series.