Populations

Geography

EPAR TECHNICAL REPORT #362
Self Help Groups Prevalence and Coverage
Publication Date: 01/16/2019
Type: Data Analysis
Abstract

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.

Indicator Cross-Comparisons, All Countries Pivot Tables
EPAR Research Brief #167
LSMS-ISA Tanzania Section B: Median Farmer Profile
Publication Date: 10/07/2011
Type: Data Analysis
Abstract

This is "Section B" of a report that presents estimates and summary statistics 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 present our analyses of household characteristics by gender and by administrative zone, considering landholding size, number of crops grown, yields, livestock, input use, and food consumption.

Full Report
EPAR Technical Report #163
LSMS-ISA Tanzania Section F: Farm Inputs
Publication Date: 10/03/2011
Type: Data Analysis
Abstract

This is "Section F" of a report that presents estimates and summary statistics 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 present our analyses of soil characteristics and soil management, of input use by crop and gender at the plot and household levels, and of improved variety seeds and water management.

Full Report
EPAR Technical Report #161
LSMS-ISA Tanzania Section D: Farm Characteristics, Crops, and Productivity
Publication Date: 10/01/2011
Type: Data Analysis
Abstract

This is "Section D" of a report that presents estimates and summary statistics 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 present our analyses of basic farm characteristics, land and labor productivity, crop sales, yield measures, intercropping, and pre- and post-harvest losses, including comparisons by gender of household head and by zone.

Full Report
EPAR Technical Report #133
Tanzania: Agricultural Sector Overview
Publication Date: 03/07/2011
Type: Literature Review
Abstract

This report provides a summary of Tanzania’s agriculture sector, crop production, agricultural productivity and yield levels, risks, and policies and reforms. This review uses resources found on the University of Washington Libraries system and Google Scholar, as well as the websites of the Government of Tanzania, FAO, and World Bank. We find that Tanzanian agriculture workers comprise 80% of the population and farm a wide variety of crops, ranging from staple crops such as maize, cassava, and rice, to export crops such as coffee, cotton, tobacco, tea, and sugar. Smallholder farmers face increasing risks from climate change, pests, diseases, and land degradation, among others. While they have some resources available, such as farmer groups and limited access to ICTs, they lack important resources such as credit and inputs. We find that Tanzania’s land tenure and agriculture policies may further complicate the lives of smallholders through increased taxes and administrative processes. Through the Agricultural Sector Development Programme (ASDP) reform, however, the Government of Tanzania hopes to empower farmers and improve service delivery.  

Literature Review
EPAR Technical Report #130
Waste Treatment and Reuse
Publication Date: 01/29/2011
Type: Literature Review
Abstract

The purpose of this literature review is to provide qualitative and quantitative examples of technologies, constraints and incentives for efficient waste treatment and reuse in Sub-Saharan Africa and Southeast Asia.  We present relevant case studies and expert observations and experiences on the nutrient content in urine and feces, contaminants frequently found in untreated sludge and wastewater, waste treatment technologies that may be relevant for low-income countries, risks associated with waste reuse, benefits to resource recovery in agriculture. We further discuss reasons for waste treatment failures, including urbanization, observations on challenges with market-driven reuse in less developed countries, and examples of net-positive energy facilities in Europe and the United States. Much of the evidence presented in the literature relates to wastewater treatment processes or the sludge produced from wastewater treatment as opposed to untreated fecal sludge.  However, examples of risks, failures, and opportunities for raw sludge treatment and reuse are discussed when available.  In some cases, empirical evidence or case studies were not available for developing countries and alternatives are presented.  Overall we found the empirical evidence on waste treatment and reuse in developing countries is quite thin. 

Full Report
EPAR Technical Report #5
The Links Between Fertilizer and Nutrition in South Asia and Africa
Publication Date: 12/15/2008
Type: Literature Review
Abstract

As our understanding of the impacts of hidden hunger on human nutrition grows, understanding the link between fertilizer use and human nutrition becomes increasingly important. This report presents an analysis of both grey and peer-reviewed literature on the effects of fertilizer use on nutritional quality of food, particularly the staples of maize, rice, wheat, cassava and legumes. We find that some nutrient deficiencies, such as zinc, can be effectively addressed through fertilizer use while others, such as iron deficiency, are more difficult to address.  Promising breakthroughs with fortified and complete fertilizers present the opportunity to correct multiple deficiencies. Current fertilizer products exist that, when applied with the proper agronomic methods, can have a significant effect on nutrition in the developing world.  However, it is important to recognize that there are many factors in the developing world that have the potential to inhibit the benefits of fertilizer for human nutrition.  Two significant factors are poor farmers’ difficulty in procuring the correct product and the relative sophistication required to apply fertilizers at the correct amounts and time to achieve desired results.  In addition, researchers have not focused on fertilizer and nutrition studies until recently, particularly micronutrient fertilizer studies, and few studies specifically study the impacts of fertilizer on human nutrition.  More research needs to be done to understand the most effective combinations and techniques, and to understand whether these methods truly increase the amount of nutrients bioavailable to humans. 

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