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Much literature discusses the importance of investing in human capital—or “the sum of a population’s health, skills, knowledge, experience, and habits” (World Bank, 2018, p. 42)—to a country’s economic growth. For example, the World Bank reports a “chronic underinvestment” in health and education in Nigeria, noting that investing in human capital has the potential to significantly contribute to economic growth, poverty reduction, and societal well-being (World Bank, 2018). This research brief reports on the evidence linking investment in human capital—specifically, health and education—with changes in economic growth. It reviews the literature for five topic areas: Education, Infectious Diseases, Nutrition, Primary Health Care, and Child and Maternal Health. This review gives priority focus to the countries of Bangladesh, Burkina Faso, Democratic Republic of Congo, Ethiopia, India, Kenya, Madagascar, Nigeria, Rwanda, and Tanzania. For each topic area, we report the evidence in support of a pathway from investing in human capital to economic growth.
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:
- Ethiopia Socioeconomic Survey (ESS), Wave 3 (2015-16)
- Kenya:
- Kenya FinScope, Wave 4 (2015)
- Kenya FII, Wave 4 (2016)
- Nigeria
- Nigeria FII, Wave 4 (2016)
- Rwanda:
- Rwanda FII, Wave 4 (2016)
- Tanzania:
- Tanzania National Panel Survey (TNPS), Wave 4 (2014-15)
- Tanzania FinScope, Wave 4 (2017)
- Tanzania FII, Wave 4 (2016)
- Uganda:
- 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:
Sub-Populations
- 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
Characteristics
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.
This 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. We summarize the public good characteristics of R&D for agriculture in general and for commodity and subsistence crops in particular, as well as R&D for health in general and for neglected diseases in particular, with a focus on Sub-Saharan Africa and South Asia. Finally, we present rationales for which funders are predicted to fund which R&D types based on these funder and R&D characteristics. We then compile available statistics on funding for agricultural and health R&D from private, public and philanthropic sources, and compare trends in funding from these sources against expectations. We find private agricultural R&D spending focuses on commodity crops (as expected). However contrary to expectations we find public and philanthropic spending also goes largely towards these same crops rather than staples not targeted by private funds. For health R&D private funders similarly concentrate on diseases with higher potential financial returns. However unlike in agricultural R&D, in health R&D we observe some specialization across funders – especially for neglected diseases R&D - consistent with funders’ expected relative advantages.
This brief presents an overview of EPAR’s previous research on nutrition and food security and outlines summaries and key findings from 15 technical reports and research briefs. Key findings are drawn from our own original analyses as well as from other sources, which are cited in the individual reports. We also include appendices briefly summarizing EPAR’s research on health and climate change, topics somewhat related to nutrition and food security, and EPAR’s confidential work on nutrition and food security.
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 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.
Water supply and sanitation is the responsibility of sub-national state governments under the Indian Constitution. At present, the national government sets water supply and sanitation policy while states plan, design, and execute water supply schemes accordingly. Furthermore, while state governments are in charge of operation and maintenance, they may pass the responsibility to village or district levels. Given the highly decentralized provision of water and sanitation services, there is no autonomous regulatory agency for the water supply and sanitation sector in India at the state or national level. This report reviews literature on India’s urban sanitation policy. The methodology includes Google, Lexis-Nexis, and University of Washington Library searches, searches of two major Indian newspapers, and searches of websites and blogs sponsored by non-governmental organizations. Sources also include the India Sanitation Portal, a forum on sanitation in India used by governmental and nongovernmental organizations, and WASH Sanitation Updates, a sanitation news feed with considerable material on India. We find that urban sanitation policy, as embodied in the National Urban Sanitation Plan of 2008, remains focused on decentralized approaches. Our research reveals no evidence of a change in official policy, nor evidence suggesting that government sanitation programs conflict with official policy.
Limited sanitation infrastructure, poor hygienic practices, and unsafe drinking water negatively affect the health of millions of people in the developing world. Using sanitation interventions to interrupt disease pathways can significantly improve public health. Sanitation interventions primarily benefit public health by reducing the prevalence of enteric pathogenic illnesses, which cause diarrhea. Health benefits are realized and accrue to the direct recipients of sanitation interventions and also to their neighbors and others in their communities. In a report to the United Nations Development Programme (UNDP), Hutton et al. (2006) estimate that the cost-benefit ratio of sanitation interventions in all developing countries worldwide is 11.2. This literature review summarizes the risks of inadequate sanitation to public health and presents the empirical evidence on the public health benefits of complete, intermediate and multiple factor sanitation interventions. We find that complete or improved sanitary systems can offer concrete public health benefits by reducing exposure pathways to a variety of infectious diseases contained in human feces and wastewater. Substantial complementary economic gains are also predicted to accrue as a result of providing increased sanitation. In addition, community-wide sanitation interventions seem to offer the greatest promise for reducing pathogenic health risks from feces.
Without availability and access to a variety of foods, populations in the developing world are suffering from deficiencies in iron, zinc, iodine, vitamin A, and other micronutrients in addition to deficiencies in energy and protein. Supplementation and fortification programs have demonstrated effectiveness, but there is an increasing interest in potentially more sustainable solutions via agricultural interventions. The review examines the literature regarding agricultural interventions and pathways to diet diversification and whether desired nutritional outcomes are achieved. We find a strong sentiment that agricultural interventions can improve dietary diversity, and that dietary diversity can improve nutrition and related health outcomes. The programs with demonstrated ability to improve nutrition outcomes are most often cross-cutting interventions, borrowing from the agriculture, nutrition, and public health traditions. While these multi-platform programs can be costly to evaluate and difficult to implement, the evidence supports their potential to create sustainable quality-of-life improvements in target regions. The pathways by which agricultural interventions achieve impact are not fully clear, however. The greatest knowledge gaps are directly related to the lack of integration between program design and evaluation. Many evaluations are based on small sample sizes, lack control groups or baseline data, are subject to selection bias, or face other challenges to rigorous statistical analysis.